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9,146,126 | 10 | 16 | 10. A method comprising: receiving, on a graphical user interface, at least a first user input for a destination; calculating a first route from an origin to the destination; displaying a representation of the first route on the graphical user interface; displaying, on the graphical user interface, an interactive sign icon representative of a real world sign for an exit from a road of the first route from the origin to the destination, wherein the interactive sign icon includes a representation of the exit from the road that leads to the destination; receiving, on the graphical user interface, a second user input for the interactive icon representative of the real world sign; calculating a second route to the destination including the exit from the road from the interactive sign icon, wherein the second route is an alternative route to the destination; and displaying the second route on the graphical user interface. | 10. A method comprising: receiving, on a graphical user interface, at least a first user input for a destination; calculating a first route from an origin to the destination; displaying a representation of the first route on the graphical user interface; displaying, on the graphical user interface, an interactive sign icon representative of a real world sign for an exit from a road of the first route from the origin to the destination, wherein the interactive sign icon includes a representation of the exit from the road that leads to the destination; receiving, on the graphical user interface, a second user input for the interactive icon representative of the real world sign; calculating a second route to the destination including the exit from the road from the interactive sign icon, wherein the second route is an alternative route to the destination; and displaying the second route on the graphical user interface. 16. The method of claim 10 , wherein the exit from the road that leads to the destination is not a point of interest or an intermediate destination between the origin and the destination. | 0.685185 |
9,589,012 | 1 | 12 | 1. A computer-implemented method, comprising: receiving from a user a selection of an object among one or more objects included in a data model, the selection made through an object-selection interface; retrieving from computer memory a previously stored object definition that corresponds to the selected object, the previously stored object definition includes: an object query that, when executed, retrieves a set of time stamped events from a data store on a computing device, each event including a portion of raw machine data reflecting activity in an information technology environment; and an object schema identifying a set of one or more fields, each field defined by an extraction rule or regular expression that locates the field in the raw machine data and can be used to extract a field value from the field location from the raw machine data in each event in a subset of the set of time stamped events, each extraction rule or regular expression operating on the raw machine data in an event without modifying the event's raw machine data; and executing, against events in the data store that meet filtering criteria of the object query, a search query that references only field values that are extracted using the object schema and that produces a result based at least in part on the data reflecting the activity of the information technology environment. | 1. A computer-implemented method, comprising: receiving from a user a selection of an object among one or more objects included in a data model, the selection made through an object-selection interface; retrieving from computer memory a previously stored object definition that corresponds to the selected object, the previously stored object definition includes: an object query that, when executed, retrieves a set of time stamped events from a data store on a computing device, each event including a portion of raw machine data reflecting activity in an information technology environment; and an object schema identifying a set of one or more fields, each field defined by an extraction rule or regular expression that locates the field in the raw machine data and can be used to extract a field value from the field location from the raw machine data in each event in a subset of the set of time stamped events, each extraction rule or regular expression operating on the raw machine data in an event without modifying the event's raw machine data; and executing, against events in the data store that meet filtering criteria of the object query, a search query that references only field values that are extracted using the object schema and that produces a result based at least in part on the data reflecting the activity of the information technology environment. 12. The method of claim 1 , wherein the selected object is a root object whose object query provides for broader search criteria than a child object query of a child object that is also included in the data model and is selectable through the object-selection interface. | 0.865538 |
7,945,598 | 11 | 12 | 11. The computer program product of claim 9 , wherein the computer usable program code for creating a process document for each task in the multi-step process includes computer usable program code for updating pointers in a parent field in the process metadata data structure to point to a parent of the process document, and computer usable program code for updating pointers in a child field in the process metadata data structure to point to a child of the process document based on the order of execution in the procedure information. | 11. The computer program product of claim 9 , wherein the computer usable program code for creating a process document for each task in the multi-step process includes computer usable program code for updating pointers in a parent field in the process metadata data structure to point to a parent of the process document, and computer usable program code for updating pointers in a child field in the process metadata data structure to point to a child of the process document based on the order of execution in the procedure information. 12. The computer program product of claim 11 , further comprising: computer usable program code for searching the metadata in the metadata repository to locate the process information about the multi-step process; computer usable program code for determining from the metadata about the multi-step process that the multi-step process comprises a plurality of tasks; and computer usable program code for locating, using the pointers in the metadata about the multi-step process, the process information for the plurality of tasks in accordance with the execution order specified by the practice requirements. | 0.5 |
7,574,044 | 5 | 9 | 5. An image processing apparatus comprising: an extracting unit that extracts a text part from an image; a dividing unit that classifies text in the text part based on color information of the text, wherein the color information used for classifying is expressed in a certain color space, and threshold values are set in components of the certain color space in advance; a search condition specifying unit configured to specify a search condition including color information; and a text searching unit that searches the text based on the color information of the search condition. | 5. An image processing apparatus comprising: an extracting unit that extracts a text part from an image; a dividing unit that classifies text in the text part based on color information of the text, wherein the color information used for classifying is expressed in a certain color space, and threshold values are set in components of the certain color space in advance; a search condition specifying unit configured to specify a search condition including color information; and a text searching unit that searches the text based on the color information of the search condition. 9. The image processing apparatus according to claim 5 , further comprising: a compression unit compresses the text part extracted by the extracting unit and other parts individually. | 0.598684 |
8,996,375 | 10 | 14 | 10. A speech processing method, comprising: determining a variable set of available commands; determining command structures corresponding to the determined set of available commands; processing a natural language speech input representing at least one command with respect to the determined command structures, with at least one automated processor, wherein an interpretation of the natural language speech input is dependent on the determined variable set of available commands; determining and preserving in a system state of the at least one automated processor prior to the natural language speech input; determining if the natural language speech input likely represents a command; determining a completeness and an ambiguity of the represented command with respect to the determined command structures, and if the likely at least one command is too ambiguous or incomplete for execution, obtaining further speech input to reduce ambiguity or incompleteness, wherein at least said obtaining is adapted to change the determined system state, such that a system state before said obtaining further speech input differs from the system state after said obtaining further speech input; executing the represented command with at least one automated processor; and reverting the at least one automated processor to the determined preserved system state with further changes in the system state resulting from executing the represented command by the at least one automated processor. | 10. A speech processing method, comprising: determining a variable set of available commands; determining command structures corresponding to the determined set of available commands; processing a natural language speech input representing at least one command with respect to the determined command structures, with at least one automated processor, wherein an interpretation of the natural language speech input is dependent on the determined variable set of available commands; determining and preserving in a system state of the at least one automated processor prior to the natural language speech input; determining if the natural language speech input likely represents a command; determining a completeness and an ambiguity of the represented command with respect to the determined command structures, and if the likely at least one command is too ambiguous or incomplete for execution, obtaining further speech input to reduce ambiguity or incompleteness, wherein at least said obtaining is adapted to change the determined system state, such that a system state before said obtaining further speech input differs from the system state after said obtaining further speech input; executing the represented command with at least one automated processor; and reverting the at least one automated processor to the determined preserved system state with further changes in the system state resulting from executing the represented command by the at least one automated processor. 14. The method according to claim 10 , wherein the represented command is targeted to one of a plurality of available applications, further comprising restoring a system state to a different state than immediately preceded execution of the represented command. | 0.583333 |
8,831,957 | 9 | 15 | 9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving data corresponding to an utterance; obtaining location indicia for an area within a building where the utterance was spoken; determining a set of likelihoods based on the location indicia, each likelihood in the set corresponding to a likelihood that the utterance was spoken in a particular area of the building from a plurality of candidate areas of the building; selecting one or more candidate areas of the building from the plurality of candidate areas of the building based on the set of likelihoods; accessing, for each selected candidate area of the building, a model for speech recognition associated with the respective candidate area of the building; generating a composite model using the accessed models for speech recognition and the likelihoods associated with the corresponding candidate areas of the building; and generating a transcription of the utterance using the composite model. | 9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving data corresponding to an utterance; obtaining location indicia for an area within a building where the utterance was spoken; determining a set of likelihoods based on the location indicia, each likelihood in the set corresponding to a likelihood that the utterance was spoken in a particular area of the building from a plurality of candidate areas of the building; selecting one or more candidate areas of the building from the plurality of candidate areas of the building based on the set of likelihoods; accessing, for each selected candidate area of the building, a model for speech recognition associated with the respective candidate area of the building; generating a composite model using the accessed models for speech recognition and the likelihoods associated with the corresponding candidate areas of the building; and generating a transcription of the utterance using the composite model. 15. The system of claim 9 , wherein each model for speech recognition associated with the candidate areas of the building comprises a language model; and wherein the composite model comprises a composite language model. | 0.741745 |
9,317,499 | 6 | 8 | 6. A computer program product for optimizing generation of a regular expression utilized for entity extraction, the computer program product comprising: a computer readable tangible storage device and program instructions stored on the computer readable tangible storage device, the program instructions include: program instructions to receive, at a server, an input from a user of the server, the input enabling at least a first performance optimization parameter; program instructions to receive, from a user of a client computer, a query comprising a plain text word; program instructions to receive, at the server, data extracted from an electronic repository that is communicatively connected to the server, the data describing probabilities of spelling errors based, at least in part, on a number of syllables in the plain text word; program instructions to initialize, at the server, the first performance optimization parameter based, at least in part, on the received data and the input enabling at least the first performance optimization parameter; program instructions to optimize performance of generating a regular expression at the server, including program instructions to identify, using the first performance optimization parameter, a syllable within a plain text word that has a high probability of at least one of an incorrectly substituted and transposed character within a spelling of a word having a same number of syllables as the plain text word; program instructions to select, at the server, each character in the syllables identified; program instructions to identify, at the server, a group of characters from a confusion matrix that are commonly confused with the character selected; program instructions to generate, at the server, a set of characters for each character selected, wherein the set of characters begin with one of the each character selected followed by and ending with the group of characters from the confusion matrix; program instructions to generate, at the server, a regular expression by concatenating each set of characters; program instructions to, at the server, search, using the regular expression, the electronic repository for information relevant to the query; and program instructions to provide, to the user of the client computer, search results based on the regular expression. | 6. A computer program product for optimizing generation of a regular expression utilized for entity extraction, the computer program product comprising: a computer readable tangible storage device and program instructions stored on the computer readable tangible storage device, the program instructions include: program instructions to receive, at a server, an input from a user of the server, the input enabling at least a first performance optimization parameter; program instructions to receive, from a user of a client computer, a query comprising a plain text word; program instructions to receive, at the server, data extracted from an electronic repository that is communicatively connected to the server, the data describing probabilities of spelling errors based, at least in part, on a number of syllables in the plain text word; program instructions to initialize, at the server, the first performance optimization parameter based, at least in part, on the received data and the input enabling at least the first performance optimization parameter; program instructions to optimize performance of generating a regular expression at the server, including program instructions to identify, using the first performance optimization parameter, a syllable within a plain text word that has a high probability of at least one of an incorrectly substituted and transposed character within a spelling of a word having a same number of syllables as the plain text word; program instructions to select, at the server, each character in the syllables identified; program instructions to identify, at the server, a group of characters from a confusion matrix that are commonly confused with the character selected; program instructions to generate, at the server, a set of characters for each character selected, wherein the set of characters begin with one of the each character selected followed by and ending with the group of characters from the confusion matrix; program instructions to generate, at the server, a regular expression by concatenating each set of characters; program instructions to, at the server, search, using the regular expression, the electronic repository for information relevant to the query; and program instructions to provide, to the user of the client computer, search results based on the regular expression. 8. The computer program product of claim 6 , wherein the confusion matrix is implemented as a data structure. | 0.877803 |
9,218,807 | 3 | 4 | 3. The system of claim 1 , wherein the speech recognition software application is configured to record each instance of validated text, accumulating instances of validated text up to a first predetermined number of instances of validated text or duration of audio signal, and further wherein the speech recognition software application is configured to perform calibration of the speech recognition engine once the first predetermined number of instances of validated text or duration of audio signal has been achieved. | 3. The system of claim 1 , wherein the speech recognition software application is configured to record each instance of validated text, accumulating instances of validated text up to a first predetermined number of instances of validated text or duration of audio signal, and further wherein the speech recognition software application is configured to perform calibration of the speech recognition engine once the first predetermined number of instances of validated text or duration of audio signal has been achieved. 4. The system of claim 3 , wherein calibration of the speech recognition engine comprises the speech recognition engine selecting initial properties of an acoustic match to a voice model. | 0.5 |
9,286,289 | 12 | 13 | 12. The method of claim 11 , wherein selecting the first subset of edges of the lexicon network comprises including a target edge into the first subset of edges according to a direction of the target edge. | 12. The method of claim 11 , wherein selecting the first subset of edges of the lexicon network comprises including a target edge into the first subset of edges according to a direction of the target edge. 13. The method of claim 12 , wherein the second node is assigned to a second level of the plurality of levels, and wherein assigning the first node comprises: when the first node points to the second node, selecting the first level so that the first level precedes the second level in the ordered sequence; and when the second node points to the first node, selecting the first level so that the second level precedes the first level in the ordered sequence. | 0.74095 |
9,088,655 | 2 | 4 | 2. The system of claim 1 , wherein the response is played during a second phone call. | 2. The system of claim 1 , wherein the response is played during a second phone call. 4. The system of claim 2 , wherein the second phone call is to a different phone number than the first phone call. | 0.5 |
8,682,932 | 16 | 27 | 16. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing-devices, cause performance of: generating an index mapping data objects to terms associated with the data objects; generating a graph describing hierarchical relationships between each of the data objects; receiving a search request comprising a plurality of search terms; based on the index, calculating multiple candidate sets of data objects by, for each particular term in the plurality of search terms, identifying a particular candidate set of data objects that are mapped to the particular term; calculating priority scores for at least the data objects in the candidate sets based at least in part on one or more of: a link analysis of the graph; or metadata describing structural constraints upon the data objects; based on the graph, identifying one or more search result subgraphs, wherein each particular subgraph of the one or more search result subgraphs is a hierarchy of data objects that comprises, for each particular term, at least one data object mapped to the particular term in the index; wherein identifying the one or more search result subgraphs comprises investigating the hierarchical relationships described by the graph, in an order that is based on the priority scores, to locate at least one ancestor object that, for each particular candidate set, is the same as, or an ancestor of, at least one member object of that particular candidate set; providing information indicating the one or more search result subgraphs in response to the search request. | 16. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing-devices, cause performance of: generating an index mapping data objects to terms associated with the data objects; generating a graph describing hierarchical relationships between each of the data objects; receiving a search request comprising a plurality of search terms; based on the index, calculating multiple candidate sets of data objects by, for each particular term in the plurality of search terms, identifying a particular candidate set of data objects that are mapped to the particular term; calculating priority scores for at least the data objects in the candidate sets based at least in part on one or more of: a link analysis of the graph; or metadata describing structural constraints upon the data objects; based on the graph, identifying one or more search result subgraphs, wherein each particular subgraph of the one or more search result subgraphs is a hierarchy of data objects that comprises, for each particular term, at least one data object mapped to the particular term in the index; wherein identifying the one or more search result subgraphs comprises investigating the hierarchical relationships described by the graph, in an order that is based on the priority scores, to locate at least one ancestor object that, for each particular candidate set, is the same as, or an ancestor of, at least one member object of that particular candidate set; providing information indicating the one or more search result subgraphs in response to the search request. 27. The one or more non-transitory computer-readable media of claim 16 : wherein identifying the one or more search result subgraphs comprises expanding each data object in each candidate set until a common ancestor is found; wherein investigating the hierarchical relationships fin an order that is based on the priority scores comprises selecting an order in which to expand the data objects in the candidate sets based on the priority scores. | 0.620307 |
9,317,544 | 5 | 11 | 5. A device comprising: a processor; and executable instructions operable by the processor, the executable instructions comprising a method for generating fuzzy loins between records, the method comprising: tokenizing two records of different datasets into tokens; determining transforms for each token of the tokenized records; generating signatures for the two tokenized records using the transforms; executing a user-defined function to perform matching of signatures within the runtime layer of a database system; invoking an object manager by submission of the user-defined function, the object manager maintaining persistence of an object storing the tokens for each record and the associated transforms between a signature generation query and a similarity computation query; building signature tables with the generated signatures; identifying two signature tables with at least one common signature, wherein the two signature tables are related to the two records with different datasets; equi-joining the two signature tables based on their at least one common signature, wherein the equi-joining comprises joining record identifications from the two signature tables and combining other fields from the records in the two different datasets as identified by the joined record identifications; computing a similarity measure between the two records corresponding to the two signature tables; and creating a fuzzy join between the two records with the at least one common signature when the similarity measure is above a threshold. | 5. A device comprising: a processor; and executable instructions operable by the processor, the executable instructions comprising a method for generating fuzzy loins between records, the method comprising: tokenizing two records of different datasets into tokens; determining transforms for each token of the tokenized records; generating signatures for the two tokenized records using the transforms; executing a user-defined function to perform matching of signatures within the runtime layer of a database system; invoking an object manager by submission of the user-defined function, the object manager maintaining persistence of an object storing the tokens for each record and the associated transforms between a signature generation query and a similarity computation query; building signature tables with the generated signatures; identifying two signature tables with at least one common signature, wherein the two signature tables are related to the two records with different datasets; equi-joining the two signature tables based on their at least one common signature, wherein the equi-joining comprises joining record identifications from the two signature tables and combining other fields from the records in the two different datasets as identified by the joined record identifications; computing a similarity measure between the two records corresponding to the two signature tables; and creating a fuzzy join between the two records with the at least one common signature when the similarity measure is above a threshold. 11. The device of claim 5 , wherein the method further comprises: executing the user-defined function within the runtime layer of the database system to compute the similarity measure for the two records of the two corresponding datasets, wherein the two datasets have at least one signature in common if the similarity measure is above a threshold. | 0.5 |
8,484,017 | 13 | 15 | 13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving data including (i) audio data that encodes a spoken natural language query, and (ii) environmental audio data; obtaining a transcription of the spoken natural language query; determining a particular content type associated with one or more keywords in the transcription; providing at least a portion of the environmental audio data to a content recognition engine; and identifying a content item that (i) has been output by the content recognition engine, and (ii) matches the particular content type associated with the one or more keywords in the transcription. | 13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving data including (i) audio data that encodes a spoken natural language query, and (ii) environmental audio data; obtaining a transcription of the spoken natural language query; determining a particular content type associated with one or more keywords in the transcription; providing at least a portion of the environmental audio data to a content recognition engine; and identifying a content item that (i) has been output by the content recognition engine, and (ii) matches the particular content type associated with the one or more keywords in the transcription. 15. The system of claim 13 , the operations further including receiving additional environmental data that includes video data or image data. | 0.765 |
8,676,565 | 1 | 6 | 1. A method implemented by one or more computer processors, the method comprising: computationally matching one or more of a plurality of utterances into a respective one of a plurality of predefined topics through comparison with one or more corresponding semantic graph patterns: and for at least one said utterance that was not matched to the semantic graph patterns, computationally generating a semantic graph pattern that described information common to the at least one said utterance. | 1. A method implemented by one or more computer processors, the method comprising: computationally matching one or more of a plurality of utterances into a respective one of a plurality of predefined topics through comparison with one or more corresponding semantic graph patterns: and for at least one said utterance that was not matched to the semantic graph patterns, computationally generating a semantic graph pattern that described information common to the at least one said utterance. 6. A method as described in claim 1 , wherein the generating includes an intersection of pairs of semantic graphs representing said utterances. | 0.56135 |
7,606,856 | 24 | 26 | 24. The system of claim 21 wherein the descriptor management processor is configured to identify the topic descriptor associated with the topic key phrase by performing a lookup in a topic database. | 24. The system of claim 21 wherein the descriptor management processor is configured to identify the topic descriptor associated with the topic key phrase by performing a lookup in a topic database. 26. The system of claim 24 wherein the descriptor management processor is configured to determine the topic descriptor weight based on at least one of an importance factor, a privacy factor, and a cost factor. | 0.622744 |
9,654,592 | 13 | 14 | 13. A non-transitory machine readable medium that stores instructions which when performed by a machine, cause the machine to perform operations comprising: determining a first set of high ranking skills for a first member of a social networking service, the first set of high ranking skills selected from a plurality of skills of the first member based upon a skill ranking of the plurality of skills calculated by the social networking service, the plurality of skills entered by the first member into a member profile for the member on the social networking service, the skill ranking quantifying a proficiency of the first member in a given skill relative to other members of the social networking service; determining a set of members who are first degree connections of the first member; selecting a second member from the set of members based upon a determination that a second set of high ranking skills corresponding to the second member includes a common skill that is also in the first set of high ranking skills, the second set of high ranking skills selected from a plurality of skills of the second member based upon a skill ranking of the plurality of skills of the second member calculated by the social networking service, the plurality of skills of the second member entered by the second member into a second member profile for the second member on the social networking service, the skill ranking quantifying a proficiency of the second member in a given skill relative to other members of the social networking service; and presenting a graphical user interface to the first member, the graphical user interface preconfigured for the first member to include an indication requesting, from the first member, an endorsement of the second member for the common skill, the graphical user interface providing at least one selectable indication to the first member, the at least one selectable indication including a first selectable indication to endorse the second member for the common skill, the endorsement indicating that the first member thinks that the second member possesses the common skill, the common skill determined by the social networking service to be a high ranking skill for the first member and the second member, wherein a high ranking skill is one of a predetermined set of skills selected from a plurality of skills of a member, the predetermined set of skills starting with a highest ranked skill of the plurality of skills of the member and including at least a next highest ranked skill of the plurality of skills; and updating the second member profile based upon a selection by the first member of the at least one selectable indication. | 13. A non-transitory machine readable medium that stores instructions which when performed by a machine, cause the machine to perform operations comprising: determining a first set of high ranking skills for a first member of a social networking service, the first set of high ranking skills selected from a plurality of skills of the first member based upon a skill ranking of the plurality of skills calculated by the social networking service, the plurality of skills entered by the first member into a member profile for the member on the social networking service, the skill ranking quantifying a proficiency of the first member in a given skill relative to other members of the social networking service; determining a set of members who are first degree connections of the first member; selecting a second member from the set of members based upon a determination that a second set of high ranking skills corresponding to the second member includes a common skill that is also in the first set of high ranking skills, the second set of high ranking skills selected from a plurality of skills of the second member based upon a skill ranking of the plurality of skills of the second member calculated by the social networking service, the plurality of skills of the second member entered by the second member into a second member profile for the second member on the social networking service, the skill ranking quantifying a proficiency of the second member in a given skill relative to other members of the social networking service; and presenting a graphical user interface to the first member, the graphical user interface preconfigured for the first member to include an indication requesting, from the first member, an endorsement of the second member for the common skill, the graphical user interface providing at least one selectable indication to the first member, the at least one selectable indication including a first selectable indication to endorse the second member for the common skill, the endorsement indicating that the first member thinks that the second member possesses the common skill, the common skill determined by the social networking service to be a high ranking skill for the first member and the second member, wherein a high ranking skill is one of a predetermined set of skills selected from a plurality of skills of a member, the predetermined set of skills starting with a highest ranked skill of the plurality of skills of the member and including at least a next highest ranked skill of the plurality of skills; and updating the second member profile based upon a selection by the first member of the at least one selectable indication. 14. The machine readable medium of claim 13 , wherein the instructions for presenting a user interface comprises instructions which when performed by the machine, cause the machine to ask the first member if they would rate the second member's proficiency on the common skill. | 0.581818 |
9,202,127 | 24 | 27 | 24. A method of processing an image, the method comprising: generating first grayscale image data using first channel data of multi-channel image data associated with a multi-channel image; generating second grayscale image data using second channel data of the multi-channel image data, the first grayscale image data distinct from the second grayscale image data; identifying first text region data in the first grayscale image data; identifying second text region data in the second grayscale image data; determining first text region information from the first text region data and second text region information from the second text region data; and generating text information of the multi-channel image based on the first text region information and the second text region information. | 24. A method of processing an image, the method comprising: generating first grayscale image data using first channel data of multi-channel image data associated with a multi-channel image; generating second grayscale image data using second channel data of the multi-channel image data, the first grayscale image data distinct from the second grayscale image data; identifying first text region data in the first grayscale image data; identifying second text region data in the second grayscale image data; determining first text region information from the first text region data and second text region information from the second text region data; and generating text information of the multi-channel image based on the first text region information and the second text region information. 27. The method of claim 24 , wherein identifying the first text region data and identifying the second text region data are performed in parallel, and wherein identifying the first text region data includes: identifying first candidate text region data in the first grayscale image data; and identifying the first text region data in the identified first candidate text region data, and wherein identifying the second text region data includes: identifying a second candidate text region data in the second grayscale image data; and identifying the second text region data in the identified second candidate text region data. | 0.5 |
9,463,334 | 4 | 5 | 4. The computer implemented method of claim 1 , wherein said patient information comprises data of a plurality of sets of features, wherein each set comprise one or more features, and wherein said hierarchy comprises a plurality of intermediate levels and a lowest level comprising said plurality of predictive models, wherein each intermediate level corresponds to divisions with respect to a respective set of features, and wherein divisions corresponding to a subordinate intermediate level are nested with divisions corresponding to a superordinate intermediate level. | 4. The computer implemented method of claim 1 , wherein said patient information comprises data of a plurality of sets of features, wherein each set comprise one or more features, and wherein said hierarchy comprises a plurality of intermediate levels and a lowest level comprising said plurality of predictive models, wherein each intermediate level corresponds to divisions with respect to a respective set of features, and wherein divisions corresponding to a subordinate intermediate level are nested with divisions corresponding to a superordinate intermediate level. 5. The computer implemented method of claim 4 , wherein each of said plurality of predictive models is associated with a respective division with respect to each set of features, and wherein said automatically selecting comprises: identifying a first division on a first level of said plurality of intermediate levels based on data of a set of features corresponding to said first intermediate level; identifying a second division that is nested with said first division on a second level of said plurality of intermediate levels based on data of a set of features corresponding to said second intermediate level; and selecting said one or more predictive models based on a set of features corresponding to an intermediate level that is immediately above said lowest level. | 0.5 |
9,607,081 | 11 | 12 | 11. A system for categorizing a user, the system comprising: a monitor that monitors a user's usage of one or more marked GUI features of an application; a hardware memory that stores a plurality of defined ontologies; an ontology generator that generates one or more user-specific ontologies for the user in accordance with the user's monitored usage, wherein a user-specific ontology is represented by a graph including one or more edges connected to one or more vertices, wherein each vertex of the one or more vertices corresponds to a GUI feature selected by the user interacting with the application, and each edge of the one or more edges corresponds to a sequence of the GUI features selected by the user, wherein the ontology generator classifies a length of one or more of a user's application sessions, wherein for each classified length, the ontology generator determines whether a user-specific ontology exists for the respective classified length of the session for the user, wherein in response to a determination that the user-specific ontology exists for the respective classified length of the session, the ontology generator appends the user's monitored usage to the existing user-specific ontology for the respective classified length of the session, and in response to a determination that the user-specific ontology does not exist for the respective classified length of the session, the ontology generator generates a user-specific ontology for the respective classified length of the session; and a categorizer coupled to the memory, wherein the categorizer compares the one or more user-specific ontologies with plurality of defined ontologies stored in the hardware memory, and categorizes the user in accordance with the comparison of the one or more user-specific ontologies and the plurality of defined ontologies, wherein each defined ontology corresponds to a category of a plurality of categories. | 11. A system for categorizing a user, the system comprising: a monitor that monitors a user's usage of one or more marked GUI features of an application; a hardware memory that stores a plurality of defined ontologies; an ontology generator that generates one or more user-specific ontologies for the user in accordance with the user's monitored usage, wherein a user-specific ontology is represented by a graph including one or more edges connected to one or more vertices, wherein each vertex of the one or more vertices corresponds to a GUI feature selected by the user interacting with the application, and each edge of the one or more edges corresponds to a sequence of the GUI features selected by the user, wherein the ontology generator classifies a length of one or more of a user's application sessions, wherein for each classified length, the ontology generator determines whether a user-specific ontology exists for the respective classified length of the session for the user, wherein in response to a determination that the user-specific ontology exists for the respective classified length of the session, the ontology generator appends the user's monitored usage to the existing user-specific ontology for the respective classified length of the session, and in response to a determination that the user-specific ontology does not exist for the respective classified length of the session, the ontology generator generates a user-specific ontology for the respective classified length of the session; and a categorizer coupled to the memory, wherein the categorizer compares the one or more user-specific ontologies with plurality of defined ontologies stored in the hardware memory, and categorizes the user in accordance with the comparison of the one or more user-specific ontologies and the plurality of defined ontologies, wherein each defined ontology corresponds to a category of a plurality of categories. 12. The system of claim 11 , wherein the monitor modifies a hypertext markup language (HTML) file of the application. | 0.71875 |
8,498,999 | 1 | 8 | 1. A method of delivering a search result comprising: receiving a query; identifying a first term in the query that is a first portion of a first abbreviation pair, wherein the first abbreviation pair includes a second portion; identifying a second term in the query; identifying a topic corresponding to the second term; identifying that the first term in the query is also present in a second abbreviation pair as a third portion of the second abbreviation pair, wherein the second abbreviation pair includes a fourth portion and wherein the fourth portion of the second abbreviation pair is different from the second portion of the first abbreviation pair; revising the query by selectively including as additional parameters in the query, one of: (1) the second portion, (2) the fourth portion, or (3) both the second and fourth portions, wherein the fourth portion comprises a plurality of terms representing an acronym expansion of the third portion and wherein the selection is based at least in part on a topical score associated with each of the second portion and the fourth portion, respectively, the topical scores corresponding to relevance of the second and fourth portions to the topic and calculated according to both of relevance of a plurality of constituent terms of the second portion and the plurality of terms of the fourth portion to the topic and relevance of the combined constituent terms of the second portion and the plurality of terms of the fourth portion to the topic, respectively; locating one or more search results for the revised query; and returning the one or more search results. | 1. A method of delivering a search result comprising: receiving a query; identifying a first term in the query that is a first portion of a first abbreviation pair, wherein the first abbreviation pair includes a second portion; identifying a second term in the query; identifying a topic corresponding to the second term; identifying that the first term in the query is also present in a second abbreviation pair as a third portion of the second abbreviation pair, wherein the second abbreviation pair includes a fourth portion and wherein the fourth portion of the second abbreviation pair is different from the second portion of the first abbreviation pair; revising the query by selectively including as additional parameters in the query, one of: (1) the second portion, (2) the fourth portion, or (3) both the second and fourth portions, wherein the fourth portion comprises a plurality of terms representing an acronym expansion of the third portion and wherein the selection is based at least in part on a topical score associated with each of the second portion and the fourth portion, respectively, the topical scores corresponding to relevance of the second and fourth portions to the topic and calculated according to both of relevance of a plurality of constituent terms of the second portion and the plurality of terms of the fourth portion to the topic and relevance of the combined constituent terms of the second portion and the plurality of terms of the fourth portion to the topic, respectively; locating one or more search results for the revised query; and returning the one or more search results. 8. The method of claim 1 further comprising including the second portion in the received query as an AND term. | 0.84058 |
8,972,423 | 9 | 14 | 9. A computer readable medium for storing executable instructions to perform a method of parsing a schema across a plurality of disparate vendors having interoperability of at least one web service, comprising: instructions for communicating a plurality of data in a data defining mark-up language file by a transport protocol stack; instructions for parsing said data defining mark-up language to determine at least one opaque schema element by a deep copy mechanism comprising: instructions for calling a deep copy helper to extract a plurality of opaque data corresponding to input type; instructions for filling a plurality of objects with said opaque data in a recursive manner; and instructions for returning said objects to convert to an opaque string; and instructions for translating said at least one opaque schema element to a mark-up language string element. | 9. A computer readable medium for storing executable instructions to perform a method of parsing a schema across a plurality of disparate vendors having interoperability of at least one web service, comprising: instructions for communicating a plurality of data in a data defining mark-up language file by a transport protocol stack; instructions for parsing said data defining mark-up language to determine at least one opaque schema element by a deep copy mechanism comprising: instructions for calling a deep copy helper to extract a plurality of opaque data corresponding to input type; instructions for filling a plurality of objects with said opaque data in a recursive manner; and instructions for returning said objects to convert to an opaque string; and instructions for translating said at least one opaque schema element to a mark-up language string element. 14. The computer readable medium of claim 9 , wherein said instructions for communicating occurs over a network capable of interoperable machine-to-machine interaction. | 0.5 |
9,779,079 | 1 | 2 | 1. A method for supervising text comprising: receiving input text in a natural language into memory of a computing device, the input text including at least one source sentence; with an authoring system of the computing device, analyzing the input text including, for a source sentence in the input text, generating a syntactic representation; generating a target sentence in the same natural language as the input text, based on the syntactic representation; comparing the source sentence with the target sentence to determine whether there is a match, wherein the sentences are a match when each word and its position in the sentence is identical for the source and target sentences; and outputting a decision based on the comparison. | 1. A method for supervising text comprising: receiving input text in a natural language into memory of a computing device, the input text including at least one source sentence; with an authoring system of the computing device, analyzing the input text including, for a source sentence in the input text, generating a syntactic representation; generating a target sentence in the same natural language as the input text, based on the syntactic representation; comparing the source sentence with the target sentence to determine whether there is a match, wherein the sentences are a match when each word and its position in the sentence is identical for the source and target sentences; and outputting a decision based on the comparison. 2. The method of claim 1 , wherein the analyzing includes automatically identifying syntactic relationships between pairs of words in the source sentence, the syntactic representation including the identified syntactic relationships. | 0.628981 |
10,055,602 | 1 | 12 | 1. A computer-implemented method, comprising steps of: separately encrypting a set of plain text data using two or more encryption functions, thereby producing an encrypted domain comprising at least two distinct groups of encrypted data items, wherein the two or more encryption functions comprise (i) a brute force safe function and (ii) a range safe function; converting a range query over plain text data items into a query over at least one of the distinct groups of encrypted data items; and combining results from the query over the distinct groups of encrypted data items, thereby generating a final encrypted result to the range query; wherein the steps are carried out by at least one computing device. | 1. A computer-implemented method, comprising steps of: separately encrypting a set of plain text data using two or more encryption functions, thereby producing an encrypted domain comprising at least two distinct groups of encrypted data items, wherein the two or more encryption functions comprise (i) a brute force safe function and (ii) a range safe function; converting a range query over plain text data items into a query over at least one of the distinct groups of encrypted data items; and combining results from the query over the distinct groups of encrypted data items, thereby generating a final encrypted result to the range query; wherein the steps are carried out by at least one computing device. 12. The computer-implemented method of claim 1 , comprising: decrypting the final encrypted result, thereby generating a plain text result set. | 0.743728 |
7,774,361 | 12 | 18 | 12. A computer-implemented method for aggregating and presenting a database intrusion incident, the method comprising: using a computer processor configured to execute method steps, the steps comprising: receiving, from a database intrusion detection system, an anomalous database query requesting data from a database, the database intrusion detection system configured to separate acceptable database queries from anomalous database queries that are expected to have undesired effects on the database, wherein database queries are determined to be anomalous when the database queries differ from the acceptable database queries observed by the database intrusion detection system, the anomalous database query having at least one anomalous attribute; identifying an anomaly type for the query received, the anomaly type defining a category of anomalous database queries having similar anomalous attributes; converting the anomalous database query into a characteristic representation, the characteristic representation describing the anomalous attribute of the anomalous database query in a generic form for grouping according to the anomaly type; aggregating the anomalous database query and other anomalous database queries with substantially similar characteristic representations into a group of anomalous database queries to represent a single intrusion incident, wherein the other anomalous database queries are identified for aggregation into the group using an index generated based on the characteristic representation of the anomalous database query; and generating a database intrusion incident report describing the group of anomalous database queries. | 12. A computer-implemented method for aggregating and presenting a database intrusion incident, the method comprising: using a computer processor configured to execute method steps, the steps comprising: receiving, from a database intrusion detection system, an anomalous database query requesting data from a database, the database intrusion detection system configured to separate acceptable database queries from anomalous database queries that are expected to have undesired effects on the database, wherein database queries are determined to be anomalous when the database queries differ from the acceptable database queries observed by the database intrusion detection system, the anomalous database query having at least one anomalous attribute; identifying an anomaly type for the query received, the anomaly type defining a category of anomalous database queries having similar anomalous attributes; converting the anomalous database query into a characteristic representation, the characteristic representation describing the anomalous attribute of the anomalous database query in a generic form for grouping according to the anomaly type; aggregating the anomalous database query and other anomalous database queries with substantially similar characteristic representations into a group of anomalous database queries to represent a single intrusion incident, wherein the other anomalous database queries are identified for aggregation into the group using an index generated based on the characteristic representation of the anomalous database query; and generating a database intrusion incident report describing the group of anomalous database queries. 18. The method of claim 12 , wherein the anomaly type comprises known query text with anomalous parameters. | 0.853425 |
6,024,289 | 12 | 14 | 12. A method of encoding a data string into a symbol, the method of encoding comprising the steps of: receiving the data string comprising a plurality of character codes selected from a first set of character codes, wherein the first set of character codes map to a first set of data characters, and wherein a second set of data characters form a subset of the data characters in the first set of data characters; converting each of the plurality of character codes corresponding to data characters contained only in the second set of data characters into a first defined number of symbol values; converting each of the plurality of character codes corresponding to characters in both the first and the second sets of data characters into a second defined number of symbol values, the second defined number of symbol values being greater than the first defined number of symbol values; and outputting the converted symbol values. | 12. A method of encoding a data string into a symbol, the method of encoding comprising the steps of: receiving the data string comprising a plurality of character codes selected from a first set of character codes, wherein the first set of character codes map to a first set of data characters, and wherein a second set of data characters form a subset of the data characters in the first set of data characters; converting each of the plurality of character codes corresponding to data characters contained only in the second set of data characters into a first defined number of symbol values; converting each of the plurality of character codes corresponding to characters in both the first and the second sets of data characters into a second defined number of symbol values, the second defined number of symbol values being greater than the first defined number of symbol values; and outputting the converted symbol values. 14. The method of claim 12, further comprising the steps of: receiving a string comprising a plurality of data characters, the data characters selected from the first set of data characters and the second set of data characters; determining the plurality of character codes corresponding to the plurality of data characters, the character codes selected from the first set of character codes; and outputting the plurality of character codes as the data string. | 0.5 |
5,500,919 | 1 | 6 | 1. A text-to-speech controller for controllably feeding a text file from a text buffer to a text-to-speech converter, the text file being comprised by text characters organized into words, including: an interface for inputting user commands which indicate how the text characters in the text file are fed from the text buffer to the text-to-speech converter; and a controller for effectuating the user commands at interword text boundaries such that the text characters are fed at interword text boundaries from the text buffer to the text-to-speech converter in accordance with the user commands. | 1. A text-to-speech controller for controllably feeding a text file from a text buffer to a text-to-speech converter, the text file being comprised by text characters organized into words, including: an interface for inputting user commands which indicate how the text characters in the text file are fed from the text buffer to the text-to-speech converter; and a controller for effectuating the user commands at interword text boundaries such that the text characters are fed at interword text boundaries from the text buffer to the text-to-speech converter in accordance with the user commands. 6. A controller according to claim 1, further comprising a voice telephone interface including a DTMF decoder, wherein the user commands are received via the DTMF decoder. | 0.600467 |
8,117,208 | 1 | 19 | 1. A method comprising: (a) receiving an input query q including one or more keywords and one or more entity types; (b) searching a database D that indexes keywords and instances of entities having entity types in a collection of documents, the searching including searching for documents having the keywords and entities with the entity types in the input query; (c) aggregating a respective score p o (q(t)) for each q(t) of a plurality of resultant entity tuples, where t consists of entities of the types in the input query, across the plurality of document d in the database D, where p(d) is a discriminative measure of d and p(q(t)|d) a local score of q(t), as follows: p o ( q ( t ) ) = p ( q ( t ) | D ) = ∑ d ∈ D p ( d ) · p ( q ( t ) | d ) ; (d) normalizing the aggregated scores by statistically validating the significance of said score over the database, each respective normalized score providing a ranking of a respective entity tuple, relative to other entity tuples, as an answer to the input query; and (e) outputting a list, including a subset of the entity tuples having the highest normalized scores among the plurality of entity tuples, to a storage or display device or a network. | 1. A method comprising: (a) receiving an input query q including one or more keywords and one or more entity types; (b) searching a database D that indexes keywords and instances of entities having entity types in a collection of documents, the searching including searching for documents having the keywords and entities with the entity types in the input query; (c) aggregating a respective score p o (q(t)) for each q(t) of a plurality of resultant entity tuples, where t consists of entities of the types in the input query, across the plurality of document d in the database D, where p(d) is a discriminative measure of d and p(q(t)|d) a local score of q(t), as follows: p o ( q ( t ) ) = p ( q ( t ) | D ) = ∑ d ∈ D p ( d ) · p ( q ( t ) | d ) ; (d) normalizing the aggregated scores by statistically validating the significance of said score over the database, each respective normalized score providing a ranking of a respective entity tuple, relative to other entity tuples, as an answer to the input query; and (e) outputting a list, including a subset of the entity tuples having the highest normalized scores among the plurality of entity tuples, to a storage or display device or a network. 19. The method of claim 1 , wherein the entity tuples in the list are arranged by normalized scores in descending order. | 0.842932 |
9,736,318 | 12 | 14 | 12. A computer program product, comprising: a computer readable storage medium having computer readable program code embodied therewith, where the computer readable storage medium is not a transitory signal per se and where the computer readable program code when executed on a computer causes the computer to: create, responsive to determining to transition a voice call from voice communications over a voice network to streamed text over a packetized data network, a voice conversation correlation identifier that identifies the voice call and specifies incoming and outgoing streamed text data as part of the voice call; convert additional outgoing speech spoken by a user associated with the voice call to streamed text data; send the streamed text data identified by the voice conversation correlation identifier within an outgoing text stream over the packetized data network; receive streamed response text data identified by the voice conversation correlation identifier within an incoming text stream over the packetized data network; and convert the received streamed response text data within the incoming text stream to speech output as part of the voice call; where, in causing the computer to receive the streamed response text data identified by the voice conversation correlation identifier within the incoming text stream over the packetized data network, the computer readable program code when executed on the computer causes the computer to one of: receive text advertisement content within the received streamed response text data within the incoming text stream associated with a subject matter of the voice call and rendering the text advertisement content during the voice call; or receive text represented in a different language from a language spoken by the user and performing a language conversion of the text represented in the different language to the language spoken by the user, where the received streamed response text data converted to the speech output comprises the language-converted text. | 12. A computer program product, comprising: a computer readable storage medium having computer readable program code embodied therewith, where the computer readable storage medium is not a transitory signal per se and where the computer readable program code when executed on a computer causes the computer to: create, responsive to determining to transition a voice call from voice communications over a voice network to streamed text over a packetized data network, a voice conversation correlation identifier that identifies the voice call and specifies incoming and outgoing streamed text data as part of the voice call; convert additional outgoing speech spoken by a user associated with the voice call to streamed text data; send the streamed text data identified by the voice conversation correlation identifier within an outgoing text stream over the packetized data network; receive streamed response text data identified by the voice conversation correlation identifier within an incoming text stream over the packetized data network; and convert the received streamed response text data within the incoming text stream to speech output as part of the voice call; where, in causing the computer to receive the streamed response text data identified by the voice conversation correlation identifier within the incoming text stream over the packetized data network, the computer readable program code when executed on the computer causes the computer to one of: receive text advertisement content within the received streamed response text data within the incoming text stream associated with a subject matter of the voice call and rendering the text advertisement content during the voice call; or receive text represented in a different language from a language spoken by the user and performing a language conversion of the text represented in the different language to the language spoken by the user, where the received streamed response text data converted to the speech output comprises the language-converted text. 14. The computer program product of claim 12 , where, in causing the computer to determine to transition the voice call from the voice network to the streamed text over the data network, the computer readable program code when executed on the computer causes the computer to: detect signal degradation of the voice network. | 0.868485 |
8,407,211 | 1 | 2 | 1. One or more computers comprising: a processor; a memory; wherein the one or more computers are configured to perform operations comprising: storing a respective plurality of category-location relevance scores for each location of a plurality of geographic locations, wherein each category-location relevance score for each location estimates a relevance of a respective category to the location, and wherein a category-location relevance score is based on a plurality of category-entity-location relevance scores for a plurality of entities associated with the category at the location, wherein storing a category-location relevance score for a location comprises storing a plurality of Taylor coefficients for a function at the location, wherein an evaluation of the function for a location provides a category-location relevance score for the category, and wherein an evaluation of the function at a location is determined by evaluating a sub-function for each of the plurality of entities, and wherein an evaluation of the sub-function for an entity provides a category-entity-location relevance score for the entity and the location; determining a first category-location relevance score for a first geographic location that is not one of the plurality of geographic locations, including: selecting a second geographic location in the plurality of geographic locations, and calculating the first category-location relevance score based on a second category-location relevance score for the second geographic location and a physical distance between the first geographic location and the second geographic location; and selecting an item from a plurality of candidate items using the first category location relevance score, wherein each candidate item is associated with a respective category, and wherein selecting the item comprises: ranking the plurality of candidate items using the first category location relevance score, and selecting a highest ranked candidate item. | 1. One or more computers comprising: a processor; a memory; wherein the one or more computers are configured to perform operations comprising: storing a respective plurality of category-location relevance scores for each location of a plurality of geographic locations, wherein each category-location relevance score for each location estimates a relevance of a respective category to the location, and wherein a category-location relevance score is based on a plurality of category-entity-location relevance scores for a plurality of entities associated with the category at the location, wherein storing a category-location relevance score for a location comprises storing a plurality of Taylor coefficients for a function at the location, wherein an evaluation of the function for a location provides a category-location relevance score for the category, and wherein an evaluation of the function at a location is determined by evaluating a sub-function for each of the plurality of entities, and wherein an evaluation of the sub-function for an entity provides a category-entity-location relevance score for the entity and the location; determining a first category-location relevance score for a first geographic location that is not one of the plurality of geographic locations, including: selecting a second geographic location in the plurality of geographic locations, and calculating the first category-location relevance score based on a second category-location relevance score for the second geographic location and a physical distance between the first geographic location and the second geographic location; and selecting an item from a plurality of candidate items using the first category location relevance score, wherein each candidate item is associated with a respective category, and wherein selecting the item comprises: ranking the plurality of candidate items using the first category location relevance score, and selecting a highest ranked candidate item. 2. The system of claim 1 , wherein selecting the item comprises selecting an ad from a plurality of ads for a user associated with the first geographic location. | 0.761834 |
9,081,848 | 1 | 5 | 1. A method for conducting one or more investigative matters, the method comprising: providing for categorization of a plurality of knowledge elements into a plurality of issue categories to produce a plurality of categorized knowledge elements, the knowledge elements each comprising a text drafted by one or more users and derived by the one or more users from one or more source materials; providing for association of the one or more source materials and the knowledge elements with one of the investigative matters; providing an editor configured for drafting of an editable narrative by the one or more users relating to the one of the investigative matters based at least in part on the categorized knowledge elements; providing access to the categorized knowledge elements associated with the one of the investigative matters during drafting of the editable narrative by the one or more users via a hopper in which the knowledge elements are organized by the issue categories, the hopper being positioned adjacent the editor such that the knowledge elements are simultaneously viewable with the editor and the editable narrative included therein; providing for confirmation and questioning of the knowledge elements; providing for selection of a plurality of incorporation buttons within the hopper, each of the incorporation buttons being respectively associated with one of the knowledge elements, each of the incorporation buttons being configured to insert the text of the one of the knowledge elements associated therewith into the editable narrative; providing for adding a link to a portion of the editable narrative drafted by the one or more users, the link linking to one or more of the knowledge elements the portion is based upon; and outputting the one or more knowledge elements upon selection of the portion of the editable narrative that is linked thereto via a processor. | 1. A method for conducting one or more investigative matters, the method comprising: providing for categorization of a plurality of knowledge elements into a plurality of issue categories to produce a plurality of categorized knowledge elements, the knowledge elements each comprising a text drafted by one or more users and derived by the one or more users from one or more source materials; providing for association of the one or more source materials and the knowledge elements with one of the investigative matters; providing an editor configured for drafting of an editable narrative by the one or more users relating to the one of the investigative matters based at least in part on the categorized knowledge elements; providing access to the categorized knowledge elements associated with the one of the investigative matters during drafting of the editable narrative by the one or more users via a hopper in which the knowledge elements are organized by the issue categories, the hopper being positioned adjacent the editor such that the knowledge elements are simultaneously viewable with the editor and the editable narrative included therein; providing for confirmation and questioning of the knowledge elements; providing for selection of a plurality of incorporation buttons within the hopper, each of the incorporation buttons being respectively associated with one of the knowledge elements, each of the incorporation buttons being configured to insert the text of the one of the knowledge elements associated therewith into the editable narrative; providing for adding a link to a portion of the editable narrative drafted by the one or more users, the link linking to one or more of the knowledge elements the portion is based upon; and outputting the one or more knowledge elements upon selection of the portion of the editable narrative that is linked thereto via a processor. 5. The method of claim 1 , wherein providing access to the categorized knowledge elements comprises providing for selection of the issue categories; and outputting the categorized knowledge elements included in a selected one of the issue categories. | 0.793729 |
8,214,421 | 12 | 14 | 12. The method of claim 1 , further comprising: passively monitoring the plurality of messages exchanged between the two or more participants. | 12. The method of claim 1 , further comprising: passively monitoring the plurality of messages exchanged between the two or more participants. 14. The method of claim 12 , wherein said testing conformance is performed after runtime. | 0.505556 |
9,792,900 | 2 | 3 | 2. The method of claim 1 , wherein synthesizing a targeted training data set comprises: obtaining training data from a speech corpus; over-selecting training data examples including the target problematic phoneme; and synthesizing a randomized targeted training data set for the target problematic phoneme using the selections from the speech corpus. | 2. The method of claim 1 , wherein synthesizing a targeted training data set comprises: obtaining training data from a speech corpus; over-selecting training data examples including the target problematic phoneme; and synthesizing a randomized targeted training data set for the target problematic phoneme using the selections from the speech corpus. 3. The method of claim 2 , wherein synthesizing a targeted training data set comprises over-selecting training data examples including at least one conflicting phoneme associated with the target problematic phoneme. | 0.5 |
9,517,559 | 9 | 17 | 9. A robot control system including a robot capable of autonomously moving in a space that an exhibition is placed, comprising: an acquiring module that acquires a position and a direction of a user in the space; a first determining module that determines whether the user enters a predetermined first range corresponding to the exhibition; a second determining module that determines whether the direction of the user turns to the exhibition; and an outputting module that makes the robot output an utterance content about the exhibition when it is determined that the user enters the predetermined first range and that the direction of the user turns to the exhibition; a third determining module that determines whether the user is out of a second range; and a stop module that stops the output of the utterance content when it is determined that the user is out of the second range, wherein the second range surrounds the predetermined first range and is broader than the predetermined first range. | 9. A robot control system including a robot capable of autonomously moving in a space that an exhibition is placed, comprising: an acquiring module that acquires a position and a direction of a user in the space; a first determining module that determines whether the user enters a predetermined first range corresponding to the exhibition; a second determining module that determines whether the direction of the user turns to the exhibition; and an outputting module that makes the robot output an utterance content about the exhibition when it is determined that the user enters the predetermined first range and that the direction of the user turns to the exhibition; a third determining module that determines whether the user is out of a second range; and a stop module that stops the output of the utterance content when it is determined that the user is out of the second range, wherein the second range surrounds the predetermined first range and is broader than the predetermined first range. 17. A robot control system according to claim 9 , wherein the robot comprises a pointing member for pointing to a direction, and the robot outputs the utterance content while pointing at the exhibition. | 0.751232 |
8,959,443 | 1 | 8 | 1. A method for providing an interface for object relationships, comprising: (a) receiving, at a host system from a user machine that is remote from the host system, a selection of at least a first object and a second object stored in an on-demand database service on a memory system of the host system and a definition of at least one relationship between the first object and the second object; (b) providing, to the user machine, based upon the at least one relationship between the first object and the second object, a diagram pictorially illustrating the at least one relationship; and (c) providing, to the user machine, a pictorial representation of a report that illustrates the at least one relationship, the pictorial representation having a visual appearance suggestive of a report; the pictorial representation not being the report; and the pictorial representation of the report being different than the diagram; (d) providing, to the user machine, in association with the pictorial representation of the report and the diagram, a representation of choices of data relationships, the representation of choices including at least one or more links for accepting user input, and a configurable hierarchical arrangement of selected relationships; (e) receiving, at the host system, user input at the server via the one or more links; (f) computing a new arrangement that is an update to the configurable hierarchical arrangement, an update to the diagram, and an update to the pictorial representation of the report; (g) providing to the user machine the update to the diagram, the update to the pictorial representation of the report and the new arrangement in association with the diagram and the pictorial indication. | 1. A method for providing an interface for object relationships, comprising: (a) receiving, at a host system from a user machine that is remote from the host system, a selection of at least a first object and a second object stored in an on-demand database service on a memory system of the host system and a definition of at least one relationship between the first object and the second object; (b) providing, to the user machine, based upon the at least one relationship between the first object and the second object, a diagram pictorially illustrating the at least one relationship; and (c) providing, to the user machine, a pictorial representation of a report that illustrates the at least one relationship, the pictorial representation having a visual appearance suggestive of a report; the pictorial representation not being the report; and the pictorial representation of the report being different than the diagram; (d) providing, to the user machine, in association with the pictorial representation of the report and the diagram, a representation of choices of data relationships, the representation of choices including at least one or more links for accepting user input, and a configurable hierarchical arrangement of selected relationships; (e) receiving, at the host system, user input at the server via the one or more links; (f) computing a new arrangement that is an update to the configurable hierarchical arrangement, an update to the diagram, and an update to the pictorial representation of the report; (g) providing to the user machine the update to the diagram, the update to the pictorial representation of the report and the new arrangement in association with the diagram and the pictorial indication. 8. The method of claim 1 , the further providing an icon of an arrow pointing from the diagram to the pictorial representation, the diagram having an appearance of a Venn diagram. | 0.898064 |
9,472,022 | 14 | 15 | 14. The method of claim 1 , wherein the applying a part matching comprises using a training module trained using a machine learning algorithm. | 14. The method of claim 1 , wherein the applying a part matching comprises using a training module trained using a machine learning algorithm. 15. The method of claim 14 , wherein the machine learning algorithm is an adaboost training procedure. | 0.694611 |
9,183,288 | 1 | 2 | 1. A computer-based method of organizing data for search, the method comprising the steps of: accessing a domain corpus; parsing the domain corpus into a plurality of documents; parsing each document into at least one term that corresponds to the document; generating a term-to-document matrix that correlates each document with the at least one term that corresponds to the document, the at least one term defining a document node for the document; performing a singular value decomposition and a dimension reduction on the term-to-document matrix to form a reformed term-to-document matrix having document nodes with fewer dimensions than the document nodes of the term-to-document matrix; comparing at least one document node of the reformed term-to-document matrix against another document node of the reformed term-to-document matrix; and combining at least one document node of the term-to-document matrix with another document node of the term-to-document matrix, based on the comparison of the at least one document node of the reformed tem-to-document matrix against the another document node of the reformed term-to-document matrix, to form a combined document node representing the combination of the at least one document node of the term-to-document matrix with the another document node of the term-to-document matrix, thereby clustering at least two document nodes of the term-to-document matrix. | 1. A computer-based method of organizing data for search, the method comprising the steps of: accessing a domain corpus; parsing the domain corpus into a plurality of documents; parsing each document into at least one term that corresponds to the document; generating a term-to-document matrix that correlates each document with the at least one term that corresponds to the document, the at least one term defining a document node for the document; performing a singular value decomposition and a dimension reduction on the term-to-document matrix to form a reformed term-to-document matrix having document nodes with fewer dimensions than the document nodes of the term-to-document matrix; comparing at least one document node of the reformed term-to-document matrix against another document node of the reformed term-to-document matrix; and combining at least one document node of the term-to-document matrix with another document node of the term-to-document matrix, based on the comparison of the at least one document node of the reformed tem-to-document matrix against the another document node of the reformed term-to-document matrix, to form a combined document node representing the combination of the at least one document node of the term-to-document matrix with the another document node of the term-to-document matrix, thereby clustering at least two document nodes of the term-to-document matrix. 2. The computer-based method of claim 1 , wherein the step of comparing the at least one document node of the reformed term-to-document matrix against the another document node of the reformed term-to-document matrix, includes determining the cosine similarity between the at least one document node of the reformed term-to-document matrix and the another document node of the reformed tem-to-document matrix, | 0.795295 |
9,190,063 | 13 | 23 | 13. A method of performing recognition of a speech utterance from a user with a distributed client-server system comprising: receiving user speech data from a client device in streaming packets through a network interface of a network server system employing an application level Internet based protocol overlaid on transmission control protocol (TCP) such that said streaming packets are processed as they are received, said speech data resulting from a first set of speech recognition operations being performed on the speech utterance by a client device; recognizing the speech utterance as well as a natural language used in said speech utterance using processing routines executing at said network server system which implement a second set of speech recognition operations, wherein recognizing includes converting the speech utterance into text using a Hidden Markov Modeling technique; sending text corresponding to the speech utterance to a natural language engine and a database engine; performing linguistic processing of the text at the natural language engine, wherein linguistic processing of the text includes tokenizing the text, tagging one or more tokens, grouping the tagged tokens and storing one or more noun phrases associated with the text; transferring the one or more noun phrases to the database engine for construction of an SQL query; providing a response to the user in a same natural language as was recognized; automatically adjusting said second set of speech recognition operations based on an automated evaluation of resources available at the network server system and/or the client device; and automatically adjusting said first set of speech recognition operations based on an automated evaluation of resources available at the client device. | 13. A method of performing recognition of a speech utterance from a user with a distributed client-server system comprising: receiving user speech data from a client device in streaming packets through a network interface of a network server system employing an application level Internet based protocol overlaid on transmission control protocol (TCP) such that said streaming packets are processed as they are received, said speech data resulting from a first set of speech recognition operations being performed on the speech utterance by a client device; recognizing the speech utterance as well as a natural language used in said speech utterance using processing routines executing at said network server system which implement a second set of speech recognition operations, wherein recognizing includes converting the speech utterance into text using a Hidden Markov Modeling technique; sending text corresponding to the speech utterance to a natural language engine and a database engine; performing linguistic processing of the text at the natural language engine, wherein linguistic processing of the text includes tokenizing the text, tagging one or more tokens, grouping the tagged tokens and storing one or more noun phrases associated with the text; transferring the one or more noun phrases to the database engine for construction of an SQL query; providing a response to the user in a same natural language as was recognized; automatically adjusting said second set of speech recognition operations based on an automated evaluation of resources available at the network server system and/or the client device; and automatically adjusting said first set of speech recognition operations based on an automated evaluation of resources available at the client device. 23. The method of claim 13 , wherein a confidence level for identifying said response as processed by a natural language engine can be specified for the speech utterance. | 0.755747 |
8,233,671 | 5 | 6 | 5. The apparatus of claim 1 , comprising memory having an OCR module to generate the text blocks when executed by the at least one processor. | 5. The apparatus of claim 1 , comprising memory having an OCR module to generate the text blocks when executed by the at least one processor. 6. The apparatus of claim 5 , comprising memory having a characterization module configured to characterize the text blocks when executed by the at least one processor. | 0.5 |
9,372,905 | 8 | 14 | 8. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive metadata associated with data stored in a data structure; determine, based on the metadata, a category associated with the data; present, for display, a user interface associated with building a graphical query based on the category, the graphical query including a visual representation of a data structure query used to search the data in the data structure, the user interface including one or more input elements that allow a user to build the graphical query, at least one input element of the one or more input elements being associated with information that identifies a group of categories including the category, and at least one other input element of the one or more input elements being associated with information that identifies one or more operators associated with filtering the data; receive information associated with the graphical query via the user interface, the information associated with the graphical query including information indicating the data structure query is to be based on the category; present, for display, the information associated with the graphical query by creating a visual tree, the visual tree including at least one representation of the category and at least one representation of an operator of the one or more operators; and provide, to a query device, the information associated with the graphical query to cause the query device to convert the graphical query into the data structure query, and without requiring the user to generate the data structure query. | 8. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive metadata associated with data stored in a data structure; determine, based on the metadata, a category associated with the data; present, for display, a user interface associated with building a graphical query based on the category, the graphical query including a visual representation of a data structure query used to search the data in the data structure, the user interface including one or more input elements that allow a user to build the graphical query, at least one input element of the one or more input elements being associated with information that identifies a group of categories including the category, and at least one other input element of the one or more input elements being associated with information that identifies one or more operators associated with filtering the data; receive information associated with the graphical query via the user interface, the information associated with the graphical query including information indicating the data structure query is to be based on the category; present, for display, the information associated with the graphical query by creating a visual tree, the visual tree including at least one representation of the category and at least one representation of an operator of the one or more operators; and provide, to a query device, the information associated with the graphical query to cause the query device to convert the graphical query into the data structure query, and without requiring the user to generate the data structure query. 14. The non-transitory computer-readable medium of claim 8 , where the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: determine information associated with a stored graphical query; and where the one or more instructions, that cause the one or more processors to present, for display, the user interface associated with building the graphical query, cause the one or more processors to: present, for display, the information associated with the stored graphical query. | 0.544143 |
9,875,305 | 11 | 16 | 11. A computer program product comprising at least one non-transitory computer-readable medium storing instructions translatable by at least one processor of a computerized search system for instructing a search engine of the computerized search system to: receive an indexing request associated with an object; identify any derived metadata fields in a search index that would be affected by the indexing request associated with the object, the search index stored in a storage unit of the computerized search system; determine whether any of the identified derived metadata fields in the search index that would be affected by the indexing request associated with the object are within a list or record of protected metadata fields; retain any of the identified derived metadata fields in the search index that would be affected by the indexing request associated with the object and that are determined to be within the list or record of protected metadata fields such that any of the identified derived metadata fields in the search index thus retained are protected from change caused by the indexing request associated with the object; and execute an indexing command to update the search index with data associated with the object and without any of the identified derived metadata fields in the search index thus retained by the search engine such that the search index is updated without the search engine deleting or changing any value of the derived metadata fields in the search index that have been identified by the search engine as would be affected by the indexing request associated with the object and that have been determined by the search engine to be associated with the list or record of protected metadata fields, the data comprising text, metadata, or both. | 11. A computer program product comprising at least one non-transitory computer-readable medium storing instructions translatable by at least one processor of a computerized search system for instructing a search engine of the computerized search system to: receive an indexing request associated with an object; identify any derived metadata fields in a search index that would be affected by the indexing request associated with the object, the search index stored in a storage unit of the computerized search system; determine whether any of the identified derived metadata fields in the search index that would be affected by the indexing request associated with the object are within a list or record of protected metadata fields; retain any of the identified derived metadata fields in the search index that would be affected by the indexing request associated with the object and that are determined to be within the list or record of protected metadata fields such that any of the identified derived metadata fields in the search index thus retained are protected from change caused by the indexing request associated with the object; and execute an indexing command to update the search index with data associated with the object and without any of the identified derived metadata fields in the search index thus retained by the search engine such that the search index is updated without the search engine deleting or changing any value of the derived metadata fields in the search index that have been identified by the search engine as would be affected by the indexing request associated with the object and that have been determined by the search engine to be associated with the list or record of protected metadata fields, the data comprising text, metadata, or both. 16. The computer program product of claim 11 , wherein the list or record of protected metadata fields that are to be protected from change includes a metadata field derived by identifying keywords or concepts in the text using semantic or statistical methods. | 0.577922 |
8,286,218 | 10 | 14 | 10. An interactive television network comprising: a plurality of programming content, the plurality of programming content provided by a plurality of content from different providers, the plurality of programming content received from multiple video cameras positioned at different locations; at least one server at a production facility that receives the plurality of programming content from the Internet, wherein the production facility manipulates the programming content to create a viewer-customized production; first viewer input received from user computers that are remotely located from the production facility, the first viewer input submitted by multiple first viewers over the Internet to the server at the production facility, wherein the multiple first viewers vote on different portions of the programming content received from the multiple video cameras to select different portions of the programming content received from the multiple video cameras; wherein the multiple first viewers vote on different portions of the music to select desired music from different music from different providers, wherein the different music is composed by the different providers; different audio commentaries about the programming content from different providers, wherein the different audio commentaries represent different points of view; second viewer input that selects a desired commentary from the different audio commentaries, wherein the server is configured to combine the selected different portions of the programming content from the multiple video cameras and the desired music based on the first viewer input with the desired commentary based on the second viewer input , and wherein the viewer-customized production is viewed over the Internet by at least the second viewer; wherein the server is further configured to track usage of items included in the viewer-customized production, the items comprising the programming content and music selected with the first viewer input, and the desired commentary selected with the second viewer input; wherein the server is further configured to track which of the different providers provided the programming content, which of the different providers provided the desired commentary, and which of the different providers provided the desired music included in the viewer-customized production; and wherein the server is further configured to pay the different providers that provided the programming content, the desired music and the desired commentary a share of revenues associated with the viewer-customized production. | 10. An interactive television network comprising: a plurality of programming content, the plurality of programming content provided by a plurality of content from different providers, the plurality of programming content received from multiple video cameras positioned at different locations; at least one server at a production facility that receives the plurality of programming content from the Internet, wherein the production facility manipulates the programming content to create a viewer-customized production; first viewer input received from user computers that are remotely located from the production facility, the first viewer input submitted by multiple first viewers over the Internet to the server at the production facility, wherein the multiple first viewers vote on different portions of the programming content received from the multiple video cameras to select different portions of the programming content received from the multiple video cameras; wherein the multiple first viewers vote on different portions of the music to select desired music from different music from different providers, wherein the different music is composed by the different providers; different audio commentaries about the programming content from different providers, wherein the different audio commentaries represent different points of view; second viewer input that selects a desired commentary from the different audio commentaries, wherein the server is configured to combine the selected different portions of the programming content from the multiple video cameras and the desired music based on the first viewer input with the desired commentary based on the second viewer input , and wherein the viewer-customized production is viewed over the Internet by at least the second viewer; wherein the server is further configured to track usage of items included in the viewer-customized production, the items comprising the programming content and music selected with the first viewer input, and the desired commentary selected with the second viewer input; wherein the server is further configured to track which of the different providers provided the programming content, which of the different providers provided the desired commentary, and which of the different providers provided the desired music included in the viewer-customized production; and wherein the server is further configured to pay the different providers that provided the programming content, the desired music and the desired commentary a share of revenues associated with the viewer-customized production. 14. The network of claim 10 , wherein the second viewer comprises the production facility. | 0.934018 |
8,942,768 | 1 | 6 | 1. A method, comprising: receiving a communication message at a mobile device having a primary display and a secondary display, the primary and secondary displays comprising separate displays; determining whether the communication message is a voice message, an e-mail message or a text message; using one or more words from the voice message as text for a text title when the communication message is a voice message; using one or more words from the e-mail message as text for a text title when the communication message is an e-mail message; using one or more words from the text message as text for a text title when the communication message is a text message; and displaying the text title associated with the communication message on the secondary display, the secondary display including a prism arranged to create an illusion that the text title is floating in a middle of the prism and the prism is rounded toward a front face of a device to enable a user to read a side display screen when the device is lying flat on a back side of the device. | 1. A method, comprising: receiving a communication message at a mobile device having a primary display and a secondary display, the primary and secondary displays comprising separate displays; determining whether the communication message is a voice message, an e-mail message or a text message; using one or more words from the voice message as text for a text title when the communication message is a voice message; using one or more words from the e-mail message as text for a text title when the communication message is an e-mail message; using one or more words from the text message as text for a text title when the communication message is a text message; and displaying the text title associated with the communication message on the secondary display, the secondary display including a prism arranged to create an illusion that the text title is floating in a middle of the prism and the prism is rounded toward a front face of a device to enable a user to read a side display screen when the device is lying flat on a back side of the device. 6. The method of claim 1 , comprising: determining that the communication message is an e-mail message; creating a text title with denoted text when the e-mail has denoted text for the text title; and creating a text title using a subject line of the e-mail as the text title when the e-mail does not have text denoted for the text title. | 0.518519 |
7,542,979 | 34 | 35 | 34. A method as in claim 33 , wherein the variable rule comprises a condition, a parsedescriptor, and a values clause. | 34. A method as in claim 33 , wherein the variable rule comprises a condition, a parsedescriptor, and a values clause. 35. A method as in claim 34 , wherein the variable rule further includes an endcondition. | 0.505556 |
8,620,080 | 1 | 5 | 1. A method for locating text in a digital image, said method comprising: receiving a first plurality of candidate components; filtering said first plurality of candidate components based on component properties, thereby producing a second plurality of candidate components; forming a first plurality of text lines from said second plurality of candidate components; filtering said first plurality of text lines based on a first text-line property associated with text-line length, thereby producing a second plurality of text lines; and filtering said second plurality of text lines based on a second text-line property associated with text-line orientation to locate a plurality of text components associated with said digital image. | 1. A method for locating text in a digital image, said method comprising: receiving a first plurality of candidate components; filtering said first plurality of candidate components based on component properties, thereby producing a second plurality of candidate components; forming a first plurality of text lines from said second plurality of candidate components; filtering said first plurality of text lines based on a first text-line property associated with text-line length, thereby producing a second plurality of text lines; and filtering said second plurality of text lines based on a second text-line property associated with text-line orientation to locate a plurality of text components associated with said digital image. 5. A method as described in claim 1 , wherein said filtering said first plurality of candidate components based on component properties comprises: filtering said first plurality of candidate components based on a first component property, wherein said filtering said first plurality of candidate components based on a first component property associates a membership value with each candidate component in said first plurality of candidate components, thereby producing a first plurality of membership values; filtering said first plurality of candidate components based on a second component property, wherein said filtering said first plurality of candidate components based on a second component property associates a membership value with each candidate component in said first plurality of candidate components, thereby producing a second plurality of membership values; and combining said first plurality of membership values and said second plurality of membership values to produce said second plurality of candidate components. | 0.5 |
7,617,187 | 6 | 10 | 6. A system for searching a second dataset from a first dataset, the system comprising: a first dataset operating with a first collation, the first collation having a case sensitivity flag, an accent use sensitivity flag, a character width sensitivity flag, and a kana sensitivity flag for a first human language; a second dataset operating with a second collation different from the first collation; receiving means that accepts a first query from the first dataset against the second dataset; an algebrizer that rewrites the first query into a second query; an optimizer that chooses an index plan for the second query; a query execution unit that executes the second query; a processor, having access to memory for retrieving instructions, the instructions, when executed by the processor, causing the processor to perform acts comprising: receiving a first query from the first dataset, the first query being generated using the first collation associated with the first dataset, the first collation having the case sensitivity flag, the accent use sensitivity flag, the character width sensitivity flag, and the kana sensitivity flag for the first human language; rewriting the first query to form a second query, the second query comprising a second collation and a residue predicate, the second collation comprising a superset of the first collation, the second collation of the second query being broader than the first collation of the first query and being insensitive with respect to at least one of case, accent use, character width, and kana, the second collation encompassing the first collation, the second collation having an associated index for the second collation, and the residue predicate comprising an original search term from the first query including the first collation, wherein the residue predicate is selected to ensure that a set of results returned in response to the second query satisfies the case sensitivity flag, the accent use sensitivity flag, the character width sensitivity flag, and the kana sensitivity flag of the first collation; optimizing the second query by choosing an index plan that targets an index associated with multiple human languages that is useful in searching across a multiplicity of human language collations; executing the second query to search the first dataset; and returning information satisfying the first query; wherein the first and second datasets each comprise one of a database, a user session and an explicit user query. | 6. A system for searching a second dataset from a first dataset, the system comprising: a first dataset operating with a first collation, the first collation having a case sensitivity flag, an accent use sensitivity flag, a character width sensitivity flag, and a kana sensitivity flag for a first human language; a second dataset operating with a second collation different from the first collation; receiving means that accepts a first query from the first dataset against the second dataset; an algebrizer that rewrites the first query into a second query; an optimizer that chooses an index plan for the second query; a query execution unit that executes the second query; a processor, having access to memory for retrieving instructions, the instructions, when executed by the processor, causing the processor to perform acts comprising: receiving a first query from the first dataset, the first query being generated using the first collation associated with the first dataset, the first collation having the case sensitivity flag, the accent use sensitivity flag, the character width sensitivity flag, and the kana sensitivity flag for the first human language; rewriting the first query to form a second query, the second query comprising a second collation and a residue predicate, the second collation comprising a superset of the first collation, the second collation of the second query being broader than the first collation of the first query and being insensitive with respect to at least one of case, accent use, character width, and kana, the second collation encompassing the first collation, the second collation having an associated index for the second collation, and the residue predicate comprising an original search term from the first query including the first collation, wherein the residue predicate is selected to ensure that a set of results returned in response to the second query satisfies the case sensitivity flag, the accent use sensitivity flag, the character width sensitivity flag, and the kana sensitivity flag of the first collation; optimizing the second query by choosing an index plan that targets an index associated with multiple human languages that is useful in searching across a multiplicity of human language collations; executing the second query to search the first dataset; and returning information satisfying the first query; wherein the first and second datasets each comprise one of a database, a user session and an explicit user query. 10. The system of claim 6 , wherein the method step of executing the second query to search the first dataset comprises executing the second query to search for system objects in a system resource database of a SQL database management system. | 0.592593 |
9,378,296 | 1 | 5 | 1. A computer implemented method for generating a customized virtual world, the computer implemented comprising: receiving, by a query server, a query from a client computing device comprising a target style, wherein the query requests entry points to virtual worlds having content associated with at least one criterion and wherein the target style is a user selected style for portal representations; identifying, by the query server data processing system, a set of portals from a virtual world database to be rendered within the customized virtual world, wherein the set of portals are objects representing entry points to alternate virtual worlds that satisfy the query and wherein each portal is an entry point at a location within the customized virtual world; selecting, by a construction server, a representation associated with the target style for each portal in the set of portals to form a set of selected representations, wherein selecting a representation associated with the target style further comprises: identifying a given portal in the set of portals; searching a set of preferred representations associated with the given portal for a preferred representation matching the target style; and responsive a failure to identify a matching preferred representation for the given portal matching the target style, selecting a default representation to form the selected representation for the given portal; constructing, by the construction server, a virtual world with the set of selected representations to form the customized virtual world, wherein the set of representations are rendered within the customized virtual world; and returning the customized virtual world to the client computing device as a response to the query. | 1. A computer implemented method for generating a customized virtual world, the computer implemented comprising: receiving, by a query server, a query from a client computing device comprising a target style, wherein the query requests entry points to virtual worlds having content associated with at least one criterion and wherein the target style is a user selected style for portal representations; identifying, by the query server data processing system, a set of portals from a virtual world database to be rendered within the customized virtual world, wherein the set of portals are objects representing entry points to alternate virtual worlds that satisfy the query and wherein each portal is an entry point at a location within the customized virtual world; selecting, by a construction server, a representation associated with the target style for each portal in the set of portals to form a set of selected representations, wherein selecting a representation associated with the target style further comprises: identifying a given portal in the set of portals; searching a set of preferred representations associated with the given portal for a preferred representation matching the target style; and responsive a failure to identify a matching preferred representation for the given portal matching the target style, selecting a default representation to form the selected representation for the given portal; constructing, by the construction server, a virtual world with the set of selected representations to form the customized virtual world, wherein the set of representations are rendered within the customized virtual world; and returning the customized virtual world to the client computing device as a response to the query. 5. The computer implemented method of claim 1 further comprising: receiving review data associated with a given representation for a portal from a set of users; generating a rating for the representation based on a set of user suggested ratings; and responsive to a threshold number of negative ratings for the representation, indicating that the given representation is an unsuitable representation, wherein an unsuitable representation is unavailable for utilization. | 0.791741 |
10,003,923 | 1 | 7 | 1. A method performed by a computer server for inferring location context categories for a set of mobile users having at least two members, comprising: for each mobile user in the set, obtaining at least one location context category; and applying multi-user collaborative machine learning with an objective function to the at least one location context category for each mobile user in the set to infer a single refined location context category for each mobile user in the set to form a matrix. | 1. A method performed by a computer server for inferring location context categories for a set of mobile users having at least two members, comprising: for each mobile user in the set, obtaining at least one location context category; and applying multi-user collaborative machine learning with an objective function to the at least one location context category for each mobile user in the set to infer a single refined location context category for each mobile user in the set to form a matrix. 7. The method of claim 1 , wherein the objective function is expressed using a convex envelope of a non-convex rank function subject to a row constraint on the matrix. | 0.839114 |
7,792,667 | 1 | 8 | 1. A method of automatic, computer based identification of a significant phrase in a document, the method comprising: storing the document, a threshold score, a verbosity setting, and a significant phrases data structure in a memory; accessing the memory to read a sequence of words from the document; determining by a processing unit a score for each word in the sequence based on the length of each word; operating the processing unit to compare the score for each word in the sequence against the threshold score; adding the sequence of words as a significant phrase to the significant phrase data structure if: the number of words in the sequence that have the score greater than the threshold score equals or exceeds a predetermined number and the number of words in the sequence satisfies the verbosity setting; retrieving a sentence from the document, in the memory if the sentence contains a significant phrase stored in the significant phrases data structure; and operating the processing unit to search an abstract of the document to determine whether the sentence is included in the abstract. | 1. A method of automatic, computer based identification of a significant phrase in a document, the method comprising: storing the document, a threshold score, a verbosity setting, and a significant phrases data structure in a memory; accessing the memory to read a sequence of words from the document; determining by a processing unit a score for each word in the sequence based on the length of each word; operating the processing unit to compare the score for each word in the sequence against the threshold score; adding the sequence of words as a significant phrase to the significant phrase data structure if: the number of words in the sequence that have the score greater than the threshold score equals or exceeds a predetermined number and the number of words in the sequence satisfies the verbosity setting; retrieving a sentence from the document, in the memory if the sentence contains a significant phrase stored in the significant phrases data structure; and operating the processing unit to search an abstract of the document to determine whether the sentence is included in the abstract. 8. The method of claim 1 , wherein the threshold score is based on an average of the scores of words in the sequence of words. | 0.730769 |
8,122,022 | 1 | 6 | 1. A computer-implemented method comprising: receiving a compound term that includes multiple constituent terms, and a candidate abbreviation for the compound term; pairing, with the candidate abbreviation, a constituent term, wherein the paired constituent term is one of the multiple constituent terms that make up a portion of the compound term; applying a similarity criterion to the paired candidate abbreviation and constituent term; determining that the paired candidate abbreviation and constituent term satisfy the applied similarity criterion; and establishing that the candidate abbreviation is not an abbreviation for the compound term, based on determining that the paired candidate abbreviation and constituent term satisfy the applied similarity criterion. | 1. A computer-implemented method comprising: receiving a compound term that includes multiple constituent terms, and a candidate abbreviation for the compound term; pairing, with the candidate abbreviation, a constituent term, wherein the paired constituent term is one of the multiple constituent terms that make up a portion of the compound term; applying a similarity criterion to the paired candidate abbreviation and constituent term; determining that the paired candidate abbreviation and constituent term satisfy the applied similarity criterion; and establishing that the candidate abbreviation is not an abbreviation for the compound term, based on determining that the paired candidate abbreviation and constituent term satisfy the applied similarity criterion. 6. The computer-implemented method of claim 1 , wherein the similarity criterion is a stemming criterion; wherein applying the similarity criterion to the paired candidate abbreviation and constituent term comprises: determining that the constituent term of the pair and the candidate abbreviation share a common prefix, and based on determining that the constituent term of the pair and the candidate abbreviation share a common prefix, determining a comparison value by dividing a number of characters of the common prefix by a length of one of the constituent term of the pair and the candidate abbreviation; and wherein determining that the paired candidate abbreviation and constituent term satisfy the applied similarity criterion comprises determining that the comparison value is greater than or equal to a threshold value. | 0.537305 |
9,684,701 | 14 | 16 | 14. A computer program product for replicating IP address assignment changes in a distributed database having a plurality of nodes, the computer program product being embodied in a non-transitory computer readable medium and comprising computer instructions for: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, wherein a change request to modify the distributed database is expressed as the semantic command, the semantic command being expressed as one of a predefined set of commands, wherein the receiving of the semantic command at the first node comprises: receiving credentials of a user; and determining whether to authorize the user based on the received credentials, the user being authorized in the event that the user has not been previously authorized within a predetermined time period; and provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node, wherein the provisional applying the semantic command to the first local version of the database comprises modifying the first local version of the database before reconciling the modification with the master node, wherein the reconciling of the modification with the master comprises: forwarding the received credentials to the master; determining whether the modification would cause a conflict on the master, comprising: determining whether the same user has been authorized on a second node within the predetermined time period; and in the event that the modification would not cause a conflict, performing the modification on the master node. | 14. A computer program product for replicating IP address assignment changes in a distributed database having a plurality of nodes, the computer program product being embodied in a non-transitory computer readable medium and comprising computer instructions for: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, wherein a change request to modify the distributed database is expressed as the semantic command, the semantic command being expressed as one of a predefined set of commands, wherein the receiving of the semantic command at the first node comprises: receiving credentials of a user; and determining whether to authorize the user based on the received credentials, the user being authorized in the event that the user has not been previously authorized within a predetermined time period; and provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node, wherein the provisional applying the semantic command to the first local version of the database comprises modifying the first local version of the database before reconciling the modification with the master node, wherein the reconciling of the modification with the master comprises: forwarding the received credentials to the master; determining whether the modification would cause a conflict on the master, comprising: determining whether the same user has been authorized on a second node within the predetermined time period; and in the event that the modification would not cause a conflict, performing the modification on the master node. 16. A computer program product as recited in claim 14 , the computer program product further comprising computer instructions for interpreting the semantic command, including determining an operation associated with the semantic command, wherein the semantic command is defined by one or more instructions or operations. | 0.697543 |
8,909,566 | 12 | 22 | 12. A non-transitory computer-readable storage medium comprising a plurality of computer-readable instructions tangibly embodied on the computer-readable storage medium, which, when executed by a data processor, provide for analyzing symbols in a computer system, the plurality of instructions comprising: instructions that cause the data processor to to receive a message including symbols; instructions that cause the data processor to perform a lexical analysis of the message, the lexical analysis generating a sequence of tokens based on the symbols included in the message, wherein a token in the sequence of tokens corresponds to a category of symbols, and wherein the category of symbols corresponds to a plurality of symbols having different values; instructions that cause the data processor to determine a message digest for the sequence of tokens, wherein the message digest is updated as each token in the sequence of tokens is identified during the lexical analysis; instructions that cause the data processor to assign the message to a cluster group based on the message digest. | 12. A non-transitory computer-readable storage medium comprising a plurality of computer-readable instructions tangibly embodied on the computer-readable storage medium, which, when executed by a data processor, provide for analyzing symbols in a computer system, the plurality of instructions comprising: instructions that cause the data processor to to receive a message including symbols; instructions that cause the data processor to perform a lexical analysis of the message, the lexical analysis generating a sequence of tokens based on the symbols included in the message, wherein a token in the sequence of tokens corresponds to a category of symbols, and wherein the category of symbols corresponds to a plurality of symbols having different values; instructions that cause the data processor to determine a message digest for the sequence of tokens, wherein the message digest is updated as each token in the sequence of tokens is identified during the lexical analysis; instructions that cause the data processor to assign the message to a cluster group based on the message digest. 22. The non-transitory computer-readable storage medium of claim 12 , wherein a message comprises a sequence of one or more machine instructions that are executed by a micro-processor within the computer system. | 0.815559 |
7,596,574 | 45 | 47 | 45. The computer program product of claim 44 wherein the facet analysis component is configured to receive input information and discover the facets, facet attributes, and facet attribute hierarchies of the input information, said input information comprising at least one of information of the domain to be classified and said dimensional concept taxonomy information. | 45. The computer program product of claim 44 wherein the facet analysis component is configured to receive input information and discover the facets, facet attributes, and facet attribute hierarchies of the input information, said input information comprising at least one of information of the domain to be classified and said dimensional concept taxonomy information. 47. The computer program product of claim 45 wherein the facet analysis component is configured to define the facets, facet attributes, and facet attribute hierarchies using pattern augmentation and statistical analyses to identify patterns of facet attribute relationships in the input information, wherein said facet attribute relationships are determined from facet attributes in related concept definitions and concept relationships in the input information and in accordance with a prevalence of the facet attribute relationships derived from the input information. | 0.5 |
8,799,765 | 1 | 11 | 1. A digital computing device for viewing shared annotations of at least one electronic reference document, the device comprising a digital memory, a display, a user input interface, and a network interface; and said computing device being configured to: receive, over a network, via the network interface, a digital location identifier for navigation to a shared reading location with an associated annotation, said digital location identifier specifying the shared reading location within a version of the electronic reference document and does not include the version of the electronic reference document; upon receipt of a selection to navigate to the shared reading location, determine if a user of the digital computing device has sufficient rights to use a copy of the electronic reference document referenced by the digital location identifier, and, if the user does not have sufficient rights, (i) provide a prompt with an option for the user to purchase said rights, (ii) responsive to confirmation of the purchase of the rights to use the copy of the electronic reference document, receive the copy of the electronic reference document, and (iii) store the copy of the electronic reference document in the digital memory; and upon successful confirmation of the user's rights to use the copy of the electronic reference document and responsive to the selection to navigate to the shared reading location (i) determining that the content referenced by the digital location identifier exists in the copy of the reference document, (ii) displaying at least a portion of the copy of the electronic reference document at the shared reading location and the associated annotation within the copy of the electronic reference document at the shared reading location. | 1. A digital computing device for viewing shared annotations of at least one electronic reference document, the device comprising a digital memory, a display, a user input interface, and a network interface; and said computing device being configured to: receive, over a network, via the network interface, a digital location identifier for navigation to a shared reading location with an associated annotation, said digital location identifier specifying the shared reading location within a version of the electronic reference document and does not include the version of the electronic reference document; upon receipt of a selection to navigate to the shared reading location, determine if a user of the digital computing device has sufficient rights to use a copy of the electronic reference document referenced by the digital location identifier, and, if the user does not have sufficient rights, (i) provide a prompt with an option for the user to purchase said rights, (ii) responsive to confirmation of the purchase of the rights to use the copy of the electronic reference document, receive the copy of the electronic reference document, and (iii) store the copy of the electronic reference document in the digital memory; and upon successful confirmation of the user's rights to use the copy of the electronic reference document and responsive to the selection to navigate to the shared reading location (i) determining that the content referenced by the digital location identifier exists in the copy of the reference document, (ii) displaying at least a portion of the copy of the electronic reference document at the shared reading location and the associated annotation within the copy of the electronic reference document at the shared reading location. 11. The computing device of claim 1 , wherein the computing device is configured to display the copy of the electronic reference document, with the annotation automatically shown at a nearest similar location on the display responsive to determining that the content referenced by the digital location identifier does not exist in the copy of the electronic reference document. | 0.5 |
10,032,191 | 19 | 32 | 19. The method of claim 12 , further comprising: accessing a pairing server when processing an identification data associated with the sandbox reachable service of the networked device that shares a public address with the client device, wherein the pairing server performs a discovery lookup of any device that has announced that it shares the public address associated with the client device, and wherein the sandbox reachable service announces itself to the pairing server prior to establishment of a communication session between the sandboxed application and the sandbox reachable service; appending a header of a hypertext transfer protocol to permit the networked device to communicate with the sandboxed application as a permitted origin domain through a CORS algorithm, the header being either one of a origin header when the CORS algorithm is applied and a referrer header in an alternate algorithm in accordance with the client device: processing the identification data associated with the sandbox reachable service sharing the public address with the client device; determining a private address pair of the sandbox reachable service based on the identification data; and establishing the communication session between the sandboxed application and the sandbox reachable service using a cross-site scripting technique of the security sandbox, wherein the sandboxed application queries a MAC address of the sandbox reachable service in a common private network, wherein the method further comprises the sandbox reachable service optionally verifying that the sandboxed application is in the common private network, wherein the method further comprises the sandbox reachable service communicating a MAC address of the sandboxed application to the sandboxed application when the common private network is shared, wherein the sandboxed application stores the MAC address of the sandboxed application and a unique identifier derived from the MAC address of the sandboxed application, and wherein the sandboxed application communicates the MAC address and the unique identifier to the pairing server; and automatically regenerating the script embedded in the at least one of the client device, the supply-side platform, and the data provider integrated with the supply side platform when the common private network is shared by the sandboxed application and the sandbox reachable service based on the MAC address of the sandboxed application and the unique identifier communicated to the pairing server. | 19. The method of claim 12 , further comprising: accessing a pairing server when processing an identification data associated with the sandbox reachable service of the networked device that shares a public address with the client device, wherein the pairing server performs a discovery lookup of any device that has announced that it shares the public address associated with the client device, and wherein the sandbox reachable service announces itself to the pairing server prior to establishment of a communication session between the sandboxed application and the sandbox reachable service; appending a header of a hypertext transfer protocol to permit the networked device to communicate with the sandboxed application as a permitted origin domain through a CORS algorithm, the header being either one of a origin header when the CORS algorithm is applied and a referrer header in an alternate algorithm in accordance with the client device: processing the identification data associated with the sandbox reachable service sharing the public address with the client device; determining a private address pair of the sandbox reachable service based on the identification data; and establishing the communication session between the sandboxed application and the sandbox reachable service using a cross-site scripting technique of the security sandbox, wherein the sandboxed application queries a MAC address of the sandbox reachable service in a common private network, wherein the method further comprises the sandbox reachable service optionally verifying that the sandboxed application is in the common private network, wherein the method further comprises the sandbox reachable service communicating a MAC address of the sandboxed application to the sandboxed application when the common private network is shared, wherein the sandboxed application stores the MAC address of the sandboxed application and a unique identifier derived from the MAC address of the sandboxed application, and wherein the sandboxed application communicates the MAC address and the unique identifier to the pairing server; and automatically regenerating the script embedded in the at least one of the client device, the supply-side platform, and the data provider integrated with the supply side platform when the common private network is shared by the sandboxed application and the sandbox reachable service based on the MAC address of the sandboxed application and the unique identifier communicated to the pairing server. 32. The method of claim 19 , further comprising: eliminating a communication through a centralized infrastructure when the sandboxed application and the sandbox reachable service communicate in a shared network common to the client device and the networked device when the communication session is established, the shared network being at least one of a local area network, a multicast network, an anycast network, and a multilan network; minimizing a latency in the communication session when the sandboxed application and the sandbox reachable service communicate in the shared network common to the client device and the networked device when the communication session is established; and improving privacy in the communication session when the sandboxed application and the sandbox reachable service communicate in the shared network common to the client device and the networked device when the communication session is established. | 0.5 |
9,002,866 | 14 | 26 | 14. A computer-implemented method, comprising: receiving, by one or more computers, a query comprising three or more terms; identifying, by the one or more computers and from among the terms of the query, an entity name and two or more context terms; obtaining, by the one or more computers, a plurality of candidate corrected spellings for the entity name; determining a respective count of co-occurrences of each context term with each candidate corrected spelling for the entity name, in a plurality of texts comprising: counting, as one co-occurrence, each distinct text from the plurality of texts in which the context term and the candidate corrected spelling both appear at least once; or counting, as one co-occurrence, each distinct window of text from the plurality of texts in which the context term and the candidate corrected spelling both appear at least once; determining a score for each candidate corrected spelling for the entity name based at least one the respective counts of co-occurrences of each context term with the respective candidate corrected spelling for the entity name, in the plurality of texts; selecting, by the one or more computers, one or more of the candidate corrected spellings for the entity name based at least on the scores; and using, by the one or more computers, the selected one or more candidate corrected spellings to generate a response to the query. | 14. A computer-implemented method, comprising: receiving, by one or more computers, a query comprising three or more terms; identifying, by the one or more computers and from among the terms of the query, an entity name and two or more context terms; obtaining, by the one or more computers, a plurality of candidate corrected spellings for the entity name; determining a respective count of co-occurrences of each context term with each candidate corrected spelling for the entity name, in a plurality of texts comprising: counting, as one co-occurrence, each distinct text from the plurality of texts in which the context term and the candidate corrected spelling both appear at least once; or counting, as one co-occurrence, each distinct window of text from the plurality of texts in which the context term and the candidate corrected spelling both appear at least once; determining a score for each candidate corrected spelling for the entity name based at least one the respective counts of co-occurrences of each context term with the respective candidate corrected spelling for the entity name, in the plurality of texts; selecting, by the one or more computers, one or more of the candidate corrected spellings for the entity name based at least on the scores; and using, by the one or more computers, the selected one or more candidate corrected spellings to generate a response to the query. 26. The method of claim 14 , wherein using the selected one or more candidate corrected spellings to generate a response to the query comprises: generating a respective spell-corrected query for each selected candidate corrected spelling; submitting the respective spell-corrected query for each of the selected candidate corrected spellings to a search engine; receiving search results for each respective spell-corrected query from the search engine; and presenting each of the selected candidate corrected spellings and the received search results for the respective spell-corrected query for the candidate corrected spelling. | 0.5 |
7,627,818 | 7 | 8 | 7. A system comprising: a processor; a data bus coupled to the processor; a memory coupled to the data bus; and a computer-usable medium embodying computer program code, the computer program code comprising instructions executable by the processor and configured for: receiving, at a receiving console that lacks software for displaying a HyperText Markup Language (HTML) coded message, an HTML coded message that includes a text message that has been encoded using a sender's character set; identifying a character map pseudonym of a current character map of the receiving console; identifying the sender's character set that was used to encode the text message; identifying true character map names of character maps that are available to the receiving console; using the character map pseudonym to perform a first fuzzy search of the true character map names of the character maps that are available to the receiving console, wherein the first fuzzy search identifies a console character map that is identified by the character map pseudonym; using the sender's character set to perform a second fuzzy search of the true character map names of the character maps that are available to the receiving console, wherein the second fuzzy search identifies a sender's character map that is associated with the sender's character set; and transencoding, if the sender's character map and the console character map are different, the text message from the sender's character map to the console character map. | 7. A system comprising: a processor; a data bus coupled to the processor; a memory coupled to the data bus; and a computer-usable medium embodying computer program code, the computer program code comprising instructions executable by the processor and configured for: receiving, at a receiving console that lacks software for displaying a HyperText Markup Language (HTML) coded message, an HTML coded message that includes a text message that has been encoded using a sender's character set; identifying a character map pseudonym of a current character map of the receiving console; identifying the sender's character set that was used to encode the text message; identifying true character map names of character maps that are available to the receiving console; using the character map pseudonym to perform a first fuzzy search of the true character map names of the character maps that are available to the receiving console, wherein the first fuzzy search identifies a console character map that is identified by the character map pseudonym; using the sender's character set to perform a second fuzzy search of the true character map names of the character maps that are available to the receiving console, wherein the second fuzzy search identifies a sender's character map that is associated with the sender's character set; and transencoding, if the sender's character map and the console character map are different, the text message from the sender's character map to the console character map. 8. The system of claim 7 , wherein the instructions that are configured for the first fuzzy search are further configured for: alphanumerically matching similar but unequal true character map names, which are supported by the receiving console, to the character map pseudonym. | 0.590504 |
9,218,589 | 3 | 8 | 3. A system for automating the issuance, management and conveyance of endorsements to authorities, the system comprising: an endorsement issuance module configured to issue an endorsement associated with an endorsee, wherein the issued endorsement prescribes to specified endorsement issuance, rule definitions provided by one or more authorities, the endorsement issuance module further comprising: an endorsee identification unit that retrieves at least one credential from said endorsee via an input device, wherein each credential provides for at least one endorsement from at least one authority and wherein each credential includes a digital seal that restricts access to the credential from at least one other authority different from the at least one authority; and an endorsement creation unit for adding at least one new endorsement to at least one of said credentials, said new endorsement added within a private field of a digital seal of a bar code; an endorsement conveyance module configured to receive the new endorsement from the endorsement issuance module, and to validate the new endorsement according to specified endorsement conveyance rules; and an endorsement management module configured to maintain specified rules according to an endorsement management module, wherein results of endorsement validation are presented to at least one of the following: an automated environment for providing access to endorsee, an automated environment for recording validation results, a display for providing validation results to a user. | 3. A system for automating the issuance, management and conveyance of endorsements to authorities, the system comprising: an endorsement issuance module configured to issue an endorsement associated with an endorsee, wherein the issued endorsement prescribes to specified endorsement issuance, rule definitions provided by one or more authorities, the endorsement issuance module further comprising: an endorsee identification unit that retrieves at least one credential from said endorsee via an input device, wherein each credential provides for at least one endorsement from at least one authority and wherein each credential includes a digital seal that restricts access to the credential from at least one other authority different from the at least one authority; and an endorsement creation unit for adding at least one new endorsement to at least one of said credentials, said new endorsement added within a private field of a digital seal of a bar code; an endorsement conveyance module configured to receive the new endorsement from the endorsement issuance module, and to validate the new endorsement according to specified endorsement conveyance rules; and an endorsement management module configured to maintain specified rules according to an endorsement management module, wherein results of endorsement validation are presented to at least one of the following: an automated environment for providing access to endorsee, an automated environment for recording validation results, a display for providing validation results to a user. 8. The system of claim 3 , further comprising an endorsement rules database capable of receiving rules from the authority. | 0.745833 |
7,634,398 | 1 | 2 | 1. A method of forming a reconstructed parse structure for a text segment, the method comprising: a processor identifying a reattach node in an initial parse structure, where the reattach node is a node that is to be moved; the processor selecting nodes and rules used to form nodes associated with the initial parse structure constructed for the text segment; the processor placing the selected nodes and rules and at least one additional rule that is not taken from the initial parse structure in a deconstruction queue as an ordered list of entries wherein each node and each rule in the deconstruction queue appears in a separate respective entry in the ordered list of entries and wherein a rule used to combine the reattach node with another node in the initial parse structure is not placed in the deconstruction queue and wherein at least one selected node placed in the deconstruction queue is not affected by moving the reattach node; the processor sequentially retrieving entries from the deconstruction queue based on the order of the entries in the deconstruction queue; for each node retrieved from the deconstruction queue, the processor placing the node in a working stack; and for each rule retrieved from the deconstruction queue, including the additional rule: the processor determining the number of nodes required by the rule; the processor removing the determined number of nodes from the top of the working stack; the processor executing the rule using the nodes removed from the working stack to form a resulting node; and the processor placing the resulting node at the top of the working stack. | 1. A method of forming a reconstructed parse structure for a text segment, the method comprising: a processor identifying a reattach node in an initial parse structure, where the reattach node is a node that is to be moved; the processor selecting nodes and rules used to form nodes associated with the initial parse structure constructed for the text segment; the processor placing the selected nodes and rules and at least one additional rule that is not taken from the initial parse structure in a deconstruction queue as an ordered list of entries wherein each node and each rule in the deconstruction queue appears in a separate respective entry in the ordered list of entries and wherein a rule used to combine the reattach node with another node in the initial parse structure is not placed in the deconstruction queue and wherein at least one selected node placed in the deconstruction queue is not affected by moving the reattach node; the processor sequentially retrieving entries from the deconstruction queue based on the order of the entries in the deconstruction queue; for each node retrieved from the deconstruction queue, the processor placing the node in a working stack; and for each rule retrieved from the deconstruction queue, including the additional rule: the processor determining the number of nodes required by the rule; the processor removing the determined number of nodes from the top of the working stack; the processor executing the rule using the nodes removed from the working stack to form a resulting node; and the processor placing the resulting node at the top of the working stack. 2. The method of claim 1 wherein executing the rules comprises forming a reconstructed parse structure that differs from the initial parse structure in that a node in the initial parse structure is moved to a different position in the reconstructed parse structure. | 0.5 |
9,922,352 | 1 | 4 | 1. A method, implemented by one or more processors in a computing system, for generating a multidimensional synopsis of a stream of textual data, the method comprising: accessing, by the one or more processors, a stream of textual data that includes a number of elements of textual data, each element of textual data comprising plain text content that is associated with an author and is directed to a particular subject; identifying, by the one or more processors, a first dimension and a second dimension for the stream of textual data, the first dimension including a number of concepts that each represent a subject attribute of the particular subject, the second dimension including a number of concepts that each represent an author attribute; processing, by the one or more processors, each of the number of elements of textual data to identify which of the concepts of the first and second dimension appear in the plain text content included in the element, and for each concept within the first dimension that appears in the plain text content included in the element, generating a quantitative value; and generating, by the one or more processors, the multidimensional synopsis of the stream of textual data by generating a score for each intersecting set of concepts from the corresponding quantitative values, each score representing a prevalence of the intersecting set of concepts within the stream of textual data. | 1. A method, implemented by one or more processors in a computing system, for generating a multidimensional synopsis of a stream of textual data, the method comprising: accessing, by the one or more processors, a stream of textual data that includes a number of elements of textual data, each element of textual data comprising plain text content that is associated with an author and is directed to a particular subject; identifying, by the one or more processors, a first dimension and a second dimension for the stream of textual data, the first dimension including a number of concepts that each represent a subject attribute of the particular subject, the second dimension including a number of concepts that each represent an author attribute; processing, by the one or more processors, each of the number of elements of textual data to identify which of the concepts of the first and second dimension appear in the plain text content included in the element, and for each concept within the first dimension that appears in the plain text content included in the element, generating a quantitative value; and generating, by the one or more processors, the multidimensional synopsis of the stream of textual data by generating a score for each intersecting set of concepts from the corresponding quantitative values, each score representing a prevalence of the intersecting set of concepts within the stream of textual data. 4. The method of claim 1 , wherein the score is generated by summing the quantitative values. | 0.937834 |
8,606,728 | 1 | 4 | 1. A computer-implemented method comprising: calculating one or more types of suggestion scores for each of a plurality of training examples, wherein each type of suggestion score is based at least in part on a plurality of computed predictions for each training example by generated by a plurality of different trained models, including weighting each type of suggestion score by an accuracy of the trained model that generated the prediction; calculating an overall suggestion score for each training example based at least in part on a combination of the one or more types of suggestion scores for each training example; ranking the training examples by the corresponding overall suggestion scores; and providing one or more highest-ranked training examples as a set of suggested training examples. | 1. A computer-implemented method comprising: calculating one or more types of suggestion scores for each of a plurality of training examples, wherein each type of suggestion score is based at least in part on a plurality of computed predictions for each training example by generated by a plurality of different trained models, including weighting each type of suggestion score by an accuracy of the trained model that generated the prediction; calculating an overall suggestion score for each training example based at least in part on a combination of the one or more types of suggestion scores for each training example; ranking the training examples by the corresponding overall suggestion scores; and providing one or more highest-ranked training examples as a set of suggested training examples. 4. The method of claim 1 , wherein one of the one or more types of suggestion scores is a difficulty score, wherein the difficulty score for a particular training example in the training examples is based on comparing a confidence associated with an incorrectly predicted category for the training example to a threshold. | 0.720383 |
9,009,658 | 1 | 4 | 1. A computer implemented model-driven method for generating platform specific code for a software component based software system, comprising: capturing customer requirements of the software component in a schema, wherein the software component includes a self contained software application which encapsulates and implements a single business process; modeling business-software architecture of the software component in a first level of the schema as business functions, business activities, forms, actions, and business rules, wherein each of the business functions comprises functions performed in the single business process of a software system, and wherein each of the business activities comprises activities performed in each of the business functions, and wherein each of the forms comprises semantics to capture and retrieve information for each of the business activities, and wherein each of the actions comprises tasks performed in each of the forms, and wherein each of the business rules comprises rules that govern each of the actions; modeling technical architecture of the software system from the modeled business-software architecture as components, system entry points, user interfaces, services, and methods in a second level of the schema, wherein each of the components corresponds to each of the business functions of the single business process, and wherein each of the system entry points corresponds to visual-interface elements of each of the business activities, and wherein each of the user interfaces with visual-interface elements corresponds to each of the forms, and wherein each of the services corresponds to each of the actions performed in each of the user interfaces, and wherein each of the methods corresponds to each of the business rules that are invoked in handling each of the services; defining events in the schema that connect the first level and the second level of the schema, Wherein the events comprise entry events and exit events, and wherein each of the entry events is a stimulus that triggers a business function, a business activity, or a form and each of the exit events is a response from the respective business function, business activity, or form to the stimulus; defining links in the schema that represent interactions between the user interfaces, wherein each of the links comprises cross connections between the visual-interface elements in the user interfaces and the events associated with at least one of the business functions, business activities, and forms; defining integration services in the schema for each of the events, wherein integration services define cross connections for data updates between the events associated with at least one of the business functions, business activities, and forms in the first level and services and methods in the second level; mapping each of the business functions, business activities, forms, actions, and business rules in the first level to a corresponding one of the components, system entry points, user interfaces, services, and methods in the second level using the events, links, and integration services in the schema; providing connector interfaces, interface specifications, and interface behavior specifications for the software component in the schema, wherein the connector interfaces define interfaces through which the software component interacts with a plurality of other software components of the software system, the interface specifications define structure of information exchanged with interacting software components, and the interface behavior specifications define logic flow within the software component when an interface is invoked; loading the schema of the software component into a code generation repository; generating a standalone version and an integrated version of the platform specific code of the software component from the code generation repository based on the modeled technical architecture, defined events, defined links, defined integration services, and mappings in the schema; performing unit testing of the standalone version of the software component, wherein stubs are provided to serve as connector interfaces to ensure independent deployment of the software component for the unit testing; and performing a separate integration testing of the integrated version of the software component along with software components interacting with the integrated version of the software component using the connector interfaces provided in the schema. | 1. A computer implemented model-driven method for generating platform specific code for a software component based software system, comprising: capturing customer requirements of the software component in a schema, wherein the software component includes a self contained software application which encapsulates and implements a single business process; modeling business-software architecture of the software component in a first level of the schema as business functions, business activities, forms, actions, and business rules, wherein each of the business functions comprises functions performed in the single business process of a software system, and wherein each of the business activities comprises activities performed in each of the business functions, and wherein each of the forms comprises semantics to capture and retrieve information for each of the business activities, and wherein each of the actions comprises tasks performed in each of the forms, and wherein each of the business rules comprises rules that govern each of the actions; modeling technical architecture of the software system from the modeled business-software architecture as components, system entry points, user interfaces, services, and methods in a second level of the schema, wherein each of the components corresponds to each of the business functions of the single business process, and wherein each of the system entry points corresponds to visual-interface elements of each of the business activities, and wherein each of the user interfaces with visual-interface elements corresponds to each of the forms, and wherein each of the services corresponds to each of the actions performed in each of the user interfaces, and wherein each of the methods corresponds to each of the business rules that are invoked in handling each of the services; defining events in the schema that connect the first level and the second level of the schema, Wherein the events comprise entry events and exit events, and wherein each of the entry events is a stimulus that triggers a business function, a business activity, or a form and each of the exit events is a response from the respective business function, business activity, or form to the stimulus; defining links in the schema that represent interactions between the user interfaces, wherein each of the links comprises cross connections between the visual-interface elements in the user interfaces and the events associated with at least one of the business functions, business activities, and forms; defining integration services in the schema for each of the events, wherein integration services define cross connections for data updates between the events associated with at least one of the business functions, business activities, and forms in the first level and services and methods in the second level; mapping each of the business functions, business activities, forms, actions, and business rules in the first level to a corresponding one of the components, system entry points, user interfaces, services, and methods in the second level using the events, links, and integration services in the schema; providing connector interfaces, interface specifications, and interface behavior specifications for the software component in the schema, wherein the connector interfaces define interfaces through which the software component interacts with a plurality of other software components of the software system, the interface specifications define structure of information exchanged with interacting software components, and the interface behavior specifications define logic flow within the software component when an interface is invoked; loading the schema of the software component into a code generation repository; generating a standalone version and an integrated version of the platform specific code of the software component from the code generation repository based on the modeled technical architecture, defined events, defined links, defined integration services, and mappings in the schema; performing unit testing of the standalone version of the software component, wherein stubs are provided to serve as connector interfaces to ensure independent deployment of the software component for the unit testing; and performing a separate integration testing of the integrated version of the software component along with software components interacting with the integrated version of the software component using the connector interfaces provided in the schema. 4. The method according to claim 1 , further comprising providing code generators with standard semantics for multiple technologies. | 0.629213 |
9,727,654 | 1 | 3 | 1. A method comprising: accessing a target member profile representing a member in an on-line social network system, the target member profile associated with a profile summary user interface (UI), the profile summary UI comprising a display area suitable for receiving user input; determining, from profiles representing further respective members in the on-line social network system, a plurality of similar member profiles, profiles from the plurality of similar member profiles being similar to the target member profile, the plurality of similar member profiles and the target profile being a sub-network of similar profiles in the on-line social network system; from the sub-network of similar profiles, extracting a plurality of phrases; calculating, for phrases from the plurality of phrases, respective discriminative strength values, using at least one processor, a discriminative strength value for a phrase from the plurality of phrases expresses probability of the phrase being indicative of a member profile that contains the phrase belonging to the sub-network of similar profiles, wherein the calculating of a discriminative strength value for a particular phrase from the plurality of phrases comprises utilizing the number of profiles in the sub-network of similar profiles that include that particular phrase and the number of profiles outside the sub-network of similar profiles that include that particular phrase; identifying suggested keywords for presentation in a further display area of the summary UI of the target profile, based on respective discriminative strength values of the phrases from the plurality of phrases; and causing presentation of the suggested keywords in the further display area of the profile summary UI subsequent to the accessing of the target member profile. | 1. A method comprising: accessing a target member profile representing a member in an on-line social network system, the target member profile associated with a profile summary user interface (UI), the profile summary UI comprising a display area suitable for receiving user input; determining, from profiles representing further respective members in the on-line social network system, a plurality of similar member profiles, profiles from the plurality of similar member profiles being similar to the target member profile, the plurality of similar member profiles and the target profile being a sub-network of similar profiles in the on-line social network system; from the sub-network of similar profiles, extracting a plurality of phrases; calculating, for phrases from the plurality of phrases, respective discriminative strength values, using at least one processor, a discriminative strength value for a phrase from the plurality of phrases expresses probability of the phrase being indicative of a member profile that contains the phrase belonging to the sub-network of similar profiles, wherein the calculating of a discriminative strength value for a particular phrase from the plurality of phrases comprises utilizing the number of profiles in the sub-network of similar profiles that include that particular phrase and the number of profiles outside the sub-network of similar profiles that include that particular phrase; identifying suggested keywords for presentation in a further display area of the summary UI of the target profile, based on respective discriminative strength values of the phrases from the plurality of phrases; and causing presentation of the suggested keywords in the further display area of the profile summary UI subsequent to the accessing of the target member profile. 3. The method of claim 1 , comprising storing one or more phrases from the plurality of phrases and their respective discriminative strength values for future access. | 0.720539 |
7,734,620 | 6 | 10 | 6. A method for optimizing a database query that includes a Select statement with a Fetch First n Rows Only clause, the method comprising the steps of: analyzing the query to determine the query is optimizable by determining that the query contains a Group By clause and that an index exists for a leftmost column but not all the columns of the Group By clause; generating for the query an optimized access plan that eliminates records defined by a Where clause prior to ordering records by creating an access plan that eliminates records prior to grouping by fetching n rows from the index over the leftmost column and remaining rows until a unique value of the index is encountered; and using the optimized access plan to retrieve data from the database table. | 6. A method for optimizing a database query that includes a Select statement with a Fetch First n Rows Only clause, the method comprising the steps of: analyzing the query to determine the query is optimizable by determining that the query contains a Group By clause and that an index exists for a leftmost column but not all the columns of the Group By clause; generating for the query an optimized access plan that eliminates records defined by a Where clause prior to ordering records by creating an access plan that eliminates records prior to grouping by fetching n rows from the index over the leftmost column and remaining rows until a unique value of the index is encountered; and using the optimized access plan to retrieve data from the database table. 10. The method of claim 6 further comprising the steps of: determining the query contains an Order By clause; and wherein the access plan eliminates records prior to a sort by fetching n rows from the index over the leftmost column and remaining rows until a unique value of the index is encountered. | 0.651163 |
9,870,203 | 13 | 20 | 13. A non-transitory computer-readable storage medium having stored thereon computer executable program code which, when executed on a computer system, causes the computer system to perform steps comprising: generate a Service Adaptation Definition Language (SADL) definition for each of a plurality business entities associated with different model layer frameworks, the SADL definition being based on an intermediate representation of each of the plurality of business entities; and publish the SADL definition as a service of a SADL engine configured to delegate at least one of query, create, read, update and delete operations associated with the business entities, wherein the SADL engine interacts with a user interface defined using at least two of the plurality of business entities, the new user interface working with the different model layer frameworks of the at least two of the plurality of business entities. | 13. A non-transitory computer-readable storage medium having stored thereon computer executable program code which, when executed on a computer system, causes the computer system to perform steps comprising: generate a Service Adaptation Definition Language (SADL) definition for each of a plurality business entities associated with different model layer frameworks, the SADL definition being based on an intermediate representation of each of the plurality of business entities; and publish the SADL definition as a service of a SADL engine configured to delegate at least one of query, create, read, update and delete operations associated with the business entities, wherein the SADL engine interacts with a user interface defined using at least two of the plurality of business entities, the new user interface working with the different model layer frameworks of the at least two of the plurality of business entities. 20. The non-transitory computer-readable storage medium of claim 13 , wherein the SADL definition is programming language independent of a model layer framework. | 0.728041 |
7,765,271 | 28 | 32 | 28. A method as claimed in claim 21 , further comprising the steps of: k) user inputting predetermined index data into an index field defined by the HTML document separately from a document display portion in which the document data from the scanner is displayed by the web browser of the user interface of the client device; l) generating a send data signal using the control element operated by a user with the input device and defined by the HTML document displayed by the web browser of the user interface of the client device; m) transmitting the document data and index data from the client device to the server over an internetwork in response to the send data signal generated in said step (l); n) receiving the document data and index data at the server; and a) storing the document data in association with the index data in a database of a data storage unit separate from the server. | 28. A method as claimed in claim 21 , further comprising the steps of: k) user inputting predetermined index data into an index field defined by the HTML document separately from a document display portion in which the document data from the scanner is displayed by the web browser of the user interface of the client device; l) generating a send data signal using the control element operated by a user with the input device and defined by the HTML document displayed by the web browser of the user interface of the client device; m) transmitting the document data and index data from the client device to the server over an internetwork in response to the send data signal generated in said step (l); n) receiving the document data and index data at the server; and a) storing the document data in association with the index data in a database of a data storage unit separate from the server. 32. A method as claimed in claim 28 , wherein the start scan signal is input by a user with the input device via a first control element displayed within the web browser of the user interface for a first scan mode in the performance of said step (a) and the send data signal is input by a user with the input device via a second control element displayed within the web browser of the user interface in the performance of said step (m). | 0.5 |
8,185,482 | 11 | 12 | 11. The process of claim 10 , further comprising representing the second semantic term by the equation:
∥{right arrow over (θ)} (i) ∥1 for the i th post. | 11. The process of claim 10 , further comprising representing the second semantic term by the equation:
∥{right arrow over (θ)} (i) ∥1 for the i th post. 12. The process of claim 11 , further comprising representing the first structure term by the equation: θ → ( i ) - ∑ k = 1 i - 1 b → k ( i ) · θ → ( k ) F 2 , where {right arrow over (b)} k (i) is the structural coefficient between the i th post and the k th post. | 0.5 |
8,805,684 | 8 | 9 | 8. The article of manufacture of claim 7 , wherein the operations further comprise: receiving new feature-space speaker adaptation parameters; and replacing the updated feature-space speaker adaptation parameters with the new feature-space speaker adaptation parameters. | 8. The article of manufacture of claim 7 , wherein the operations further comprise: receiving new feature-space speaker adaptation parameters; and replacing the updated feature-space speaker adaptation parameters with the new feature-space speaker adaptation parameters. 9. The article of manufacture of claim 8 , wherein the feature-space speaker adaptation parameters include a first diagonal matrix, wherein updating the feature vectors based on the feature-space speaker adaptation parameters comprises applying the first diagonal matrix to the feature vectors, and wherein the updated feature-space speaker adaptation parameters include a second diagonal matrix, the operations further comprising: applying the second diagonal matrix to a first subsequently-received feature vector. | 0.5 |
10,120,933 | 27 | 38 | 27. A non-transitory computer-readable medium including computer program instructions, which when executed by a computer, cause the computer to perform the method according to claim 1 . | 27. A non-transitory computer-readable medium including computer program instructions, which when executed by a computer, cause the computer to perform the method according to claim 1 . 38. The non-transitory computer readable medium of claim 27 , wherein the determining further comprises: repeating the encoding and the computing, for the second data element being a successor of the first data element. | 0.772349 |
8,543,715 | 10 | 20 | 10. A system for limiting user redirects in a web browser, comprising: one or more processors; a parser, implemented on the one or more processors, to parse a frame element in a plurality of elements to identify one or more attributes of the frame element, the plurality of elements encoded in a web page retrieved in response to a user request, and to determine a redirect limit for the frame element from among the one or more identified attributes, wherein the redirect limit specifies a maximum number of user redirects for a third-party resource corresponding to the frame element; and a network engine, implemented on the one or more processors, to respond to a redirect request associated with the third-party resource based on the redirect limit, wherein the redirect request is ignored when the redirect limit is exceeded. | 10. A system for limiting user redirects in a web browser, comprising: one or more processors; a parser, implemented on the one or more processors, to parse a frame element in a plurality of elements to identify one or more attributes of the frame element, the plurality of elements encoded in a web page retrieved in response to a user request, and to determine a redirect limit for the frame element from among the one or more identified attributes, wherein the redirect limit specifies a maximum number of user redirects for a third-party resource corresponding to the frame element; and a network engine, implemented on the one or more processors, to respond to a redirect request associated with the third-party resource based on the redirect limit, wherein the redirect request is ignored when the redirect limit is exceeded. 20. The system of claim 10 , wherein the parser and the network engine are implemented as components of the web browser. | 0.5 |
8,706,724 | 1 | 14 | 1. A computer-implemented feature extraction device comprising: a search unit which searches a document tree having a plurality of elements according to a rule given in advance, and sequentially detects an element of said plurality of elements as a search element; a distance calculation unit which calculates an inter-element distance between an extraction target element specified in advance among a plurality of elements of said document tree and said search element; an exclusive element confirmation unit which generates exclusivity information which indicates whether said search element is an exclusive element to said extraction target element, with reference to an exclusive element name specified in advance; an element feature vector calculation unit which calculates a weight for a phrase included in the element corresponding to said element based on the inter-element distance and said exclusivity information, and calculates an element feature vector, having a plurality of dimensions and each dimension uniquely corresponding to a predetermined phrase, based on the calculated weight corresponding to each search element; and a partial document feature vector calculation unit which calculates a partial document feature vector of a partial document related to said extraction target element based on said element feature vector. | 1. A computer-implemented feature extraction device comprising: a search unit which searches a document tree having a plurality of elements according to a rule given in advance, and sequentially detects an element of said plurality of elements as a search element; a distance calculation unit which calculates an inter-element distance between an extraction target element specified in advance among a plurality of elements of said document tree and said search element; an exclusive element confirmation unit which generates exclusivity information which indicates whether said search element is an exclusive element to said extraction target element, with reference to an exclusive element name specified in advance; an element feature vector calculation unit which calculates a weight for a phrase included in the element corresponding to said element based on the inter-element distance and said exclusivity information, and calculates an element feature vector, having a plurality of dimensions and each dimension uniquely corresponding to a predetermined phrase, based on the calculated weight corresponding to each search element; and a partial document feature vector calculation unit which calculates a partial document feature vector of a partial document related to said extraction target element based on said element feature vector. 14. The feature extraction device according to claim 1 , further comprising: a feature vector output unit which outputs the partial document feature vector. | 0.886628 |
8,566,351 | 1 | 6 | 1. A Boolean search formula generation apparatus comprising: a processor; a memory coupled with said processor; a Boolean search formula generation unit that generates one or more Boolean search formulas for searching a base set including one or more documents from a document set as a search target and stores the Boolean search formulas in the memory, where the base set is a first search result generated from a first search formula and each of the Boolean search formulas consists of search products including one or more search terms; and a search result acquisition unit that uses each of the Boolean search formulas to acquire second search results of searching the search target and that outputs the second search results of searching the search target to the Boolean search formula generation unit, wherein the processor controls the Boolean search formula generation unit to: acquire the second search results, which are obtained when the search target is searched using each of the Boolean search formulas, from the search result acquisition unit to calculate, for each of the Boolean search formulas, a recall indicating a proportion, to the base set, of the documents included in the base set among the second search results and a precision indicating a proportion, to the second search results, of the documents included in the base set among the second search results, evaluate each of the Boolean search formulas by an evaluation formula established using the respective recall and the respective precision, and combine the Boolean search formulas with maximum evaluation values based on the evaluation formula to generate a combined Boolean search formula expressed by a standard sum of products of the Boolean search formulas with maximum evaluation values, where the combined Boolean search formula approximates the base set generated by the first search formula, wherein: the search result acquisition unit acquires a number of hits of each search term in the search products from the number of hits of each search term recorded in a search index of the search target when the Boolean search formula generation unit calculates the precision of the search products, and the Boolean search formula generation unit uses the number of hits to approximate the precision. | 1. A Boolean search formula generation apparatus comprising: a processor; a memory coupled with said processor; a Boolean search formula generation unit that generates one or more Boolean search formulas for searching a base set including one or more documents from a document set as a search target and stores the Boolean search formulas in the memory, where the base set is a first search result generated from a first search formula and each of the Boolean search formulas consists of search products including one or more search terms; and a search result acquisition unit that uses each of the Boolean search formulas to acquire second search results of searching the search target and that outputs the second search results of searching the search target to the Boolean search formula generation unit, wherein the processor controls the Boolean search formula generation unit to: acquire the second search results, which are obtained when the search target is searched using each of the Boolean search formulas, from the search result acquisition unit to calculate, for each of the Boolean search formulas, a recall indicating a proportion, to the base set, of the documents included in the base set among the second search results and a precision indicating a proportion, to the second search results, of the documents included in the base set among the second search results, evaluate each of the Boolean search formulas by an evaluation formula established using the respective recall and the respective precision, and combine the Boolean search formulas with maximum evaluation values based on the evaluation formula to generate a combined Boolean search formula expressed by a standard sum of products of the Boolean search formulas with maximum evaluation values, where the combined Boolean search formula approximates the base set generated by the first search formula, wherein: the search result acquisition unit acquires a number of hits of each search term in the search products from the number of hits of each search term recorded in a search index of the search target when the Boolean search formula generation unit calculates the precision of the search products, and the Boolean search formula generation unit uses the number of hits to approximate the precision. 6. The Boolean search formula generation apparatus according to claim 1 , wherein the search result acquisition unit acquires a weighting factor of each document in the search results searched using the search products as a search condition, and the Boolean search formula generation unit uses the weighting factor to calculate at least one of the recall and the precision. | 0.53607 |
10,121,468 | 1 | 2 | 1. A method comprising: incorporating a granularity description of a present location of a device into a local language model, the granularity description using topologically concentric locations to determine probabilities; combining the local language model with a global language model according to the probabilities, to yield a combined language model; and outputting, using the combined language model and via a spoken dialog system, audible spoken language results for a spoken query based on the present location and a term in the spoken query. | 1. A method comprising: incorporating a granularity description of a present location of a device into a local language model, the granularity description using topologically concentric locations to determine probabilities; combining the local language model with a global language model according to the probabilities, to yield a combined language model; and outputting, using the combined language model and via a spoken dialog system, audible spoken language results for a spoken query based on the present location and a term in the spoken query. 2. The method of claim 1 , wherein the granularity description uses business density to determine weights. | 0.820339 |
7,949,524 | 1 | 6 | 1. A speech recognition apparatus comprising: a speech input unit configured to receive an input of a speech utterance; a keyword recognition unit configured to recognize a plurality of keywords included in the speech utterance as a recognition result using a processor; a presentation unit configured to present the recognition result; a correction input unit configured to receive a correction input for the recognition result; a correction unit configured to correct the recognition result based on the correction input to create a correction result; a dictionary generation unit configured to generate a standby-word dictionary as a union of recognition target vocabulary elements including the plurality of keywords corrected by the correction unit for recognizing the speech utterance; and a speech utterance recognition unit configured to recognize the speech utterance using the standby-word dictionary. | 1. A speech recognition apparatus comprising: a speech input unit configured to receive an input of a speech utterance; a keyword recognition unit configured to recognize a plurality of keywords included in the speech utterance as a recognition result using a processor; a presentation unit configured to present the recognition result; a correction input unit configured to receive a correction input for the recognition result; a correction unit configured to correct the recognition result based on the correction input to create a correction result; a dictionary generation unit configured to generate a standby-word dictionary as a union of recognition target vocabulary elements including the plurality of keywords corrected by the correction unit for recognizing the speech utterance; and a speech utterance recognition unit configured to recognize the speech utterance using the standby-word dictionary. 6. The speech recognition apparatus according to claim 1 wherein the presentation unit is configured to select at least two keywords based on a similarity of acoustic features from among the recognition result and to present the selected keywords. | 0.654062 |
9,081,825 | 1 | 6 | 1. A computer-implemented method for querying a reputation system, comprising: obtaining a query specifying one or more dimensions and one or more quantiles, wherein each of the specified one or more dimensions is associated with one of the specified one or more quantiles, and wherein the dimensions comprise skills; obtaining a set of items in the reputation system with reputations scores in the one or more dimensions, wherein the items comprise users; generating a ranking of the set of items based on a closeness of a subset of the reputation scores for each of the items to the one or more quantiles, wherein the closeness of the subset of the reputation scores to the one or more quantiles is based on a rectilinear distance between the subset of the reputation scores and the one or more quantiles; and providing the ranking of the set of items in a response to the query. | 1. A computer-implemented method for querying a reputation system, comprising: obtaining a query specifying one or more dimensions and one or more quantiles, wherein each of the specified one or more dimensions is associated with one of the specified one or more quantiles, and wherein the dimensions comprise skills; obtaining a set of items in the reputation system with reputations scores in the one or more dimensions, wherein the items comprise users; generating a ranking of the set of items based on a closeness of a subset of the reputation scores for each of the items to the one or more quantiles, wherein the closeness of the subset of the reputation scores to the one or more quantiles is based on a rectilinear distance between the subset of the reputation scores and the one or more quantiles; and providing the ranking of the set of items in a response to the query. 6. The computer-implemented method of claim 1 , wherein the reputation scores comprise an explicit reputation score and an inferred reputation score. | 0.788952 |
8,874,495 | 15 | 17 | 15. A computer-readable medium storing computer executable instructions that when executed by a computer cause the computer to perform a method, the method comprising: accessing a set of triples and inference rules associated with a semantic model, where a triple includes a subject component, an object component, and a predicate component; creating a source table to store the set of triples, where the source table is partitioned on triple predicate; storing the set of triples in the source table; and firing the inference rules in parallel on the triples in the source table to generate inferred triples associated with the semantic model. | 15. A computer-readable medium storing computer executable instructions that when executed by a computer cause the computer to perform a method, the method comprising: accessing a set of triples and inference rules associated with a semantic model, where a triple includes a subject component, an object component, and a predicate component; creating a source table to store the set of triples, where the source table is partitioned on triple predicate; storing the set of triples in the source table; and firing the inference rules in parallel on the triples in the source table to generate inferred triples associated with the semantic model. 17. The computer-readable medium of claim 15 , the instructions comprising performing a union of selection operations on all triples associated with one or more semantic models to create the source table. | 0.516588 |
9,405,848 | 2 | 19 | 2. The method of claim 1 wherein determining the semantic information about the indicated content item includes processing text of the Web page to identify the one or more entities referenced by the indicated content item. | 2. The method of claim 1 wherein determining the semantic information about the indicated content item includes processing text of the Web page to identify the one or more entities referenced by the indicated content item. 19. The method of claim 2 further comprising: presenting on the mobile device an activity recommender user interface that includes multiple user interface controls that are each configured to initiate one of the determined plurality of activities. | 0.5 |
9,880,987 | 11 | 12 | 11. The computer system of claim 10 , wherein the parameterization module is configured to modify a second value associated with the first parameter to equal the first value associated with the first node. | 11. The computer system of claim 10 , wherein the parameterization module is configured to modify a second value associated with the first parameter to equal the first value associated with the first node. 12. The computer system of claim 11 , wherein the parameterization module is configured to evaluate the second document comprises by modifying a third value associated with the second parameter included in the second document based on the second value associated with the first parameter. | 0.5 |
9,003,529 | 11 | 13 | 11. An apparatus comprising processing circuitry configured to execute instructions for: receiving binary code; breaking the binary code into code portions that correspond to respective functional components by converting the code portions into functional representation code and breaking the functional representation code into individual functional units; generating a compressed representation of the code portions; and storing the compressed representation of each code portion for comparison to at least one other compressed representation of a code portion to determine a similarity measure between at least some of the code portions, wherein generating the compressed representation comprises assigning a respective token to each corresponding unit portion of each respective one of the individual functional units, and mapping each token to a character to define an ordered string of characters that form the compressed representation. | 11. An apparatus comprising processing circuitry configured to execute instructions for: receiving binary code; breaking the binary code into code portions that correspond to respective functional components by converting the code portions into functional representation code and breaking the functional representation code into individual functional units; generating a compressed representation of the code portions; and storing the compressed representation of each code portion for comparison to at least one other compressed representation of a code portion to determine a similarity measure between at least some of the code portions, wherein generating the compressed representation comprises assigning a respective token to each corresponding unit portion of each respective one of the individual functional units, and mapping each token to a character to define an ordered string of characters that form the compressed representation. 13. The apparatus of claim 11 , wherein the similarity measure comprises a similarity score determined based on sequence alignment. | 0.5 |
10,157,426 | 27 | 29 | 27. The method of claim 26 , the prioritization data comprising: ranking data, wherein each question or topic is assigned a ranking or score; and categorization data, wherein each question or topic is assigned a category from a plurality of categories. | 27. The method of claim 26 , the prioritization data comprising: ranking data, wherein each question or topic is assigned a ranking or score; and categorization data, wherein each question or topic is assigned a category from a plurality of categories. 29. The method of claim 27 , the first paginated screen being structured based at least in part upon categorization data taking priority over ranking data. | 0.79765 |
8,301,995 | 26 | 32 | 26. A method of utilizing a digital acquisition device having a built-in microphone, comprising: recording a first memorandum in the acquisition device by speech through the microphone, acquiring a first digital content item and a plurality of subsequently acquired digital content items in succession in the acquisition device, associating without user intervention the recorded first memorandum with the first acquired digital content items, thereafter automatically associating without user intervention the recorded first memorandum with one or more of the subsequently acquired digital content items, thereafter recording a second memorandum in the acquisition device by speech through the microphone, thereafter automatically associating the second memorandum with one or more of the subsequently acquired digital content items acquired subsequent to recording the second memorandum, storing the data of the first digital content item and the plurality of subsequently acquired digital content items along with the associated first and second memoranda and recording linking references of the associated memoranda into headers of the digital content items; when the acquisition device is turned on, determining whether the acquisition device had been turned off for more than a predetermined time period before the acquisition device being turned on; and if the acquisition device had been turned off for more than the predetermined time period before the acquisition device being turned on, automatically generating an alert of whether to associate a previous memorandum with a next digital content item to be acquired, wherein the previous memorandum is associated with a last digital content item acquired in the acquisition device before the acquisition device was turned off. | 26. A method of utilizing a digital acquisition device having a built-in microphone, comprising: recording a first memorandum in the acquisition device by speech through the microphone, acquiring a first digital content item and a plurality of subsequently acquired digital content items in succession in the acquisition device, associating without user intervention the recorded first memorandum with the first acquired digital content items, thereafter automatically associating without user intervention the recorded first memorandum with one or more of the subsequently acquired digital content items, thereafter recording a second memorandum in the acquisition device by speech through the microphone, thereafter automatically associating the second memorandum with one or more of the subsequently acquired digital content items acquired subsequent to recording the second memorandum, storing the data of the first digital content item and the plurality of subsequently acquired digital content items along with the associated first and second memoranda and recording linking references of the associated memoranda into headers of the digital content items; when the acquisition device is turned on, determining whether the acquisition device had been turned off for more than a predetermined time period before the acquisition device being turned on; and if the acquisition device had been turned off for more than the predetermined time period before the acquisition device being turned on, automatically generating an alert of whether to associate a previous memorandum with a next digital content item to be acquired, wherein the previous memorandum is associated with a last digital content item acquired in the acquisition device before the acquisition device was turned off. 32. The method of claim 26 , wherein at least one of the first and second memoranda relates to at least one person who is expected to participate in at least one of the digital content item to be acquired after the memorandum is recorded. | 0.777985 |
6,038,531 | 9 | 10 | 9. A similar word discrimination method for discriminating words that may be misrecognized because of their similarity, comprising the steps of: receiving voice data of input words; creating a learning dynamic recurrent neural networks (DRNN) sub-voice model, that uses a DRNN voice model, to obtain a specified DRNN output for the characteristic components of respective similar words showing a level of correctness in response to the voice data of input words; processing the DRNN output to establish a specified period in which the characteristic components of the input words are included in the DRNN output, when the DRNN output shows a level of correctness of a predetermined amount or greater; examining the characteristics of the voice data of said input words during the specified period; and discriminating between the input words and words that are similar to the input words on the basis of the examination. | 9. A similar word discrimination method for discriminating words that may be misrecognized because of their similarity, comprising the steps of: receiving voice data of input words; creating a learning dynamic recurrent neural networks (DRNN) sub-voice model, that uses a DRNN voice model, to obtain a specified DRNN output for the characteristic components of respective similar words showing a level of correctness in response to the voice data of input words; processing the DRNN output to establish a specified period in which the characteristic components of the input words are included in the DRNN output, when the DRNN output shows a level of correctness of a predetermined amount or greater; examining the characteristics of the voice data of said input words during the specified period; and discriminating between the input words and words that are similar to the input words on the basis of the examination. 10. The similar word discrimination method of claim 9, wherein: the discrimination of the input words and the words that are similar to the input words is accomplished based on the value of the DRNN output which shows the level of correctness above a specified level in accordance with the DRNN sub-voice model. | 0.503195 |
6,072,494 | 26 | 27 | 26. A system as recited in claim 20 further comprising a status updater for updating a status report containing data on key points reached in a dimension after obtaining a next data frame thereby determining whether the subject gesture has reached a next key point. | 26. A system as recited in claim 20 further comprising a status updater for updating a status report containing data on key points reached in a dimension after obtaining a next data frame thereby determining whether the subject gesture has reached a next key point. 27. A system as recited in claim 26 further comprising a status checker for checking the status report to determine if the subject gesture is a partial completion of a recognizable gesture by comparing a previous data frame to the positional data for a recognizable gesture and determining how many key points have been reached. | 0.5 |
9,910,864 | 7 | 11 | 7. A device, comprising: one or more memories; and circuitry coupled to the one or more memories, which, in operation, extracts grayscale descriptors the query image; outputs compressed grayscale descriptors based on the extracted grayscale descriptors; and distinguishes at least some search results of a search, performed using the compressed grayscale descriptors, of a data base by: extracting color descriptors from the query image, and at least one of: outputting compressed color descriptors based on the extracted color descriptors and receiving distinguished search results, the distinguished search results being based at least on the compressed color descriptors; and receiving the search results to be distinguished and distinguishing the received search results based on the extracted color descriptors, wherein when the search results based on the compressed grayscale descriptors of the query image include plural results, the search results based on the compressed grayscale descriptors of the query images are distinguished based on the extracted color descriptors. | 7. A device, comprising: one or more memories; and circuitry coupled to the one or more memories, which, in operation, extracts grayscale descriptors the query image; outputs compressed grayscale descriptors based on the extracted grayscale descriptors; and distinguishes at least some search results of a search, performed using the compressed grayscale descriptors, of a data base by: extracting color descriptors from the query image, and at least one of: outputting compressed color descriptors based on the extracted color descriptors and receiving distinguished search results, the distinguished search results being based at least on the compressed color descriptors; and receiving the search results to be distinguished and distinguishing the received search results based on the extracted color descriptors, wherein when the search results based on the compressed grayscale descriptors of the query image include plural results, the search results based on the compressed grayscale descriptors of the query images are distinguished based on the extracted color descriptors. 11. The device of claim 7 wherein when search results of a search of the data base based on compressed grayscale descriptors of the query image are not to be distinguished, the circuitry, in operation, does not extract color descriptors of the query image. | 0.715556 |
9,762,387 | 7 | 13 | 7. An apparatus, comprising: at least one processor; and at least one non-transitory computer-readable medium including computer program code which when executed by the at least one processor causes the apparatus to at least: generate at least one query identifier based on a first set of keywords, wherein each query identifier comprises a first hash of an identified keyword from the first set of keywords; transmit, to at least one other apparatus, a query comprising the at least one query identifier, wherein the query is transmitted via an ad hoc network; receive, from the other apparatus, a response comprising at least one match identifier and an encrypted message, wherein each match identifier comprises a second hash of the identified keyword that the other apparatus is able to identify based on the at least one query identifier; determine one or more keywords from the first set of keywords that corresponds to the at least one match identifier; generate an encryption key based on the one or more keywords identified by the at least one match identifier; and decrypt the encrypted message using the encryption key. | 7. An apparatus, comprising: at least one processor; and at least one non-transitory computer-readable medium including computer program code which when executed by the at least one processor causes the apparatus to at least: generate at least one query identifier based on a first set of keywords, wherein each query identifier comprises a first hash of an identified keyword from the first set of keywords; transmit, to at least one other apparatus, a query comprising the at least one query identifier, wherein the query is transmitted via an ad hoc network; receive, from the other apparatus, a response comprising at least one match identifier and an encrypted message, wherein each match identifier comprises a second hash of the identified keyword that the other apparatus is able to identify based on the at least one query identifier; determine one or more keywords from the first set of keywords that corresponds to the at least one match identifier; generate an encryption key based on the one or more keywords identified by the at least one match identifier; and decrypt the encrypted message using the encryption key. 13. The apparatus of claim 7 , wherein the generating of the encryption key further causes the apparatus to at least: combine the one or more keywords to create a key combination; hash the key combination to create a key hash; and divide the key hash into the encryption key and one or more channel identifiers. | 0.726232 |
7,945,929 | 11 | 12 | 11. A system for locating programs of interest to a user, the system comprising: a receiver that receives a plurality of program listings, wherein at least one of the program listings is associated with two or more simple categories; and a processor that generates at least one combination category by: identifying the two or more simple categories associated with the at least one program listing; and combining at least a subset of the identified simple categories associated with the at least one program listing into the at least one combination category, wherein the combination category comprises more than one of the identified simple categories. | 11. A system for locating programs of interest to a user, the system comprising: a receiver that receives a plurality of program listings, wherein at least one of the program listings is associated with two or more simple categories; and a processor that generates at least one combination category by: identifying the two or more simple categories associated with the at least one program listing; and combining at least a subset of the identified simple categories associated with the at least one program listing into the at least one combination category, wherein the combination category comprises more than one of the identified simple categories. 12. The system of claim 11 , wherein the processor is configured to combine at least a subset of the identified simple categories associated with the at least one program listing into the at least one combination category by: combining the identified simple categories into groups of two or more of the identified simple categories; and determining, for each of the groups of simple categories, whether the respective group is contained within a list of supported categories; wherein the at least one combination category comprises one of the groups of simple categories contained within the list of supported categories. | 0.5 |
10,074,102 | 16 | 17 | 16. The non-transitory computer readable storage medium as recited in claim 15 , further comprising instructions that, when executed by the at least one processor, cause the computer system to include the calculated average in the engagement model associated with the users of the social media system having the plurality of characteristics of the target audience. | 16. The non-transitory computer readable storage medium as recited in claim 15 , further comprising instructions that, when executed by the at least one processor, cause the computer system to include the calculated average in the engagement model associated with the users of the social media system having the plurality of characteristics of the target audience. 17. The non-transitory computer readable storage medium as recited in claim 16 , further comprising instructions that, when executed by the at least one processor, cause the computer system to store, in the engagement model associated with the user of the social media system having the plurality of characteristics of the target audience, the determined engagement score for the combination of the keyword and each of the one or more features in association with the calculated average. | 0.5 |
8,352,491 | 1 | 3 | 1. A computer program product comprising a computer readable storage device having a computer readable program code embodied therein, said computer readable program code containing instructions that, upon being executed by a processor of a computer system, perform a method of searching a web service registry system by use of a search module, said method comprising: a search controller of the search module, executed by the processor, receiving a service name through the web service registry system interface, through which the web service registry system communicates with components external to the web service registry system, wherein the web service registry system comprises the search module, the web service registry system interface, and a service registry program product, wherein the search module comprises the search controller, a name parser, a dictionary, and a name composer, wherein the search controller is configured to communicate with the service registry program product via a first internal interface comprising an application programming interface (API) inherent to the service registry program product, wherein the search controller is configured to communicate with the name parser, the dictionary, and the name composer via a second internal interface, a third internal interface, and a fourth internal interface, respectively, wherein the second internal interface, the third internal interface, and the fourth internal interface are uniform within the search module, such that the search controller orchestrates operations of the service registry program product and the name parser, the dictionary, and the name composer of the search module by use of the first internal interface, the second internal interface, the third internal interface, and the fourth internal interface, and wherein the service registry program product comprises at least one service description searchable by a respectively associated service name; performing, by said processor, a first search of the service registry program product with the received service name and subsequently determining that the received service name does not have a service description associated with the received service name in the service registry program product; coordinating, by said processor, a second search of the service registry program product with a candidate service name by use of the search module, wherein the candidate service name is semantically and syntactically interchangeable with the received service name such that the candidate service name identifies the service description associated with the received service name within the service registry program product; and discovering, by said processor, the service description is associated with the candidate service name within the service registry program product and subsequently outputting the discovered service description through the web service registry system interfaces, said coordinating comprising: sending the received service name to the name parser of the search module via the second internal interface and subsequently receiving a component word list from the name parser via the second internal interface, wherein the component word list comprises all words constituting the received service name; sending the component word list to the dictionary of the search module via the third internal interface and subsequently receiving a respective synonym list for each word in the component word list from the dictionary via the third internal interface, wherein the respective synonym list comprises at least one synonym of said each word in the component word list; sending the respective synonym list to the name composer of the search module via the fourth internal interface and subsequently receiving the candidate service name from the name composer via the fourth internal interface; and sending a second search request for the service description associated with the candidate service name to the service registry program product via the first internal interface and subsequently receiving the service description in response to the second search request via the first internal interface. | 1. A computer program product comprising a computer readable storage device having a computer readable program code embodied therein, said computer readable program code containing instructions that, upon being executed by a processor of a computer system, perform a method of searching a web service registry system by use of a search module, said method comprising: a search controller of the search module, executed by the processor, receiving a service name through the web service registry system interface, through which the web service registry system communicates with components external to the web service registry system, wherein the web service registry system comprises the search module, the web service registry system interface, and a service registry program product, wherein the search module comprises the search controller, a name parser, a dictionary, and a name composer, wherein the search controller is configured to communicate with the service registry program product via a first internal interface comprising an application programming interface (API) inherent to the service registry program product, wherein the search controller is configured to communicate with the name parser, the dictionary, and the name composer via a second internal interface, a third internal interface, and a fourth internal interface, respectively, wherein the second internal interface, the third internal interface, and the fourth internal interface are uniform within the search module, such that the search controller orchestrates operations of the service registry program product and the name parser, the dictionary, and the name composer of the search module by use of the first internal interface, the second internal interface, the third internal interface, and the fourth internal interface, and wherein the service registry program product comprises at least one service description searchable by a respectively associated service name; performing, by said processor, a first search of the service registry program product with the received service name and subsequently determining that the received service name does not have a service description associated with the received service name in the service registry program product; coordinating, by said processor, a second search of the service registry program product with a candidate service name by use of the search module, wherein the candidate service name is semantically and syntactically interchangeable with the received service name such that the candidate service name identifies the service description associated with the received service name within the service registry program product; and discovering, by said processor, the service description is associated with the candidate service name within the service registry program product and subsequently outputting the discovered service description through the web service registry system interfaces, said coordinating comprising: sending the received service name to the name parser of the search module via the second internal interface and subsequently receiving a component word list from the name parser via the second internal interface, wherein the component word list comprises all words constituting the received service name; sending the component word list to the dictionary of the search module via the third internal interface and subsequently receiving a respective synonym list for each word in the component word list from the dictionary via the third internal interface, wherein the respective synonym list comprises at least one synonym of said each word in the component word list; sending the respective synonym list to the name composer of the search module via the fourth internal interface and subsequently receiving the candidate service name from the name composer via the fourth internal interface; and sending a second search request for the service description associated with the candidate service name to the service registry program product via the first internal interface and subsequently receiving the service description in response to the second search request via the first internal interface. 3. The computer program product of claim 1 , wherein an Integrated Development Environment (IDE) programming tool comprises the web service registry system, wherein a user of the web service registry system develops a Service Oriented Architecture (SOA) business application by use of the IDE programming tool, wherein the user provides the service name to the web service registry system through an IDE user interface, wherein the web service registry system interface is coupled to the IDE user interface such that the search module receives the service name directly from the user, wherein the user receives the service description associated with the service name from the web service registry system via the IDE user interface, and wherein the received service description is employed in the SOA business application that provides a service described in the received service description. | 0.582006 |
9,460,074 | 13 | 17 | 13. An apparatus comprising: a processing device, wherein the processing device executes instructions that cause the apparatus to: parse training data using a plurality of pattern matching rules; assign a pattern matching rule as a parent rule of one or more child rules upon determining that failure of the parent rule to match the training data is a predictor of the one or more child rules failure to match the training data; receive data as input to be parsed; and parse the data using the plurality of pattern matching rules, the plurality of pattern matching rules organized according to a hierarchy including the parent rule and the one or more child rules of the parent rule, and wherein the parsing comprises: applying the parent rule to the data, determining the parent rule is unable to find a pattern match in the data, and bypassing application of each child rule to the data in response to the determination that the parent rule is unable to find a pattern match. | 13. An apparatus comprising: a processing device, wherein the processing device executes instructions that cause the apparatus to: parse training data using a plurality of pattern matching rules; assign a pattern matching rule as a parent rule of one or more child rules upon determining that failure of the parent rule to match the training data is a predictor of the one or more child rules failure to match the training data; receive data as input to be parsed; and parse the data using the plurality of pattern matching rules, the plurality of pattern matching rules organized according to a hierarchy including the parent rule and the one or more child rules of the parent rule, and wherein the parsing comprises: applying the parent rule to the data, determining the parent rule is unable to find a pattern match in the data, and bypassing application of each child rule to the data in response to the determination that the parent rule is unable to find a pattern match. 17. The apparatus of claim 13 , wherein parsing the data using a plurality of pattern matching rules further comprises instructions to cause the processor to: order parent rules for application ahead of independent rules, wherein independent rules are neither a parent rule nor a child rule. | 0.698758 |
8,340,971 | 1 | 9 | 1. A method of analyzing dialogs, the method comprising: receiving, via a processor, call-logs associated with a plurality of dialogs between a dialog system and users and external information about at least one user; extracting a first portion of turn-by-turn details of dialogs from the call-logs comprising at least a time stamp associated with a turn in the plurality of dialogs; inferring a second portion of the turn-by-turn details unavailable in the call-logs based on the first portion of the turn-by-turn details using a call-flow specification as a guide, the second portion of the turn-by-turn details comprising an interleaved sequence of at least two attributes that characterize a system state and a user response; and generating, from the first portion of the turn-by-turn details, the external information about the user, and the second portion of the turn-by-turn details, an empirical call-flow representation of the dialog. | 1. A method of analyzing dialogs, the method comprising: receiving, via a processor, call-logs associated with a plurality of dialogs between a dialog system and users and external information about at least one user; extracting a first portion of turn-by-turn details of dialogs from the call-logs comprising at least a time stamp associated with a turn in the plurality of dialogs; inferring a second portion of the turn-by-turn details unavailable in the call-logs based on the first portion of the turn-by-turn details using a call-flow specification as a guide, the second portion of the turn-by-turn details comprising an interleaved sequence of at least two attributes that characterize a system state and a user response; and generating, from the first portion of the turn-by-turn details, the external information about the user, and the second portion of the turn-by-turn details, an empirical call-flow representation of the dialog. 9. The method of claim 1 , wherein the empirical call-flow representation of the dialog is a stochastic finite-state machine. | 0.703791 |
8,073,804 | 11 | 14 | 11. A method for rendering a decision by use of a series of correlations, the method comprising: receiving on a digital electronic computer, a request to issue rules, the request including information in a semantic format; providing at least one proposed rule for insertion into a set of rules; determining a semantic relationship between the proposed rule and other rules in the set of rules; determining a placement of the proposed rules in the set of rules in accordance with the semantic relationship and, in the case of two rules having a relatively close semantic relationship, the rule having the most specific creative transform of the two rules having a relatively close semantic relationship receives a hierarchical placement at a head and the rule having the least specific creative transform of the two rules having a relatively close semantic relationship receives a hierarchical placement at a tail; in the case of the set of rules reaching a predetermined overflow limit, removing rules from the hierarchy according to predetermined criteria; responding to the request to issue rules by applying the rules in the hierarchy in accordance with semantics in the information in the request to find and apply a most specific creative transformation to a rule context; responding to the request to issue rules by applying the rules in the hierarchy in accordance with semantics in the information in the request to find and apply a most specific optimization to a rule consequent; determining if the application of the rules resulted in a transformation; and displaying an output of one of the rule or the result of the application of the rule. | 11. A method for rendering a decision by use of a series of correlations, the method comprising: receiving on a digital electronic computer, a request to issue rules, the request including information in a semantic format; providing at least one proposed rule for insertion into a set of rules; determining a semantic relationship between the proposed rule and other rules in the set of rules; determining a placement of the proposed rules in the set of rules in accordance with the semantic relationship and, in the case of two rules having a relatively close semantic relationship, the rule having the most specific creative transform of the two rules having a relatively close semantic relationship receives a hierarchical placement at a head and the rule having the least specific creative transform of the two rules having a relatively close semantic relationship receives a hierarchical placement at a tail; in the case of the set of rules reaching a predetermined overflow limit, removing rules from the hierarchy according to predetermined criteria; responding to the request to issue rules by applying the rules in the hierarchy in accordance with semantics in the information in the request to find and apply a most specific creative transformation to a rule context; responding to the request to issue rules by applying the rules in the hierarchy in accordance with semantics in the information in the request to find and apply a most specific optimization to a rule consequent; determining if the application of the rules resulted in a transformation; and displaying an output of one of the rule or the result of the application of the rule. 14. The method of claim 11 , further comprising: using networked processor clusters to process coherent or domain-specific knowledge in the respective clusters, thereby concentrating related knowledge in ones of the clusters to allow the individual clusters to share a maximal number of common antecedents and consequents. | 0.760773 |
7,568,171 | 20 | 21 | 20. The method of claim 17 , wherein moving the element is based at least in part on a curvature of the stroke. | 20. The method of claim 17 , wherein moving the element is based at least in part on a curvature of the stroke. 21. The method of claim 20 , wherein the curvature of the stroke is used to determine an orientation of the element about an axis thereof. | 0.5 |
8,145,678 | 13 | 15 | 13. A system configured to provide a social computing environment comprising: processor and memory resources; a collector to collect information using one or more back-end systems associated with users of the system; a filter to filter the collected information and provide enterprise-based events associated with one or more users of interest; a comment component configured to provide commenting functionality to system users; a feed generator to create an enterprise-based event feed that includes the one or more filtered events based in part on an organizational context of an enterprise and information associated with one or more user comments, provide the enterprise-based event feed to a target user, and update the enterprise-based event feed to delineate one or more user comments interleaved with the enterprise-based events to provide comment information as part of the enterprise-based event feed; and, a user relation management component to automatically add one or more commenting users to an enterprise-based social network of the target user without requiring mutual collaboration in order for commenting users to be included in tracking lists of a tracking users. | 13. A system configured to provide a social computing environment comprising: processor and memory resources; a collector to collect information using one or more back-end systems associated with users of the system; a filter to filter the collected information and provide enterprise-based events associated with one or more users of interest; a comment component configured to provide commenting functionality to system users; a feed generator to create an enterprise-based event feed that includes the one or more filtered events based in part on an organizational context of an enterprise and information associated with one or more user comments, provide the enterprise-based event feed to a target user, and update the enterprise-based event feed to delineate one or more user comments interleaved with the enterprise-based events to provide comment information as part of the enterprise-based event feed; and, a user relation management component to automatically add one or more commenting users to an enterprise-based social network of the target user without requiring mutual collaboration in order for commenting users to be included in tracking lists of a tracking users. 15. The system of claim 13 , wherein the feed generator can populate the enterprise-based event feed with a user comment, including a time and an identity of a commenting user. | 0.548718 |
5,384,894 | 5 | 10 | 5. The system according to claim 4, further comprising: a fuzzy evaluator for calculating and storing a joined confidence value of each record in the original text database, the joined confidence value of each record based on the fuzzy expected value for each word in that record. | 5. The system according to claim 4, further comprising: a fuzzy evaluator for calculating and storing a joined confidence value of each record in the original text database, the joined confidence value of each record based on the fuzzy expected value for each word in that record. 10. The system according to claim 5, wherein the system further comprises means for retrieving a record having a joined confidence value greater than a predetermined value. | 0.783375 |
8,140,449 | 8 | 10 | 8. A memory device that stores computer-executable instructions, the memory device comprising: instructions for obtaining one or more textual sequences from a document of a sequence of documents; instructions for identifying one or more pairs of the one or more textual sequences that occur within a paragraph of one another in the document; instructions for identifying, based on the one or more textual sequences and the one or more pairs, a presence of novel content in the document where the novel content includes content that does not occur in other documents in the sequence of documents; and instructions for assigning a score to the document based on the identified novel content of the document. | 8. A memory device that stores computer-executable instructions, the memory device comprising: instructions for obtaining one or more textual sequences from a document of a sequence of documents; instructions for identifying one or more pairs of the one or more textual sequences that occur within a paragraph of one another in the document; instructions for identifying, based on the one or more textual sequences and the one or more pairs, a presence of novel content in the document where the novel content includes content that does not occur in other documents in the sequence of documents; and instructions for assigning a score to the document based on the identified novel content of the document. 10. The memory device of claim 8 , where the sequence of documents comprises a temporally-ordered sequence of documents. | 0.617834 |
9,779,135 | 1 | 4 | 1. A method, utilizing at least one computing device, comprising: retrieving data definitions defining types of a plurality of business objects stored in enterprise data, the data definitions specify one or more attributes for each of the types of the plurality of business objects; generating, based at least in part on the data definitions, a meta-model of the enterprise data, the meta-model provides semantic information characterizing conceptual meaning to the one or more attributes; using the meta-model of the enterprise data to generate a rule definition that maps the enterprise data to the semantic information; using the rule definition to generate at least one semantic object and at least one semantic relation from the plurality of business objects stored in the enterprise data; and storing the at least one semantic object and the at least one semantic relation in a meta-model semantic network, the meta-model semantic network associating a term to the at least one semantic object. | 1. A method, utilizing at least one computing device, comprising: retrieving data definitions defining types of a plurality of business objects stored in enterprise data, the data definitions specify one or more attributes for each of the types of the plurality of business objects; generating, based at least in part on the data definitions, a meta-model of the enterprise data, the meta-model provides semantic information characterizing conceptual meaning to the one or more attributes; using the meta-model of the enterprise data to generate a rule definition that maps the enterprise data to the semantic information; using the rule definition to generate at least one semantic object and at least one semantic relation from the plurality of business objects stored in the enterprise data; and storing the at least one semantic object and the at least one semantic relation in a meta-model semantic network, the meta-model semantic network associating a term to the at least one semantic object. 4. The method of claim 1 , further comprising: receiving a message with a search query; identifying a relevant term in the search query; identifying that the at least one semantic relation is associated with the search query; searching the meta-model semantic network for semantic objects linked to the relevant term according to the at least one semantic relation; and communicating the semantic objects in a search result. | 0.5 |
7,814,042 | 119 | 120 | 119. The machine-readable storage medium of claim 118 , wherein the one or more sequences of instructions further comprise instructions which, when executed by the one or more processors, cause the one or more processors to perform the step of determining the alternative query block based on the first query block. | 119. The machine-readable storage medium of claim 118 , wherein the one or more sequences of instructions further comprise instructions which, when executed by the one or more processors, cause the one or more processors to perform the step of determining the alternative query block based on the first query block. 120. The machine-readable storage medium of claim 119 , wherein the first query block is a first subquery and wherein the instructions that cause determining the alternative query block comprise instructions which, when executed by the one or more processors, cause the one or more processors to perform the steps of: unnesting the first subquery; and determining the alternative query block based on the unnesting step. | 0.631579 |
8,209,629 | 8 | 9 | 8. The computer-implemented method of claim 1 , wherein the content displayed in the content pane comprises content associated with the contextual data displayed in the context pane. | 8. The computer-implemented method of claim 1 , wherein the content displayed in the content pane comprises content associated with the contextual data displayed in the context pane. 9. The computer-implemented method of claim 8 , wherein the contextual data displayed in the context pane is subordinate to the content displayed in the content pane. | 0.5 |
8,478,787 | 21 | 22 | 21. A system comprising: a machine-readable storage device having instructions stored thereon; and data processing apparatus programmed to execute the instructions to perform operations comprising: generating a raw name detection model using a collection of family names and an annotated corpus including a collection of n-grams, each n-gram having a corresponding probability of occurring as a respective name in the annotated corpus; applying the raw name detection model to a collection of semi-structured data to form annotated semi-structured data, the annotated semi-structured data identifying n-grams identifying names and n-grams not identifying names; applying the raw name detection model to a large unannotated corpus to form a large annotated corpus data identifying n-grams of the large unannotated corpus identifying names and n-grams not identifying names; and generating a name detection model including: deriving a name model using the annotated semi-structured data identifying names and the large annotated corpus data identifying names, deriving a not-name model using the semi-structured data not identifying names, and deriving a language model using the large annotated corpus. | 21. A system comprising: a machine-readable storage device having instructions stored thereon; and data processing apparatus programmed to execute the instructions to perform operations comprising: generating a raw name detection model using a collection of family names and an annotated corpus including a collection of n-grams, each n-gram having a corresponding probability of occurring as a respective name in the annotated corpus; applying the raw name detection model to a collection of semi-structured data to form annotated semi-structured data, the annotated semi-structured data identifying n-grams identifying names and n-grams not identifying names; applying the raw name detection model to a large unannotated corpus to form a large annotated corpus data identifying n-grams of the large unannotated corpus identifying names and n-grams not identifying names; and generating a name detection model including: deriving a name model using the annotated semi-structured data identifying names and the large annotated corpus data identifying names, deriving a not-name model using the semi-structured data not identifying names, and deriving a language model using the large annotated corpus. 22. The system of claim 21 wherein the operations further comprise: applying the name detection model to the collection of semi-structured data to form the annotated semi-structured data, the annotated semi-structured data identifying the n-grams identifying names and the n-grams not identifying names; applying the name detection model to the large unannotated corpus to form the large annotated corpus data identifying the n-grams of the large unannotated corpus identifying names and the n-grams not identifying names; and generating a refined name detection model including: deriving a refined name model using the annotated semi-structured data identifying names and the large annotated corpus data identifying names, deriving a refined not-name model using the semi-structured data not identifying names, and deriving a refined language model using the large annotated corpus. | 0.5 |
10,002,143 | 18 | 19 | 18. A computer implemented database system according to claim 17 , wherein the fifth table comprises a reference to the sixth table. | 18. A computer implemented database system according to claim 17 , wherein the fifth table comprises a reference to the sixth table. 19. A computer implemented database system according to claim 18 , wherein the directed links correspond to entries in the fifth table and the sixth table. | 0.5 |
9,922,033 | 1 | 5 | 1. A computer-implemented method for efficiently extracting contents of container files, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: receiving, at a first stage of a file-archiving system, an unnested container file containing a first constituent file and a second constituent file, wherein: the first constituent file is a nested container file that contains the second constituent file; and the file-archiving system is configured to perform a time-consuming file-indexing operation; enabling high file throughput at the first stage of the file-archiving system by refraining, at the first stage of the file-archiving system, from performing the time-consuming file-indexing operation; enabling a second stage of the file-archiving system to perform the time-consuming file-indexing operation on the second constituent file by creating, at the first stage of the file-archiving system, a content hierarchy for the unnested container file that comprises: metadata of the second constituent file; first hierarchical metadata that indicates that the unnested container file contains the nested container file; and second hierarchical metadata that indicates that the nested container file contains the second constituent file; using, at the second stage of the file-archiving system, the content hierarchy to locate the second constituent file within the nested container file; extracting, at the second stage of the file-archiving system, the second constituent file from the nested container file; performing, at the second stage of the file-archiving system, the time-consuming file-indexing operation on the second constituent file. | 1. A computer-implemented method for efficiently extracting contents of container files, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: receiving, at a first stage of a file-archiving system, an unnested container file containing a first constituent file and a second constituent file, wherein: the first constituent file is a nested container file that contains the second constituent file; and the file-archiving system is configured to perform a time-consuming file-indexing operation; enabling high file throughput at the first stage of the file-archiving system by refraining, at the first stage of the file-archiving system, from performing the time-consuming file-indexing operation; enabling a second stage of the file-archiving system to perform the time-consuming file-indexing operation on the second constituent file by creating, at the first stage of the file-archiving system, a content hierarchy for the unnested container file that comprises: metadata of the second constituent file; first hierarchical metadata that indicates that the unnested container file contains the nested container file; and second hierarchical metadata that indicates that the nested container file contains the second constituent file; using, at the second stage of the file-archiving system, the content hierarchy to locate the second constituent file within the nested container file; extracting, at the second stage of the file-archiving system, the second constituent file from the nested container file; performing, at the second stage of the file-archiving system, the time-consuming file-indexing operation on the second constituent file. 5. The computer-implemented method of claim 1 , wherein: the second hierarchical metadata indicates that the second constituent file is at a hierarchical level within the unnested container file; using the content hierarchy to locate the second constituent file within the nested container file comprises using the content hierarchy to locate one or more files at the hierarchical level within the unnested container file. | 0.627208 |
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