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7,680,650 | 1 | 2 | 1. A very low bit rate communication system comprising at a first location and at a second location: A) a voice-to-text module including a microphone adapted to convert a speaker's voice to text, B) a first processor programmed with: 1) software to separate the text into individual words, 2) a first dictionary which providing a pre-assigned a specific multi-bit numeric value for each of a large number of individual words, 3) software to create a numeric stream from multi-bit numeric values, C) a transmitter adapted to transmit the numeric stream to a receiver; D) a receiver adapted to receive the numeric stream, E) a second processor programmed with: 1) a second dictionary identical or substantially identical to the first dictionary, 2) software to convert the numeric stream to text stream utilizing the second dictionary, and F) a text-to-speech module for converting the text stream to speech including a speaker to broadcast the speech. | 1. A very low bit rate communication system comprising at a first location and at a second location: A) a voice-to-text module including a microphone adapted to convert a speaker's voice to text, B) a first processor programmed with: 1) software to separate the text into individual words, 2) a first dictionary which providing a pre-assigned a specific multi-bit numeric value for each of a large number of individual words, 3) software to create a numeric stream from multi-bit numeric values, C) a transmitter adapted to transmit the numeric stream to a receiver; D) a receiver adapted to receive the numeric stream, E) a second processor programmed with: 1) a second dictionary identical or substantially identical to the first dictionary, 2) software to convert the numeric stream to text stream utilizing the second dictionary, and F) a text-to-speech module for converting the text stream to speech including a speaker to broadcast the speech. 2. The system as in claim 1 wherein said transmitter is an acoustic transmitter. | 0.677419 |
8,428,933 | 1 | 3 | 1. A non-transitory computer readable medium having stored thereon a set of data operable to configure a computer to perform a set of tasks comprising: a) receiving an input string, the input string comprising a plurality of words; b) determining a plurality of divisions for the input string, wherein each division comprises a set of word groups, wherein each word from the plurality of words is a member of exactly one word group in each division; c) for each division, determining: 1) a set of parts of speech, wherein: i) cardinality for the set of word groups for the division and the set of parts of speech for the division is identical; ii) each part of speech from the set of parts of speech for the division is associated with a single word group from the set of word groups for the division; and iii) each part of speech from the set of parts of speech for the division is selected from a plurality of parts of speech, the plurality of parts of speech comprising an invented part of speech; 2) a rating, wherein the rating is based on a confidence that the set of parts of speech for the division corresponds to the set of word groups for the division; and d) identifying the input string as corresponding to the set of parts of speech and the set of word groups from a division selected from the plurality of divisions based on the rating for the division. | 1. A non-transitory computer readable medium having stored thereon a set of data operable to configure a computer to perform a set of tasks comprising: a) receiving an input string, the input string comprising a plurality of words; b) determining a plurality of divisions for the input string, wherein each division comprises a set of word groups, wherein each word from the plurality of words is a member of exactly one word group in each division; c) for each division, determining: 1) a set of parts of speech, wherein: i) cardinality for the set of word groups for the division and the set of parts of speech for the division is identical; ii) each part of speech from the set of parts of speech for the division is associated with a single word group from the set of word groups for the division; and iii) each part of speech from the set of parts of speech for the division is selected from a plurality of parts of speech, the plurality of parts of speech comprising an invented part of speech; 2) a rating, wherein the rating is based on a confidence that the set of parts of speech for the division corresponds to the set of word groups for the division; and d) identifying the input string as corresponding to the set of parts of speech and the set of word groups from a division selected from the plurality of divisions based on the rating for the division. 3. The non-transitory computer readable medium of claim 1 , wherein the set of tasks further comprises: a) receiving a raw input string, the raw input string comprising the plurality of words; and b) processing the raw input string to create the input string, wherein processing the raw input string comprises cleaning dimension data from the raw input string. | 0.876881 |
9,069,567 | 1 | 6 | 1. A computer-implemented method for accessing a native application programming interface (API) of a computing device, the method comprising: providing on the computing device, and from a first application written in a device-independent programming language, one or more control objects that include (a) state information that defines a context for accessing the native API and (b) at least one control script; compiling the control script on the computing device into a second application that is native to the operating system of the computing device; executing the second application on the computing device, wherein the executed second application accesses the native API of the computing device to generate an output through a hardware interface of the computing device based on the context; and accessing the native API by the second application, based on information about the state information in the control objects from the first application that is provided as a result of user input received by the first application, to generate one or more additional outputs through the hardware interface of the computing device. | 1. A computer-implemented method for accessing a native application programming interface (API) of a computing device, the method comprising: providing on the computing device, and from a first application written in a device-independent programming language, one or more control objects that include (a) state information that defines a context for accessing the native API and (b) at least one control script; compiling the control script on the computing device into a second application that is native to the operating system of the computing device; executing the second application on the computing device, wherein the executed second application accesses the native API of the computing device to generate an output through a hardware interface of the computing device based on the context; and accessing the native API by the second application, based on information about the state information in the control objects from the first application that is provided as a result of user input received by the first application, to generate one or more additional outputs through the hardware interface of the computing device. 6. The computer-implemented method of claim 1 , wherein the first application does not directly access the native API. | 0.887405 |
9,996,537 | 1 | 10 | 1. A system for transforming media elements into a narrative comprising: a processor; a memory in communication with the processor; a clustering module in communication with the processor and the memory, the clustering module configured to: receive a dataset comprising a plurality of media elements each comprising metadata; and organize the plurality of media elements into a plurality of clusters based on the metadata, the plurality of clusters being organized into a clustering tree; and a narrative module in communication with the processor and the memory, the narrative module configured to create a narrative comprising a plurality of the media elements arranged into a narrative sequence, the narrative sequence being structured according to the clustering tree and for a predetermined duration, the narrative sequence comprising a story introduction for introducing the narrative, a geographic introduction for contextualizing a cluster, a time introduction for identifying a cluster time period, a show of media elements for representing the media elements, and a story end, wherein the narrative module is configured to create the narrative sequence according to an algorithm comprising specific durations for at least the following entries: story introduction (SI), geographic introduction (GI), time introduction (TI), show of photos, with a minimum duration for photo representation (P min ), and story end, given (SE guess ), where T is a total duration of the narrative, N is a total number of media elements in the dataset, and the algorithm produces the following result:
T>SI+GI+TI+P min +SE guess . | 1. A system for transforming media elements into a narrative comprising: a processor; a memory in communication with the processor; a clustering module in communication with the processor and the memory, the clustering module configured to: receive a dataset comprising a plurality of media elements each comprising metadata; and organize the plurality of media elements into a plurality of clusters based on the metadata, the plurality of clusters being organized into a clustering tree; and a narrative module in communication with the processor and the memory, the narrative module configured to create a narrative comprising a plurality of the media elements arranged into a narrative sequence, the narrative sequence being structured according to the clustering tree and for a predetermined duration, the narrative sequence comprising a story introduction for introducing the narrative, a geographic introduction for contextualizing a cluster, a time introduction for identifying a cluster time period, a show of media elements for representing the media elements, and a story end, wherein the narrative module is configured to create the narrative sequence according to an algorithm comprising specific durations for at least the following entries: story introduction (SI), geographic introduction (GI), time introduction (TI), show of photos, with a minimum duration for photo representation (P min ), and story end, given (SE guess ), where T is a total duration of the narrative, N is a total number of media elements in the dataset, and the algorithm produces the following result:
T>SI+GI+TI+P min +SE guess . 10. The system of claim 1 , further comprising a ranking module in communication with the processor and the memory, the ranking module configured to: determine a ranking for the plurality of media elements in the dataset based on metadata of the plurality of media elements; wherein the narrative module is further configured to select the plurality of the media elements arranged into the narrative sequence based on the ranking. | 0.729219 |
9,837,069 | 13 | 15 | 13. The one or more non-transitory, machine-readable storage media of claim 10 , wherein the plurality of instructions further cause the automatic speech recognition device to: determine, based on the syntactic parse, a syntactic coherence end-of-sentence score, and determine, based on the phonemes, an acoustic end-of-sentence score, wherein to determine the end of the sentence comprises to determine the end of the sentence based on the syntactic coherence end-of-sentence score and the acoustic end-of-sentence score. | 13. The one or more non-transitory, machine-readable storage media of claim 10 , wherein the plurality of instructions further cause the automatic speech recognition device to: determine, based on the syntactic parse, a syntactic coherence end-of-sentence score, and determine, based on the phonemes, an acoustic end-of-sentence score, wherein to determine the end of the sentence comprises to determine the end of the sentence based on the syntactic coherence end-of-sentence score and the acoustic end-of-sentence score. 15. The one or more non-transitory, machine-readable storage media of claim 13 , wherein to determine the end of the sentence based on the syntactic coherence end-of-sentence score, the acoustic end-of-sentence score, and the word statistics end-of-sentence score comprises to determine the end of the sentence based on the syntactic coherence end-of-sentence score, the acoustic end-of-sentence score, and the word statistics end-of-sentence score using a machine-learning-based algorithm. | 0.733985 |
9,015,593 | 3 | 6 | 3. The system of claim 1 , wherein the advisory manager further comprises: a notification handler configured to correlate and analyze the notation model and the semantic model associated with the complex model to identify and aggregate the notifications for each node of the complex model, wherein an aggregate of notifications for a node encompasses notifications for semantically-related nodes; a resolution handler configured to determine, for each node, the potential resolutions to the aggregate of notifications identified by the notification handler, for that node; a plurality of processing rules defining operational guidelines for the at least one of the notification handler and the resolution handler; and an interface handler configured to manage interactions between the graphical modeling application, the notification handler, and the resolution handler. | 3. The system of claim 1 , wherein the advisory manager further comprises: a notification handler configured to correlate and analyze the notation model and the semantic model associated with the complex model to identify and aggregate the notifications for each node of the complex model, wherein an aggregate of notifications for a node encompasses notifications for semantically-related nodes; a resolution handler configured to determine, for each node, the potential resolutions to the aggregate of notifications identified by the notification handler, for that node; a plurality of processing rules defining operational guidelines for the at least one of the notification handler and the resolution handler; and an interface handler configured to manage interactions between the graphical modeling application, the notification handler, and the resolution handler. 6. The system of claim 3 , wherein the plurality of processing rules comprises a set of at least one user-configurable parameter. | 0.970788 |
9,916,827 | 1 | 4 | 1. A method of updating a grammar model used during speech recognition, the method comprising: obtaining a corpus comprising at least one word; obtaining at least one word from the corpus; splitting the obtained at least one word into a prescribed number of segments, wherein the prescribed number is determined based on a size of the grammar model; generating at least one hint for each segment, wherein the at least one hint is for recombining the segments into the at least one word; updating the grammar model by adding each segment to the grammar model with its generated hint; and performing speech recognition based on the updated grammar model. | 1. A method of updating a grammar model used during speech recognition, the method comprising: obtaining a corpus comprising at least one word; obtaining at least one word from the corpus; splitting the obtained at least one word into a prescribed number of segments, wherein the prescribed number is determined based on a size of the grammar model; generating at least one hint for each segment, wherein the at least one hint is for recombining the segments into the at least one word; updating the grammar model by adding each segment to the grammar model with its generated hint; and performing speech recognition based on the updated grammar model. 4. The method of claim 1 , wherein the at least one hint represents whether the segment is located at a boundary of the obtained at least one word. | 0.852705 |
9,798,703 | 12 | 13 | 12. The method of claim 11 , wherein executing the document validation system comprises executing an interface to an external validation system and receiving from the external validation system results from the external validation system's validation of the generated instance document including the generated status indicator corresponding to the code via the interface to the external validation system. | 12. The method of claim 11 , wherein executing the document validation system comprises executing an interface to an external validation system and receiving from the external validation system results from the external validation system's validation of the generated instance document including the generated status indicator corresponding to the code via the interface to the external validation system. 13. The method of claim 12 , wherein: executing the interface to the external validation system comprises generating a data file including the code and navigation keys, each of the navigation keys associating a specific segment of the code with one or more specific sources among the one or more tagged entries of the document, and the method further comprises associating the status indicator with the specific source among the one or more tagged entries of the document using the navigation keys. | 0.73817 |
7,882,121 | 9 | 14 | 9. A system for testing a component of a database application, the system comprising: a server configured to populate a column in a database with test data that falls within a certain range specified by a user; a query generator configured to specify, as indicated by the user, a desired cardinality constraint suitable for testing the component, the component operating on the system, wherein the component is a software component, wherein the system is a computing device; the query generator further configured to specify, as indicated by the user, a parametric pattern query that includes a parameter, wherein the parametric pattern query is compatible with the database, and wherein the parametric pattern query is configured to restrict cardinality when evaluated against the database; the query generator further configured to select a candidate value; a query evaluation layer configured for evaluating, via the component, the parametric pattern query against the database with the parameter set to the candidate value; the query generator further configured for calculating a cardinality error as a difference between a returned cardinality and the desired cardinality constraint wherein the returned cardinality results from the evaluating; the query generator further configured to adjust the candidate value based on the calculated cardinality error and further configured to then repeat the evaluating the parametric pattern query against the database with the parameter set to the adjusted candidate value and the calculating the cardinality error until the calculated cardinality error is within an allowable limit. | 9. A system for testing a component of a database application, the system comprising: a server configured to populate a column in a database with test data that falls within a certain range specified by a user; a query generator configured to specify, as indicated by the user, a desired cardinality constraint suitable for testing the component, the component operating on the system, wherein the component is a software component, wherein the system is a computing device; the query generator further configured to specify, as indicated by the user, a parametric pattern query that includes a parameter, wherein the parametric pattern query is compatible with the database, and wherein the parametric pattern query is configured to restrict cardinality when evaluated against the database; the query generator further configured to select a candidate value; a query evaluation layer configured for evaluating, via the component, the parametric pattern query against the database with the parameter set to the candidate value; the query generator further configured for calculating a cardinality error as a difference between a returned cardinality and the desired cardinality constraint wherein the returned cardinality results from the evaluating; the query generator further configured to adjust the candidate value based on the calculated cardinality error and further configured to then repeat the evaluating the parametric pattern query against the database with the parameter set to the adjusted candidate value and the calculating the cardinality error until the calculated cardinality error is within an allowable limit. 14. The system of claim 9 , wherein the parametric pattern query comprises a plurality of subqueries and wherein a distinct cardinality constraint is specified for each subquery. | 0.891065 |
9,886,245 | 1 | 9 | 1. A computer-implemented method, comprising: generating, by a computing system, declarative script models with services using a Data Notation Architecture (DNA), wherein the DNA provides a structure to identify and modify data schemas; creating instructions on how corresponding target application code is to be generated, by the computing system, using a Resolution Notation Architecture (RNA), wherein a given RNA file categorically qualifies and defines how DNA base pairs are resolved in the corresponding target application code; and generating rendered code and markup files for a corresponding target application as a part of a Genetic layer to be executed by a computing system associated with the corresponding target application using the RNA to create precompiled RNA. | 1. A computer-implemented method, comprising: generating, by a computing system, declarative script models with services using a Data Notation Architecture (DNA), wherein the DNA provides a structure to identify and modify data schemas; creating instructions on how corresponding target application code is to be generated, by the computing system, using a Resolution Notation Architecture (RNA), wherein a given RNA file categorically qualifies and defines how DNA base pairs are resolved in the corresponding target application code; and generating rendered code and markup files for a corresponding target application as a part of a Genetic layer to be executed by a computing system associated with the corresponding target application using the RNA to create precompiled RNA. 9. The computer-implemented method of claim 1 , wherein the DNA provides instructions on how to build library references, information reflective of relevant database structures, declarative markup, and script templates. | 0.805506 |
8,805,686 | 1 | 19 | 1. A method of electronically processing an utterance to locate candidate words at arbitrary positions within the utterance, including: accessing a dictionary of word sets each comprising multiple word representations; for each word representation, searching the utterance for likely instances of the word representation and scoring each likely word instance for a probability of a match to the word representation; wherein, the utterance is searched by multiple processors operating on the multiple word sets; and reporting at least a subset of likely word instances and respective probability scores for further electronic processing. | 1. A method of electronically processing an utterance to locate candidate words at arbitrary positions within the utterance, including: accessing a dictionary of word sets each comprising multiple word representations; for each word representation, searching the utterance for likely instances of the word representation and scoring each likely word instance for a probability of a match to the word representation; wherein, the utterance is searched by multiple processors operating on the multiple word sets; and reporting at least a subset of likely word instances and respective probability scores for further electronic processing. 19. The method of claim 1 , further including applying dynamic programming to hidden Markov models of the utterance and of the word representation during the searching and/or scoring. | 0.93707 |
9,892,362 | 10 | 12 | 10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a data processing system, causes the data processing system to: receive an ontology comprising a plurality of information concept objects and one or more actual links between the information concept objects; receive an indication of at least a selected information concept object for which a hypothetical ontological link is to be evaluated, wherein the hypothetical ontological link is a potential link that is not already present as an actual link in the ontology; automatically generate one or more natural language questions for processing by a Question Answering (QA) system pipeline based on at least an identification of a type of the selected information concept object; process, by the QA system pipeline, the one or more natural language questions to generate answer results; calculate a score for the hypothetical ontological link based on the answer results; and output information associated with the hypothetical ontological link based on the score for the hypothetical ontological link, wherein the computer readable program further causes the data processing system to calculate a score for the hypothetical ontological link at least by: calculating a score for each answer result in the generated answer results; generating a weighted score for each of the answer results; and combining the weighted scores for each of the answer results to generate the score for the hypothetical ontological link. | 10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a data processing system, causes the data processing system to: receive an ontology comprising a plurality of information concept objects and one or more actual links between the information concept objects; receive an indication of at least a selected information concept object for which a hypothetical ontological link is to be evaluated, wherein the hypothetical ontological link is a potential link that is not already present as an actual link in the ontology; automatically generate one or more natural language questions for processing by a Question Answering (QA) system pipeline based on at least an identification of a type of the selected information concept object; process, by the QA system pipeline, the one or more natural language questions to generate answer results; calculate a score for the hypothetical ontological link based on the answer results; and output information associated with the hypothetical ontological link based on the score for the hypothetical ontological link, wherein the computer readable program further causes the data processing system to calculate a score for the hypothetical ontological link at least by: calculating a score for each answer result in the generated answer results; generating a weighted score for each of the answer results; and combining the weighted scores for each of the answer results to generate the score for the hypothetical ontological link. 12. The computer program product of claim 10 , wherein the computer readable program further causes the data processing system to: automatically identify the hypothetical ontological link to be evaluated based on the indication of at least a selected information concept object. | 0.78179 |
7,616,190 | 7 | 10 | 7. A system for inputting characters comprising: means for receiving first input from a user, said first input including operation of a first single key on a QWERTY keyboard, wherein the operation of the first single key toggles a selection between a character-based language mode and a symbol-based language mode; means for presenting, in response to selection of the symbol-based language mode, a composition window for entry of a second input using the QWERTY keyboard, for displaying completed symbols in response to entry of the second input and for displaying a candidate window for candidate symbols associated with the second input; means for receiving the second input from the user, wherein the second input includes entry of characters by operation of distinct keys once for each character on the QWERTY keyboard to spell a phonetic syllable representing a symbol and to generate a list of candidate symbols in the composition window based on the entry of characters using the QWERTY keyboard to spell the phonetic syllable; and means for processing the second input from the user to select a symbol from the candidate list for placement in the display of completed symbols. | 7. A system for inputting characters comprising: means for receiving first input from a user, said first input including operation of a first single key on a QWERTY keyboard, wherein the operation of the first single key toggles a selection between a character-based language mode and a symbol-based language mode; means for presenting, in response to selection of the symbol-based language mode, a composition window for entry of a second input using the QWERTY keyboard, for displaying completed symbols in response to entry of the second input and for displaying a candidate window for candidate symbols associated with the second input; means for receiving the second input from the user, wherein the second input includes entry of characters by operation of distinct keys once for each character on the QWERTY keyboard to spell a phonetic syllable representing a symbol and to generate a list of candidate symbols in the composition window based on the entry of characters using the QWERTY keyboard to spell the phonetic syllable; and means for processing the second input from the user to select a symbol from the candidate list for placement in the display of completed symbols. 10. The system according to claim 7 , further comprises means for launching a property setting dialog. | 0.915563 |
9,558,280 | 17 | 21 | 17. An apparatus, comprising: one or more processors, a computer-readable medium coupled to said one or more processors having instructions stored thereon that, when executed by said one or more processors, cause said one or more processors to perform operations comprising: receiving, from a client device operated by a user, a request for a content item; in response to said request, identifying content items available to be sent to said client device; determining one or more designated geographic locations for each of the identified content items; determining one or more contacts of said user, said determined one or more contacts being members of a social network of said user; for each of the identified content items: determining a score for the content item based on a number of tagging actions that were performed by the user's contacts at the determined designated geographic location for the identified content item, wherein said tagging actions mark an association of a person with a particular geographic location; selecting, from the identified content items, a particular content item to be sent to the client device based on the scores; determining that a timestamp associated with at least one of the tagging actions performed at the designated geographic location for the particular content item is within a time period specified by a provider of the particular content item, the timestamp indicating a time of the tagging action; constructing, based on the determination that the timestamp is within the time period, an annotation that identifies at least one of the user's contacts with the tagging action corresponding to the designated geographic location and indicates the time of the tagging action based on the timestamp associated with the at least one location record; and sending said annotation to said client device. | 17. An apparatus, comprising: one or more processors, a computer-readable medium coupled to said one or more processors having instructions stored thereon that, when executed by said one or more processors, cause said one or more processors to perform operations comprising: receiving, from a client device operated by a user, a request for a content item; in response to said request, identifying content items available to be sent to said client device; determining one or more designated geographic locations for each of the identified content items; determining one or more contacts of said user, said determined one or more contacts being members of a social network of said user; for each of the identified content items: determining a score for the content item based on a number of tagging actions that were performed by the user's contacts at the determined designated geographic location for the identified content item, wherein said tagging actions mark an association of a person with a particular geographic location; selecting, from the identified content items, a particular content item to be sent to the client device based on the scores; determining that a timestamp associated with at least one of the tagging actions performed at the designated geographic location for the particular content item is within a time period specified by a provider of the particular content item, the timestamp indicating a time of the tagging action; constructing, based on the determination that the timestamp is within the time period, an annotation that identifies at least one of the user's contacts with the tagging action corresponding to the designated geographic location and indicates the time of the tagging action based on the timestamp associated with the at least one location record; and sending said annotation to said client device. 21. The apparatus of claim 17 , wherein said location record indicates a tagging action. | 0.973285 |
10,120,843 | 1 | 3 | 1. A method to generate search results using a searchable database of deep parsable documents, the method comprising: identifying, by one or more processors, one or more character errors in a document; generating, by the one or more processors, a deeply parasable document by replacing, in the document, a character having the identified one or more character errors with a replacement character based, at least in part, on a first code page used to create the document and a second code page used to create the deeply parsable document, wherein replacing the character error with the replacement character allows deep parsing of the document to complete to within a threshold; generating, by the one or more processors, a deep parsing record for the deeply parasable document in the searchable database of deep parsable documents by applying to the deeply parasable document one or both of deep parsing and natural language processing after the replacing, wherein the deep parsing record indicates both of i) an association between two or more sentences included in the deeply parsable document and ii) an association between the deeply parsable document and another deeply parsable document; and generating a set of search results based, at least in part, on the deep parsing record, wherein execution of a search returns results based on the association between the deeply parsable document and another deeply parsable document. | 1. A method to generate search results using a searchable database of deep parsable documents, the method comprising: identifying, by one or more processors, one or more character errors in a document; generating, by the one or more processors, a deeply parasable document by replacing, in the document, a character having the identified one or more character errors with a replacement character based, at least in part, on a first code page used to create the document and a second code page used to create the deeply parsable document, wherein replacing the character error with the replacement character allows deep parsing of the document to complete to within a threshold; generating, by the one or more processors, a deep parsing record for the deeply parasable document in the searchable database of deep parsable documents by applying to the deeply parasable document one or both of deep parsing and natural language processing after the replacing, wherein the deep parsing record indicates both of i) an association between two or more sentences included in the deeply parsable document and ii) an association between the deeply parsable document and another deeply parsable document; and generating a set of search results based, at least in part, on the deep parsing record, wherein execution of a search returns results based on the association between the deeply parsable document and another deeply parsable document. 3. The method of claim 1 , the method further comprising: determining, by the one or more processors, whether the document has been saved using an incorrect code page based, at least in part, on a type of character errors existing in the document. | 0.851384 |
10,157,593 | 1 | 2 | 1. A method for rendering computer-generated display components associated with an application for display on a computer-enabled display surface, the method comprising the acts of: receiving a plurality of content descriptions from an application, the plurality of content descriptions including commands on how to draw a display component; storing the plurality of content descriptions in memory; receiving a drawing request from an application to graphically display application content; determining if the application content to be graphically displayed is stored as one or more of the plurality of content descriptions; when the drawing request is stored as one or more of the plurality of content descriptions, rendering, from the stored content description, display components that are representative of the application content to be graphically displayed and displaying the display components; and when the content description is not stored in memory, calling the application for a rasterized image representative of the application content to be graphically displayed and displaying the rasterized image. | 1. A method for rendering computer-generated display components associated with an application for display on a computer-enabled display surface, the method comprising the acts of: receiving a plurality of content descriptions from an application, the plurality of content descriptions including commands on how to draw a display component; storing the plurality of content descriptions in memory; receiving a drawing request from an application to graphically display application content; determining if the application content to be graphically displayed is stored as one or more of the plurality of content descriptions; when the drawing request is stored as one or more of the plurality of content descriptions, rendering, from the stored content description, display components that are representative of the application content to be graphically displayed and displaying the display components; and when the content description is not stored in memory, calling the application for a rasterized image representative of the application content to be graphically displayed and displaying the rasterized image. 2. The method of claim 1 further comprising the acts of: requesting the application to provide an additional content description for which is there is no corresponding stored content description; immediately rendering one or more display components from the additional content description; and storing the additional content description for subsequent use. | 0.726575 |
4,511,891 | 11 | 12 | 11. The printing system of claim 10 wherein said means for introducing includes numerical data memory means for storing said numerical character string representing said amount information. | 11. The printing system of claim 10 wherein said means for introducing includes numerical data memory means for storing said numerical character string representing said amount information. 12. The printing system of claim 11 further comprising timing control means for supplying the numerical character string stored in said numerical data memory means to said means for converting one numerical character at a time. | 0.835029 |
10,109,217 | 2 | 4 | 2. The speech assessment device for the multisyllabic-word learning machine as claimed in claim 1 , wherein the standard audio file for characters or words includes a standard audio file for monosyllabic words, a standard continuous audio file for bi-syllabic words, a standard continuous audio file for multisyllabic words, a standard audio file for each separate character of the bi-syllabic words, and a standard audio file for each separate character of the multisyllabic words, each of the standard continuous audio file for bi-syllabic words, the standard continuous audio file for multisyllabic words, the standard audio file for each separate character of the bi-syllabic words, and the standard audio file for each separate character of the multisyllabic words is a standard continuous audio file for multisyllabic words, the monosyllabic reference polygonal line for each separate character includes a monosyllabic reference polygonal line for each separate character of the bi-syllabic words, and a monosyllabic reference polygonal line for each separate character of the multisyllabic words, the continuous multisyllabic reference polygonal line for multisyllabic words includes a continuous bi-syllabic reference polygonal line for bi-syllabic words and a continuous multisyllabic reference polygonal line for multisyllabic words. | 2. The speech assessment device for the multisyllabic-word learning machine as claimed in claim 1 , wherein the standard audio file for characters or words includes a standard audio file for monosyllabic words, a standard continuous audio file for bi-syllabic words, a standard continuous audio file for multisyllabic words, a standard audio file for each separate character of the bi-syllabic words, and a standard audio file for each separate character of the multisyllabic words, each of the standard continuous audio file for bi-syllabic words, the standard continuous audio file for multisyllabic words, the standard audio file for each separate character of the bi-syllabic words, and the standard audio file for each separate character of the multisyllabic words is a standard continuous audio file for multisyllabic words, the monosyllabic reference polygonal line for each separate character includes a monosyllabic reference polygonal line for each separate character of the bi-syllabic words, and a monosyllabic reference polygonal line for each separate character of the multisyllabic words, the continuous multisyllabic reference polygonal line for multisyllabic words includes a continuous bi-syllabic reference polygonal line for bi-syllabic words and a continuous multisyllabic reference polygonal line for multisyllabic words. 4. A speech assessment method for using the speech assessment device for the multisyllabic-word learning machine as claimed in claim 2 , comprising the following steps: a step of starting a learning mode including using the central processing system to let the displaying unit displays the playing interface; a step of selecting words to be learned including using the playing interface to select the standard continuous audio files for multisyllabic words, or the standard audio files for each separate character of the multisyllabic words from the standard speech database; and a step of playing including using the playing interface to control the speech playing unit to play the standard continuous audio files for multisyllabic words, or the standard audio files for each separate character of the multisyllabic words. | 0.947446 |
9,460,214 | 4 | 5 | 4. The method of claim 3 , further comprising receiving, through the mobile device, a user selection of a particular product among the portion of the plurality of products. | 4. The method of claim 3 , further comprising receiving, through the mobile device, a user selection of a particular product among the portion of the plurality of products. 5. The method of claim 4 , further comprising: communicating the user selection to the online marketplace; receiving data associated with the particular product from the online marketplace; and presenting the data associated with the particular product to the user through the mobile device. | 0.95198 |
9,251,269 | 1 | 4 | 1. A method for authorship accountability in a blog search engine, the method comprising: receiving a search engine query via a completed form by a user specifying query terms to query World Wide Web (“Web”) content (“blog content”), authorship criteria for authors of blog content and also content criteria, the authorship criteria including an indication of a degree to which a blog author of blog content in a results set is deemed both authoritative and trustworthy, wherein authoritativeness is computed by determining a number of others whom have subscribed to blog content authored by an author, wherein trustworthiness is computed by at least one of determining whether the blog author is known to a querying end user through inclusion in a list of contacts for the end user and frequent communications exchanged by the end user with the blog author, and wherein the blog author is a writer of blog content; evaluating the authorship criteria for each blog author of corresponding blog content returned by the search engine query; evaluating the content criteria for the blog content returned in the results set by the search engine query; computing a relevance for each entry in the results set based upon the evaluated authorship criteria and also the evaluated content criteria; and, presenting in order of relevance a listing of blog content corresponding to the results set. | 1. A method for authorship accountability in a blog search engine, the method comprising: receiving a search engine query via a completed form by a user specifying query terms to query World Wide Web (“Web”) content (“blog content”), authorship criteria for authors of blog content and also content criteria, the authorship criteria including an indication of a degree to which a blog author of blog content in a results set is deemed both authoritative and trustworthy, wherein authoritativeness is computed by determining a number of others whom have subscribed to blog content authored by an author, wherein trustworthiness is computed by at least one of determining whether the blog author is known to a querying end user through inclusion in a list of contacts for the end user and frequent communications exchanged by the end user with the blog author, and wherein the blog author is a writer of blog content; evaluating the authorship criteria for each blog author of corresponding blog content returned by the search engine query; evaluating the content criteria for the blog content returned in the results set by the search engine query; computing a relevance for each entry in the results set based upon the evaluated authorship criteria and also the evaluated content criteria; and, presenting in order of relevance a listing of blog content corresponding to the results set. 4. The method of claim 1 , wherein the authorship criteria comprises an extent to which the blog author of corresponding blog content is deemed trustworthy. | 0.894737 |
6,161,084 | 5 | 7 | 5. The method of claim 1, further comprising the steps of: before the constructing step, selecting the input string from a body of text to be indexed; and submitting the generated tokens to an indexing subsystem for storage in an index representing the body of text. | 5. The method of claim 1, further comprising the steps of: before the constructing step, selecting the input string from a body of text to be indexed; and submitting the generated tokens to an indexing subsystem for storage in an index representing the body of text. 7. The method of claim 5, further including the steps of: after the submitting step, determining an inverse document frequency of each of the words occurring in the alternative logical forms; and removing from the index tokens representing alternative logical forms containing words whose inverse document frequency is smaller than a preestablished minimum inverse document frequency. | 0.836735 |
9,990,232 | 11 | 15 | 11. A system comprising: a memory; and a processing device operatively coupled to the memory, to: receive a job request to allocate one or more resources in a resource environment to a job, the job being related to an application, the job request specifying the job using a first description language; extract one or more tags from the job request, the one or more tags at least one of a handling parameter of the job or a feature of the application, wherein the one or more tags are in a declarative tag format with information to describe the at least one of the handling parameter or the feature of the application without specifying a specific quantity of resources to be used in the resource environment; translate the one or more tags into a resource requirement in a second format that can be processed by a job scheduler executing by the processing device, wherein, to translate the processing device is to use mapping information that maps the one or more tags into the resource requirement that can be processed by the job scheduler; and allocate, by the job scheduler, one or more resources in the resource environment to the job in view of the resource requirement, wherein, to allocate one or more resources in the resource environment to the job in view of the one or more tags, the processing device is to: determine whether one or more tags indicate data for the job is secure data; instantiate a container for the job if one or more tags indicate that the data for the job is not secure data; and instantiate a virtual machine for the job if one or more tags indicate that the data for the job is secure data. | 11. A system comprising: a memory; and a processing device operatively coupled to the memory, to: receive a job request to allocate one or more resources in a resource environment to a job, the job being related to an application, the job request specifying the job using a first description language; extract one or more tags from the job request, the one or more tags at least one of a handling parameter of the job or a feature of the application, wherein the one or more tags are in a declarative tag format with information to describe the at least one of the handling parameter or the feature of the application without specifying a specific quantity of resources to be used in the resource environment; translate the one or more tags into a resource requirement in a second format that can be processed by a job scheduler executing by the processing device, wherein, to translate the processing device is to use mapping information that maps the one or more tags into the resource requirement that can be processed by the job scheduler; and allocate, by the job scheduler, one or more resources in the resource environment to the job in view of the resource requirement, wherein, to allocate one or more resources in the resource environment to the job in view of the one or more tags, the processing device is to: determine whether one or more tags indicate data for the job is secure data; instantiate a container for the job if one or more tags indicate that the data for the job is not secure data; and instantiate a virtual machine for the job if one or more tags indicate that the data for the job is secure data. 15. The system of claim 11 , wherein the processing device is further to: create a group of job requests, where the job requests in the group are a sub-set of job requests from a plurality of job requests having at least one matching tag; and allocate one or more same resources in the resource environment to the group of job requests. | 0.591241 |
10,055,401 | 8 | 13 | 8. A computer program product for dynamically evaluating an electronic communication, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a processor to: identify an idiom in an electronic communication; conduct a primary evaluation of the identified idiom; assign a confidence level to the identified idiom in response to the primary evaluation; identify an explanation of the idiom; and selectively update a corpus based on the assigned confidence level, including extract and transform the explanation and the idiom into an entry in the corpus including create a primary association between the explanation and the idiom. | 8. A computer program product for dynamically evaluating an electronic communication, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a processor to: identify an idiom in an electronic communication; conduct a primary evaluation of the identified idiom; assign a confidence level to the identified idiom in response to the primary evaluation; identify an explanation of the idiom; and selectively update a corpus based on the assigned confidence level, including extract and transform the explanation and the idiom into an entry in the corpus including create a primary association between the explanation and the idiom. 13. The computer program product of claim 8 , wherein the identification of the explanation includes program code to: parse the electronic communication and isolate two or more component phrases; compare a structure of the isolated component phrases to a structure of stored explanation tags in the corpus; detect a match between at least one of the isolated component phrases and a stored explanation tag in the corpus; and identify the explanation utilizing the detected match. | 0.501042 |
8,838,580 | 1 | 3 | 1. A method for providing keyword ranking using a common affix, the method comprising: providing a keyword set that comprises keywords input to an Internet search environment as search queries; counting, in the keyword set, keywords that comprise affixes with a common attribute; calculating a ranking of each affix using the counting result of the keywords and extracting a common affix, the calculating including applying a weight to the counting result of the keywords based on an attribute of each affix, the weight according to the attribute of each affix increases as query counts of each affix being a keyword itself increases; and establishing a regular expression comprising the extracted common affix and a search combination symbol. | 1. A method for providing keyword ranking using a common affix, the method comprising: providing a keyword set that comprises keywords input to an Internet search environment as search queries; counting, in the keyword set, keywords that comprise affixes with a common attribute; calculating a ranking of each affix using the counting result of the keywords and extracting a common affix, the calculating including applying a weight to the counting result of the keywords based on an attribute of each affix, the weight according to the attribute of each affix increases as query counts of each affix being a keyword itself increases; and establishing a regular expression comprising the extracted common affix and a search combination symbol. 3. The method of claim 1 , wherein the common attribute comprises a number of characters in the affixes, and the number of characters in the affixes is variable every time the keyword ranking is provided. | 0.853237 |
9,864,508 | 1 | 11 | 1. An electronic device, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving an indication of a first input that includes movement of a contact detected on a touch-sensitive surface of a device, wherein: the movement of the contact comprises a first stroke, and the first stroke has a spatial component and a temporal component; determining a first probability that the first stroke corresponds to a first character based on the spatial component of the first stroke; determining a second probability that the first stroke corresponds to the first character based on the temporal component of the first stroke; determining an aggregate probability that the first stroke corresponds to the first character based on the first probability and the second probability; detecting an end of the first stroke; and after detecting the end of the first stroke: detecting at least a portion of a second stroke; and in response to detecting the portion of the second stroke and while the second stroke is still being detected, determining whether the first stroke and the second stroke correspond to a single character based on temporal information about the first stroke and the second stroke. | 1. An electronic device, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving an indication of a first input that includes movement of a contact detected on a touch-sensitive surface of a device, wherein: the movement of the contact comprises a first stroke, and the first stroke has a spatial component and a temporal component; determining a first probability that the first stroke corresponds to a first character based on the spatial component of the first stroke; determining a second probability that the first stroke corresponds to the first character based on the temporal component of the first stroke; determining an aggregate probability that the first stroke corresponds to the first character based on the first probability and the second probability; detecting an end of the first stroke; and after detecting the end of the first stroke: detecting at least a portion of a second stroke; and in response to detecting the portion of the second stroke and while the second stroke is still being detected, determining whether the first stroke and the second stroke correspond to a single character based on temporal information about the first stroke and the second stroke. 11. The electronic device of claim 1 , wherein detecting the end of the first stroke comprises detecting a liftoff of the contact detected on the touch-sensitive surface of the device. | 0.914894 |
7,533,372 | 11 | 15 | 11. A system for modifying a computer system or computer application from a first language to at least a second language comprising: means for determining a structure of a system about to be migrated; means for storing migration information based on the determination of the structure; means for performing said migration based on said stored migration information, wherein performing said migration modifies at least some core code of the computer system from a language dependent form into a language independent form; means for performing said migration based on a module-type migration and based on said stored information to a stored link to provide a path backwards to reestablish the stored link using pre-migration information including: means for setting a user-related string; means for setting at least one system-wide string, with each user-related or system wide setting string allowing a registry value association between said stored migration information and a stored registry in an automatically generated string table; wherein said migration information can compare a file name with said stored registry, to said automatically generated string table; and means for performing said migration based on said stored migration information to a stored registry to synchronize the post-migration system structure. | 11. A system for modifying a computer system or computer application from a first language to at least a second language comprising: means for determining a structure of a system about to be migrated; means for storing migration information based on the determination of the structure; means for performing said migration based on said stored migration information, wherein performing said migration modifies at least some core code of the computer system from a language dependent form into a language independent form; means for performing said migration based on a module-type migration and based on said stored information to a stored link to provide a path backwards to reestablish the stored link using pre-migration information including: means for setting a user-related string; means for setting at least one system-wide string, with each user-related or system wide setting string allowing a registry value association between said stored migration information and a stored registry in an automatically generated string table; wherein said migration information can compare a file name with said stored registry, to said automatically generated string table; and means for performing said migration based on said stored migration information to a stored registry to synchronize the post-migration system structure. 15. The system according to claim 11 , wherein said means for performing further comprises: means for unlocking shell folders. | 0.735294 |
9,367,766 | 17 | 18 | 17. A non-transitory computer-readable storage medium storing instructions that, when executed on a computing device, configure the computing device to perform operations comprising: detecting candidate text regions in an image; generating candidate text lines between pairs of the candidate text regions; selecting text lines from the candidate text lines based on an assignment of the candidate text lines to the candidate text regions, wherein the assignment is based on features of the candidate text regions and minimizes a total number of the selected text lines; and generating a bounding box for a portion of text in the image based on the selected text lines, the bounding box facilitating recognition of text in the image. | 17. A non-transitory computer-readable storage medium storing instructions that, when executed on a computing device, configure the computing device to perform operations comprising: detecting candidate text regions in an image; generating candidate text lines between pairs of the candidate text regions; selecting text lines from the candidate text lines based on an assignment of the candidate text lines to the candidate text regions, wherein the assignment is based on features of the candidate text regions and minimizes a total number of the selected text lines; and generating a bounding box for a portion of text in the image based on the selected text lines, the bounding box facilitating recognition of text in the image. 18. The non-transitory computer-readable storage medium of claim 17 , wherein generating a bounding box for a portion of text comprises: identifying candidate text regions that a selected text line intersects; determining a start and an end of the selected text line based on coordinates of the identified candidate text regions; determining distances between adjacent candidate regions based on the coordinates; and grouping a subset of the identified candidate text regions in one group based on the distances, wherein the bounding box bound the group to indicate a word that the subset represents. | 0.731183 |
8,301,656 | 14 | 20 | 14. A system comprising: one or more server devices to: receive a first list of search results and a second list of search results, the first list being associated with a first category, the second list being associated with a second category that differs from the first category, the first category being higher ranked than the second category based on respective relevances of search results in the first list and search results in the second list to a search query; generate a document that provides information associated with the first list and the second list, where the document includes a first area and a second area, the first area being larger and more prominently presented, within the document, than the second area when the document is rendered, where the first area of the document is associated with the first list, where the first area presents information associated with at least one search result of the first list, the information presented in the first area including at least one snippet associated with, respectively, the at least one search result of the first list, and where the second area of the document is associated with the second list, where the second area presents information associated with at least one search result of the second list, and where the information presented in the second area does not include a textual snippet associated with any of the at least one search result of the second list; and output the document. | 14. A system comprising: one or more server devices to: receive a first list of search results and a second list of search results, the first list being associated with a first category, the second list being associated with a second category that differs from the first category, the first category being higher ranked than the second category based on respective relevances of search results in the first list and search results in the second list to a search query; generate a document that provides information associated with the first list and the second list, where the document includes a first area and a second area, the first area being larger and more prominently presented, within the document, than the second area when the document is rendered, where the first area of the document is associated with the first list, where the first area presents information associated with at least one search result of the first list, the information presented in the first area including at least one snippet associated with, respectively, the at least one search result of the first list, and where the second area of the document is associated with the second list, where the second area presents information associated with at least one search result of the second list, and where the information presented in the second area does not include a textual snippet associated with any of the at least one search result of the second list; and output the document. 20. The system of claim 14 , where the one or more server devices, when generating the document, are further to: include, in the document, a link to one or more search results, of the first list, that are not identified in the information presented in the first area. | 0.675182 |
8,452,795 | 10 | 11 | 10. The system of claim 9 , wherein determining the order comprises determining an order that separates the obtained candidate queries from the query specializations. | 10. The system of claim 9 , wherein determining the order comprises determining an order that separates the obtained candidate queries from the query specializations. 11. The system of claim 10 , wherein determining the order comprises ordering the candidate queries according to a respective weight for each candidate query. | 0.975016 |
9,143,511 | 1 | 7 | 1. A method comprising: receiving, by a computer system, a runtime policy set for a web service endpoint, the runtime policy set identifying a list of all web service policies whose attachment metadata indicates attachment to the web service endpoint; receiving, by the computer systems, a constraint expression for each web service policy in the runtime policy set, each constraint expression specifying one or more runtime values; aggregating, by the computer system, the web service policies included in the runtime policy set into a set of groups based on each web service policy's corresponding constraint expression, each group in the set of groups grouping web service policies by constraint expression; identifying, by the computer system, one or more groups in the set of groups whose constraint expressions indicate grouped web service policies are simultaneously attached to the web service endpoint at runtime; applying, by the computer system, one or more validation rules to the web service policies in the one or more groups; evaluating the one or more runtime values at runtime, wherein the evaluating determines whether the attachment metadata of a corresponding web service policy in a group validated by the one or more validation rules is enforced attaching the corresponding web service policy to the web service endpoint; and controlling execution behavior of the web service endpoint based on the one or more runtime values and the corresponding web service policy, wherein the execution behavior includes at least one of authentication, authorization, message encryption, or message logging. | 1. A method comprising: receiving, by a computer system, a runtime policy set for a web service endpoint, the runtime policy set identifying a list of all web service policies whose attachment metadata indicates attachment to the web service endpoint; receiving, by the computer systems, a constraint expression for each web service policy in the runtime policy set, each constraint expression specifying one or more runtime values; aggregating, by the computer system, the web service policies included in the runtime policy set into a set of groups based on each web service policy's corresponding constraint expression, each group in the set of groups grouping web service policies by constraint expression; identifying, by the computer system, one or more groups in the set of groups whose constraint expressions indicate grouped web service policies are simultaneously attached to the web service endpoint at runtime; applying, by the computer system, one or more validation rules to the web service policies in the one or more groups; evaluating the one or more runtime values at runtime, wherein the evaluating determines whether the attachment metadata of a corresponding web service policy in a group validated by the one or more validation rules is enforced attaching the corresponding web service policy to the web service endpoint; and controlling execution behavior of the web service endpoint based on the one or more runtime values and the corresponding web service policy, wherein the execution behavior includes at least one of authentication, authorization, message encryption, or message logging. 7. The method of claim 1 wherein the one or more validation rules include a rule that limits attachment of a web service policy to policy subjects of a certain type, a rule that limits ordering of certain web service policies, or a rule that indicates certain web service policy attachments to web service endpoints are incompatible. | 0.744632 |
10,032,118 | 1 | 9 | 1. A device, comprising: a memory that stores instructions; and a processing system including a processor coupled to the memory, wherein execution of the instructions facilitates performance operations, the operations comprising: receiving a plurality of blogs: detecting a media processor from a plurality of media processors requesting a media program as a requested media program from a plurality of media programs; identifying, by using a search application programming interface, subsets of blogs that are relevant to the requested media program, wherein the identifying comprises: obtaining an initial set of annotated blogs, wherein the initial set of annotated blogs are annotated as being either relevant to a requested media program or not relevant to the requested media program; training a first classifier based on the initial set of annotated blogs to generate a trained first classifier; applying the trained first classifier to unannotated blogs from the plurality of blogs to generate a first set of features associating the requested media program with the unannotated blogs; training a second classifier according to the first set of features generated by the trained first classifier to generate a trained second classifier; and applying the trained second classifier to the plurality of blogs to identify a subset of blogs relevant to the requested media program as a subset of relevant blogs; performing a sentiment analysis on the subset of relevant blogs to determine a trend based on pattern recognition, wherein the trend is related to the requested media program; selecting media program rentals according to the subset of relevant blogs; receiving a blog message from the media processor; identifying a blog leader associated with the blog message; directing the blog message to a blog group of the blog leader; subdividing the subset of relevant blogs into blog subgroups comprising one of blogs favorable to the media program or blogs unfavorable to the media program; and selecting scheduled media programming according to the subset of blogs. | 1. A device, comprising: a memory that stores instructions; and a processing system including a processor coupled to the memory, wherein execution of the instructions facilitates performance operations, the operations comprising: receiving a plurality of blogs: detecting a media processor from a plurality of media processors requesting a media program as a requested media program from a plurality of media programs; identifying, by using a search application programming interface, subsets of blogs that are relevant to the requested media program, wherein the identifying comprises: obtaining an initial set of annotated blogs, wherein the initial set of annotated blogs are annotated as being either relevant to a requested media program or not relevant to the requested media program; training a first classifier based on the initial set of annotated blogs to generate a trained first classifier; applying the trained first classifier to unannotated blogs from the plurality of blogs to generate a first set of features associating the requested media program with the unannotated blogs; training a second classifier according to the first set of features generated by the trained first classifier to generate a trained second classifier; and applying the trained second classifier to the plurality of blogs to identify a subset of blogs relevant to the requested media program as a subset of relevant blogs; performing a sentiment analysis on the subset of relevant blogs to determine a trend based on pattern recognition, wherein the trend is related to the requested media program; selecting media program rentals according to the subset of relevant blogs; receiving a blog message from the media processor; identifying a blog leader associated with the blog message; directing the blog message to a blog group of the blog leader; subdividing the subset of relevant blogs into blog subgroups comprising one of blogs favorable to the media program or blogs unfavorable to the media program; and selecting scheduled media programming according to the subset of blogs. 9. The device of claim 1 , wherein the plurality of blogs comprises a plurality of micro-blogs, and wherein each micro-blog in the plurality of micro-blogs comprises text content, audio content, image content, video content, or portions thereof, and wherein each micro-blog is associated with a leader controlling the micro-blog and followers participating in the micro-blog. | 0.587004 |
9,626,703 | 1 | 8 | 1. A method for providing voice commerce, the method being implemented on a computer system having one or more physical processors programmed with computer program instructions which, when executed, perform the method, the method comprising: receiving, by the computer system, a user input comprising a natural language utterance; providing, by the computer system, the natural language utterance as an input to a speech recognition engine; obtaining, by the computer system, one or more words or phrases recognized from the natural language utterance as an output of the speech recognition engine; determining, by the computer system, a context based at least on the one or more words or phrases; identifying, by the computer system, without further user input after the receipt of the user input, a product or service to be purchased on behalf of a user based at least on the determined context; obtaining, by the computer system, payment information with which to pay for the product or service; obtaining, by the computer system, without further user input after the receipt of the user input, shipping information with which to deliver the product or service, wherein the shipping information specifies a name or address of a recipient to which the product or service is to be delivered after the product or service is purchased; and completing, by the computer system, without further user input after the receipt of the user input, a purchase transaction for the product or service based on the payment information and shipping information. | 1. A method for providing voice commerce, the method being implemented on a computer system having one or more physical processors programmed with computer program instructions which, when executed, perform the method, the method comprising: receiving, by the computer system, a user input comprising a natural language utterance; providing, by the computer system, the natural language utterance as an input to a speech recognition engine; obtaining, by the computer system, one or more words or phrases recognized from the natural language utterance as an output of the speech recognition engine; determining, by the computer system, a context based at least on the one or more words or phrases; identifying, by the computer system, without further user input after the receipt of the user input, a product or service to be purchased on behalf of a user based at least on the determined context; obtaining, by the computer system, payment information with which to pay for the product or service; obtaining, by the computer system, without further user input after the receipt of the user input, shipping information with which to deliver the product or service, wherein the shipping information specifies a name or address of a recipient to which the product or service is to be delivered after the product or service is purchased; and completing, by the computer system, without further user input after the receipt of the user input, a purchase transaction for the product or service based on the payment information and shipping information. 8. The method of claim 1 , further comprising: receiving, at the computer system, a previous user input prior to the receipt of the user input, wherein the previous user input is related to the product or service; and storing, by the computer system, context information associated with the user based on information related to the previous user input, wherein determining the product or service as at least one product or service to be purchased on behalf of the user comprises determining, without further user input after the receipt of the user input, the product or service based on the natural language utterance and the context information related to the previous user input. | 0.636461 |
4,610,025 | 1 | 22 | 1. A system for recognizing the content of a communication in symbolic language having rules, said communication comprising a plurality of glyphs arranged in a predetermined order and defining plural glyph words, each of said glyphs being a discrete element generally comprising the smallest meaningful informational unit of said language, said system comprising sensory input means for sensing said plurality of glyphs and inputting a stream of data indicative thereof into storage menas, separating means for separating said data into a plurality of glyphs, compiling means for assigning a unique identifier to each set of substantially identical glyphs, pattern grouping means for arranging said identifiers in a grouped arrangement corresponding to the arrangement of said glyph words in said communication, decryption means including language and dictionary storage means for applying general cryptographic techniques to said identifiers to analyze said grouped identifiers in terms of contextual patterns by their sequences within at least one word and their interrelationships as words, to thereby determine the equivalent symbol of language corresponding to each of said identifiers. | 1. A system for recognizing the content of a communication in symbolic language having rules, said communication comprising a plurality of glyphs arranged in a predetermined order and defining plural glyph words, each of said glyphs being a discrete element generally comprising the smallest meaningful informational unit of said language, said system comprising sensory input means for sensing said plurality of glyphs and inputting a stream of data indicative thereof into storage menas, separating means for separating said data into a plurality of glyphs, compiling means for assigning a unique identifier to each set of substantially identical glyphs, pattern grouping means for arranging said identifiers in a grouped arrangement corresponding to the arrangement of said glyph words in said communication, decryption means including language and dictionary storage means for applying general cryptographic techniques to said identifiers to analyze said grouped identifiers in terms of contextual patterns by their sequences within at least one word and their interrelationships as words, to thereby determine the equivalent symbol of language corresponding to each of said identifiers. 22. The system of claim 1, wherein said decryption means comprises a plurality of analytical means for identifying correspondences between glyphs and symbols of language, without relying to a substantial degree on the shape or geometry of the respective glyphs. | 0.610448 |
7,620,959 | 1 | 5 | 1. A computer-readable storage media having computer executable instructions, the instructions, when executed, performing a method comprising: receiving a parsable stream that includes an identifier associated with a command; retrieving definitional information based on the identifier that describes an expected parameter for the command; creating an object based on the definitional information; storing a parameter obtained from the parsable stream in the object in accordance with the definitional information associated with the expected parameter; applying a plurality of directives to the parsable stream, the plurality of directives comprising: a processing directive configured to manipulate the parameter before providing the object with the parameter to the command and includes specific size limits for strings and for collections that can be processed; a documentation directive that, when requested, generates textual information about the parameter and provides a description of correct syntax when an invalid syntax is encountered; an interaction directive that determines a user interface for input of the expected parameter, wherein the interaction directive is applied if the expected parameter is not received in the parsable stream; and providing the object to the command, the object having a method invocable by the command, wherein: the definitional information and the plurality of directives are either derived from a reflection-based shell or extended by a developer of the command; the reflection-based shell provides one or more categories of directives and one or more directives under each category of directives; and the definition information and the plurality of directives associated with a first command are different from the definition information and the plurality of directives associated with a second command. | 1. A computer-readable storage media having computer executable instructions, the instructions, when executed, performing a method comprising: receiving a parsable stream that includes an identifier associated with a command; retrieving definitional information based on the identifier that describes an expected parameter for the command; creating an object based on the definitional information; storing a parameter obtained from the parsable stream in the object in accordance with the definitional information associated with the expected parameter; applying a plurality of directives to the parsable stream, the plurality of directives comprising: a processing directive configured to manipulate the parameter before providing the object with the parameter to the command and includes specific size limits for strings and for collections that can be processed; a documentation directive that, when requested, generates textual information about the parameter and provides a description of correct syntax when an invalid syntax is encountered; an interaction directive that determines a user interface for input of the expected parameter, wherein the interaction directive is applied if the expected parameter is not received in the parsable stream; and providing the object to the command, the object having a method invocable by the command, wherein: the definitional information and the plurality of directives are either derived from a reflection-based shell or extended by a developer of the command; the reflection-based shell provides one or more categories of directives and one or more directives under each category of directives; and the definition information and the plurality of directives associated with a first command are different from the definition information and the plurality of directives associated with a second command. 5. A computer-readable storage media of claim 1 , further providing intellisense as the parsable stream is being generated to autocomplete the parsable stream based on the definitional information, wherein the autocomplete occurs upon receiving a disambiguating portion of the parseable stream. | 0.786026 |
8,600,734 | 8 | 9 | 8. The method of claim 1 , including the step of assigning an emotional value to said electronic correspondence using a reference data structure. | 8. The method of claim 1 , including the step of assigning an emotional value to said electronic correspondence using a reference data structure. 9. The method of claim 8 wherein said emotion value is in a range that spans from a negative value to a positive value. | 0.969858 |
4,480,306 | 3 | 9 | 3. The digital computer system of claim 1, wherein said microcode control means further comprises: monitor microcode means for storing sequences of monitor microinstructions for controlling the monitor operation of said ALU means, said monitor microcode means responsive to the operation of said ALU means to provide said sequences of monitor microinstructions to said ALU means, and said ALU means further comprises monitor stack means containing at least one monitor stack frame for storing the state of execution of a monitor microinstruction when the execution of said monitor microinstruction has been interrupted. | 3. The digital computer system of claim 1, wherein said microcode control means further comprises: monitor microcode means for storing sequences of monitor microinstructions for controlling the monitor operation of said ALU means, said monitor microcode means responsive to the operation of said ALU means to provide said sequences of monitor microinstructions to said ALU means, and said ALU means further comprises monitor stack means containing at least one monitor stack frame for storing the state of execution of a monitor microinstruction when the execution of said monitor microinstruction has been interrupted. 9. The digital computer system of claim 3, wherein: said general register file means is further horizontally divided into a first set of registers, a second set of registers, and a third set of registers, said first set of registers for storing selected operands and selected addresses for general ALU operations, said second set of registers comprises said ALU microinstruction stack means, and said third set of registers comprises said monitor microinstruction stack means. | 0.924803 |
4,400,828 | 5 | 6 | 5. Apparatus as in claims 2 or 3 further characterized in that said equivalence classes are representative of reference words which are acoustically similar, and said frames are representative of discrete periods of time. | 5. Apparatus as in claims 2 or 3 further characterized in that said equivalence classes are representative of reference words which are acoustically similar, and said frames are representative of discrete periods of time. 6. Apparatus as in claim 5 further characterized in that said reference word feature templates and said input word feature template each have the same number of time frames. | 0.967395 |
7,609,848 | 8 | 10 | 8. A watermark recovery system comprising: a watermarked document including a watermark with encoded content information; a watermark specification for identifying a specific watermarking technology and identifying a target object in which the watermark is placed; a template specification identifying at least one watermark specification and providing a mapping list indicating a manner in which at least one watermark associated with the at least one watermark specification is merged into a document; a watermark scanning module for scanning the watermarked document to locate a watermark according to the template specification, the watermark scanning module including a repository for storing at least one of the template specification and a watermark specification; and a watermark recovery module for recovering the content information from the located watermark according to a watermark specification identified by the template specification. | 8. A watermark recovery system comprising: a watermarked document including a watermark with encoded content information; a watermark specification for identifying a specific watermarking technology and identifying a target object in which the watermark is placed; a template specification identifying at least one watermark specification and providing a mapping list indicating a manner in which at least one watermark associated with the at least one watermark specification is merged into a document; a watermark scanning module for scanning the watermarked document to locate a watermark according to the template specification, the watermark scanning module including a repository for storing at least one of the template specification and a watermark specification; and a watermark recovery module for recovering the content information from the located watermark according to a watermark specification identified by the template specification. 10. The system of claim 8 , wherein the content information indicates at least one of document type, document-associated application, document authenticity and document source. | 0.795349 |
9,836,502 | 1 | 4 | 1. A computer-implemented method comprising: receiving a selection of one or more identifiers of panel templates among a plurality of identifiers of panel templates, wherein each identifier of the plurality of identifiers is associated with a panel template that includes a query and a format for displaying an associated panel in a dashboard, wherein selecting the one or more identifiers of panel templates comprises: dragging each identifier of the one or more identifiers of panel templates onto a representation of a dashboard in a displayed dashboard-creation page; and dropping each dragged identifier at an associated position in the dashboard-creation page, each associated position being indicative of where the associated panel appears when the dashboard is displayed; in response to selecting an identifier of the one or more identifiers of panel templates: adding a reference to an associated panel template of the selected identifier in the associated panel in the dashboard-creation page; and adding to the dashboard-creation page an indication of the panel associated with the selected identifier; in response to a user action for a particular panel in the dashboard-creation page, executing a query included in a panel template referenced by the particular panel to generate data for display in that particular panel within the dashboard-creation page; and visualizing, within the particular panel within the dashboard-creation page, data resulting from execution of the query in the panel template referenced by the particular panel. | 1. A computer-implemented method comprising: receiving a selection of one or more identifiers of panel templates among a plurality of identifiers of panel templates, wherein each identifier of the plurality of identifiers is associated with a panel template that includes a query and a format for displaying an associated panel in a dashboard, wherein selecting the one or more identifiers of panel templates comprises: dragging each identifier of the one or more identifiers of panel templates onto a representation of a dashboard in a displayed dashboard-creation page; and dropping each dragged identifier at an associated position in the dashboard-creation page, each associated position being indicative of where the associated panel appears when the dashboard is displayed; in response to selecting an identifier of the one or more identifiers of panel templates: adding a reference to an associated panel template of the selected identifier in the associated panel in the dashboard-creation page; and adding to the dashboard-creation page an indication of the panel associated with the selected identifier; in response to a user action for a particular panel in the dashboard-creation page, executing a query included in a panel template referenced by the particular panel to generate data for display in that particular panel within the dashboard-creation page; and visualizing, within the particular panel within the dashboard-creation page, data resulting from execution of the query in the panel template referenced by the particular panel. 4. The method of claim 1 , wherein the panel template referenced by each panel includes a definition of a local input that affects the panel's display of the data generated by executing the query in that panel template. | 0.800909 |
7,665,021 | 7 | 8 | 7. A computer program product, encoded on a computer-readable medium, operable to cause data processing apparatus to perform operations comprising: displaying a text script on a display; receiving input from a user positioning a plurality of graphical icons associated with a plurality of media events adjacent to said text script in a scrollable portion of said display to establish a spatial relationship between said plurality of visual images and said text script, such that each graphical icon's position corresponds to one or more words in said text script with which said associated media event is to begin during a presentation; scrolling said text script on said display while maintaining said spatial relationship between said text script and said graphical icons; causing said media events associated with said graphical icons to begin approximately upon the corresponding one or more words of the text script scrolling through a predetermined region of said display during said presentation; and generating said presentation, including audio information corresponding to the user speaking at least a portion of said text script. | 7. A computer program product, encoded on a computer-readable medium, operable to cause data processing apparatus to perform operations comprising: displaying a text script on a display; receiving input from a user positioning a plurality of graphical icons associated with a plurality of media events adjacent to said text script in a scrollable portion of said display to establish a spatial relationship between said plurality of visual images and said text script, such that each graphical icon's position corresponds to one or more words in said text script with which said associated media event is to begin during a presentation; scrolling said text script on said display while maintaining said spatial relationship between said text script and said graphical icons; causing said media events associated with said graphical icons to begin approximately upon the corresponding one or more words of the text script scrolling through a predetermined region of said display during said presentation; and generating said presentation, including audio information corresponding to the user speaking at least a portion of said text script. 8. The computer program product of claim 7 , further comprising instructions operable to cause a programmable processor to perform operations comprising receiving said text script as typed input. | 0.735054 |
6,137,041 | 9 | 15 | 9. The computer-readable recording medium storing a music score reading program comprising: sign recognizing function of recognizing all signs and notes of a music score; notation estimating function of estimating a drum notation in a drum part of the music score based on information obtained by said sign recognizing function; musical instrument allocating function of allocating actual tone generating musical instruments to the recognized signs of the drum part according to the drum notation estimated by said notation estimating function, such that the music score is converted into a readable music score data format. | 9. The computer-readable recording medium storing a music score reading program comprising: sign recognizing function of recognizing all signs and notes of a music score; notation estimating function of estimating a drum notation in a drum part of the music score based on information obtained by said sign recognizing function; musical instrument allocating function of allocating actual tone generating musical instruments to the recognized signs of the drum part according to the drum notation estimated by said notation estimating function, such that the music score is converted into a readable music score data format. 15. A computer-readable recording medium storing a music score reading program according to claim 9 wherein said notation estimating function estimates a drum notation with respect to drum instruments of cymbals such that, under a condition that drum heads other than a black head exist above a fourth space of the staff, drum notations are classified into a case where the drum heads exist at one staff position and a case where the drum heads exist at two staff positions, said classification is further divided depending on kinds of the drum heads and still further divided depending on tone lengths determined by flags of the drum notes and other tone lengths determined by the kinds of the heads based on existence of the tone lengths of the drum notes derived by said flags, a conversion table is prepared depending on said still further divided classification, and kinds of the drum instruments of cymbals estimated depending on the staff positions of the drum heads, the kinds of the drum heads, a hi-hat open sign relating to the drum notes, a hi-hat close sign relating to the drum notes, an accent sign relating to the drum notes and character strings for designation of drum tones of the notes are specified in the conversion table so as to estimate the drum notation based on said conversion table. | 0.600548 |
9,508,044 | 1 | 7 | 1. A method comprising: collecting a plurality of configurations from a plurality of computing resources, respectively; processing the plurality of configurations to generate one or more rules, wherein the one or more rules are generated by an analyzer; analyzing one or more first configurations out of the plurality of configurations using the one or more rules to produce an analysis result, wherein each of the first configuration(s) defines a configuration of a respective computing resource; training a Bayesian classifier using the analysis result, wherein the training generates one or more weights, and the Bayesian classifier takes as an input the first configurations of the respective computing resources; classifying a second configuration using the trained Bayesian classifier, wherein the classifying uses the weight(s); and modifying the trained Bayesian classifier in response to a modification of the classified second configuration, wherein the trained Bayesian classifier adjusts at least one of the weight(s) based on the modified Bayesian classifier. | 1. A method comprising: collecting a plurality of configurations from a plurality of computing resources, respectively; processing the plurality of configurations to generate one or more rules, wherein the one or more rules are generated by an analyzer; analyzing one or more first configurations out of the plurality of configurations using the one or more rules to produce an analysis result, wherein each of the first configuration(s) defines a configuration of a respective computing resource; training a Bayesian classifier using the analysis result, wherein the training generates one or more weights, and the Bayesian classifier takes as an input the first configurations of the respective computing resources; classifying a second configuration using the trained Bayesian classifier, wherein the classifying uses the weight(s); and modifying the trained Bayesian classifier in response to a modification of the classified second configuration, wherein the trained Bayesian classifier adjusts at least one of the weight(s) based on the modified Bayesian classifier. 7. The method of claim 1 , wherein each first configuration comprises one or more features that indicate the configuration of a respective resource, and the weight(s) are associated with the feature(s) of the first configuration(s). | 0.819596 |
9,779,728 | 12 | 14 | 12. The system of claim 11 , wherein the punctuation-addition module includes: an aggregate-weight-determination component configured to determine the first aggregate weight R1 and the second aggregate weight R2; an aggregate-weight-integration component configured to generate the third aggregate weight R3; and a punctuation-addition component configured to modify the voice file. | 12. The system of claim 11 , wherein the punctuation-addition module includes: an aggregate-weight-determination component configured to determine the first aggregate weight R1 and the second aggregate weight R2; an aggregate-weight-integration component configured to generate the third aggregate weight R3; and a punctuation-addition component configured to modify the voice file. 14. The system of claim 12 , wherein the aggregate-weight-determination component is further configured to: acquire from the language model a mapping between the one or more second feature units and one or more of the preliminary weights for one or more of the preliminary punctuation states associated with the one or more second feature units; determine one or more word weights related to the one or more preliminary punctuation states based on at least the mapping; and calculate the second aggregate weight R2 based on at least the second word weights. | 0.872072 |
9,697,192 | 13 | 16 | 13. A system, comprising: one or more processors; a memory device coupled to the one or more processors and storing instructions which, when executed by the one or more processors, cause the system to perform functions that include: reading text data corresponding to one or more messages; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by at least one trained statistical language model trained by machine learning, one or more predictive labels as annotations corresponding to language patterns associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store, wherein the aggregating comprises constructing a global knowledge representation associated with the aggregated one or more annotated messages; performing an automated process, based at least in part on the global knowledge representation, the automated process comprising one or more global analytics functions that include: (a) identifying an annotation error in the created one or more semantic annotations, (b) automatically updating the respective semantic annotation in the global knowledge representation to correct the annotation error, to form an updated semantic annotation, and (c) back-propagating the updated semantic annotation into training data for further language model training by machine learning, wherein the back-propagating comprises forming updated training data, that includes the updated semantic annotation, for additional training of the at least one statistical language model, wherein the additional training comprises training the at least one statistical language model to perform one or more local analytics functions and to generate predictive labels for additional semantic annotations to text data; and performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. | 13. A system, comprising: one or more processors; a memory device coupled to the one or more processors and storing instructions which, when executed by the one or more processors, cause the system to perform functions that include: reading text data corresponding to one or more messages; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by at least one trained statistical language model trained by machine learning, one or more predictive labels as annotations corresponding to language patterns associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store, wherein the aggregating comprises constructing a global knowledge representation associated with the aggregated one or more annotated messages; performing an automated process, based at least in part on the global knowledge representation, the automated process comprising one or more global analytics functions that include: (a) identifying an annotation error in the created one or more semantic annotations, (b) automatically updating the respective semantic annotation in the global knowledge representation to correct the annotation error, to form an updated semantic annotation, and (c) back-propagating the updated semantic annotation into training data for further language model training by machine learning, wherein the back-propagating comprises forming updated training data, that includes the updated semantic annotation, for additional training of the at least one statistical language model, wherein the additional training comprises training the at least one statistical language model to perform one or more local analytics functions and to generate predictive labels for additional semantic annotations to text data; and performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. 16. The system of claim 13 , wherein the global knowledge representation associated with the aggregated one or more annotated messages is a global knowledge graph representation, and wherein updating the semantic annotation comprises updating the respective semantic annotation in the global knowledge graph representation to correct the annotation error. | 0.501404 |
9,916,379 | 11 | 16 | 11. The computer-readable storage medium of claim 10 , wherein said instructions further comprise instructions that when executed by the processor, cause the processor to: identify a first set of fields in the unstructured data to obtain field identification data from the unstructured data source, the unstructured data including text records, each of the fields in the first set of fields corresponding to a portion of text extracted from a portion of at least one of the text records; wherein generating the second query in the second query language associated with the unstructured data store includes generating the second query by using the identified first set of fields. | 11. The computer-readable storage medium of claim 10 , wherein said instructions further comprise instructions that when executed by the processor, cause the processor to: identify a first set of fields in the unstructured data to obtain field identification data from the unstructured data source, the unstructured data including text records, each of the fields in the first set of fields corresponding to a portion of text extracted from a portion of at least one of the text records; wherein generating the second query in the second query language associated with the unstructured data store includes generating the second query by using the identified first set of fields. 16. The computer-readable storage medium of claim 11 , wherein the first query comprises a Structured Query Language (“SQL”) query. | 0.950641 |
7,707,220 | 1 | 24 | 1. A search method, comprising: A) causing a first information set to be generated, comprising a first plurality of items, wherein each item of the first plurality of items is associated with at least one characteristic; B) representing at least some of the first information set in a first presentation; C) receiving a first feedback based upon the first presentation from a user; D) applying an evolutionary algorithm to a plurality of characteristics associated with the first plurality of items to generate a first search query, wherein the evolutionary algorithm is based on the first feedback; E) causing the first search query to be executed to generate a second information set comprising a second plurality of items, wherein each item of the second plurality of items is associated with at least one characteristic; F) representing at least some of the second information set in a second presentation; G) in response to a user input, repeating step B and representing at least some of the first information set in the first presentation; H) receiving a second feedback based upon the second presentation from a user; I) applying an evolutionary algorithm to a plurality of characteristics associated with the second plurality of items to generate a second search query, wherein the evolutionary algorithm is based on the second feedback; J) causing the second search query to be executed to generate a third information set comprising a third plurality of items, wherein each item of the third plurality of items is associated with at least one characteristic; and K) representing at least some of the third information set in a third presentation; wherein at least one characteristic associated with each item is chosen from a group comprising: at least one descriptor made available by a search engine or web directory service; at least one tag; at least one keyword; at least one classification-oriented identifier; at least one categorization-oriented identifier; and at least one semantic web-oriented identifier; and wherein at least one characteristic associated with each item is not a word or phrase selected from text displayed as part of the item. | 1. A search method, comprising: A) causing a first information set to be generated, comprising a first plurality of items, wherein each item of the first plurality of items is associated with at least one characteristic; B) representing at least some of the first information set in a first presentation; C) receiving a first feedback based upon the first presentation from a user; D) applying an evolutionary algorithm to a plurality of characteristics associated with the first plurality of items to generate a first search query, wherein the evolutionary algorithm is based on the first feedback; E) causing the first search query to be executed to generate a second information set comprising a second plurality of items, wherein each item of the second plurality of items is associated with at least one characteristic; F) representing at least some of the second information set in a second presentation; G) in response to a user input, repeating step B and representing at least some of the first information set in the first presentation; H) receiving a second feedback based upon the second presentation from a user; I) applying an evolutionary algorithm to a plurality of characteristics associated with the second plurality of items to generate a second search query, wherein the evolutionary algorithm is based on the second feedback; J) causing the second search query to be executed to generate a third information set comprising a third plurality of items, wherein each item of the third plurality of items is associated with at least one characteristic; and K) representing at least some of the third information set in a third presentation; wherein at least one characteristic associated with each item is chosen from a group comprising: at least one descriptor made available by a search engine or web directory service; at least one tag; at least one keyword; at least one classification-oriented identifier; at least one categorization-oriented identifier; and at least one semantic web-oriented identifier; and wherein at least one characteristic associated with each item is not a word or phrase selected from text displayed as part of the item. 24. The method of claim 1 , further comprising: L) receiving from the user a selection of a first desired item from one of the plurality of items; M) receiving from the user a selection of a second desired item from another of the plurality of items; and N) generating a fourth search query based on the first desired item and the second desired item. | 0.803911 |
9,225,788 | 1 | 6 | 1. A method comprising: identifying, by a social networking system, a first content object with which a first user of the social networking system has interacted; identifying, by the social networking system, a second content object with which a second user of the social networking system has interacted; associating, by the social networking system, a first keyword phrase with the first user, wherein the first keyword phrase is associated with the first content object by conducting a reverse keyword search on the first content object, wherein the reverse keyword search includes searching a social network search pattern database containing information of social network relationships between content objects of the social network system and keyword phrases, and wherein the reverse keyword search receives the first content object or an identifier of the first content object as an input, and generates a keyword phrase that is related to the first content object as an output, and wherein the social network search pattern database is updated by results of a new reverse keyword search; associating, by the social networking system, a second keyword phrase with the second user, wherein the second keyword phrase is associated with the second content object by conducting a reverse keyword search of the second content object; and determining, by the social networking system, a common interest for the first user and the second user of the social networking system toward a topic by identifying a match between the first keyword phrase associated with the first user with the second keyword phrase associated with the second user. | 1. A method comprising: identifying, by a social networking system, a first content object with which a first user of the social networking system has interacted; identifying, by the social networking system, a second content object with which a second user of the social networking system has interacted; associating, by the social networking system, a first keyword phrase with the first user, wherein the first keyword phrase is associated with the first content object by conducting a reverse keyword search on the first content object, wherein the reverse keyword search includes searching a social network search pattern database containing information of social network relationships between content objects of the social network system and keyword phrases, and wherein the reverse keyword search receives the first content object or an identifier of the first content object as an input, and generates a keyword phrase that is related to the first content object as an output, and wherein the social network search pattern database is updated by results of a new reverse keyword search; associating, by the social networking system, a second keyword phrase with the second user, wherein the second keyword phrase is associated with the second content object by conducting a reverse keyword search of the second content object; and determining, by the social networking system, a common interest for the first user and the second user of the social networking system toward a topic by identifying a match between the first keyword phrase associated with the first user with the second keyword phrase associated with the second user. 6. The method of claim 1 , further comprising: notifying the first user that another user of the social networking system in close proximity of the first user shares the mutual interest. | 0.786207 |
10,157,240 | 8 | 10 | 8. The system of claim 1 , the operations further comprising: from a client device, a query that matches one of the query nodes from the generated graph; and wherein: using the generated graph, identifying a specific query node that matches the query received from the client device. | 8. The system of claim 1 , the operations further comprising: from a client device, a query that matches one of the query nodes from the generated graph; and wherein: using the generated graph, identifying a specific query node that matches the query received from the client device. 10. The system of claim 8 , the operations further comprising: receiving the trending queries from devices operated by the users of the publication system. | 0.940749 |
7,942,410 | 8 | 9 | 8. A printing system according to claim 1 , wherein said document transport system includes a document transport roll having an outer surface for contacting and frictionally engaging the associated original document, said outer surface having a cylindrical shape and a radius of curvature, and said plurality of guide surface portions having a curvature between said proximal edge and said distal edge with said curvature being complimentary to said radius of curvature of said document transport roll such that said document transport pathway is at least partially defined therebetween. | 8. A printing system according to claim 1 , wherein said document transport system includes a document transport roll having an outer surface for contacting and frictionally engaging the associated original document, said outer surface having a cylindrical shape and a radius of curvature, and said plurality of guide surface portions having a curvature between said proximal edge and said distal edge with said curvature being complimentary to said radius of curvature of said document transport roll such that said document transport pathway is at least partially defined therebetween. 9. A printing system according to claim 8 , wherein said free end of said at least one document biasing element abuttingly engages said outer surface of said document transport roll. | 0.961587 |
8,589,161 | 3 | 5 | 3. The method of claim 1 , wherein collating the intent determination responses includes: receiving the intent determination responses from the one or more secondary devices in an interleaved manner; and arbitrating among the interleaved intent determination responses received from the one or more secondary devices and the preliminary intent determined on the central device to generate the intent hypothesis associated with the multi-modal natural language input. | 3. The method of claim 1 , wherein collating the intent determination responses includes: receiving the intent determination responses from the one or more secondary devices in an interleaved manner; and arbitrating among the interleaved intent determination responses received from the one or more secondary devices and the preliminary intent determined on the central device to generate the intent hypothesis associated with the multi-modal natural language input. 5. The method of claim 3 , wherein arbitrating among the interleaved intent determination responses and the preliminary intent includes: evaluating, at the central device, the constellation model to determine whether the intent determination capabilities associated with any of the one or more secondary devices include multi-pass speech recognition; and assigning a higher weight to confidence levels associated with any of the interleaved intent determination responses that were generated using multi-pass speech recognition. | 0.883082 |
5,379,057 | 9 | 10 | 9. The self-contained, general-purpose, portable, keyboardless computer of claim 8 wherein said pictograms comprise graphical images of objects and wherein a third library created by said application generator includes a pictogram library of said pictograms. | 9. The self-contained, general-purpose, portable, keyboardless computer of claim 8 wherein said pictograms comprise graphical images of objects and wherein a third library created by said application generator includes a pictogram library of said pictograms. 10. The self-contained, general-purpose, portable, keyboardless computer of claim 9 wherein a fourth library created by said application generator includes a syntax library of predefined message outputs displayed on said screen, and whereby changes to said predefined message outputs are effected by accessing said syntax library and manually entering desired message outputs. | 0.834943 |
8,965,971 | 8 | 9 | 8. The method of claim 1 , wherein the input source corresponds to at least one metadata source and the processing comprises: extracting metadata from the metadata source; and processing the metadata to create extracted information based on the metadata source. | 8. The method of claim 1 , wherein the input source corresponds to at least one metadata source and the processing comprises: extracting metadata from the metadata source; and processing the metadata to create extracted information based on the metadata source. 9. The method of claim 8 , wherein the extracted information comprises GPS coordinates related to the metadata source. | 0.950295 |
8,751,213 | 1 | 12 | 1. A computer implemented method comprising: for each of a plurality of members of a social networking system, maintaining a respective set of connections to other members of the social networking system; selecting, by a computer system and for a text phrase in a first language, a translation of the text phrase from a set of translations of the text phrase in a second language, wherein the selecting is based on one or more actions by one or more other members identified in the set of connections for a particular member maintained by the social networking system, wherein the actions are associated with translations from the set of translations; and presenting the selected translation of the text phrase to the particular member. | 1. A computer implemented method comprising: for each of a plurality of members of a social networking system, maintaining a respective set of connections to other members of the social networking system; selecting, by a computer system and for a text phrase in a first language, a translation of the text phrase from a set of translations of the text phrase in a second language, wherein the selecting is based on one or more actions by one or more other members identified in the set of connections for a particular member maintained by the social networking system, wherein the actions are associated with translations from the set of translations; and presenting the selected translation of the text phrase to the particular member. 12. The method of claim 1 , wherein presenting the selected translation to the member further comprises: displaying a confidence level associated with the selected translation, the confidence level based on actions by the one or more other members connected to the particular member in the social network, the actions associated with translations from the set of translations. | 0.643939 |
9,355,568 | 11 | 14 | 11. A computer program product for implementing within a computer system a method for utilizing an electronic reader to provide output by the electronic reader at a rate corresponding to a user in order to overcome a lack of user-specific focus, the computer program product comprising: a computer-readable, non-transitory medium for providing computer program code means utilized to implement the method, wherein the computer program code means is comprised of executable code for implementing the steps for: providing, by a processor of the computer system, a text for digital access within the computer system, the computer system comprising a tactile input device and a visually perceptible output device; displaying, by the processor, a first page of the text on the visually perceptible output device; and emphasizing, by the processor, a word of the text at a rate determined by the user when the word is selected through the use of the tactile input device, wherein the emphasizing of the word includes at least one of the following: (i) a first mode in which the word is visually distinguished on the visually perceptible output device from a neighboring word when a pointer passes over or near the word from any direction, and in which the word is both audibly and visually emphasized when the pointer specifically passes over or near the word in a reading direction, wherein the executable code requires the pointer to pass over or near the word in the reading direction in order for the word to be both audibly and visually emphasized; and (ii) a second mode in which the word is visually distinguished on the visually perceptible output device from the neighboring word through a first selection process which occurs when the pointer passes over or near the word, and in which the word is audibly emphasized when the word is selected through a second selection process that comprises an action that is different from the first selection process, and wherein a report of words selected through the second selection process is generated. | 11. A computer program product for implementing within a computer system a method for utilizing an electronic reader to provide output by the electronic reader at a rate corresponding to a user in order to overcome a lack of user-specific focus, the computer program product comprising: a computer-readable, non-transitory medium for providing computer program code means utilized to implement the method, wherein the computer program code means is comprised of executable code for implementing the steps for: providing, by a processor of the computer system, a text for digital access within the computer system, the computer system comprising a tactile input device and a visually perceptible output device; displaying, by the processor, a first page of the text on the visually perceptible output device; and emphasizing, by the processor, a word of the text at a rate determined by the user when the word is selected through the use of the tactile input device, wherein the emphasizing of the word includes at least one of the following: (i) a first mode in which the word is visually distinguished on the visually perceptible output device from a neighboring word when a pointer passes over or near the word from any direction, and in which the word is both audibly and visually emphasized when the pointer specifically passes over or near the word in a reading direction, wherein the executable code requires the pointer to pass over or near the word in the reading direction in order for the word to be both audibly and visually emphasized; and (ii) a second mode in which the word is visually distinguished on the visually perceptible output device from the neighboring word through a first selection process which occurs when the pointer passes over or near the word, and in which the word is audibly emphasized when the word is selected through a second selection process that comprises an action that is different from the first selection process, and wherein a report of words selected through the second selection process is generated. 14. The computer program product of claim 11 , further comprising compiling a report of words that are selected through the first selection process. | 0.904021 |
7,779,049 | 1 | 3 | 1. A method of optimizing a regular expression using a system comprising an authoring tool, an optimizer, and a compiler, the method comprising: receiving the regular expression in a single source-level language with the authoring tool of the system; normalizing the regular expression; responsive to normalizing the regular expression, determining at least one optimized form by the optimizer of the system in the same single source-level language for the regular expression; presenting the at least one optimized form for the regular expression to a user with the authoring tool of the system in a source-level representation in the same single source-level language; determining whether the at least one optimized form for the regular expression produces different results than the regular expression; responsive to the at least one optimized form for the regular expression producing different results than the regular expression, presenting the at least one optimized form for the regular expression to the user; and incorporating the at least one optimized form of the regular expression into application logic using the compiler. | 1. A method of optimizing a regular expression using a system comprising an authoring tool, an optimizer, and a compiler, the method comprising: receiving the regular expression in a single source-level language with the authoring tool of the system; normalizing the regular expression; responsive to normalizing the regular expression, determining at least one optimized form by the optimizer of the system in the same single source-level language for the regular expression; presenting the at least one optimized form for the regular expression to a user with the authoring tool of the system in a source-level representation in the same single source-level language; determining whether the at least one optimized form for the regular expression produces different results than the regular expression; responsive to the at least one optimized form for the regular expression producing different results than the regular expression, presenting the at least one optimized form for the regular expression to the user; and incorporating the at least one optimized form of the regular expression into application logic using the compiler. 3. The method of claim 1 wherein the act of determining at least one optimized form comprises: iteratively applying pre-selected transformations to the received regular expression, wherein each iterative transformation produces a candidate optimized regular expression; determining whether each candidate optimized regular expression matches a previously generated optimized regular expression; upon determining that a candidate optimized regular expression matches a previously generated optimized regular expression, discarding the candidate optimized regular expression when the candidate optimized regular expression does not change a result obtained when implementing a collection of regular expressions; and upon completing application of all of the pre-selected transformations without determining that candidate optimized regular expression matches a previously generated optimized regular expression, outputting the candidate regular expression as an optimized regular expression. | 0.500505 |
8,279,466 | 7 | 8 | 7. A document processing method by a document processing system comprising: a document management apparatus adapted to execute a processing task according to a job flow that defines an execution order of a plurality of processing tasks; and a document property management apparatus adapted to manage a property of a document, said method comprising: an input step of inputting the document into the document management apparatus; a job flow processing step of executing each respective processing task that is included in the job flow that has been directed for execution, according to the job flow, on the document that is inputted via the input step, on the document management apparatus; an output step of performing an output processing on the document that is processed by the job flow processing step, according to the job flow, on the document management apparatus; a document property acquiring step of acquiring a property of the document from the document property management apparatus when the document is inputted, on the document management apparatus; a check step of checking, based on the property of the document acquired at said document property acquiring step, what authorization to the document a first user executing the job flow has, and what authorization to the document a second user related to the job flow has, wherein the second user is different from the first user and is an output destination of the document; and a changing step of changing a processing content of the processing task that the job flow processing step executes, or an output content of the output step, according to a check result of the check step, wherein the job flow processing step or the output step operates according to the processing content or the output content, respectively, as changed in the change step. | 7. A document processing method by a document processing system comprising: a document management apparatus adapted to execute a processing task according to a job flow that defines an execution order of a plurality of processing tasks; and a document property management apparatus adapted to manage a property of a document, said method comprising: an input step of inputting the document into the document management apparatus; a job flow processing step of executing each respective processing task that is included in the job flow that has been directed for execution, according to the job flow, on the document that is inputted via the input step, on the document management apparatus; an output step of performing an output processing on the document that is processed by the job flow processing step, according to the job flow, on the document management apparatus; a document property acquiring step of acquiring a property of the document from the document property management apparatus when the document is inputted, on the document management apparatus; a check step of checking, based on the property of the document acquired at said document property acquiring step, what authorization to the document a first user executing the job flow has, and what authorization to the document a second user related to the job flow has, wherein the second user is different from the first user and is an output destination of the document; and a changing step of changing a processing content of the processing task that the job flow processing step executes, or an output content of the output step, according to a check result of the check step, wherein the job flow processing step or the output step operates according to the processing content or the output content, respectively, as changed in the change step. 8. The document processing method according to claim 7 , wherein: the document property that the document property management apparatus manages is a document policy property, and includes an authorization to execute any of browsing, editing, printing, or copying on the document, at a minimum. | 0.622423 |
7,739,602 | 21 | 22 | 21. In an Internet based network with a plurality of registered users, wherein each of said users is either or both of a publisher to publish his information to others and a subscriber to subscribe shared information from others, a computer readable storage medium encoded with instructions, which when loaded into a digital computational device establishes a system for hosting an address card service comprising: means for a publisher to set up an address card having multiple views, each of said views being associated with a different label which, when being clicked, brings said associated view to the front of screen; means for managing said address card, whereby said publisher designates a sharing relationship to one or more groups of subscribers; means for defining a period of time after which a publish offer lapses; means for publishing said address card to a number of selected subscribers based on different sharing relationships; and means for updating local copies of said address card possessed by said subscribers; wherein a subscriber of said publisher's address card can edit published information in a local copy of said address card, said edited published information being overwritten by any update published by said publisher based on an on-going subscription; wherein when said publisher chooses to publish to a recipient who is not a registered member of said Internet based network, a notification along with an image of said publisher's address card is sent to said recipient via e-mail, said notification comprising a first link which enables said recipient to subscribe future modifications of said publisher's address; and wherein each of said views has metadata describing sharing styles, as well as version, creation date and size, wherein each sharing style corresponds to a specific sharing relationship of the publisher. | 21. In an Internet based network with a plurality of registered users, wherein each of said users is either or both of a publisher to publish his information to others and a subscriber to subscribe shared information from others, a computer readable storage medium encoded with instructions, which when loaded into a digital computational device establishes a system for hosting an address card service comprising: means for a publisher to set up an address card having multiple views, each of said views being associated with a different label which, when being clicked, brings said associated view to the front of screen; means for managing said address card, whereby said publisher designates a sharing relationship to one or more groups of subscribers; means for defining a period of time after which a publish offer lapses; means for publishing said address card to a number of selected subscribers based on different sharing relationships; and means for updating local copies of said address card possessed by said subscribers; wherein a subscriber of said publisher's address card can edit published information in a local copy of said address card, said edited published information being overwritten by any update published by said publisher based on an on-going subscription; wherein when said publisher chooses to publish to a recipient who is not a registered member of said Internet based network, a notification along with an image of said publisher's address card is sent to said recipient via e-mail, said notification comprising a first link which enables said recipient to subscribe future modifications of said publisher's address; and wherein each of said views has metadata describing sharing styles, as well as version, creation date and size, wherein each sharing style corresponds to a specific sharing relationship of the publisher. 22. The computer readable storage medium of claim 21 , wherein said address card comprises a page for centrally entering said publisher's contact information, and wherein any of said entered contact information is automatically populated to one or more of said views. | 0.806522 |
8,332,909 | 1 | 6 | 1. One or more computer-readable storage media comprising computer-executable instructions for generating software restriction policy rules, the computer-executable instructions directed to steps comprising: receiving a user's specification of preferred types of software restriction policy rules that are preferred by the user; receiving the user's specification of a metadata source; determining a software restriction policy rule for each entry in the metadata source in accordance with the specified preferred types of software restriction policy rules; determining if the software restriction policy rule is duplicative of a previously generated software restriction policy rule; determining if the software restriction policy rule is an exception to the previously generated software restriction policy rule; generating the software restriction policy rule determining reveals that the software restriction policy rule is neither duplicative of the previously generated software restriction policy rule nor is the exception to the previously generated software restriction policy rule; and generating the exception to the previously generated software restriction policy rule instead of generating software restriction policy rule if the determining reveals that the software restriction policy rule is not duplicative of the previously generated software restriction policy rule but is the exception to the previously generated software restriction policy rule. | 1. One or more computer-readable storage media comprising computer-executable instructions for generating software restriction policy rules, the computer-executable instructions directed to steps comprising: receiving a user's specification of preferred types of software restriction policy rules that are preferred by the user; receiving the user's specification of a metadata source; determining a software restriction policy rule for each entry in the metadata source in accordance with the specified preferred types of software restriction policy rules; determining if the software restriction policy rule is duplicative of a previously generated software restriction policy rule; determining if the software restriction policy rule is an exception to the previously generated software restriction policy rule; generating the software restriction policy rule determining reveals that the software restriction policy rule is neither duplicative of the previously generated software restriction policy rule nor is the exception to the previously generated software restriction policy rule; and generating the exception to the previously generated software restriction policy rule instead of generating software restriction policy rule if the determining reveals that the software restriction policy rule is not duplicative of the previously generated software restriction policy rule but is the exception to the previously generated software restriction policy rule. 6. The computer-readable storage media of claim 1 , wherein the metadata source specified by the user comprises a folder; and wherein further the each entry in the metadata source comprises an executable file in the folder. | 0.899095 |
8,024,715 | 1 | 12 | 1. A method for transforming code to detect transient faults, comprising: translating binary code to an intermediate language code; identifying an instruction of interest in the intermediate language code; inserting reliability instructions in the intermediate language code to validate register values in memory accessed by the instruction of interest; and translating the intermediate language code to binary code. | 1. A method for transforming code to detect transient faults, comprising: translating binary code to an intermediate language code; identifying an instruction of interest in the intermediate language code; inserting reliability instructions in the intermediate language code to validate register values in memory accessed by the instruction of interest; and translating the intermediate language code to binary code. 12. The method of claim 1 , wherein the reliability instructions are inserted at locations specified by a user. | 0.836283 |
9,692,894 | 13 | 22 | 13. A method of generating a customer satisfaction score based on behavioral assessment data across one or more recorded communications, which comprises: analyzing one or more communications between a customer and an agent, wherein the analyzing comprises applying a linguistic-based psychological behavioral model to each communication to determine a personality type of the customer by analyzing behavioral characteristics of the customer based on the one or more communications; selecting at least one filter criterion which comprises a customer, an agent, a team, or a call type; calculating a customer satisfaction score using the at least one selected filter criterion across a selected time interval and based on the one or more communications; and displaying a report including the calculated customer satisfaction score to a user that matches the at least one selected filter criterion for the selected time interval. | 13. A method of generating a customer satisfaction score based on behavioral assessment data across one or more recorded communications, which comprises: analyzing one or more communications between a customer and an agent, wherein the analyzing comprises applying a linguistic-based psychological behavioral model to each communication to determine a personality type of the customer by analyzing behavioral characteristics of the customer based on the one or more communications; selecting at least one filter criterion which comprises a customer, an agent, a team, or a call type; calculating a customer satisfaction score using the at least one selected filter criterion across a selected time interval and based on the one or more communications; and displaying a report including the calculated customer satisfaction score to a user that matches the at least one selected filter criterion for the selected time interval. 22. The method of claim 13 , wherein the report displayed comprises a program report, a detail level report, a non-analyzed call report, a call type report, a customer satisfaction report, a report based on customer satisfaction, a report based on agent performance, or a combination thereof. | 0.811856 |
8,756,053 | 7 | 8 | 7. The method according to claim 1 , wherein the updating comprises: calculating an optimal value of a link generation parameter, τ. | 7. The method according to claim 1 , wherein the updating comprises: calculating an optimal value of a link generation parameter, τ. 8. The method according to claim 7 , wherein the optimal value of the link generation parameter τ is a value of τ that maximize the log likelihood of the input data. | 0.959717 |
10,127,221 | 1 | 2 | 1. A method for detecting ruby text in a fixed format document, the method comprising: receiving, at a parser, a fixed format document containing one or more lines of text on one or more pages; detecting, by a line detection engine, one or more lines in the fixed format document containing one or more attributes of a ruby line; retaining the one or more lines in the fixed format document containing one or more attributes of a ruby line as ruby line candidates and a line successive to the one or more lines as ruby base line candidates; analyzing, by a document processor, the ruby line candidate for finding one or more ruby texts contained in the ruby line candidate; matching the one or more ruby texts with a corresponding ruby base text in a successive ruby base line candidate for reconstruction in a flow format document; and reconstructing, by a serializer, the fixed format document to a flow format document containing the matched one or more ruby texts and corresponding ruby base text. | 1. A method for detecting ruby text in a fixed format document, the method comprising: receiving, at a parser, a fixed format document containing one or more lines of text on one or more pages; detecting, by a line detection engine, one or more lines in the fixed format document containing one or more attributes of a ruby line; retaining the one or more lines in the fixed format document containing one or more attributes of a ruby line as ruby line candidates and a line successive to the one or more lines as ruby base line candidates; analyzing, by a document processor, the ruby line candidate for finding one or more ruby texts contained in the ruby line candidate; matching the one or more ruby texts with a corresponding ruby base text in a successive ruby base line candidate for reconstruction in a flow format document; and reconstructing, by a serializer, the fixed format document to a flow format document containing the matched one or more ruby texts and corresponding ruby base text. 2. The method of claim 1 , wherein detecting one or more lines in the fixed format document containing one or more attributes of a ruby line comprises: analyzing the one or more lines of text for finding an empty line or a line consisting of whitespace characters; if a line of text is empty or consists of whitespace characters, discarding the line of text as a ruby line candidate or as a ruby base line candidate. | 0.678516 |
8,392,666 | 11 | 14 | 11. A method performed by a hardware apparatus for detecting a load-store collision within a microprocessor between a load operation and an older store operation each of which accesses data in the same cache line, the method comprising: determining whether the data specified by the load operation and the data specified by the store operation begin in the same word of the cache line, wherein a word comprises a plurality of bytes; using byte masks to detect the load-store collision, if the data specified by the load operation and the data specified by the store operation begin in the same word of the cache line; and using word masks to detect the load-store collision, if the data specified by the load operation and the data specified by the store operation do not begin in the same word of the cache line. | 11. A method performed by a hardware apparatus for detecting a load-store collision within a microprocessor between a load operation and an older store operation each of which accesses data in the same cache line, the method comprising: determining whether the data specified by the load operation and the data specified by the store operation begin in the same word of the cache line, wherein a word comprises a plurality of bytes; using byte masks to detect the load-store collision, if the data specified by the load operation and the data specified by the store operation begin in the same word of the cache line; and using word masks to detect the load-store collision, if the data specified by the load operation and the data specified by the store operation do not begin in the same word of the cache line. 14. The method of claim 11 , wherein the number of bits of the word masks is equal to the number of words of the largest memory operation supported by the microarchitecture of the microprocessor. | 0.848837 |
7,853,629 | 17 | 18 | 17. The method according to claim 15 , further comprising the steps of: determining at least one task associated with the document based on the stored document profile and at least one rule. | 17. The method according to claim 15 , further comprising the steps of: determining at least one task associated with the document based on the stored document profile and at least one rule. 18. The method according to claim 17 , further comprising the step of: reporting the at least one task as complete. | 0.968285 |
8,275,771 | 17 | 27 | 17. A method performed by data processing apparatus, the method comprising: selecting a non-text content item that is associated with each of a plurality of web pages; receiving label data that includes a set of initial labels for the non-text content item and a resource identifier for each initial label, wherein each initial label includes one or more words; selecting one or more sets of matching web pages from the plurality of web pages, wherein each set of matching web pages includes two or more matching web pages; grouping, for each set of matching web pages, initial labels that are associated with the set of matching web pages into a separate initial label group that corresponds to the set of matching web pages; selecting one or more sets of matching labels, wherein each set of matching labels includes two or more initial labels; grouping each set of matching labels into a separate initial label group that corresponds to the set of matching labels; and selecting, as a final label for the non-text content item, an n-gram of one or more words that are included in at least a threshold number of separate initial label groups. | 17. A method performed by data processing apparatus, the method comprising: selecting a non-text content item that is associated with each of a plurality of web pages; receiving label data that includes a set of initial labels for the non-text content item and a resource identifier for each initial label, wherein each initial label includes one or more words; selecting one or more sets of matching web pages from the plurality of web pages, wherein each set of matching web pages includes two or more matching web pages; grouping, for each set of matching web pages, initial labels that are associated with the set of matching web pages into a separate initial label group that corresponds to the set of matching web pages; selecting one or more sets of matching labels, wherein each set of matching labels includes two or more initial labels; grouping each set of matching labels into a separate initial label group that corresponds to the set of matching labels; and selecting, as a final label for the non-text content item, an n-gram of one or more words that are included in at least a threshold number of separate initial label groups. 27. The method of claim 17 , wherein selecting sets of matching web pages comprises selecting web pages corresponding to a same domain. | 0.854526 |
9,460,715 | 9 | 10 | 9. One or more non-transitory computer-readable media as recited in claim 8 , the acts further comprising identifying a characteristic, other than the second voice signature associated with the second speech, and wherein the calculating further comprises calculating the confidence level with reference to the characteristic. | 9. One or more non-transitory computer-readable media as recited in claim 8 , the acts further comprising identifying a characteristic, other than the second voice signature associated with the second speech, and wherein the calculating further comprises calculating the confidence level with reference to the characteristic. 10. One or more non-transitory computer-readable media as recited in claim 9 , wherein calculating the confidence level with reference to the characteristic comprises calculating a similarity between the characteristic and a corresponding characteristic associated with the user. | 0.925321 |
9,286,358 | 1 | 3 | 1. A processor-implemented method for generating and utilizing a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, the processor-implemented method comprising: associating, by a processor, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; associating, by the processor, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; and constructing, by the processor, a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same context object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different non-contextual data objects. | 1. A processor-implemented method for generating and utilizing a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, the processor-implemented method comprising: associating, by a processor, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; associating, by the processor, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; and constructing, by the processor, a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same context object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different non-contextual data objects. 3. The processor-implemented method of claim 1 , wherein the specific subject-matter for a particular data store in the data structure is exclusive to only said particular data store. | 0.812883 |
8,750,630 | 7 | 9 | 7. The method according to claim 6 , further comprising invalidating all feature watermarks in a sub-chain of the hierarchical relationship that emanate from the invalidated parent. | 7. The method according to claim 6 , further comprising invalidating all feature watermarks in a sub-chain of the hierarchical relationship that emanate from the invalidated parent. 9. The method according to claim 7 , further comprising re-preprocessing all data content associated with parents and children in the hierarchical relationship that have invalidated feature watermarks. | 0.940036 |
8,149,841 | 7 | 8 | 7. The method of claim 1 , wherein parsing comprises at least one of pattern matching and comparing variables. | 7. The method of claim 1 , wherein parsing comprises at least one of pattern matching and comparing variables. 8. The method of claim 7 , further comprising at least one of token and metadata declaration, token and pattern matching, logic functions and variable operations, and/or metadata registration and extraction. | 0.880623 |
8,566,301 | 19 | 20 | 19. The system of claim 17 , wherein the user has control over the manner in which the plurality of revision frames are created and presented. | 19. The system of claim 17 , wherein the user has control over the manner in which the plurality of revision frames are created and presented. 20. The system of claim 19 , wherein an input/output (“IO”) device controls a graphical control including a scroll bar, and wherein manipulation of the scroll bar advances or retards the sequence of the revision frames. | 0.917545 |
8,638,465 | 1 | 2 | 1. An image forming apparatus, comprising: a processor; a storage unit that a text language processing program has been stored; an operation panel; a communication interface; and an input unit; wherein a user application is stored in the storage unit, and the user application includes descriptions on (a) a conditioned reset statement with a first condition expression that includes an input value from the input unit and (b) a pair of (b1) at least one process executing statement and (b2) an attribution of an icon to be displayed on either a remote console via the communication interface or the operation panel; and the text language processing program is configured to cause the processor (a) to interpret the user application, (b) to determine whether the first condition expression is satisfied or not, (c) to detect a user operation to the icon, if a result of the determination is a predetermined one, and (d) upon detecting the user operation, to execute the at least one process executing statement. | 1. An image forming apparatus, comprising: a processor; a storage unit that a text language processing program has been stored; an operation panel; a communication interface; and an input unit; wherein a user application is stored in the storage unit, and the user application includes descriptions on (a) a conditioned reset statement with a first condition expression that includes an input value from the input unit and (b) a pair of (b1) at least one process executing statement and (b2) an attribution of an icon to be displayed on either a remote console via the communication interface or the operation panel; and the text language processing program is configured to cause the processor (a) to interpret the user application, (b) to determine whether the first condition expression is satisfied or not, (c) to detect a user operation to the icon, if a result of the determination is a predetermined one, and (d) upon detecting the user operation, to execute the at least one process executing statement. 2. The image forming apparatus according to claim 1 , wherein: the text language processing program is further configured to cause the processor to display the icon based on the attribution of the icon on either the operation panel and the remote console, and to delete the icon on either the operation panel or the remote console after the at least one process executing statement is executed. | 0.685304 |
8,631,071 | 10 | 13 | 10. A computer system comprising: one or more processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to semantically search for available computing resources for a plurality of businesses conducting commerce in different industries, the available computing resources being searched using an industry model repository (IMR) architecture system comprising: (a) a first layer of abstraction comprising business specific model assets, (b) a second layer of abstraction comprising a plurality of topic maps, each of the topic maps comprising a set of topics of capturing characteristics and relationships among the business specific model assets and other topics, associations having a specific association type and association role played by a designated topic, and occurrences defining business specific instances of the business specific model assets, each of the occurrences having an occurrence type that links to a specific one of the topics and an occurrence locator indicating an accessible network location in a federated asset repository where a corresponding specific instance is stored; and (c) a third layer of abstraction comprising service oriented architecture (“SOA”) program services that utilize the topic maps of the second layer to semantically search for the business specific model assets, wherein one or more of the services of the third layer of abstraction and linkages between the topic maps of the second layer of abstraction change over time as indicated by different versions of the industry model repository (IMR) of the second layer, wherein the searching step searches the computing resources based on linkages specific to a particular one of the different versions of the industry model repository (IMR), wherein a plurality of different versions are concurrently active at runtime and are used by different ones of the plurality of different businesses to access the business specific model assets of the first layer using the SOA program services of the third layer; a first computing device executing a first SOA service available for the searching and use at a first time when a first version of the different versions of the industry model repository (IMR) is available to the first computing device and a second SOA available for the searching and use at a second, later time using a second version of the industry model repository but not available for the searching and use at the first time; a second computing device executing the second SOA service at approximately the first time when the first version of the industry model repository is available to the second computing device, the second computing device executing the second SOA service at approximately the second time; and at least one computing device of the industry model repository (IMR) enabling the first computing device to execute the first SOA service at the first time, enabling the first computing device to execute the second SOA at the second time, enabling the second computing device to execute the second SOA service at approximately the first and at approximately the second time, thereby permitting concurrent use of different versions of the industry model repository (IMR) by different devices without modification or redeployment of the industry model repository (IMR). | 10. A computer system comprising: one or more processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to semantically search for available computing resources for a plurality of businesses conducting commerce in different industries, the available computing resources being searched using an industry model repository (IMR) architecture system comprising: (a) a first layer of abstraction comprising business specific model assets, (b) a second layer of abstraction comprising a plurality of topic maps, each of the topic maps comprising a set of topics of capturing characteristics and relationships among the business specific model assets and other topics, associations having a specific association type and association role played by a designated topic, and occurrences defining business specific instances of the business specific model assets, each of the occurrences having an occurrence type that links to a specific one of the topics and an occurrence locator indicating an accessible network location in a federated asset repository where a corresponding specific instance is stored; and (c) a third layer of abstraction comprising service oriented architecture (“SOA”) program services that utilize the topic maps of the second layer to semantically search for the business specific model assets, wherein one or more of the services of the third layer of abstraction and linkages between the topic maps of the second layer of abstraction change over time as indicated by different versions of the industry model repository (IMR) of the second layer, wherein the searching step searches the computing resources based on linkages specific to a particular one of the different versions of the industry model repository (IMR), wherein a plurality of different versions are concurrently active at runtime and are used by different ones of the plurality of different businesses to access the business specific model assets of the first layer using the SOA program services of the third layer; a first computing device executing a first SOA service available for the searching and use at a first time when a first version of the different versions of the industry model repository (IMR) is available to the first computing device and a second SOA available for the searching and use at a second, later time using a second version of the industry model repository but not available for the searching and use at the first time; a second computing device executing the second SOA service at approximately the first time when the first version of the industry model repository is available to the second computing device, the second computing device executing the second SOA service at approximately the second time; and at least one computing device of the industry model repository (IMR) enabling the first computing device to execute the first SOA service at the first time, enabling the first computing device to execute the second SOA at the second time, enabling the second computing device to execute the second SOA service at approximately the first and at approximately the second time, thereby permitting concurrent use of different versions of the industry model repository (IMR) by different devices without modification or redeployment of the industry model repository (IMR). 13. The computer system of claim 10 , further comprising: program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to determine from stored differences between the first version and the second version of the industry model repository that input parameters differ between a first SOA service for handling a received request and the second SOA version of a corresponding SOA service the first SOA being compliant with a first version of the IMR and the corresponding SOA service being compliant with the second version of the IMR, said corresponding SOA service being an updated version of the SOA service; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, at the second layer of abstraction, receive a message from the first layer or from the second layer, said message having input parameters compliant with the first SOA and not complaint with the second SOA, at runtime, programs executing at the second layer of abstraction dynamically modifying the message to be compatible with the corresponding SOA service using the stored differences; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to convey the modified message to the corresponding SOA service, which executes in the third layer of abstraction in response to receiving the modified message. | 0.500301 |
9,020,911 | 10 | 18 | 10. A computer system for matching names, comprising: a processor; and a storage device coupled to the processor, wherein the storage device has stored thereon a program, and wherein the processor is configured to execute instructions of the program to perform operations, wherein the operations comprise: creating a first bitmap distribution of character n-grams distributed into bitmap positions in descending order of frequency of occurrence of the character n-grams in a set of names based on bitmap positions with a lowest cumulative frequency, wherein at least two distinct character n-grams are assigned to a same bitmap position of the bitmap positions; creating a second bitmap distribution of the character n-grams distributed into the bitmap positions so that the at least two distinct character n-grams are assigned to different bitmap positions and so that any overlapping character n-grams in the first bitmap distribution do not overlap in the second bitmap distribution; using the first bitmap distribution, determining whether a first bitmap signature of a query name and a second bitmap signature of a target name in a set of names have a number of character n-grams overlapping that meet or exceed a first configurable threshold to generate a first preliminary value; using the second bitmap distribution, determining whether a third bitmap signature of the query name and a fourth bitmap signature of the target name have a number of character n-grams overlapping that meet or exceed a second configurable threshold to generate a second preliminary value; and in response to determining that a logical operation applied to the first preliminary value and the second preliminary value results in a value of true, determining that the query name and the target name are to be processed for further comparisons. | 10. A computer system for matching names, comprising: a processor; and a storage device coupled to the processor, wherein the storage device has stored thereon a program, and wherein the processor is configured to execute instructions of the program to perform operations, wherein the operations comprise: creating a first bitmap distribution of character n-grams distributed into bitmap positions in descending order of frequency of occurrence of the character n-grams in a set of names based on bitmap positions with a lowest cumulative frequency, wherein at least two distinct character n-grams are assigned to a same bitmap position of the bitmap positions; creating a second bitmap distribution of the character n-grams distributed into the bitmap positions so that the at least two distinct character n-grams are assigned to different bitmap positions and so that any overlapping character n-grams in the first bitmap distribution do not overlap in the second bitmap distribution; using the first bitmap distribution, determining whether a first bitmap signature of a query name and a second bitmap signature of a target name in a set of names have a number of character n-grams overlapping that meet or exceed a first configurable threshold to generate a first preliminary value; using the second bitmap distribution, determining whether a third bitmap signature of the query name and a fourth bitmap signature of the target name have a number of character n-grams overlapping that meet or exceed a second configurable threshold to generate a second preliminary value; and in response to determining that a logical operation applied to the first preliminary value and the second preliminary value results in a value of true, determining that the query name and the target name are to be processed for further comparisons. 18. The computer system of claim 10 , wherein the minimum number of matching preliminary values is equal to at least a half of a number of total distinct character n-gram distributions. | 0.890273 |
4,489,435 | 7 | 14 | 7. An apparatus for recognizing at least one keyword in an audio speech signal, each keyword being characterized by a template having at least one target pattern, each pattern representing at least two short term power spectra, and each target pattern having associated therewith at least two required dwell time positions and at least one optional dwell time position, the recognition apparatus comprising, means for forming, at a repetitive frame time rate, a sequence of input frame patterns from, and representing, said audio signal, each frame pattern corresponding to a said frame time, and successive frame patterns corresponding to successive dwell time positions, means for generating a numerical measure of the similarity of each said frame pattern with each of said target patterns, means for accumulating, for each said target pattern required dwell time position and each said target pattern optional dwell time position, and using said numerical measure of the similarity of the just formed frame pattern and said each target pattern, a numerical value representing the alignment of the just formed audio representing frame pattern with the respective target pattern dwell time position, and means for generating a recognition decision, based upon the accumulated numerical values, when a predetermined sequence occurs in said audio signal. | 7. An apparatus for recognizing at least one keyword in an audio speech signal, each keyword being characterized by a template having at least one target pattern, each pattern representing at least two short term power spectra, and each target pattern having associated therewith at least two required dwell time positions and at least one optional dwell time position, the recognition apparatus comprising, means for forming, at a repetitive frame time rate, a sequence of input frame patterns from, and representing, said audio signal, each frame pattern corresponding to a said frame time, and successive frame patterns corresponding to successive dwell time positions, means for generating a numerical measure of the similarity of each said frame pattern with each of said target patterns, means for accumulating, for each said target pattern required dwell time position and each said target pattern optional dwell time position, and using said numerical measure of the similarity of the just formed frame pattern and said each target pattern, a numerical value representing the alignment of the just formed audio representing frame pattern with the respective target pattern dwell time position, and means for generating a recognition decision, based upon the accumulated numerical values, when a predetermined sequence occurs in said audio signal. 14. The method of claim 7 wherein the decision generating and accumulating means comprise means for directing the transfer of accumulated scores in response to a syntax generating element. | 0.906 |
7,474,654 | 1 | 5 | 1. A method, comprising: receiving a packet having a plurality of fields in a header of the packet; defining at least one packet classification rule using a command-line interface (CLI), wherein the at least one packet classification rule comprises a structured part and an unstructured part, the structured part having a predetermined logical operator relation between at least two of the plurality of fields, the unstructured part having a user configurable relation among the plurality of fields; performing a first classification of the packet based on the structured part of the at least one packet classification rule; using the predetermined logical operator relation between the at least two of the plurality of fields for the structured part in the first classification to provide a first classification result; performing a second classification of the packet based on the unstructured part of the at least one packet classification rule and the first classification result; and using the user configurable relation among the plurality of fields with keywords identifying values in the plurality of fields for the unstructured part in the second classification, wherein the first and second classifications form a classification of the packet. | 1. A method, comprising: receiving a packet having a plurality of fields in a header of the packet; defining at least one packet classification rule using a command-line interface (CLI), wherein the at least one packet classification rule comprises a structured part and an unstructured part, the structured part having a predetermined logical operator relation between at least two of the plurality of fields, the unstructured part having a user configurable relation among the plurality of fields; performing a first classification of the packet based on the structured part of the at least one packet classification rule; using the predetermined logical operator relation between the at least two of the plurality of fields for the structured part in the first classification to provide a first classification result; performing a second classification of the packet based on the unstructured part of the at least one packet classification rule and the first classification result; and using the user configurable relation among the plurality of fields with keywords identifying values in the plurality of fields for the unstructured part in the second classification, wherein the first and second classifications form a classification of the packet. 5. The method of claim 1 , wherein the at least one packet classification rule comprises Modular Quality of Service Command Line Interface (MQC) class maps. | 0.860215 |
9,690,779 | 3 | 5 | 3. A pseudo natural language based dialog device ( 5 ) of claim 1 , wherein at least one of said semantic-logic-representation devices ( 1 ) works jointly with a registry or index system, whereby said registry has one or more semantics-to-language converting devices ( 2 ) registered for each one or set of said semantic-logic-representation devices ( 1 ); in accordance to services provided by the said registry, said conversion functions ( 11 ) is capable of being locating and delegating its implementation to said one or more semantics-to-language converting devices. | 3. A pseudo natural language based dialog device ( 5 ) of claim 1 , wherein at least one of said semantic-logic-representation devices ( 1 ) works jointly with a registry or index system, whereby said registry has one or more semantics-to-language converting devices ( 2 ) registered for each one or set of said semantic-logic-representation devices ( 1 ); in accordance to services provided by the said registry, said conversion functions ( 11 ) is capable of being locating and delegating its implementation to said one or more semantics-to-language converting devices. 5. A pseudo natural language based dialog device ( 5 ) of claim 3 , wherein a process of construction, registration or indexing of each said one or more semantics-to-language converting devices ( 2 ) is based on a constituent component that is predicate of a sentence or a property of a conceptual object. | 0.956774 |
9,225,679 | 10 | 12 | 10. The system of claim 1 , wherein the server is further configured to: receive a subscriber identification with the message; and provide the information to the VCS based on the subscriber identification. | 10. The system of claim 1 , wherein the server is further configured to: receive a subscriber identification with the message; and provide the information to the VCS based on the subscriber identification. 12. The system of claim 10 , wherein the subscriber is determined by an Account Manager Service database. | 0.897461 |
9,250,706 | 14 | 15 | 14. The method for signing a document with a unique signature as described in claim 12 , wherein the step of storing securely the unique signature electronically is followed by a step of registering the unique signature as a legal signature of the user. | 14. The method for signing a document with a unique signature as described in claim 12 , wherein the step of storing securely the unique signature electronically is followed by a step of registering the unique signature as a legal signature of the user. 15. The method for signing a document with a unique signature as described in claim 14 , wherein the continuous line has a plurality of segments, each having a span, and wherein the step of drawing a line on screen by inputting the sequence of the symbols in the array includes a step of choosing patterns and colors to fill the spans of the segments. | 0.843304 |
8,380,840 | 1 | 11 | 1. A method comprising: receiving, by a Session Initiation Protocol (SIP) server, first call event information, associated with a first call event, from a first module, the first call event information from the first module being processed by the first module using a first type of proprietary application; receiving, by the SIP server, second call event information, associated with a second call event, from a second module, the second call event information from the second module being processed by the second module using a second type of proprietary application, the second type of proprietary application being different from the first type of proprietary application; converting, by the SIP server, the first call event information from a first format associated with the first type of proprietary application into a first Extensible Markup Language (XML) document to generate a first call event record for the first call event information; converting, by the SIP server, the second call event information from a second format associated with the second type of proprietary application into a second XML document to generate a second call event record for the second call event information; creating, by the SIP server, an XML call event file based on the first XML document and the second XML document, creating the XML call event file including: generating a first section that includes data identifying relationships associated with one or more tags included in the XML call event file, generating a second section that includes data identifying the SIP server, generating third section that identifies a type of a first message associated with the first call event and a type of a second message associated with the second call event record, and generating a fourth section that includes information associated with a processing of the first message and information associated with a processing of the second message; and monitoring, by the SIP server, network traffic associated with the SIP server based on the XML call event file using a third type of proprietary application that is different than the first type of proprietary application and the second type of proprietary application. | 1. A method comprising: receiving, by a Session Initiation Protocol (SIP) server, first call event information, associated with a first call event, from a first module, the first call event information from the first module being processed by the first module using a first type of proprietary application; receiving, by the SIP server, second call event information, associated with a second call event, from a second module, the second call event information from the second module being processed by the second module using a second type of proprietary application, the second type of proprietary application being different from the first type of proprietary application; converting, by the SIP server, the first call event information from a first format associated with the first type of proprietary application into a first Extensible Markup Language (XML) document to generate a first call event record for the first call event information; converting, by the SIP server, the second call event information from a second format associated with the second type of proprietary application into a second XML document to generate a second call event record for the second call event information; creating, by the SIP server, an XML call event file based on the first XML document and the second XML document, creating the XML call event file including: generating a first section that includes data identifying relationships associated with one or more tags included in the XML call event file, generating a second section that includes data identifying the SIP server, generating third section that identifies a type of a first message associated with the first call event and a type of a second message associated with the second call event record, and generating a fourth section that includes information associated with a processing of the first message and information associated with a processing of the second message; and monitoring, by the SIP server, network traffic associated with the SIP server based on the XML call event file using a third type of proprietary application that is different than the first type of proprietary application and the second type of proprietary application. 11. The method of claim 1 , where one of the first call event or the second call event comprises receiving a SIP proxying response message. | 0.90427 |
7,966,163 | 1 | 5 | 1. A computer-implemented system for simulating a scenario involving at least one participant, the computer-implemented system comprising: a role assigned to the participant; a user interface associated with the participant and with the role, the user interface configured to allow the participant to select from a plurality of choices upon the role being presented with a plurality of choices; decision logic configured to present a decision to the role upon the decision logic being triggered, the decision comprising a plurality of choices; a first event configured to be activated upon accumulating a quantity of points over a first threshold; and a second event configured to be activated upon accumulating a quantity of points over a second threshold; whereby the first event and the second event are simulated as part of the scenario upon activation. | 1. A computer-implemented system for simulating a scenario involving at least one participant, the computer-implemented system comprising: a role assigned to the participant; a user interface associated with the participant and with the role, the user interface configured to allow the participant to select from a plurality of choices upon the role being presented with a plurality of choices; decision logic configured to present a decision to the role upon the decision logic being triggered, the decision comprising a plurality of choices; a first event configured to be activated upon accumulating a quantity of points over a first threshold; and a second event configured to be activated upon accumulating a quantity of points over a second threshold; whereby the first event and the second event are simulated as part of the scenario upon activation. 5. The system of claim 1 further comprising message logic configured to present a message to the role upon the message logic being triggered, wherein the second event is configured to activate the message logic upon the second event being activated. | 0.765977 |
10,133,790 | 8 | 9 | 8. The system of claim 7 , wherein selecting candidate resources that are associated with the topic comprises identifying a set of candidate resources from a plurality of resources based on an expertise level score, for the determined topic, of each resource of the plurality of resources. | 8. The system of claim 7 , wherein selecting candidate resources that are associated with the topic comprises identifying a set of candidate resources from a plurality of resources based on an expertise level score, for the determined topic, of each resource of the plurality of resources. 9. The system of claim 8 , wherein the one or more contextual factors correspond to one or more demographic characteristics. | 0.970164 |
9,367,583 | 1 | 2 | 1. A method of evaluating a performance of a content group via a computer network, the method comprising: receiving, by a processor executing on a data processing system, a request to display performance of a content group of a content provider; accessing a data structure storing, in a memory element, a plurality of keywords, a quality metric for each keyword, and an impression count for each keyword; identifying, by the data processing system, one or more keywords of the plurality of keywords of the data structure corresponding to the content group of the content provider, obtaining, for each of the one or more keywords, via the data structure, the quality metric and the impression count associated with the content group of the content provider; determining, for the content group, a performance score based on a weighted average of the quality metric and impression count of each of the one or more keywords of the plurality of keywords by performing a summation of products of the quality metric and impression count of each of the one or more keywords of the plurality of keywords and dividing the summation by a sum of the impression count of each of the one or more keywords of the plurality of keywords; and transmitting, for display on a user device, the performance score. | 1. A method of evaluating a performance of a content group via a computer network, the method comprising: receiving, by a processor executing on a data processing system, a request to display performance of a content group of a content provider; accessing a data structure storing, in a memory element, a plurality of keywords, a quality metric for each keyword, and an impression count for each keyword; identifying, by the data processing system, one or more keywords of the plurality of keywords of the data structure corresponding to the content group of the content provider, obtaining, for each of the one or more keywords, via the data structure, the quality metric and the impression count associated with the content group of the content provider; determining, for the content group, a performance score based on a weighted average of the quality metric and impression count of each of the one or more keywords of the plurality of keywords by performing a summation of products of the quality metric and impression count of each of the one or more keywords of the plurality of keywords and dividing the summation by a sum of the impression count of each of the one or more keywords of the plurality of keywords; and transmitting, for display on a user device, the performance score. 2. The method of claim 1 , wherein the data structure comprises a historical quality metric and a corresponding historical impression count for each of the plurality of keywords, and the method comprises: generating a second performance score based on the historical quality metric and corresponding impression count; and determining, based on a comparison of the performance score with the second performance score, that the content performance of the content group is improving. | 0.54023 |
9,888,279 | 11 | 12 | 11. The method of claim 1 , further comprising: displaying the plurality of video segments; receiving a selection of one of the plurality of video segments; and displaying the one of the plurality of video segments. | 11. The method of claim 1 , further comprising: displaying the plurality of video segments; receiving a selection of one of the plurality of video segments; and displaying the one of the plurality of video segments. 12. The method of claim 11 , further comprising adding supplemental content in association with the one of the plurality of video segments based on a feature associated with the one of the plurality of video segments. | 0.945993 |
9,767,094 | 1 | 7 | 1. A method, in a data processing system having a processor and a memory storing a store of semantic types and instructions for implementing a natural language processing engine for generating a question/answer pair list with semantically equivalent variants, the method comprising: generating a user interface for generating a question/answer pair list; receiving user input in the user interface specifying a question and an answer term and specifying an answer type from a list of previously created answer types, wherein the input term comprises the answer term; identifying, by the natural language processing engine executing on the data processing system, a semantic type of the answer term based on the store of semantic types; performing, by the natural language processing engine, a type-specific series of rule-based expansions of the answer term based on the identified semantic type of the answer term of the answer term; adding, by the natural language processing engine, at least one semantically equivalent variant from the set of semantically equivalent variants of the answer term in association with the specified question to the question/answer pair list to form an expanded question/answer pair list; and training, by the natural language processing engine, a question answering machine learning model for a question answering cognitive system using the expanded question/answer pair list as ground truth. | 1. A method, in a data processing system having a processor and a memory storing a store of semantic types and instructions for implementing a natural language processing engine for generating a question/answer pair list with semantically equivalent variants, the method comprising: generating a user interface for generating a question/answer pair list; receiving user input in the user interface specifying a question and an answer term and specifying an answer type from a list of previously created answer types, wherein the input term comprises the answer term; identifying, by the natural language processing engine executing on the data processing system, a semantic type of the answer term based on the store of semantic types; performing, by the natural language processing engine, a type-specific series of rule-based expansions of the answer term based on the identified semantic type of the answer term of the answer term; adding, by the natural language processing engine, at least one semantically equivalent variant from the set of semantically equivalent variants of the answer term in association with the specified question to the question/answer pair list to form an expanded question/answer pair list; and training, by the natural language processing engine, a question answering machine learning model for a question answering cognitive system using the expanded question/answer pair list as ground truth. 7. The method of claim 1 , further comprising performing normalization of regular expressions to account for special characters. | 0.849765 |
9,058,331 | 1 | 2 | 1. A computer-implemented method, the method comprising: receiving an image from a user device; searching, with one or more processors, the database of mixed media objects to identify and retrieve a mixed media object in which the image occurs; identifying, with the one or more processors, a cluster including the mixed media object in which the image occurs; transmitting, to a social network application, a reference to the cluster; determining, by the social network application, whether a conversation associated with the cluster exists in a social network; and responsive to an absence of the conversation, generating the conversation associated with the cluster in the social network. | 1. A computer-implemented method, the method comprising: receiving an image from a user device; searching, with one or more processors, the database of mixed media objects to identify and retrieve a mixed media object in which the image occurs; identifying, with the one or more processors, a cluster including the mixed media object in which the image occurs; transmitting, to a social network application, a reference to the cluster; determining, by the social network application, whether a conversation associated with the cluster exists in a social network; and responsive to an absence of the conversation, generating the conversation associated with the cluster in the social network. 2. The method of claim 1 , wherein the mixed media object corresponds to a source material and the conversation includes a plurality of discussions that relate to the source material. | 0.824376 |
8,024,191 | 1 | 3 | 1. The method for recognizing speech, the method comprising: receiving, via a processor, an input speech having at least one pre-vocalic consonant or at least one post-vocalic consonant; generating at least one output lattice that calculates a first score by comparing the input speech to a training model to provide a result; distinguishing between the at least one pre-vocalic consonant and the at least one post-vocalic consonant in the input speech; calculating a second score by measuring a similarity between the at least one pre-vocalic consonant or the at least one post-vocalic consonant in the input speech and the first score; determining at least one category for at least one pre-vocalic match or mismatch or at least one post-vocalic match or mismatch by using the second score; and refining the results of the an automated speech recognition system by using the at least one category for at least one pre-vocalic match or mismatch or at least one post-vocalic match or mismatch. | 1. The method for recognizing speech, the method comprising: receiving, via a processor, an input speech having at least one pre-vocalic consonant or at least one post-vocalic consonant; generating at least one output lattice that calculates a first score by comparing the input speech to a training model to provide a result; distinguishing between the at least one pre-vocalic consonant and the at least one post-vocalic consonant in the input speech; calculating a second score by measuring a similarity between the at least one pre-vocalic consonant or the at least one post-vocalic consonant in the input speech and the first score; determining at least one category for at least one pre-vocalic match or mismatch or at least one post-vocalic match or mismatch by using the second score; and refining the results of the an automated speech recognition system by using the at least one category for at least one pre-vocalic match or mismatch or at least one post-vocalic match or mismatch. 3. The method of claim 1 , wherein at least one output lattice comprises syllabified words. | 0.890887 |
8,140,547 | 8 | 13 | 8. A system for generating calculation context classes from a relationship between structured data and a calculation procedure, the context classes having parent-child relationships, the system comprising: a computer processor coupled to a memory; and a process residing in the memory, the process having instructions causing the computer processor to: search the calculation procedure for at least one of a data definition N 0 and an operation, wherein the calculation procedure is configured to derive Key Performance Indicators from a business operation, and wherein the context classes having the parent-child relationships are from the Key Performance Indicators; in response to identifying the operation, registering the operation for the first data definition N 0 that is an input of the operation and registering the operation for the first data definition N 0 that is an output of the operation; generate a context M 0 from a scope L 0 applied to the data definition N 0 ; trace back the calculation procedure to obtain a data definition N 1 for calculating the data definition N 0 and to which the scope L 0 is applied; copy the calculation procedure into the context M 0 until the data definition N 1 is obtained; obtain a scope L 1 applied to the data definition N 1 ; obtain a context M 1 generated from the scope L 1 ; determine an existence of an order comparison of the scope L 0 with the scope L 1 ; obtain an order from the structured data; in response to the scope L 1 being less than the scope L 0 , register the context M 0 as a parent and the context M 1 as a child; in response to the scope L 1 being greater than the first the scope L 0 , register the second context as a parent and the context M 0 as a child; and in response to the scope L 1 being equal to the scope L 0 , register both the first and second contexts M 0 , M 1 as a single context class, and register both the first and second scopes L 0 , L 1 as a single scope of the single context class, wherein in response to an inability to compare an order of the first scope with an order of the second scope, the first and second contexts, M 0 , M 1 exist independently without a parent-child relationship, wherein the scopes L 0 , L 1 each describe a level of business operations at which the Key Performance Indicators are to be monitored, the scopes L 0 , L 1 each holding a name, a level name of structured data concerning an operation, and an event mapping rule for deriving an identifier for each of the scopes L 0 , L 1 . | 8. A system for generating calculation context classes from a relationship between structured data and a calculation procedure, the context classes having parent-child relationships, the system comprising: a computer processor coupled to a memory; and a process residing in the memory, the process having instructions causing the computer processor to: search the calculation procedure for at least one of a data definition N 0 and an operation, wherein the calculation procedure is configured to derive Key Performance Indicators from a business operation, and wherein the context classes having the parent-child relationships are from the Key Performance Indicators; in response to identifying the operation, registering the operation for the first data definition N 0 that is an input of the operation and registering the operation for the first data definition N 0 that is an output of the operation; generate a context M 0 from a scope L 0 applied to the data definition N 0 ; trace back the calculation procedure to obtain a data definition N 1 for calculating the data definition N 0 and to which the scope L 0 is applied; copy the calculation procedure into the context M 0 until the data definition N 1 is obtained; obtain a scope L 1 applied to the data definition N 1 ; obtain a context M 1 generated from the scope L 1 ; determine an existence of an order comparison of the scope L 0 with the scope L 1 ; obtain an order from the structured data; in response to the scope L 1 being less than the scope L 0 , register the context M 0 as a parent and the context M 1 as a child; in response to the scope L 1 being greater than the first the scope L 0 , register the second context as a parent and the context M 0 as a child; and in response to the scope L 1 being equal to the scope L 0 , register both the first and second contexts M 0 , M 1 as a single context class, and register both the first and second scopes L 0 , L 1 as a single scope of the single context class, wherein in response to an inability to compare an order of the first scope with an order of the second scope, the first and second contexts, M 0 , M 1 exist independently without a parent-child relationship, wherein the scopes L 0 , L 1 each describe a level of business operations at which the Key Performance Indicators are to be monitored, the scopes L 0 , L 1 each holding a name, a level name of structured data concerning an operation, and an event mapping rule for deriving an identifier for each of the scopes L 0 , L 1 . 13. The system as claimed in claim 8 wherein the instructions further include instructions to: in response to the inability to compare an order of the scope L 0 with an order of the scope L 1 , performing: replace a name of the data definition N 0 to generate a variable, n 0 , of the context M 0 ; copy attributes of the context M 1 to the context M 0 ; and refer to a copied variable, n 1 , in the context M 0 , wherein the attributes of the context M 1 include variables, data types and functions. | 0.500998 |
9,851,215 | 16 | 19 | 16. A non-transitory computer readable medium including instructions for a navigation system comprising: receiving user input regarding a navigation route for controlling guidance communication along the navigation route for a system user wherein the user input corresponds to a passive-navigation portion for representing one or more locations of the navigation route not requiring communication of the guidance communication for the system user; generating a user geographic-knowledge model based on the user input regarding the navigation route; calculating a system route based on the user geographic-knowledge model; and communicating the system route for guiding the system user in traversing the system route. | 16. A non-transitory computer readable medium including instructions for a navigation system comprising: receiving user input regarding a navigation route for controlling guidance communication along the navigation route for a system user wherein the user input corresponds to a passive-navigation portion for representing one or more locations of the navigation route not requiring communication of the guidance communication for the system user; generating a user geographic-knowledge model based on the user input regarding the navigation route; calculating a system route based on the user geographic-knowledge model; and communicating the system route for guiding the system user in traversing the system route. 19. The non-transitory computer readable medium including the instructions as claimed in claim 16 further comprising: determining a user history based on the navigation route for representing locations previously visited by the system user; determining a familiarity distribution function associated with the user history for calculating a user familiarity estimate for the system user regarding a location not included in the user history; and wherein: generating the user geographic-knowledge model includes generating the user geographic-knowledge model based on the user familiarity estimate and the familiarity distribution function. | 0.546875 |
8,867,891 | 1 | 4 | 1. A method for determining a semantic concept classification for a digital video clip including a temporal sequence of video frames and a corresponding audio soundtrack, the method comprising: analyzing, by a processing device, the temporal sequence of video frames to determine a set of visual features; analyzing, by the processing device, the audio soundtrack to determine a set of audio features; determining, by the processing device, similarity scores between the digital video clip and each of a plurality of audio-visual grouplets from an audio-visual dictionary, wherein the plurality of audio-visual grouplets includes distinct visual background codewords representing visual background content, distinct visual foreground codewords representing visual foreground content, distinct audio background codewords representing audio background content, and distinct audio foreground codewords representing audio foreground content, wherein the distinct visual background codewords and the distinct visual foreground codewords are separate and distinct from each other, wherein the distinct audio background codewords and the distinct audio foreground codewords are separate and distinct from each other, and wherein the distinct visual background codewords and the distinct visual foreground codewords are separate and distinct from the distinct audio background codewords and the distinct audio foreground codewords, and wherein the determining similarity scores comprises: comparing the set of visual features to distinct visual background codewords and distinct visual foreground codewords associated with a particular audio-visual grouplet; and comparing the set of audio features to distinct audio background codewords and distinct audio foreground codewords associated with the particular audio-visual grouplet; determining, by the processing device, one or more semantic concept classifications using trained semantic classifiers responsive to the determined similarity scores; and storing, by the processing device, indications of the one or more semantic concept classifications in a processor-accessible memory. | 1. A method for determining a semantic concept classification for a digital video clip including a temporal sequence of video frames and a corresponding audio soundtrack, the method comprising: analyzing, by a processing device, the temporal sequence of video frames to determine a set of visual features; analyzing, by the processing device, the audio soundtrack to determine a set of audio features; determining, by the processing device, similarity scores between the digital video clip and each of a plurality of audio-visual grouplets from an audio-visual dictionary, wherein the plurality of audio-visual grouplets includes distinct visual background codewords representing visual background content, distinct visual foreground codewords representing visual foreground content, distinct audio background codewords representing audio background content, and distinct audio foreground codewords representing audio foreground content, wherein the distinct visual background codewords and the distinct visual foreground codewords are separate and distinct from each other, wherein the distinct audio background codewords and the distinct audio foreground codewords are separate and distinct from each other, and wherein the distinct visual background codewords and the distinct visual foreground codewords are separate and distinct from the distinct audio background codewords and the distinct audio foreground codewords, and wherein the determining similarity scores comprises: comparing the set of visual features to distinct visual background codewords and distinct visual foreground codewords associated with a particular audio-visual grouplet; and comparing the set of audio features to distinct audio background codewords and distinct audio foreground codewords associated with the particular audio-visual grouplet; determining, by the processing device, one or more semantic concept classifications using trained semantic classifiers responsive to the determined similarity scores; and storing, by the processing device, indications of the one or more semantic concept classifications in a processor-accessible memory. 4. The method of claim 1 , wherein the set of audio features are temporal audio features. | 0.95296 |
9,058,505 | 7 | 8 | 7. A method to control access to information, the method comprising: computer hardware determining that a first type of field of a first document has restricted access; the computer hardware generating a modified list of index terms by using a first set of encryption settings to encrypt one or more tokens included in the first type of field; the computer hardware executing an indexing step using the modified list of index terms; the computer hardware determining whether a user has authorization to view the first type of field based on a degree of authorization of the user; the computer hardware generating a modified list of search terms by adding first additional search terms to a list of search terms, wherein the first additional terms include synonyms of the search terms; the computer hardware removing frequently used words from the modified list of search terms; responsive to a determination that the user has authorization to view the first type of field, the computer hardware adding to the modified list of search terms an encrypted version of a search term included in the list of search terms such that execution of a search using the modified list of search terms returns a result that identifies the first document as a search result when either an unencrypted or an encrypted version of that search term is found in the index terms associated with the first document; the computer hardware executing a search using the modified list of search terms; and the computer hardware identifying a first search result that includes the first type of field, wherein the first type of field of the first search result includes a search term that is included in the modified list of search terms. | 7. A method to control access to information, the method comprising: computer hardware determining that a first type of field of a first document has restricted access; the computer hardware generating a modified list of index terms by using a first set of encryption settings to encrypt one or more tokens included in the first type of field; the computer hardware executing an indexing step using the modified list of index terms; the computer hardware determining whether a user has authorization to view the first type of field based on a degree of authorization of the user; the computer hardware generating a modified list of search terms by adding first additional search terms to a list of search terms, wherein the first additional terms include synonyms of the search terms; the computer hardware removing frequently used words from the modified list of search terms; responsive to a determination that the user has authorization to view the first type of field, the computer hardware adding to the modified list of search terms an encrypted version of a search term included in the list of search terms such that execution of a search using the modified list of search terms returns a result that identifies the first document as a search result when either an unencrypted or an encrypted version of that search term is found in the index terms associated with the first document; the computer hardware executing a search using the modified list of search terms; and the computer hardware identifying a first search result that includes the first type of field, wherein the first type of field of the first search result includes a search term that is included in the modified list of search terms. 8. The method of claim 7 , the method further including: the computer hardware determining, based on the degree of authorization of the user, that the user is authorized to view a second type of field; and the computer hardware generating the modified list of search terms by adding second additional search terms to the list of search terms, wherein the second additional search terms further include one or both of encrypted search terms and encrypted document terms. | 0.644158 |
8,352,405 | 12 | 15 | 12. A method of performing sentiment classification of content comprising: classifying the content as being related to a particular aspect of a plurality of aspects of information by an aspect classifier, wherein the aspect classifier incorporates at least a portion of a domain specific sentiment lexicon, wherein the domain specific sentiment lexicon is configured by (i) obtaining domain specific words and/or phrases by filtering an annotated corpus, (ii) obtaining domain specific words and/or phrases by searching the world wide web via the internet using a predetermined linguistic pattern and filtering returned search results, and (iii) performing a dictionary expansion operation on domain specific words and/or phrases obtained via (i) and (ii); classifying the content classified by the aspect classifier as having one of a positive sentiment of the particular aspect of information, a negative sentiment of the particular aspect of information or as having no sentiment of the particular aspect of information by use of a polarity classifier, wherein the polarity classifier incorporates at least a portion of the domain specific sentiment lexicon; and aggregating received results of predictions by the aspect classifier and received results of predictions by the polarity classifier, wherein the method is performed using at least one electronic processor. | 12. A method of performing sentiment classification of content comprising: classifying the content as being related to a particular aspect of a plurality of aspects of information by an aspect classifier, wherein the aspect classifier incorporates at least a portion of a domain specific sentiment lexicon, wherein the domain specific sentiment lexicon is configured by (i) obtaining domain specific words and/or phrases by filtering an annotated corpus, (ii) obtaining domain specific words and/or phrases by searching the world wide web via the internet using a predetermined linguistic pattern and filtering returned search results, and (iii) performing a dictionary expansion operation on domain specific words and/or phrases obtained via (i) and (ii); classifying the content classified by the aspect classifier as having one of a positive sentiment of the particular aspect of information, a negative sentiment of the particular aspect of information or as having no sentiment of the particular aspect of information by use of a polarity classifier, wherein the polarity classifier incorporates at least a portion of the domain specific sentiment lexicon; and aggregating received results of predictions by the aspect classifier and received results of predictions by the polarity classifier, wherein the method is performed using at least one electronic processor. 15. The method of claim 12 wherein the aspect classifier and the polarity classifier are assembled together to form a sentiment classifier implemented as a Support Vector Machine. | 0.920936 |
8,954,402 | 15 | 16 | 15. A character string generation system including a processor and a memory for generating a character string to be displayed, the system comprising: a retrieving unit retrieving a document to be searched; a generating unit generating a frequency ordered suffix tree from the retrieved document, wherein the frequency ordered suffix tree is a list of each possible string of the document arranged according to a frequency of use of each possible string within the document; a searching unit searching the frequency ordered suffix tree on the basis of a keyword to retrieve a set context strings, wherein the set of context strings includes all of the each possible strings of the frequency ordered suffix tree beginning with the keyword, the retrieved set of context strings being a frequency ordered context tree as the context strings thereof are arranged according to frequency of use of the each possible string within the document; a compressing unit compressing the retrieved set of context strings of the frequency ordered context tree to optimize the frequency ordered context tree for display within a limited display region of a display device capable of displaying a limited number of context strings, the compressing including obtaining one or more context strings of the frequency ordered context tree to maximize a sum of areas under the condition that only a predetermined maximum number of context strings are displayed within the limited display region, wherein each area is defined as the frequency of use of a given context string multiplied by within the document multiplied by a length of the context string; and the display device displaying the compressed context strings of the frequency ordered context tree within the limited display region thereof. | 15. A character string generation system including a processor and a memory for generating a character string to be displayed, the system comprising: a retrieving unit retrieving a document to be searched; a generating unit generating a frequency ordered suffix tree from the retrieved document, wherein the frequency ordered suffix tree is a list of each possible string of the document arranged according to a frequency of use of each possible string within the document; a searching unit searching the frequency ordered suffix tree on the basis of a keyword to retrieve a set context strings, wherein the set of context strings includes all of the each possible strings of the frequency ordered suffix tree beginning with the keyword, the retrieved set of context strings being a frequency ordered context tree as the context strings thereof are arranged according to frequency of use of the each possible string within the document; a compressing unit compressing the retrieved set of context strings of the frequency ordered context tree to optimize the frequency ordered context tree for display within a limited display region of a display device capable of displaying a limited number of context strings, the compressing including obtaining one or more context strings of the frequency ordered context tree to maximize a sum of areas under the condition that only a predetermined maximum number of context strings are displayed within the limited display region, wherein each area is defined as the frequency of use of a given context string multiplied by within the document multiplied by a length of the context string; and the display device displaying the compressed context strings of the frequency ordered context tree within the limited display region thereof. 16. The system according to claim 15 , wherein the compressing unit includes dynamic programming. | 0.85479 |
9,787,597 | 7 | 8 | 7. A system for implementing model definition, constraint enforcement, and validation, comprising: a client computing device that comprises at least a processor, a browser installed thereupon, and non-transitory memory allocated for the browser and is configured to at least: request a reference to one or more model definition resources for a representation of a model that pertains to a tax preparation or financial management software application at least by transmitting a request for the reference to a remote host computer hosting the tax preparation or financial management application via a network element; execute a model definition resolver, residing on and stored at least partially in memory of the client computing device, that identifies or determines one or more actual locations for the one or more model definition resources at least by resolving the reference and retrieving the one or more model definition resources from the one or more actual locations, wherein the one or more model definition resources specify constraints for constraint enforcement or validation on the model; reduce data processing and data to be populated into the model at least by removing a portion of the data and populating a remaining portion of the data into the model through using one or more validation modules and one or more formatting modules stored at least partially in the memory of the client computing device, wherein the client computing device reducing the data processing and the data is further configured to: disable the constraint enforcement or validation for a portion of a flow of the tax preparation or financial management application; reduce a total number of data elements and a total number of invalid data elements at least by formatting one or more user inputs for the tax preparation or financial management application at the one or more formatting modules; and perform the constraint enforcement or validation at the one or more validation modules on at least the one or more user inputs, which have been formatted, based in part or in whole upon at least the one or more model definition resources obtained by the model definition resolver residing on the client computing device from the remote host computer via the network element; and perform data binding for the data to bind the data to the model by using a first application programming interface located on the client computing device, wherein the client computing device that performs the data binding is further configured to: identify a model definition for a requested key of a key-value pair for the data and obtaining an actual implementation of the one or more model definition resources from the remote host computer by processing the reference with a mapping module; generate a first result at least by determining whether the requested key for the data is allowed in the model based at least in part upon the actual implementation of the one or more model definition resources and further generating a second result at least by determining whether a requested value of the key-value pair for the data matches the model definition; and perform the data binding for the data and the model based at least in part upon the first result and the second result. | 7. A system for implementing model definition, constraint enforcement, and validation, comprising: a client computing device that comprises at least a processor, a browser installed thereupon, and non-transitory memory allocated for the browser and is configured to at least: request a reference to one or more model definition resources for a representation of a model that pertains to a tax preparation or financial management software application at least by transmitting a request for the reference to a remote host computer hosting the tax preparation or financial management application via a network element; execute a model definition resolver, residing on and stored at least partially in memory of the client computing device, that identifies or determines one or more actual locations for the one or more model definition resources at least by resolving the reference and retrieving the one or more model definition resources from the one or more actual locations, wherein the one or more model definition resources specify constraints for constraint enforcement or validation on the model; reduce data processing and data to be populated into the model at least by removing a portion of the data and populating a remaining portion of the data into the model through using one or more validation modules and one or more formatting modules stored at least partially in the memory of the client computing device, wherein the client computing device reducing the data processing and the data is further configured to: disable the constraint enforcement or validation for a portion of a flow of the tax preparation or financial management application; reduce a total number of data elements and a total number of invalid data elements at least by formatting one or more user inputs for the tax preparation or financial management application at the one or more formatting modules; and perform the constraint enforcement or validation at the one or more validation modules on at least the one or more user inputs, which have been formatted, based in part or in whole upon at least the one or more model definition resources obtained by the model definition resolver residing on the client computing device from the remote host computer via the network element; and perform data binding for the data to bind the data to the model by using a first application programming interface located on the client computing device, wherein the client computing device that performs the data binding is further configured to: identify a model definition for a requested key of a key-value pair for the data and obtaining an actual implementation of the one or more model definition resources from the remote host computer by processing the reference with a mapping module; generate a first result at least by determining whether the requested key for the data is allowed in the model based at least in part upon the actual implementation of the one or more model definition resources and further generating a second result at least by determining whether a requested value of the key-value pair for the data matches the model definition; and perform the data binding for the data and the model based at least in part upon the first result and the second result. 8. The system of claim 7 , wherein the client computing device is further configured to: identify a user input for the model, wherein the user input includes the data that is validated by the client computing device; and render one or more fields on a display of the client computing device based at least in part upon a result of the client computing device performing the constraint enforcement or validation on the data. | 0.65832 |
10,133,920 | 11 | 12 | 11. An information handling device, comprising: an input device; a display device; an audio capture device; a processor; a memory device that stores instructions executable by the processor to: receive handwriting input; receive voice input, wherein to receive voice input comprises receiving voice input at a time associated with receipt of the handwriting input; generate at least one first word based on the handwriting input and a probability associated with the at least one first word; generate at least one second word based on the voice input and a probability associated with the at least one second word, wherein the probability is based on a context of the voice input; determine a highest probability word based on the at least one first word and the at least one second word, wherein to determines comprises using at least one of: the at least one first word and the at least one second word to modify a probability of the other of: the at least one first word and the at least one second word; and provide the determined highest probability word. | 11. An information handling device, comprising: an input device; a display device; an audio capture device; a processor; a memory device that stores instructions executable by the processor to: receive handwriting input; receive voice input, wherein to receive voice input comprises receiving voice input at a time associated with receipt of the handwriting input; generate at least one first word based on the handwriting input and a probability associated with the at least one first word; generate at least one second word based on the voice input and a probability associated with the at least one second word, wherein the probability is based on a context of the voice input; determine a highest probability word based on the at least one first word and the at least one second word, wherein to determines comprises using at least one of: the at least one first word and the at least one second word to modify a probability of the other of: the at least one first word and the at least one second word; and provide the determined highest probability word. 12. The information handling device of claim 11 , further comprising: displaying, on the input and display device, at least one high probability words prior to the handwriting input being complete. | 0.809109 |
9,881,059 | 1 | 4 | 1. A computer implemented method for suggesting headlines, comprising: training a machine learning topic model using search logs and historic click through data to account for the potential of a word in a headline to induce a click; receiving, at a computing device, an input of a headline and an article associated with the headline; determining, by a computing device, a topic associated with the article and headline; determining a plurality of words associated with the topic; inputting each of the plurality of words associated with the topic into the trained machine learning topic model to determine a topical click value for each of the plurality of words; and recommending at least one word of the plurality of words having a higher topical click value compared to other words among the plurality of words. | 1. A computer implemented method for suggesting headlines, comprising: training a machine learning topic model using search logs and historic click through data to account for the potential of a word in a headline to induce a click; receiving, at a computing device, an input of a headline and an article associated with the headline; determining, by a computing device, a topic associated with the article and headline; determining a plurality of words associated with the topic; inputting each of the plurality of words associated with the topic into the trained machine learning topic model to determine a topical click value for each of the plurality of words; and recommending at least one word of the plurality of words having a higher topical click value compared to other words among the plurality of words. 4. The method of claim 1 , wherein the at least one word includes at least one bigram formed of two words. | 0.839879 |
9,864,590 | 1 | 3 | 1. A computer implemented method of program compilation to improve parallelism during the linking of the program by a compiler, the method comprising: converting statements of the program to canonical form; constructing a traversable representation for each procedure in the program; and traversing the program to construct a functional dataflow graph, in which an assignment statement or function call is represented as a node, a control flow decision is represented by a first set of nodes, an array or set is represented as a second set of nodes, and edges of the functional dataflow graph represent typed data; identifying at least one loop in the functional dataflow graph that can be executed in parallel; and transforming the at least one loop to a set operation by retyping connections between nodes of the functional dataflow graph. | 1. A computer implemented method of program compilation to improve parallelism during the linking of the program by a compiler, the method comprising: converting statements of the program to canonical form; constructing a traversable representation for each procedure in the program; and traversing the program to construct a functional dataflow graph, in which an assignment statement or function call is represented as a node, a control flow decision is represented by a first set of nodes, an array or set is represented as a second set of nodes, and edges of the functional dataflow graph represent typed data; identifying at least one loop in the functional dataflow graph that can be executed in parallel; and transforming the at least one loop to a set operation by retyping connections between nodes of the functional dataflow graph. 3. The method of claim 1 , further comprising: identifying indirect procedure calls; and converting the indirect procedure calls to switch structures in the traversable representation. | 0.818898 |
9,460,719 | 1 | 2 | 1. A system for delivering one or more transcription products, the system comprising: a memory; at least one processor coupled to the memory; a customer interface component executable by the at least one processor and configured to receive transcription request information identifying at least one media file, the at least one media file including content; an automatic speech recognition component executable by the at least one processor and configured to generate draft transcription information that represents a draft transcription of the content; an editor interface component executable by the at least one processor and configured to generate edited transcription information that represents an edited transcription of the content; and a delivery agent component executable by the at least one processor and configured to: evaluate first delivery criteria to determine whether to deliver a first transcription product of the one or more transcription products; transmit the first transcription product in response to determining that the first delivery criteria is satisfied; evaluate second delivery criteria at least in part by: calculating a value of a quality metric using the edited transcription information; and determining that the value is less than a quality threshold value; and not transmit a second transcription product of the one or more transcription products in response to determining that the value is less than the quality threshold value. | 1. A system for delivering one or more transcription products, the system comprising: a memory; at least one processor coupled to the memory; a customer interface component executable by the at least one processor and configured to receive transcription request information identifying at least one media file, the at least one media file including content; an automatic speech recognition component executable by the at least one processor and configured to generate draft transcription information that represents a draft transcription of the content; an editor interface component executable by the at least one processor and configured to generate edited transcription information that represents an edited transcription of the content; and a delivery agent component executable by the at least one processor and configured to: evaluate first delivery criteria to determine whether to deliver a first transcription product of the one or more transcription products; transmit the first transcription product in response to determining that the first delivery criteria is satisfied; evaluate second delivery criteria at least in part by: calculating a value of a quality metric using the edited transcription information; and determining that the value is less than a quality threshold value; and not transmit a second transcription product of the one or more transcription products in response to determining that the value is less than the quality threshold value. 2. The system according to claim 1 , wherein the delivery agent component is configured to transmit the first transcription product at least in part by modifying a web page to embed the first transcription product within the web page as Hypertext Markup Language (HTML). | 0.774624 |
8,713,025 | 19 | 20 | 19. A system, comprising: a computing device and a storage device having computer-executable instructions stored therein which, if executed by the computing device, cause the computing device to perform operations comprising: obtaining a subject entity definition of a subject entity, a node depth criteria and an impact cutoff criteria; aggregating and preparing a plurality of data items that include data related to the subject entity for processing, wherein the data comprises at least one entity function, one or more entity function measures and a creation date for each of the plurality of data items; storing the aggregated plurality of data items in one or more context layers by a component of context; developing a subject entity situation summary by analyzing the subject entity related data, wherein the subject entity situation summary comprises a linear or nonlinear regression model of each of the one or more entity function measures, a relevance for each of the measures and one or more of the context layers; using the subject entity situation summary, the node depth criteria and the impact cutoff criteria to identify components of context to include in a composite index; creating a composite index for the data associated with the identified components of context, wherein the composite index comprises a column for the creation dates of the plurality of data items, a column for each of the identified components of context and a ranking for each of the plurality of data items of the composite index; receiving a search request from a mobile access device, and providing a plurality of search results in response to the search request, wherein the plurality of search results are prioritized using a weight comprised of a mathematical combination of an index position ranking and a ranking provided by a relevance measure, and wherein at least part of the data and the search request are obtained from a mobile device. | 19. A system, comprising: a computing device and a storage device having computer-executable instructions stored therein which, if executed by the computing device, cause the computing device to perform operations comprising: obtaining a subject entity definition of a subject entity, a node depth criteria and an impact cutoff criteria; aggregating and preparing a plurality of data items that include data related to the subject entity for processing, wherein the data comprises at least one entity function, one or more entity function measures and a creation date for each of the plurality of data items; storing the aggregated plurality of data items in one or more context layers by a component of context; developing a subject entity situation summary by analyzing the subject entity related data, wherein the subject entity situation summary comprises a linear or nonlinear regression model of each of the one or more entity function measures, a relevance for each of the measures and one or more of the context layers; using the subject entity situation summary, the node depth criteria and the impact cutoff criteria to identify components of context to include in a composite index; creating a composite index for the data associated with the identified components of context, wherein the composite index comprises a column for the creation dates of the plurality of data items, a column for each of the identified components of context and a ranking for each of the plurality of data items of the composite index; receiving a search request from a mobile access device, and providing a plurality of search results in response to the search request, wherein the plurality of search results are prioritized using a weight comprised of a mathematical combination of an index position ranking and a ranking provided by a relevance measure, and wherein at least part of the data and the search request are obtained from a mobile device. 20. The system of claim 19 , wherein the linear or nonlinear regression model is developed using automated learning, and wherein the automated learning comprises: completing a multi-stage process, wherein each stage of the multi-stage process comprises an automated selection of an output from a plurality of outputs produced by a plurality of modeling algorithms after processing at least part of the data, wherein linearity of the linear or nonlinear regression model is determined by learning from the data, and wherein the plurality of modeling algorithms are selected from the group consisting of: neural network; classification and regression tree; generalized autoregressive conditional heteroskedasticity; projection pursuit regression; generalized additive model; linear regression, path analysis; Bayesian; multivariate adaptive regression spline and support vector method. | 0.500566 |
9,135,361 | 1 | 5 | 1. A computer-implemented method comprising: extracting, by a computing device, structured content from a web page; determining multiple subcategories of a known category by applying category rules to the structured content from the web page, the category rules being customized for a known structure of the web page, the multiple subcategories including multiple known subcategories of the known category and a new subcategory, the new subcategory being based on a new item within the known structure of the web page; and updating a stored taxonomy by adding the new subcategory to the stored taxonomy. | 1. A computer-implemented method comprising: extracting, by a computing device, structured content from a web page; determining multiple subcategories of a known category by applying category rules to the structured content from the web page, the category rules being customized for a known structure of the web page, the multiple subcategories including multiple known subcategories of the known category and a new subcategory, the new subcategory being based on a new item within the known structure of the web page; and updating a stored taxonomy by adding the new subcategory to the stored taxonomy. 5. The method of claim 1 , wherein the extracting structured content from the web page comprises periodically extracting structured content from the web page. | 0.820455 |
8,214,319 | 20 | 24 | 20. A method for producing a unified semantic knowledge model from a plurality of data sources having individual data elements in disparate data formats, the method comprising using a computerized cell graph to: progressively building the unified semantic knowledge model from the plurality of data sources using the computerized cell graph comprising a plurality of importer cells, a plurality of data element repositories, and the plurality of processing cells arranged to perform the steps of: translating an individual data element retrieved from data sources of the plurality of data sources into a common semantic information representation by a plurality of computerized importer cells; storing translated individual data elements received from importer cells of the plurality of importer cells in the common semantic information representation in a plurality of data repositories; and enhancing an individual data element retrieved from data repositories of the plurality of data repositories in a plurality of computerized processing cells and storing the enhanced retrieved data in the common semantic information representation in a data repository of the plurality of data repositories. | 20. A method for producing a unified semantic knowledge model from a plurality of data sources having individual data elements in disparate data formats, the method comprising using a computerized cell graph to: progressively building the unified semantic knowledge model from the plurality of data sources using the computerized cell graph comprising a plurality of importer cells, a plurality of data element repositories, and the plurality of processing cells arranged to perform the steps of: translating an individual data element retrieved from data sources of the plurality of data sources into a common semantic information representation by a plurality of computerized importer cells; storing translated individual data elements received from importer cells of the plurality of importer cells in the common semantic information representation in a plurality of data repositories; and enhancing an individual data element retrieved from data repositories of the plurality of data repositories in a plurality of computerized processing cells and storing the enhanced retrieved data in the common semantic information representation in a data repository of the plurality of data repositories. 24. The method of claim 20 , further comprising configuring importer cells of the plurality of importer cells to use the Resource Description Framework (RDF) language as the common semantic information representation. | 0.845881 |
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