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32. An apparatus comprising a processor and a memory storing program code, the memory and program code being configured to, with the processor, cause the apparatus to at least: cause streamed data to be stored in a file, wherein the file consists of media data and metadata enclosed separately, wherein causing the streamed data to be stored in a file includes storing in a reception hint track; identifying metadata applicable to two or more samples of the streamed data; cause at least one timed metadata track to be created based on the identified metadata, the at least one timed metadata track describing a referred media track and the reception hint track, wherein the hint track refers to samples comprising instructions for constructing packets for transmission over an indicated communication protocol, wherein the media track refers to samples formatted according to a media compression format; form at least one group from the two or more samples of the streamed data, each sample in a group having identical metadata content for a metadata type; select each sample to group box associated with the reception hint track and the media track; and find a sample group description index of a particular reception hint sample or media sample.
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32. An apparatus comprising a processor and a memory storing program code, the memory and program code being configured to, with the processor, cause the apparatus to at least: cause streamed data to be stored in a file, wherein the file consists of media data and metadata enclosed separately, wherein causing the streamed data to be stored in a file includes storing in a reception hint track; identifying metadata applicable to two or more samples of the streamed data; cause at least one timed metadata track to be created based on the identified metadata, the at least one timed metadata track describing a referred media track and the reception hint track, wherein the hint track refers to samples comprising instructions for constructing packets for transmission over an indicated communication protocol, wherein the media track refers to samples formatted according to a media compression format; form at least one group from the two or more samples of the streamed data, each sample in a group having identical metadata content for a metadata type; select each sample to group box associated with the reception hint track and the media track; and find a sample group description index of a particular reception hint sample or media sample. 33. The apparatus of claim 32 , wherein the apparatus is further caused to identify the at least one group in a file stored in the memory.
| 0.558345 |
23. A system for processing pointer input comprising: a processor; and memory having stored therein computer executable instructions comprising: providing a transparent first graphical user interface overlaying a second graphical user interface; receiving pointer input in a handwriting area corresponding to the transparent first graphical user interface; displaying a guideline at a first position when a pen contacts a first position in the handwriting area; displaying the guideline at a second position only when the pen is lifted from the first position and subsequently contacts a second position in the handwriting area a threshold distance from the first position, wherein the threshold distance depends upon a direction of movement of the pen from the first position to the second position; displaying handwriting objects represented by the pointer input in the transparent first graphical user interface; recognizing text from the pointer input; and providing the recognized text to a software application.
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23. A system for processing pointer input comprising: a processor; and memory having stored therein computer executable instructions comprising: providing a transparent first graphical user interface overlaying a second graphical user interface; receiving pointer input in a handwriting area corresponding to the transparent first graphical user interface; displaying a guideline at a first position when a pen contacts a first position in the handwriting area; displaying the guideline at a second position only when the pen is lifted from the first position and subsequently contacts a second position in the handwriting area a threshold distance from the first position, wherein the threshold distance depends upon a direction of movement of the pen from the first position to the second position; displaying handwriting objects represented by the pointer input in the transparent first graphical user interface; recognizing text from the pointer input; and providing the recognized text to a software application. 30. The system recited in claim 23 , wherein the instructions further comprise: deleting the handwriting guideline when the pen has moved outside of the handwriting area.
| 0.579178 |
22. A method comprising: collecting a set of context-data. from at least one context-data provider with at least one server, wherein the context-data. is related to a meaning of a short message content; algorithmically selecting a relevant context data according to a metric, wherein the metric comprises a monetary cost of the context-data, and wherein the context-data is obtained by a physical sensor; linking the relevant context data to the short message; and formatting the relevant context data and the short message according to a communication protocol.
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22. A method comprising: collecting a set of context-data. from at least one context-data provider with at least one server, wherein the context-data. is related to a meaning of a short message content; algorithmically selecting a relevant context data according to a metric, wherein the metric comprises a monetary cost of the context-data, and wherein the context-data is obtained by a physical sensor; linking the relevant context data to the short message; and formatting the relevant context data and the short message according to a communication protocol. 23. The method of claim 22 , wherein the communication protocol comprises a cellular network short message protocol.
| 0.732427 |
3. The method of claim 1 , comprising allowing a user to select a plane that cuts through the three dimensional collection of cubes, the plane being oriented relative to one common axis of the cubes, wherein selecting the plane indicates a subset of the multiple pieces of communication data.
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3. The method of claim 1 , comprising allowing a user to select a plane that cuts through the three dimensional collection of cubes, the plane being oriented relative to one common axis of the cubes, wherein selecting the plane indicates a subset of the multiple pieces of communication data. 4. The method of claim 3 , comprising displaying an expanded 2D representation of the communication data indicated by the plane.
| 0.884827 |
16. The system of claim 15 , wherein said at least one attribute includes a name, a residence or business address, a telephone number, an electronic mail address, education data, past employer data, or salary data.
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16. The system of claim 15 , wherein said at least one attribute includes a name, a residence or business address, a telephone number, an electronic mail address, education data, past employer data, or salary data. 18. The system of claim 16 , wherein the education data includes a degree, a major, a year, or a school name.
| 0.955156 |
1. A computer based method implemented by at least one computer processor of developing user affinity knowledge, the method comprising: displaying a plurality of user-selectable objects on each of a plurality of user systems, each of the plurality of user-selectable objects associated with one or more meanings prior to selection by users; receiving, from a particular user, at least one selection of one or more of the plurality of the displayed user-selectable objects from each of the user systems wherein each selection creates a personal expression based at least in part on associated meanings of the one or more selected objects; analyzing time durations of when two or more user-selected objects of different data types are present simultaneously within the personal expression; analyzing direct proximity between the two or more user-selected objects of different data types to each other without consideration of any intermediate user-selected objects; and defining and storing at least one user affinity profile for the particular user, wherein the at least one user affinity profile indicates personal emotions of the particular user derived from the analyzing steps; and the receiving further comprises receiving a selection of the two or more user-selectable objects of the different data types from each of the user systems, wherein each object has a data type selectable from a group consisting of a word, an image, a video clip, an audio clip, and a symbol.
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1. A computer based method implemented by at least one computer processor of developing user affinity knowledge, the method comprising: displaying a plurality of user-selectable objects on each of a plurality of user systems, each of the plurality of user-selectable objects associated with one or more meanings prior to selection by users; receiving, from a particular user, at least one selection of one or more of the plurality of the displayed user-selectable objects from each of the user systems wherein each selection creates a personal expression based at least in part on associated meanings of the one or more selected objects; analyzing time durations of when two or more user-selected objects of different data types are present simultaneously within the personal expression; analyzing direct proximity between the two or more user-selected objects of different data types to each other without consideration of any intermediate user-selected objects; and defining and storing at least one user affinity profile for the particular user, wherein the at least one user affinity profile indicates personal emotions of the particular user derived from the analyzing steps; and the receiving further comprises receiving a selection of the two or more user-selectable objects of the different data types from each of the user systems, wherein each object has a data type selectable from a group consisting of a word, an image, a video clip, an audio clip, and a symbol. 4. The method of claim 1 , wherein the plurality of user-selected objects includes individual objects that are individually known to have strong affinities with users.
| 0.782473 |
1. A method for segmenting an image, comprising: registering an annotated template image to an acquired reference image using only rigid transformations to define a transformation function relating the annotated template image to the acquired reference image; refining the defined transformation function by registering the annotated template image to the acquired reference image using only the rigid transformations and scaling in which scale is held equal for x, y, and z axes; further refining the refined transformation function by registering the annotated template image to the acquired reference image using only multi-affine transformations, wherein the step of further refining using only multi-affine transformations is divided into multiple registration steps wherein at each successive step thereof, registration is iterated by including additional transformation centers such that a number of transformation centers used during each successive registration step progressively increases; and still further refining the twice refined transformation function by registering the annotated template image to the acquired reference image using deformation transformations.
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1. A method for segmenting an image, comprising: registering an annotated template image to an acquired reference image using only rigid transformations to define a transformation function relating the annotated template image to the acquired reference image; refining the defined transformation function by registering the annotated template image to the acquired reference image using only the rigid transformations and scaling in which scale is held equal for x, y, and z axes; further refining the refined transformation function by registering the annotated template image to the acquired reference image using only multi-affine transformations, wherein the step of further refining using only multi-affine transformations is divided into multiple registration steps wherein at each successive step thereof, registration is iterated by including additional transformation centers such that a number of transformation centers used during each successive registration step progressively increases; and still further refining the twice refined transformation function by registering the annotated template image to the acquired reference image using deformation transformations. 7. The method of claim 1 , wherein the multi-affine or deformation transformations are Sigmoid weighted.
| 0.945876 |
25. A documentation browsing program stored in a program memory characterized by causing a computer to execute the process of: generating correspondence between voices or images included in audio data or image data with a document included in document data; displaying the voices or the images included in said audio data or said image data and the document included in said document data associated with each other based on said correspondence; and updating said document data associated based on user editing instruction; displaying a displaying location of a document included in document data on a display screen in association with time information which indicates an elapsed time of voices or images; and outputting recalculation instruction information for instructing recalculation of relationship between a document and voices or images and recalculating said relationship when said document data is updated.
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25. A documentation browsing program stored in a program memory characterized by causing a computer to execute the process of: generating correspondence between voices or images included in audio data or image data with a document included in document data; displaying the voices or the images included in said audio data or said image data and the document included in said document data associated with each other based on said correspondence; and updating said document data associated based on user editing instruction; displaying a displaying location of a document included in document data on a display screen in association with time information which indicates an elapsed time of voices or images; and outputting recalculation instruction information for instructing recalculation of relationship between a document and voices or images and recalculating said relationship when said document data is updated. 47. The documentation browsing program according to claim 25 , causing a computer to execute the process of outputting a document based on document data.
| 0.730519 |
2. The method of claim 1 , further including the step of filtering the identified files, prior to said examining step, to select files having a predetermined designation.
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2. The method of claim 1 , further including the step of filtering the identified files, prior to said examining step, to select files having a predetermined designation. 3. The method of claim 2 , wherein said predetermined designation is a creator designation.
| 0.960065 |
1. A method for populating forms based on a user interview, comprising: generating, using a computer processor, a plurality of binary questions according to a first rule to form a top level menu; receiving a plurality of binary answers corresponding to the plurality of binary questions from the user; adjusting, using the computer processor, at least one of the plurality of binary questions based on the plurality of binary answers according to a second rule during the user interview; identifying, using the computer processor, a plurality of forms from a forms library based on the plurality of binary answers according to a third rule, wherein the plurality of forms comprises a Federal tax return form and a state tax return form associated with a first State; extracting, based on the plurality of binary answers, a plurality of data entry fields from the plurality of forms by at least: excluding any duplicate data entry field in the plurality of forms, and combining at least two related data entry fields based on a pre-determined criterion; presenting the plurality of data entry fields to the user in a unified format by: grouping related data entry fields of the plurality of data entry fields based on the plurality of binary answers to form a plurality of data entry menus, wherein the plurality of data entry menus are organized as multiple levels in lower level menu structures associated with the top level menu; and selectively presenting the plurality of data entry menus to the user based on a condition of the plurality of binary answers; receiving data from the user for the plurality of data entry fields, wherein the lower level menu structures of the unified format are further generated and added to the user interview based on the data, wherein further generating the lower level menu structures of the unified format comprises: identifying an additional state tax return form associated with a second State based on the data; and grouping additional binary questions associated with all data entry fields for a particular deduction required by the Federal tax return form, the State tax return form, and the additional State tax return form together in a single data entry menu for the particular deduction; populating at least a portion of the plurality of forms to generate a plurality of populated forms; and storing the plurality of populated forms in a repository on behalf of the user.
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1. A method for populating forms based on a user interview, comprising: generating, using a computer processor, a plurality of binary questions according to a first rule to form a top level menu; receiving a plurality of binary answers corresponding to the plurality of binary questions from the user; adjusting, using the computer processor, at least one of the plurality of binary questions based on the plurality of binary answers according to a second rule during the user interview; identifying, using the computer processor, a plurality of forms from a forms library based on the plurality of binary answers according to a third rule, wherein the plurality of forms comprises a Federal tax return form and a state tax return form associated with a first State; extracting, based on the plurality of binary answers, a plurality of data entry fields from the plurality of forms by at least: excluding any duplicate data entry field in the plurality of forms, and combining at least two related data entry fields based on a pre-determined criterion; presenting the plurality of data entry fields to the user in a unified format by: grouping related data entry fields of the plurality of data entry fields based on the plurality of binary answers to form a plurality of data entry menus, wherein the plurality of data entry menus are organized as multiple levels in lower level menu structures associated with the top level menu; and selectively presenting the plurality of data entry menus to the user based on a condition of the plurality of binary answers; receiving data from the user for the plurality of data entry fields, wherein the lower level menu structures of the unified format are further generated and added to the user interview based on the data, wherein further generating the lower level menu structures of the unified format comprises: identifying an additional state tax return form associated with a second State based on the data; and grouping additional binary questions associated with all data entry fields for a particular deduction required by the Federal tax return form, the State tax return form, and the additional State tax return form together in a single data entry menu for the particular deduction; populating at least a portion of the plurality of forms to generate a plurality of populated forms; and storing the plurality of populated forms in a repository on behalf of the user. 5. The method of claim 1 , further comprising: analyzing, using the computer processor, a structure of the plurality of forms to generate a context based rule; identifying a context based on at least a portion of the plurality of binary answers and the data; and adjusting, using the computer processor, at least one of the plurality of data entry fields presented to the user based on the context according to the context based rule.
| 0.752278 |
3. The system of claim 1 , wherein the calculating further includes normalizing the sum to a value between 0 and 1 using a refining function.
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3. The system of claim 1 , wherein the calculating further includes normalizing the sum to a value between 0 and 1 using a refining function. 4. The system of claim 3 , wherein the refining function includes: calculating a first value as the natural log of the negative of the sum; adding 1 to the first value to obtain a second value; and inverting the second value.
| 0.903004 |
15. The apparatus of claim 14 , wherein formulating the collection of attribute suggestions comprises comparing characteristics of a preexisting structured presentation with content of electronic documents in the electronic document collection.
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15. The apparatus of claim 14 , wherein formulating the collection of attribute suggestions comprises comparing characteristics of a preexisting structured presentation with content of electronic documents in the electronic document collection. 20. The apparatus of claim 15 , wherein comparing the characteristics of the preexisting structured presentation with the content of the electronic documents comprises comparing an attribute or a value of an attribute used to characterize an instance in the preexisting structured presentation with the content of the electronic documents.
| 0.928631 |
1. A method for message translation for multiple social media systems, comprising the steps of: a. receiving at a Messaging Translation Service Application Server (MTS AS) a message written in a first language; b. requesting and obtaining from multiple Social Media servers (SM servers) information related to a language used by each one of the SM servers; c. requesting translation of the message from the first language into the language or languages used by the SM servers; and d. sending a translation of the message in the language used by each one of the SM servers to the respective one of the multiple SM server.
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1. A method for message translation for multiple social media systems, comprising the steps of: a. receiving at a Messaging Translation Service Application Server (MTS AS) a message written in a first language; b. requesting and obtaining from multiple Social Media servers (SM servers) information related to a language used by each one of the SM servers; c. requesting translation of the message from the first language into the language or languages used by the SM servers; and d. sending a translation of the message in the language used by each one of the SM servers to the respective one of the multiple SM server. 6. The method of claim 1 , wherein step b. comprises the steps of: b.1. sending a request for the information related to the language used by the each one of the multiple SM servers, wherein the language used by the each one of the multiple SM servers is a language associated with a group of users within the SM server; and b.2. receiving back from the each one of the SM servers the information related to the language associated with the group of users within the SM server.
| 0.625966 |
4. The image processing apparatus according to claim 1 , wherein: when at least one of the start position and the end position of the mark, which defines the mark is identified by the second identifying unit, is less than a beginning of the position of the string or an end of the position of the string, the character string extracting unit determines whether or not the string identified by the first identifying unit is to be extracted based on a extraction condition that is preset.
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4. The image processing apparatus according to claim 1 , wherein: when at least one of the start position and the end position of the mark, which defines the mark is identified by the second identifying unit, is less than a beginning of the position of the string or an end of the position of the string, the character string extracting unit determines whether or not the string identified by the first identifying unit is to be extracted based on a extraction condition that is preset. 6. The image processing apparatus according to claim 4 , wherein the extraction condition is based on a type of word represented by the given string.
| 0.90942 |
11. A computer program product for driving genomic data processing workflows using metadata, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: receive, at the processor: workflow data; metadata associated with the workflow data, wherein the metadata comprise a plurality of metadata generations, each metadata generation corresponding to at least one operation of the workflow, each metadata generation including: anchoring metadata configured to uniquely identify the workflow by using an alphanumeric string; common metadata comprising one or more characteristics selected from: sample characteristics, processing site characteristics, laboratory characteristics, instrument characteristics, assay characteristics, temporal characteristics, security characteristics and project characteristics; and custom metadata comprising workflow characteristics and/or data characteristics; and a request to manage a workflow using the metadata; distribute, by the processor, the workflow data and the associated metadata across a plurality of distributed resources of a cloud computing environment; and associate the metadata with the workflow data by indexing, using the processor, the workflow data according to the metadata; and drive at least a portion of the workflow based on the metadata, wherein driving the workflow based at least in part on the metadata comprises: determining new data and/or at least one new processing setting to use in connection with repeating at least a portion of the workflow; and repeating the portion of the workflow using the new data and/or the new processing setting, wherein the determining is based at least in part on the common metadata and/or the custom metadata; and wherein the new data and/or the new processing setting comprise a modified number of permissible gaps in an alignment based at least in part on an average sequence length of input sequence data.
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11. A computer program product for driving genomic data processing workflows using metadata, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: receive, at the processor: workflow data; metadata associated with the workflow data, wherein the metadata comprise a plurality of metadata generations, each metadata generation corresponding to at least one operation of the workflow, each metadata generation including: anchoring metadata configured to uniquely identify the workflow by using an alphanumeric string; common metadata comprising one or more characteristics selected from: sample characteristics, processing site characteristics, laboratory characteristics, instrument characteristics, assay characteristics, temporal characteristics, security characteristics and project characteristics; and custom metadata comprising workflow characteristics and/or data characteristics; and a request to manage a workflow using the metadata; distribute, by the processor, the workflow data and the associated metadata across a plurality of distributed resources of a cloud computing environment; and associate the metadata with the workflow data by indexing, using the processor, the workflow data according to the metadata; and drive at least a portion of the workflow based on the metadata, wherein driving the workflow based at least in part on the metadata comprises: determining new data and/or at least one new processing setting to use in connection with repeating at least a portion of the workflow; and repeating the portion of the workflow using the new data and/or the new processing setting, wherein the determining is based at least in part on the common metadata and/or the custom metadata; and wherein the new data and/or the new processing setting comprise a modified number of permissible gaps in an alignment based at least in part on an average sequence length of input sequence data. 13. The computer program product as recited in claim 11 , wherein the cloud computing environment comprises: a plurality of computer readable storage media configured as a cloud storage environment; and a plurality of processing nodes arranged in at least one cloud processing cluster.
| 0.602203 |
13. The system of claim 11 , wherein determining that the first search query is a search query for which real-time search results should be returned comprises: receiving data for the first search query; generating one or more scores from the data; and determining that each of the one or more scores satisfies a respective threshold.
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13. The system of claim 11 , wherein determining that the first search query is a search query for which real-time search results should be returned comprises: receiving data for the first search query; generating one or more scores from the data; and determining that each of the one or more scores satisfies a respective threshold. 15. The system of claim 13 , wherein the data includes whether the first search query includes one or more terms that indicate a desire for real-time search results.
| 0.929293 |
1. A topic map based indexing apparatus, comprising: a question/answer (Q/A) pre-processing block to, by a computer, normalize community Q/A lists for plural different community sites on web, respectively, correct grammatical errors, and remove insignificant symbols, to thereby provide pre-processed community Q/A lists for the plural different community sites, respectively; a Q/A analysis block to, by a computer, analyze the pre-processed community Q/A lists to acquire Q/A analysis information; and a Q/A storage block to, by a computer, store, in a community Q/A topic map, index information containing the pre-processed community Q/A lists and the Q/A analysis information, wherein the indexing information is obtained by removing redundant answers depending on the Q/A analysis information, removing insignificant answers based on a degree of reliability, ranking answer lists, extracting a highest ranking answer as a best answer, and determining a topic, wherein the Q/A pre-processing block includes: a one unit recognizing unit to normalize, in a single form, allomorph words or words recognizable as one unit in the community Q/A lists by referring to a unit dictionary database; and an error pre-processing unit to correct the grammatical errors and remove the insignificant symbols from the community Q/A lists by referring to a pre-processing rule database.
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1. A topic map based indexing apparatus, comprising: a question/answer (Q/A) pre-processing block to, by a computer, normalize community Q/A lists for plural different community sites on web, respectively, correct grammatical errors, and remove insignificant symbols, to thereby provide pre-processed community Q/A lists for the plural different community sites, respectively; a Q/A analysis block to, by a computer, analyze the pre-processed community Q/A lists to acquire Q/A analysis information; and a Q/A storage block to, by a computer, store, in a community Q/A topic map, index information containing the pre-processed community Q/A lists and the Q/A analysis information, wherein the indexing information is obtained by removing redundant answers depending on the Q/A analysis information, removing insignificant answers based on a degree of reliability, ranking answer lists, extracting a highest ranking answer as a best answer, and determining a topic, wherein the Q/A pre-processing block includes: a one unit recognizing unit to normalize, in a single form, allomorph words or words recognizable as one unit in the community Q/A lists by referring to a unit dictionary database; and an error pre-processing unit to correct the grammatical errors and remove the insignificant symbols from the community Q/A lists by referring to a pre-processing rule database. 2. The topic map based indexing apparatus of claim 1 , wherein the Q/A analysis block includes: a language analysis unit to perform language analysis on the pre-processed community Q/A lists by morpheme analysis, named entity recognition, and partial syntactic analysis, to thereby provide language analysis results; a domain classification unit to determine domains of the pre-processed community Q/A lists by referring to a domain classification database; a topic classification unit to classify the pre-processed community Q/A lists by topic by referring to a topic classification database; a Q/A type analysis unit to analyze a type of an expected community answer in the pre-processed community Q/A lists based on an intention of a community question with reference to a Q/A type database; a keyword extraction and extension unit to extract keywords from the pre-processed community Q/A lists depending on the language analysis results by referring to a keyword extension dictionary database, and to additionally extend a range of similar words corresponding to the keywords; and a constraint word extraction unit to extract, from the pre-processed community Q/A lists, constraint words in order to restrict a search space by referring to a constraint word extraction rule database.
| 0.569231 |
1. A computer-implemented method, comprising: for each one of a plurality of documents, identifying a plurality of queries which resulted in user selection of the one of the plurality of documents from among search results provided in response to the queries; identifying itemsets within the queries, at least some of the itemsets representing recurring patterns in the queries; for each one of the plurality of documents, generating a representation of the corresponding one of the plurality of documents, wherein the representation of the one of the plurality of documents is generated based, at least in part, upon the itemsets identified within the corresponding queries which resulted in user selection of the document from among the search results provided in response to the corresponding queries; and for each one of the plurality of documents, classifying the one of the plurality of documents using the corresponding representation; wherein, for each one of the plurality of documents, the representation of the one of the plurality of documents comprises a vector including a plurality of scalar values, each scalar value representing a frequency with which a represented one of the itemsets appears within the corresponding queries.
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1. A computer-implemented method, comprising: for each one of a plurality of documents, identifying a plurality of queries which resulted in user selection of the one of the plurality of documents from among search results provided in response to the queries; identifying itemsets within the queries, at least some of the itemsets representing recurring patterns in the queries; for each one of the plurality of documents, generating a representation of the corresponding one of the plurality of documents, wherein the representation of the one of the plurality of documents is generated based, at least in part, upon the itemsets identified within the corresponding queries which resulted in user selection of the document from among the search results provided in response to the corresponding queries; and for each one of the plurality of documents, classifying the one of the plurality of documents using the corresponding representation; wherein, for each one of the plurality of documents, the representation of the one of the plurality of documents comprises a vector including a plurality of scalar values, each scalar value representing a frequency with which a represented one of the itemsets appears within the corresponding queries. 16. The method of claim 1 , wherein the representation of each of the plurality of documents is not generated with reference to terms within the corresponding one of the plurality of documents.
| 0.632369 |
18. The computer readable media of claim 17 , further comprising additional computer readable instructions recorded thereon for: assigning a priority to each of the plurality of text strings; and selecting a language associated with a high priority text string for generating the speech content.
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18. The computer readable media of claim 17 , further comprising additional computer readable instructions recorded thereon for: assigning a priority to each of the plurality of text strings; and selecting a language associated with a high priority text string for generating the speech content. 19. The computer readable media of claim 18 , further comprising additional computer readable instructions recorded thereon for: identifying a default language associated with an electronic device providing the speech content; determining that the identified languages are speakable in the default language; and selecting the default language for generating the speech content.
| 0.789377 |
1. A computer-implemented system for identifying relevant documents for display, comprising: themes for a set of documents; an extraction module to extract noun phrases from the documents as concepts; a theme generator to group two or more of the concepts as one such theme; a frequency table that identifies each of the concepts and a frequency of occurrence of each concept within each of the documents in the set; a graph generator to generate a graph of the concepts, comprising: an x-axis of the graph defining the concepts; a y-axis of the graph defining a number of the documents that reference each concept; and a mapping module to map the concepts on the graph in order of descending number of referring documents; a cluster module to cluster the documents based on the themes; a matrix for the documents comprising an inner product of document frequency occurrences and cluster concept weightings for each theme; an identification module to identify from the matrix, documents most relevant to a particular theme; and a display to present the relevant documents.
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1. A computer-implemented system for identifying relevant documents for display, comprising: themes for a set of documents; an extraction module to extract noun phrases from the documents as concepts; a theme generator to group two or more of the concepts as one such theme; a frequency table that identifies each of the concepts and a frequency of occurrence of each concept within each of the documents in the set; a graph generator to generate a graph of the concepts, comprising: an x-axis of the graph defining the concepts; a y-axis of the graph defining a number of the documents that reference each concept; and a mapping module to map the concepts on the graph in order of descending number of referring documents; a cluster module to cluster the documents based on the themes; a matrix for the documents comprising an inner product of document frequency occurrences and cluster concept weightings for each theme; an identification module to identify from the matrix, documents most relevant to a particular theme; and a display to present the relevant documents. 2. A system according to claim 1 , further comprising: an assignment module to assign an identifier to each of the concepts, wherein each identifier is a monotonically increasing integer value.
| 0.584928 |
13. A computer readable medium having stored executable instructions for determining the sensitivity of a hypothesis of interest to a parameter within an argument model, such that an associated processor executing the executable instructions performs a plurality of functions comprising: providing a continuous mechanism for a user to modify the parameter, such that the user can make multiple modifications to the parameter in rapid sequence; updating a confidence value associated with the hypothesis of interest in response to the modification of the parameter; and altering a display of the confidence value of the hypothesis of interest in real time to match the updated confidence value in response to each modification of the parameter, wherein the display of the confidence value comprises a qualitative display of the confidence value, such that a non-numerical quality of a node associated with the hypothesis of interest is altered to illustrate a change in the confidence value wherein the argument model comprises at least two contributing hypotheses, the parameter comprising an influence value associated with a logical relationship between the two contributing hypotheses, the influence value representing a degree of logical relatedness between the two contributing hypotheses.
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13. A computer readable medium having stored executable instructions for determining the sensitivity of a hypothesis of interest to a parameter within an argument model, such that an associated processor executing the executable instructions performs a plurality of functions comprising: providing a continuous mechanism for a user to modify the parameter, such that the user can make multiple modifications to the parameter in rapid sequence; updating a confidence value associated with the hypothesis of interest in response to the modification of the parameter; and altering a display of the confidence value of the hypothesis of interest in real time to match the updated confidence value in response to each modification of the parameter, wherein the display of the confidence value comprises a qualitative display of the confidence value, such that a non-numerical quality of a node associated with the hypothesis of interest is altered to illustrate a change in the confidence value wherein the argument model comprises at least two contributing hypotheses, the parameter comprising an influence value associated with a logical relationship between the two contributing hypotheses, the influence value representing a degree of logical relatedness between the two contributing hypotheses. 17. The computer readable medium of claim 13 , the continuous mechanism comprising a line graph, spanning a minimum influence value and a maximum influence value, and a slider for selecting a value on the line graph.
| 0.556487 |
12. An apparatus according to claim 6 in which said second coding means comprises means for storing a signal representative of an exceptional inflectional form expression corresponding to at least one said partial paradigm-representative signal.
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12. An apparatus according to claim 6 in which said second coding means comprises means for storing a signal representative of an exceptional inflectional form expression corresponding to at least one said partial paradigm-representative signal. 13. An apparatus according to claim 12 in which said exceptional inflectional expression-representative signal storing means comprises means for storing a signal indicative of at least one of a grammatical classification and an inflectional classification.
| 0.901108 |
16. A computer storage medium not consisting of a propagated data signal and storing computer executable instructions for performing a method of displaying one or more graphical hierarchical diagrams, the method comprising: receiving selection of a first graphic definition for rendering a first graphical hierarchical diagram, the first graphic definition specifying a first graphical element; in response to the selection of the first graphic definition, rendering the first graphical element within the first graphical hierarchical diagram in a drawing pane on the display device; receiving content text within the first graphical element; receiving a first customization to a presentation property of the first graphical element; updating the presentation property of the first graphical element with the first customization; receiving a second customization to a semantic property of the first graphical element; updating the semantic property of the first graphical element with the second customization; receiving a selection of a second graphic definition; and in response to the selection of the second graphic definition, rendering a second graphical hierarchical diagram comprising a second graphical element that includes the content text and the updated semantic property but not the updated presentation property.
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16. A computer storage medium not consisting of a propagated data signal and storing computer executable instructions for performing a method of displaying one or more graphical hierarchical diagrams, the method comprising: receiving selection of a first graphic definition for rendering a first graphical hierarchical diagram, the first graphic definition specifying a first graphical element; in response to the selection of the first graphic definition, rendering the first graphical element within the first graphical hierarchical diagram in a drawing pane on the display device; receiving content text within the first graphical element; receiving a first customization to a presentation property of the first graphical element; updating the presentation property of the first graphical element with the first customization; receiving a second customization to a semantic property of the first graphical element; updating the semantic property of the first graphical element with the second customization; receiving a selection of a second graphic definition; and in response to the selection of the second graphic definition, rendering a second graphical hierarchical diagram comprising a second graphical element that includes the content text and the updated semantic property but not the updated presentation property. 18. The computer storage medium of claim 16 , wherein the semantic property is a property that persists across all graphic definitions.
| 0.795585 |
8. A computer-implemented system comprising: one or more computers; one or more data storage devices coupled to the one or more computers and storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: while receiving a text input entered into a search engine query input field by a user, the query input field displayed in a map user interface having a viewport displaying a portion of a map at a particular zoom level, and before the user has submitted the text input as a search query to a search engine: determining the particular zoom level and a geographical location associated with the portion of the map displayed in the viewport at the particular zoom level; obtaining a plurality of query suggestions based at least in part on the received text input; grouping at least some of the query suggestions based on a common primary query term shared by the query suggestions, wherein the grouped query suggestions include one or more refinement terms that refine the common primary query term, wherein the one or more refinement terms that refine the common primary query term are selected based, at least in part, on the particular zoom level of the map as presented in the viewport while the text input is being received, and the geographical location displayed in the viewport while the text input is being received; and transmitting a set of the plurality of query suggestions to a client device for presentation to the user, wherein the set includes the grouped query suggestions that are presented as a group with the common primary query term presented in a prominent position and the one or more refinement terms presented in subordinate positions relative to the common primary query term and wherein the common primary query term and the one or more refinement terms are each user-selectable.
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8. A computer-implemented system comprising: one or more computers; one or more data storage devices coupled to the one or more computers and storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: while receiving a text input entered into a search engine query input field by a user, the query input field displayed in a map user interface having a viewport displaying a portion of a map at a particular zoom level, and before the user has submitted the text input as a search query to a search engine: determining the particular zoom level and a geographical location associated with the portion of the map displayed in the viewport at the particular zoom level; obtaining a plurality of query suggestions based at least in part on the received text input; grouping at least some of the query suggestions based on a common primary query term shared by the query suggestions, wherein the grouped query suggestions include one or more refinement terms that refine the common primary query term, wherein the one or more refinement terms that refine the common primary query term are selected based, at least in part, on the particular zoom level of the map as presented in the viewport while the text input is being received, and the geographical location displayed in the viewport while the text input is being received; and transmitting a set of the plurality of query suggestions to a client device for presentation to the user, wherein the set includes the grouped query suggestions that are presented as a group with the common primary query term presented in a prominent position and the one or more refinement terms presented in subordinate positions relative to the common primary query term and wherein the common primary query term and the one or more refinement terms are each user-selectable. 13. The computer-implemented system of claim 8 , wherein the instructions, when executed by the one or more computers, cause the one or more computers to perform operations further comprising: receiving an input from the user selecting one of the query suggestions, wherein the received text input and the selected query suggestion comprise a search query; before the user has submitted the search query: obtaining a second plurality of query suggestions based on the search query, wherein at least some of the query suggestions comprise refinement terms that refine the search query and are grouped together; and transmitting a set of the second plurality of query suggestions to the client device for presentation to the user, wherein the set includes the grouped query suggestions that are presented in a position relative to the search query that indicates the grouped query suggestions are refinement terms that refine the search query.
| 0.5 |
26. A computer system comprising: a processor; and a memory coupled to the processor, the memory having instructions stored therein which, when executed by the processor, cause the processor to: receive results of a search of data distributed among a plurality of computers on a network, the results corresponding to user-provided search criteria, the results including a plurality of hypertext documents; refine said results of the first search based on relevance of each of the hypertext documents to the user-provided search criteria by performing a content examination of the results of the search; rank the plurality of hypertext documents based on results of the content examination; generate a map of the hypertext documents based on the ranking, wherein each of the hypertext documents is represented on the display device as one of a plurality of objects; and cause the map to be displayed on a display device, such that the map visually indicates logical links between hypertext documents, wherein the map includes an arrangement of objects having a three-dimensional appearance, such that a visual indication of the ranking comprises an apparent relative positioning of the objects in each of the three dimensions.
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26. A computer system comprising: a processor; and a memory coupled to the processor, the memory having instructions stored therein which, when executed by the processor, cause the processor to: receive results of a search of data distributed among a plurality of computers on a network, the results corresponding to user-provided search criteria, the results including a plurality of hypertext documents; refine said results of the first search based on relevance of each of the hypertext documents to the user-provided search criteria by performing a content examination of the results of the search; rank the plurality of hypertext documents based on results of the content examination; generate a map of the hypertext documents based on the ranking, wherein each of the hypertext documents is represented on the display device as one of a plurality of objects; and cause the map to be displayed on a display device, such that the map visually indicates logical links between hypertext documents, wherein the map includes an arrangement of objects having a three-dimensional appearance, such that a visual indication of the ranking comprises an apparent relative positioning of the objects in each of the three dimensions. 27. A computer system according to claim 26, wherein the visual indication of the ranking comprises at least one attribute of a given object from the list of attributes consisting of: a color of the given object; a size of the given object; and a shape of the given object.
| 0.623864 |
2. The method of claim 1 wherein identifying presentation documents for a presentation comprises: creating a data structure representing a presentation; and listing at least one presentation document in the data structure representing a presentation.
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2. The method of claim 1 wherein identifying presentation documents for a presentation comprises: creating a data structure representing a presentation; and listing at least one presentation document in the data structure representing a presentation. 3. The method of claim 2 wherein: listing the at least one presentation document includes storing a location of the presentation document in the data structure representing a presentation; and storing each presentation grammar includes retrieving a presentation grammar of the presentation document in dependence upon the location of the presentation document.
| 0.864591 |
1. A method for providing an application using a computer that performs actions, comprising: when a multi-size type is provided during compilation of the application into a machine code version of the application, performing actions, including: employing architecture information of a target computer to identify one or more data types associated with the target computer that correspond to the multi-sized type; employing parameters of one or more native code calls associated with an intermediate language code call to identify matching of the one or more native code calls with the one or more data types; providing a machine code version of the intermediate language code call that corresponds to the architecture information and also corresponds to the one or more native code calls; when the target computer provides for just-in-time compiling, employing a run time engine to execute, on the target computer, a machine code version of the intermediate language code call having one or more values that correspond to the multi-size type and the one or more data types, wherein the one or more native code calls are executed using the one or more data types that correspond to the architecture information; and when the target computer provides for disabling just-in-time compiling, inserting the machine code version of the intermediate language code call in the machine code version of the application.
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1. A method for providing an application using a computer that performs actions, comprising: when a multi-size type is provided during compilation of the application into a machine code version of the application, performing actions, including: employing architecture information of a target computer to identify one or more data types associated with the target computer that correspond to the multi-sized type; employing parameters of one or more native code calls associated with an intermediate language code call to identify matching of the one or more native code calls with the one or more data types; providing a machine code version of the intermediate language code call that corresponds to the architecture information and also corresponds to the one or more native code calls; when the target computer provides for just-in-time compiling, employing a run time engine to execute, on the target computer, a machine code version of the intermediate language code call having one or more values that correspond to the multi-size type and the one or more data types, wherein the one or more native code calls are executed using the one or more data types that correspond to the architecture information; and when the target computer provides for disabling just-in-time compiling, inserting the machine code version of the intermediate language code call in the machine code version of the application. 4. The method of claim 1 , wherein compilation of the application into the machine code version of the application, further comprises encountering the multi-size type during compilation of an intermediate language version of the application into the machine code version of the application, wherein the intermediate language code is based on one or more source code files.
| 0.770885 |
19. The method as claimed in claim 18 , wherein at least one bit of the representation is a data bit and wherein at least one bit of the representation is not a data bit, and wherein the data bits of the standard and complement versions of each character are the same, and wherein at least one bit of each of the standard characters differs from the corresponding bit of its complement version.
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19. The method as claimed in claim 18 , wherein at least one bit of the representation is a data bit and wherein at least one bit of the representation is not a data bit, and wherein the data bits of the standard and complement versions of each character are the same, and wherein at least one bit of each of the standard characters differs from the corresponding bit of its complement version. 21. The method as claimed in claim 19 , wherein the bit(s) other than the data bits of the characters are isolated to check the taint status of the characters.
| 0.902095 |
8. A system comprising: one or more computers programmed to perform the following operations: receiving an initial message of a first user in a first language from a first chat client system; querying a data store for a first corresponding message in a second language, the first corresponding message being based on the initial message in the first language; determining that the data store does not include the first corresponding message and, based thereon: selecting an order for a plurality of different transformation modules based on the initial message, wherein each transformation module accepts as respective input a portion of a message and provides as respective output a transformed version of the respective input in the first language, and wherein the order is selected based on at least one of (i) precedence, (ii) a priority of transformation operations, (iii) a transformation operation that is most likely to generate a transformed message suitable for translation, and (iv) a transformation operation that generates a most formal transformed message; for each of one or more portions of the initial message, providing the portion as input to a first transformation module in the order and providing the respective output of each transformation module as the respective input to a following transformation module in the order; selecting the respective output of the last transformation module in the order as the transformed message in the first language; and querying the data store for a second corresponding message in the second language, the second corresponding message being based on the transformed message in the first language.
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8. A system comprising: one or more computers programmed to perform the following operations: receiving an initial message of a first user in a first language from a first chat client system; querying a data store for a first corresponding message in a second language, the first corresponding message being based on the initial message in the first language; determining that the data store does not include the first corresponding message and, based thereon: selecting an order for a plurality of different transformation modules based on the initial message, wherein each transformation module accepts as respective input a portion of a message and provides as respective output a transformed version of the respective input in the first language, and wherein the order is selected based on at least one of (i) precedence, (ii) a priority of transformation operations, (iii) a transformation operation that is most likely to generate a transformed message suitable for translation, and (iv) a transformation operation that generates a most formal transformed message; for each of one or more portions of the initial message, providing the portion as input to a first transformation module in the order and providing the respective output of each transformation module as the respective input to a following transformation module in the order; selecting the respective output of the last transformation module in the order as the transformed message in the first language; and querying the data store for a second corresponding message in the second language, the second corresponding message being based on the transformed message in the first language. 18. The system of claim 8 , wherein the plurality of different transformation modules utilizes statistical machine translation.
| 0.706037 |
1. A computer-implemented method comprising using at least one processor to: search a set of documents to identify a key phrase, the identifying comprising clarifying a term found in at least one of the set of documents by extracting log data related to the term from a corresponding session log of a user interaction with a service or product, the clarifying relating the term to the key phrase; select a first subset of documents from the set of documents, based on each document in the first subset of documents including the key phrase; build a syntactic tree of a sentence within a document from the first subset of documents, the syntactic tree identifying a relationship between parts of the sentence; build a lexical pattern including a plurality of tokens, the plurality of tokens including a key phrase token, a polarity token, and a special token that indicates a relationship between the key phrase token and the polarity token, the special token being separate and distinct from the key phrase token and the polarity token; and determine that the document conveys an opinion by matching the lexical pattern including the plurality of tokens to the syntactic tree.
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1. A computer-implemented method comprising using at least one processor to: search a set of documents to identify a key phrase, the identifying comprising clarifying a term found in at least one of the set of documents by extracting log data related to the term from a corresponding session log of a user interaction with a service or product, the clarifying relating the term to the key phrase; select a first subset of documents from the set of documents, based on each document in the first subset of documents including the key phrase; build a syntactic tree of a sentence within a document from the first subset of documents, the syntactic tree identifying a relationship between parts of the sentence; build a lexical pattern including a plurality of tokens, the plurality of tokens including a key phrase token, a polarity token, and a special token that indicates a relationship between the key phrase token and the polarity token, the special token being separate and distinct from the key phrase token and the polarity token; and determine that the document conveys an opinion by matching the lexical pattern including the plurality of tokens to the syntactic tree. 2. The method of claim 1 , wherein the set of documents are from an electronic community forum related to a product available through an electronic transaction system.
| 0.655747 |
16. The system of claim 15 , wherein the word images each have corresponding word features, and wherein the stored instructions further configure the system to: assign a value to each word feature in a first of the at least two word images and to its corresponding word feature in a second of the at least two word images; determine the distance between each word feature in the first of the at least two word images and its corresponding word feature in the second of the at least two word images, based on the values assigned to those word features; establish, in advance, a feature weight for each of the word features; and sum together the determined distance for all of the corresponding word features, with each determined distance weighted according to the feature weight established for that word feature.
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16. The system of claim 15 , wherein the word images each have corresponding word features, and wherein the stored instructions further configure the system to: assign a value to each word feature in a first of the at least two word images and to its corresponding word feature in a second of the at least two word images; determine the distance between each word feature in the first of the at least two word images and its corresponding word feature in the second of the at least two word images, based on the values assigned to those word features; establish, in advance, a feature weight for each of the word features; and sum together the determined distance for all of the corresponding word features, with each determined distance weighted according to the feature weight established for that word feature. 18. The system of claim 16 , wherein the determined distance is calculated based on the dimensional nature of the value, and wherein for word features having a value represented by sequence of values and for word features having a value represented by multi-dimensional values, the determined distance is calculated using dynamic time warping.
| 0.659075 |
1. A risk assessment method comprising: receiving, by an inference engine within a computing system, first sensor cohort data associated with a first cohort, said first cohort located within an aircraft; receiving, by said inference engine, first group technology inferences associated with said first cohort; generating, by said inference engine, first risk cohort inferences, said generating said first risk cohort inferences based on said first group technology inferences and said first sensor cohort data; receiving, by said inference engine, first inference data generated by said inference engine, said first inference data comprising a first plurality of inferences associated with said first cohort and a security perimeter area surrounding an airport; receiving, by said inference engine, second inference data generated by said inference engine, said second inference data comprising a second of plurality of inferences associated with said first cohort and a pre/post security area within said airport; receiving, by said inference engine, third inference data generated by said inference engine, said third inference data comprising a third of plurality of inferences associated with said first cohort and a gate area within said airport; receiving, by said inference engine, fourth inference data generated by said inference engine, said fourth inference data comprising a fourth of plurality of inferences associated with said first cohort and said aircraft; generating, by said inference engine, fifth inference data, said fifth inference data comprising a fifth plurality of inferences associated with said first cohort and said aircraft, wherein said generating said fifth inference data is based on said first risk cohort inferences, said first inference data, said second inference data, said third inference data, and said fourth inference data; generating, by said inference engine based on said fifth inference data, a first associated risk level score for said first cohort; and storing, by said computing system, said fifth inference data and said first associated risk level score.
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1. A risk assessment method comprising: receiving, by an inference engine within a computing system, first sensor cohort data associated with a first cohort, said first cohort located within an aircraft; receiving, by said inference engine, first group technology inferences associated with said first cohort; generating, by said inference engine, first risk cohort inferences, said generating said first risk cohort inferences based on said first group technology inferences and said first sensor cohort data; receiving, by said inference engine, first inference data generated by said inference engine, said first inference data comprising a first plurality of inferences associated with said first cohort and a security perimeter area surrounding an airport; receiving, by said inference engine, second inference data generated by said inference engine, said second inference data comprising a second of plurality of inferences associated with said first cohort and a pre/post security area within said airport; receiving, by said inference engine, third inference data generated by said inference engine, said third inference data comprising a third of plurality of inferences associated with said first cohort and a gate area within said airport; receiving, by said inference engine, fourth inference data generated by said inference engine, said fourth inference data comprising a fourth of plurality of inferences associated with said first cohort and said aircraft; generating, by said inference engine, fifth inference data, said fifth inference data comprising a fifth plurality of inferences associated with said first cohort and said aircraft, wherein said generating said fifth inference data is based on said first risk cohort inferences, said first inference data, said second inference data, said third inference data, and said fourth inference data; generating, by said inference engine based on said fifth inference data, a first associated risk level score for said first cohort; and storing, by said computing system, said fifth inference data and said first associated risk level score. 6. The method of claim 1 , further comprising: presenting, by said computing system, said fifth inference data and said first associated risk level score.
| 0.750982 |
6. The method of claim 3 wherein the highlighting from one or more identifiable segments is based on one or more predefined or machine-computed criteria, and highlighting from the plurality of users is synthesized based on one of the one or more predefined or machine-computer criteria.
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6. The method of claim 3 wherein the highlighting from one or more identifiable segments is based on one or more predefined or machine-computed criteria, and highlighting from the plurality of users is synthesized based on one of the one or more predefined or machine-computer criteria. 8. The method of claim 6 , wherein distinct measurable values in a range are provided for association with one of the one or more of said predefined or machine-computed criteria and highlighting by a user of an identifiable segment is associated with a measurable value in the range, and wherein said computational rules or preset algorithm for combining highlighting include computational rules for combining highlighting associated with differentiated values in said range.
| 0.849178 |
11. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, the computer-program product including instructions operable to cause a processor to perform operations comprising: receive, at a portal, and from a requesting device via a network, a first request to provide objects to the requesting device to enable the requesting device to generate a visualization of a first directed acyclic graph (DAG) of multiple task routines of a first job flow of a first analysis routine, wherein: the portal is provided on the network to control access to at least one federated area by the requesting device via the network; the at least one federated area is maintained within one or more storage devices to store a plurality of data objects, a plurality of task routines and a plurality of job flow definitions; each task routine of the plurality of task routines comprises comments that specify input and output (I/O) parameters that comprise at least one characteristic of an input to the task routine and at least one characteristic of an output generated during execution of the task routine; the I/O parameters of the comments of a subset of task routines of the plurality of task routines comprises an identifier of at least one data object of the plurality of data objects; each task routine of the multiple task routines comprises executable instructions to perform a task when executed; and each job flow definition specifies multiple tasks of a job flow of an analysis routine to be performed by task routines of the plurality of task routines; retrieve each task routine of the multiple task routines from the at least one federated area; parse the comments of each task routine of the multiple task routines to identify and retrieve the specification of the I/O parameters of the task routine from the comments; for each task routine of the multiple task routines, generate a corresponding macro of multiple macros that comprises an indication of the I/O parameters of the task routine; transmit the multiple macros to the requesting device via the network to enable the requesting device to generate, from the multiple macros, the visualization of the first DAG to include a visual representation of each task routine of the multiple task routines, and to enable the requesting device to visually output the visualization for display, wherein: each representation of a task routine comprises: a task graph object comprising an identifier of the task routine; at least one input data graph object that represents an input to the task routine, that is visually connected to the task graph object in the visualization, and that comprises a visual indication of the at least one characteristic of the input; and at least one output data graph object that represents an output of the task routine, that is visually connected to the task graph object in the visualization, and that comprises an indication of the at least one characteristic of the output; and to generate the visualization, the requesting device is to: compare identifiers of data objects in the I/O parameters specified in the comments among the multiple task routines to identify each dependency between an output of one task routine and an input of another task routine; and for each dependency identified between an output and an input of a pair of task routines of the multiple task routines, visually present a dependency marker that visually links the visual representations of the pair of task routines in the visualization; receive a second request from the requesting device to store a second DAG based on the visualization as edited in response to at least one command, wherein: the second DAG depicts a reuse of a portion of the first job flow depicted in the first DAG to define at least a portion of a second job flow of a second analysis routine derived from the first analysis routine; and at least a subset of task routines to be executed in a performance of the first job flow, as indicated in the first DAG, are to be executed in a performance of the second job flow, as indicated in the second DAG; determine whether each task routine identified in the second DAG is stored within the at least one federated area or is included in the second request; determine whether each task data object identified in the second DAG is stored within the at least one federated area or is included in the second request; and in response to a determination that each task routine identified in the second DAG and each data object identified in the second DAG is stored within the at least one federated area or is included in the second request, store the second DAG as a second job flow definition among the plurality of job flow definitions.
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11. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, the computer-program product including instructions operable to cause a processor to perform operations comprising: receive, at a portal, and from a requesting device via a network, a first request to provide objects to the requesting device to enable the requesting device to generate a visualization of a first directed acyclic graph (DAG) of multiple task routines of a first job flow of a first analysis routine, wherein: the portal is provided on the network to control access to at least one federated area by the requesting device via the network; the at least one federated area is maintained within one or more storage devices to store a plurality of data objects, a plurality of task routines and a plurality of job flow definitions; each task routine of the plurality of task routines comprises comments that specify input and output (I/O) parameters that comprise at least one characteristic of an input to the task routine and at least one characteristic of an output generated during execution of the task routine; the I/O parameters of the comments of a subset of task routines of the plurality of task routines comprises an identifier of at least one data object of the plurality of data objects; each task routine of the multiple task routines comprises executable instructions to perform a task when executed; and each job flow definition specifies multiple tasks of a job flow of an analysis routine to be performed by task routines of the plurality of task routines; retrieve each task routine of the multiple task routines from the at least one federated area; parse the comments of each task routine of the multiple task routines to identify and retrieve the specification of the I/O parameters of the task routine from the comments; for each task routine of the multiple task routines, generate a corresponding macro of multiple macros that comprises an indication of the I/O parameters of the task routine; transmit the multiple macros to the requesting device via the network to enable the requesting device to generate, from the multiple macros, the visualization of the first DAG to include a visual representation of each task routine of the multiple task routines, and to enable the requesting device to visually output the visualization for display, wherein: each representation of a task routine comprises: a task graph object comprising an identifier of the task routine; at least one input data graph object that represents an input to the task routine, that is visually connected to the task graph object in the visualization, and that comprises a visual indication of the at least one characteristic of the input; and at least one output data graph object that represents an output of the task routine, that is visually connected to the task graph object in the visualization, and that comprises an indication of the at least one characteristic of the output; and to generate the visualization, the requesting device is to: compare identifiers of data objects in the I/O parameters specified in the comments among the multiple task routines to identify each dependency between an output of one task routine and an input of another task routine; and for each dependency identified between an output and an input of a pair of task routines of the multiple task routines, visually present a dependency marker that visually links the visual representations of the pair of task routines in the visualization; receive a second request from the requesting device to store a second DAG based on the visualization as edited in response to at least one command, wherein: the second DAG depicts a reuse of a portion of the first job flow depicted in the first DAG to define at least a portion of a second job flow of a second analysis routine derived from the first analysis routine; and at least a subset of task routines to be executed in a performance of the first job flow, as indicated in the first DAG, are to be executed in a performance of the second job flow, as indicated in the second DAG; determine whether each task routine identified in the second DAG is stored within the at least one federated area or is included in the second request; determine whether each task data object identified in the second DAG is stored within the at least one federated area or is included in the second request; and in response to a determination that each task routine identified in the second DAG and each data object identified in the second DAG is stored within the at least one federated area or is included in the second request, store the second DAG as a second job flow definition among the plurality of job flow definitions. 17. The computer-program product of claim 11 , wherein: the at least one federated area comprises at least one linear hierarchy of multiple federated areas; the multiple task routines are distributed among the multiple federated areas; and the processor is caused to augment each macro with an identifier of the federated area of the multiple federated areas in which the corresponding task routine is stored to enable the requesting device to visually present, at each visual representation of one of the multiple task routines, the identifier of the federated area of the multiple federated areas in which the corresponding task routine is stored, wherein the identifier of the federated area comprises a universal resource locator (URL).
| 0.54862 |
1. A method of searching and retrieving from a database, comprising the steps of: establishing a communication link between a requestor and a service provider, and the communication link originating from the requestor; receiving requested database record information from the requestor, requestor inputting a search query that includes non-sequential first and last elements of a plurality of different terms in a single search field of a requested database record, wherein first and last elements are each a single alphanumeric character, and the search query omits a plurality of elements of the search field positioned between the first and last elements; and executing the search query; selecting at least one database record that matches the search query and supplying the requestor with information from the selected database record.
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1. A method of searching and retrieving from a database, comprising the steps of: establishing a communication link between a requestor and a service provider, and the communication link originating from the requestor; receiving requested database record information from the requestor, requestor inputting a search query that includes non-sequential first and last elements of a plurality of different terms in a single search field of a requested database record, wherein first and last elements are each a single alphanumeric character, and the search query omits a plurality of elements of the search field positioned between the first and last elements; and executing the search query; selecting at least one database record that matches the search query and supplying the requestor with information from the selected database record. 5. The method of claim 1 wherein at least one of the first and last elements is one of a format and a phoneme.
| 0.685253 |
9. The method of claim 1 : the first zoom level comprising a shallow zoom level regarding the visual element; and the second zoom level comprising a deep zoom level regarding the visual element.
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9. The method of claim 1 : the first zoom level comprising a shallow zoom level regarding the visual element; and the second zoom level comprising a deep zoom level regarding the visual element. 11. The method of claim 9 : the first zoom level comprising a first data set associated with the first topic, and the second zoom level comprising the first data set supplemented with at least one supplemental data item that is also associated with the first topic.
| 0.896852 |
10. The method of claim 7 , wherein generating an article summary comprises: 1) determining a maximal marginal relevance score for each sentence in the potential candidate sentences category based at least in part on the preliminary score for that sentence, the title of the article, a vector space of the combination of the sentences in the potential candidate sentences category and the sentences in the weakly rejected sentences category, and a weighting constant; 2) adding the sentence with the highest maximal marginal relevance score to the article summary; 3) removing the sentence with the highest maximal marginal relevance score from the potential candidate sentences category; and 4) repeating steps 1-3 until the number of characters in the article summary reaches a predetermined threshold.
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10. The method of claim 7 , wherein generating an article summary comprises: 1) determining a maximal marginal relevance score for each sentence in the potential candidate sentences category based at least in part on the preliminary score for that sentence, the title of the article, a vector space of the combination of the sentences in the potential candidate sentences category and the sentences in the weakly rejected sentences category, and a weighting constant; 2) adding the sentence with the highest maximal marginal relevance score to the article summary; 3) removing the sentence with the highest maximal marginal relevance score from the potential candidate sentences category; and 4) repeating steps 1-3 until the number of characters in the article summary reaches a predetermined threshold. 12. The method of claim 10 , further comprising categorizing each article summary into the same subject matter category as the corresponding article.
| 0.944196 |
1. A method of automatically training an optical character recognition (OCR) classification engine to recognize script character segments, the method comprising: receiving a plurality of cursive script words and a ground truth corresponding to each cursive script word; performing an initial segmentation of each cursive script word into a number of character segments based on a number of characters indicated in the ground truth corresponding to each cursive script word; for each character segment in the number of character segments: comparing the ground truth of the character segment with ground truths of pre-saved character segments to find a matching ground truth; when the ground truth of the character segment matches a ground truth of one of the pre-saved character segments, then determining the character segment and the pre-saved character segment to be similar; refining a plurality of horizontal boundaries and a plurality of vertical boundaries of the character segment based on the similar pre-saved character segment to define a shape of the character segment and to eliminate a noise; and adding the character segment to the pre-saved character segments associated with the matching ground truth for subsequent recognition of an instance of the character segment.
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1. A method of automatically training an optical character recognition (OCR) classification engine to recognize script character segments, the method comprising: receiving a plurality of cursive script words and a ground truth corresponding to each cursive script word; performing an initial segmentation of each cursive script word into a number of character segments based on a number of characters indicated in the ground truth corresponding to each cursive script word; for each character segment in the number of character segments: comparing the ground truth of the character segment with ground truths of pre-saved character segments to find a matching ground truth; when the ground truth of the character segment matches a ground truth of one of the pre-saved character segments, then determining the character segment and the pre-saved character segment to be similar; refining a plurality of horizontal boundaries and a plurality of vertical boundaries of the character segment based on the similar pre-saved character segment to define a shape of the character segment and to eliminate a noise; and adding the character segment to the pre-saved character segments associated with the matching ground truth for subsequent recognition of an instance of the character segment. 2. The method of claim 1 , wherein the plurality of cursive script words is a line of text.
| 0.601204 |
5. The search result ranking method as described in claim 1 , wherein the objects subjected to user actions are objects that were selected from among the search results.
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5. The search result ranking method as described in claim 1 , wherein the objects subjected to user actions are objects that were selected from among the search results. 6. The search result ranking method as described in claim 5 , further comprising: classifying objects selected from among the search results with the selected set, wherein the adjusting of the rank of objects that are to be displayed or to be ranked, and whose attribute characteristics comply with the reference norms comprises: calculating a commonality level of each attribute characteristic in the selected set based on the user action information on objects in the selected set; selecting attribute characteristics whose first or second commonality level is greater than a preset threshold value as reference norms; and raising the rank of objects that are to be displayed or to be ranked and whose attribute characteristics comply with the reference norms.
| 0.900496 |
15. The method of claim 1 , wherein the sub-step of performing character recognition on the segmented characters is based on a background skeletal graph.
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15. The method of claim 1 , wherein the sub-step of performing character recognition on the segmented characters is based on a background skeletal graph. 16. The method of claim 15 , wherein the sub-step of performing character segmentation on the segmented words includes the sub-steps of: performing pre-processing on the segmented characters; computing a background skeleton; computing the skeletal graph from the background skeleton; removing curves and short branches from the skeletal graph; connecting each branch corresponding to an end-point of a downward branch that goes below a baseline of the image to a nearest point in the skeletal graph that is below the baseline of the image; connecting each branch corresponding to an end-point of an upward branch that goes above the baseline of the image to a nearest point in the skeletal graph that is above the baseline of the image; removing all remaining branches of the skeletal graph; providing the segmented characters.
| 0.656716 |
12. The method of claim 11 , wherein identifying program content further comprises using user profile information.
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12. The method of claim 11 , wherein identifying program content further comprises using user profile information. 13. The method of claim 12 , wherein the user profile information includes one or more of user demographic information, user program viewing history, and user-provided information.
| 0.961349 |
3. The method of claim 1 wherein the common phrase component of the spoken phrase comprises two or more sub-phrases and the verifying further includes: calculating a respective score for each sub-phrase of the common phrase component, the respective scores indicating a level of correspondence between the two or more sub-phrases and the one or more stored voice prints; and verifying the user using the respective scores.
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3. The method of claim 1 wherein the common phrase component of the spoken phrase comprises two or more sub-phrases and the verifying further includes: calculating a respective score for each sub-phrase of the common phrase component, the respective scores indicating a level of correspondence between the two or more sub-phrases and the one or more stored voice prints; and verifying the user using the respective scores. 4. The method of claim 3 wherein verifying the user using the respective scores comprises: averaging the respective scores; and comparing the average against a predetermined threshold.
| 0.895914 |
1. A computer implemented method for performing adaptive optical character recognition on a document with distorted characters, the method comprising: providing a group of images of candidate characters; receiving a document in an image format; segmenting the document so as to provide a sub-image of a segmented character; and for one or more of the candidate characters: performing a distortion-correction transformation on the segmented character, so as to modify the segmented character in the sub-image into a transformed character more closely resembling the candidate character; comparing the transformed segmented character to the candidate character so as to calculate a comparison score; analyzing the distortion-correction transformation so as to assign the transformation a distortion score; and determining whether to identify the segmented character with the candidate character, responsively to both the comparison score and the distortion score.
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1. A computer implemented method for performing adaptive optical character recognition on a document with distorted characters, the method comprising: providing a group of images of candidate characters; receiving a document in an image format; segmenting the document so as to provide a sub-image of a segmented character; and for one or more of the candidate characters: performing a distortion-correction transformation on the segmented character, so as to modify the segmented character in the sub-image into a transformed character more closely resembling the candidate character; comparing the transformed segmented character to the candidate character so as to calculate a comparison score; analyzing the distortion-correction transformation so as to assign the transformation a distortion score; and determining whether to identify the segmented character with the candidate character, responsively to both the comparison score and the distortion score. 2. A method as claimed in claim 1 , wherein the transformation comprises a vector field that describes a change in shape between the segmented character and the candidate character and the distortion score comprises a divergence of the vector field.
| 0.602337 |
7. The method of claim 1 , wherein a quantitative value identified in the report for a particular predefined business-related category comprises a quantity of collected user comments assigned to a particular rating.
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7. The method of claim 1 , wherein a quantitative value identified in the report for a particular predefined business-related category comprises a quantity of collected user comments assigned to a particular rating. 9. The method of claim 7 , wherein the plurality of available ratings comprises positive, negative, and neutral ratings.
| 0.947219 |
11. The system of claim 8 , further comprising program instructions, stored on the computer-readable storage device for execution by the processor, to send a collaboration invitation to at least one candidate user in the set of candidate users.
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11. The system of claim 8 , further comprising program instructions, stored on the computer-readable storage device for execution by the processor, to send a collaboration invitation to at least one candidate user in the set of candidate users. 12. The system of claim 11 , further comprising program instructions, stored on the computer-readable storage device for execution by the processor, to connect the querying user and the least one candidate user in response to the sending of the set of collaboration invites.
| 0.91996 |
1. A virtual machine for executing a program, comprising: an instruction executor for executing instructions from the program using a computer, wherein: the instructions from the program have been generated in an intermediate language, by a compiler, to cause processing of an execution sequence according to a specification of a model, the model specification encoded using a model notation that is distinct from the intermediate notation; the instructions from the program are encoded in a markup language notation by the compiler and are selected by the compiler from allowable instructions of the intermediate language, the markup language notation being distinct from the intermediate language; and the allowable instructions of the intermediate language comprise: an event instruction for receiving an inbound event; an assignment instruction for assigning a value; a branch instruction for conditional transfer to a different one of the instructions; an emit instruction for specifying that an outbound event is to be emitted; a terminate instruction for specifying that a current execution context object is to be terminated; and a fan-out instruction for at least one of specifying event correlation and enabling a context switch, the context switch causing a particular execution context object to be used as the current execution context object.
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1. A virtual machine for executing a program, comprising: an instruction executor for executing instructions from the program using a computer, wherein: the instructions from the program have been generated in an intermediate language, by a compiler, to cause processing of an execution sequence according to a specification of a model, the model specification encoded using a model notation that is distinct from the intermediate notation; the instructions from the program are encoded in a markup language notation by the compiler and are selected by the compiler from allowable instructions of the intermediate language, the markup language notation being distinct from the intermediate language; and the allowable instructions of the intermediate language comprise: an event instruction for receiving an inbound event; an assignment instruction for assigning a value; a branch instruction for conditional transfer to a different one of the instructions; an emit instruction for specifying that an outbound event is to be emitted; a terminate instruction for specifying that a current execution context object is to be terminated; and a fan-out instruction for at least one of specifying event correlation and enabling a context switch, the context switch causing a particular execution context object to be used as the current execution context object. 5. The virtual machine according to claim 1 , wherein the executing of the event instruction further comprises: executing the event instruction to receive a particular inbound event according to the specification of the model; locating a fan-out instruction associated with the event instruction; executing the located fan-out instruction to determine, using correlation predicate information associated with the located fan-out instruction, zero or more execution context objects to use for processing the particular inbound event; and directing the particular inbound event to each determined execution context object, if any, for the processing of the particular inbound event therein.
| 0.529412 |
19. The method of claim 18 , wherein the screen scraping further comprises: extracting dates from XHTML for a page of the weblog; sorting the extracted dates into ordered lists, each ordered list corresponding to a relative XPath; filtering the ordered lists according to a set of heuristics to determine which of the lists corresponds to actual entry dates of the weblog posts; segmenting the weblog into entries, using dates from the determined list as markers for the entries; segmenting each weblog entry into a post using post titles markers; and identifying a permalink and author for each post.
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19. The method of claim 18 , wherein the screen scraping further comprises: extracting dates from XHTML for a page of the weblog; sorting the extracted dates into ordered lists, each ordered list corresponding to a relative XPath; filtering the ordered lists according to a set of heuristics to determine which of the lists corresponds to actual entry dates of the weblog posts; segmenting the weblog into entries, using dates from the determined list as markers for the entries; segmenting each weblog entry into a post using post titles markers; and identifying a permalink and author for each post. 26. The method of claim 19 , wherein identifying the permalink and author further comprises identifying patterns indicative of an author byline.
| 0.773504 |
1. A computer-implementable method for performing cognitive computing operations comprising: receiving streams of data from a plurality of data sources; processing the streams of data from the plurality of data sources, the processing the streams of data from the plurality of data sources performing data enriching for incorporation into a cognitive graph, the data enriching performing sentiment analysis, geotagging and entity detection operations on the streams of data from the plurality of data sources, the processing being performed by a cognitive inference and learning system, the cognitive inference and learning system executing on a hardware processor of an information processing system and interacting with the plurality of data sources, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising a cognitive engine, the cognitive engine processing the streams of data from the plurality of data sources; incorporating enriched data resulting from the performing of the data enriching into the cognitive graph as nodes within the cognitive graph; defining a cognitive persona within the cognitive graph, the cognitive persona corresponding to an archetype user model, the defining comprising associating attributes with respective nodes of a set of nodes in the cognitive graph; associating a user with the cognitive persona; and, defining a cognitive profile within the cognitive graph, the cognitive profile comprising an instance of the cognitive persona that references personal data associated with the user, the personal data associated with the user being stored as at least one node within the cognitive graph; associating the user with the cognitive profile; and, performing a cognitive computing operation based upon the cognitive profile associated with the user, the cognitive computing operation comprising at least one of performing a spatial navigation operation, a machine vision operation and a pattern recognition operation on at least some of the streams of data from the plurality of data sources.
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1. A computer-implementable method for performing cognitive computing operations comprising: receiving streams of data from a plurality of data sources; processing the streams of data from the plurality of data sources, the processing the streams of data from the plurality of data sources performing data enriching for incorporation into a cognitive graph, the data enriching performing sentiment analysis, geotagging and entity detection operations on the streams of data from the plurality of data sources, the processing being performed by a cognitive inference and learning system, the cognitive inference and learning system executing on a hardware processor of an information processing system and interacting with the plurality of data sources, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising a cognitive engine, the cognitive engine processing the streams of data from the plurality of data sources; incorporating enriched data resulting from the performing of the data enriching into the cognitive graph as nodes within the cognitive graph; defining a cognitive persona within the cognitive graph, the cognitive persona corresponding to an archetype user model, the defining comprising associating attributes with respective nodes of a set of nodes in the cognitive graph; associating a user with the cognitive persona; and, defining a cognitive profile within the cognitive graph, the cognitive profile comprising an instance of the cognitive persona that references personal data associated with the user, the personal data associated with the user being stored as at least one node within the cognitive graph; associating the user with the cognitive profile; and, performing a cognitive computing operation based upon the cognitive profile associated with the user, the cognitive computing operation comprising at least one of performing a spatial navigation operation, a machine vision operation and a pattern recognition operation on at least some of the streams of data from the plurality of data sources. 6. The method of claim 1 , further comprising: receiving user provided personal information; and, associating the user with the cognitive profile based upon user provided personal information.
| 0.508597 |
32. The method of claim 31 , wherein the step of identifying a text summarization segment further includes: identifying a plurality of different document segments of the first document; calculating a respective sum for each document segment to create a plurality of sums, each sum being based on the query token weights and on the occurrences of the corresponding query tokens in a respective document segment; and identifying a high-scoring document segment based on the plurality of sums.
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32. The method of claim 31 , wherein the step of identifying a text summarization segment further includes: identifying a plurality of different document segments of the first document; calculating a respective sum for each document segment to create a plurality of sums, each sum being based on the query token weights and on the occurrences of the corresponding query tokens in a respective document segment; and identifying a high-scoring document segment based on the plurality of sums. 33. The method of claim 32 , further comprising highlighting one or more terms related to the query in the returned text summarization segment.
| 0.916567 |
1. A method of providing video information in response to text based searches comprising: receiving, at a server, a user submission of identifier information with a video file for storage in an electronic storage device, wherein the identifier information comprises a text description of the video file; storing, in the electronic storage device, the identifier information; generating an identifier of the video file based on the identifier information, wherein the generated identifier comprises an author and an owner of the video file; storing the identifier in the electronic storage device; receiving a user input of search criteria matching the identifier; and in response to receiving the user input: determining a location at which the video file is accessible; providing, in a results page, a user-selectable link to the video file based on the determined location; retrieving at least some of the identifier information from the electronic storage device; and providing, in the results page, the retrieved identifier information.
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1. A method of providing video information in response to text based searches comprising: receiving, at a server, a user submission of identifier information with a video file for storage in an electronic storage device, wherein the identifier information comprises a text description of the video file; storing, in the electronic storage device, the identifier information; generating an identifier of the video file based on the identifier information, wherein the generated identifier comprises an author and an owner of the video file; storing the identifier in the electronic storage device; receiving a user input of search criteria matching the identifier; and in response to receiving the user input: determining a location at which the video file is accessible; providing, in a results page, a user-selectable link to the video file based on the determined location; retrieving at least some of the identifier information from the electronic storage device; and providing, in the results page, the retrieved identifier information. 4. The method of claim 1 , wherein the results page is provided through an Internet interface.
| 0.901247 |
17. A computer readable medium encoded with computer executable instructions for detecting a plurality of anatomical landmarks in an image, the computer executable instructions defining steps comprising: detecting a first landmark of the plurality of anatomical landmarks in the image using marginal space learning (MSL); estimating locations of remaining landmarks of the plurality of anatomical landmarks in the image based on the detected first landmark using a learned geometric model relating the plurality of anatomical landmarks; and detecting each of said remaining landmarks using MSL in a portion of the image constrained based on the estimated location of each of said remaining landmarks.
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17. A computer readable medium encoded with computer executable instructions for detecting a plurality of anatomical landmarks in an image, the computer executable instructions defining steps comprising: detecting a first landmark of the plurality of anatomical landmarks in the image using marginal space learning (MSL); estimating locations of remaining landmarks of the plurality of anatomical landmarks in the image based on the detected first landmark using a learned geometric model relating the plurality of anatomical landmarks; and detecting each of said remaining landmarks using MSL in a portion of the image constrained based on the estimated location of each of said remaining landmarks. 18. The computer readable medium of claim 17 , wherein the computer executable instructions defining the step of detecting a first landmark of the plurality of anatomical landmarks in the image using MSL comprise computer executable instructions defining the steps of: detecting position candidates in the image for the first landmark using a trained position classifier; generating position-orientation hypotheses from said position candidates; detecting position-orientation candidates from said position-orientation hypotheses using a trained position-orientation classifier; generating similarity transformation hypotheses from said position-orientation candidates; and detecting at least one similarity transformation candidate from said similarity transformation hypotheses using a trained similarity transformation classifier.
| 0.557343 |
12. A non-transitory computer readable medium including a sequence of instructions stored thereon for causing a computer to execute a method, comprising: generating a search term entry area operable to allow a user to enter text as a search term; generating a mapping area operable to display data elements on a map, wherein the data elements are representative of searchable data in a database; generating a search result area operable to display a result of a search query; and generating a search criteria tree area operable to allow a user to enter a new search query of the searchable data in response to the user's selection of one or more of the search term from the search term entry area, the data elements from the mapping area, and the result from the search result area, wherein the search criteria tree area enables the user to select the search term from the search term entry area, the data elements from the mapping area, and the result from the search result area for the new search query, and wherein the search term entry area, map area, search results area, and search criteria tree area are displayed together in a single window on a graphical user interface.
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12. A non-transitory computer readable medium including a sequence of instructions stored thereon for causing a computer to execute a method, comprising: generating a search term entry area operable to allow a user to enter text as a search term; generating a mapping area operable to display data elements on a map, wherein the data elements are representative of searchable data in a database; generating a search result area operable to display a result of a search query; and generating a search criteria tree area operable to allow a user to enter a new search query of the searchable data in response to the user's selection of one or more of the search term from the search term entry area, the data elements from the mapping area, and the result from the search result area, wherein the search criteria tree area enables the user to select the search term from the search term entry area, the data elements from the mapping area, and the result from the search result area for the new search query, and wherein the search term entry area, map area, search results area, and search criteria tree area are displayed together in a single window on a graphical user interface. 16. The non-transitory computer readable medium of claim 12 , wherein selection of one or more of the data elements and result is achieved by dragging and dropping the one or more data elements and result to the search criteria tree area using an input device.
| 0.661645 |
1. A method to enable improved analysis and use of sociological data, the method comprising: identifying causal relationships between a plurality of documents; identifying a plurality of characteristics of a communication, including a modality used, actors involved, proximate events of relevance, and a tone used by an actor in the communication; and enabling a user to query based on available characteristics.
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1. A method to enable improved analysis and use of sociological data, the method comprising: identifying causal relationships between a plurality of documents; identifying a plurality of characteristics of a communication, including a modality used, actors involved, proximate events of relevance, and a tone used by an actor in the communication; and enabling a user to query based on available characteristics. 9. The method of claim 1 , further comprising: identifying, for a particular actor, divergence in tones in communications with different actors on a particular topic within a given timeframe.
| 0.617504 |
1. A method for determining age categories of people, comprising the following steps of: a) annotating a facial image database according to the demographics classes of the individual face, b) training a plurality of learning machines so that each learning machine outputs auxiliary demographics class information and age information of any given facial image, c) detecting and tracking a facial image from the input image frame, d) processing said facial image to extract image features, and e) processing said image features obtained from said facial image using classification techniques for determining age or age categories, whereby the age classes can be any partition based on age in multiple groups, wherein the method further comprises a step of determining the target outputs of the plurality of learning machines so that each learning machine maps a first input data, whose facial images belong to a first auxiliary demographics class, to first vector-valued points on a manifold in the space of facial images, whereas each learning machine maps a second input data, whose facial images do not belong to a first auxiliary demographics class, to second vector-valued points away from the manifold.
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1. A method for determining age categories of people, comprising the following steps of: a) annotating a facial image database according to the demographics classes of the individual face, b) training a plurality of learning machines so that each learning machine outputs auxiliary demographics class information and age information of any given facial image, c) detecting and tracking a facial image from the input image frame, d) processing said facial image to extract image features, and e) processing said image features obtained from said facial image using classification techniques for determining age or age categories, whereby the age classes can be any partition based on age in multiple groups, wherein the method further comprises a step of determining the target outputs of the plurality of learning machines so that each learning machine maps a first input data, whose facial images belong to a first auxiliary demographics class, to first vector-valued points on a manifold in the space of facial images, whereas each learning machine maps a second input data, whose facial images do not belong to a first auxiliary demographics class, to second vector-valued points away from the manifold. 4. The method according to claim 1 , wherein the method further comprises a step of setting up a plurality of learning machines so that each learning machine represents an auxiliary demographics class, whereby the auxiliary demographics class comprises facial images having the same gender and ethnicity classes.
| 0.652244 |
1. A speech synthesizer comprising: first indication means for indicating the amplitude of a waveform by using a random number; second indication means for indicating the superposition period for waveforms by using a random number; waveform generating means for generating a waveform having an amplitude indicated by said first indication means; waveform superposition means for superposing and adding the waveform generated by said waveform generating means onto a waveform obtained by delaying the waveform, which is previously generated by said waveform generating means, by a superposition period indicated by said second indication means; and output means for outputting the waveform added by said waveform superposition means as unvoiced speech.
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1. A speech synthesizer comprising: first indication means for indicating the amplitude of a waveform by using a random number; second indication means for indicating the superposition period for waveforms by using a random number; waveform generating means for generating a waveform having an amplitude indicated by said first indication means; waveform superposition means for superposing and adding the waveform generated by said waveform generating means onto a waveform obtained by delaying the waveform, which is previously generated by said waveform generating means, by a superposition period indicated by said second indication means; and output means for outputting the waveform added by said waveform superposition means as unvoiced speech. 3. A speech synthesizer according to claim 1, further including: identification means for identifying whether speech to be synthesized is voiced speech or unvoiced speech; and control means for controlling the superposition of the waveforms in accordance with the result of identification by said identification means.
| 0.5 |
2. The method of claim 1 , further comprising: identifying one or more actions based on one or more of the one or more factual claims, the one or more facts and the confidence score; and transmitting the one or more actions for display in the GUI.
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2. The method of claim 1 , further comprising: identifying one or more actions based on one or more of the one or more factual claims, the one or more facts and the confidence score; and transmitting the one or more actions for display in the GUI. 4. The method of claim 2 , further comprising: receiving user input indicating selection of at least one action of the one or more actions; and in response to receiving the user input, invoking the at least one action.
| 0.873531 |
14. The method of claim 12 further comprising the step of prompting for said requisite information by audio prompt.
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14. The method of claim 12 further comprising the step of prompting for said requisite information by audio prompt. 15. The method of claim 14 wherein said audio prompt is pre-recorded and stored on said mobile device.
| 0.90941 |
5. The method of claim 1 , further comprising: analyzing the first document to determine if the first document contains data likely to be relevant to the object.
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5. The method of claim 1 , further comprising: analyzing the first document to determine if the first document contains data likely to be relevant to the object. 6. The method of claim 5 , wherein the data likely to be relevant to the object comprises the name of the entity associated with the object.
| 0.955536 |
21. The method of claim 1 wherein the secured destination file has an associated intermediate file format that is interpretable by an interpreter.
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21. The method of claim 1 wherein the secured destination file has an associated intermediate file format that is interpretable by an interpreter. 24. The method of claim 21 wherein the interpreter is a software virtual machine or a hardware instruction-processing unit.
| 0.971042 |
33. The apparatus according to claim 29 wherein the memory stores further executable instructions configured to, with the processor, cause the apparatus to use at least two sorting tables, and use the hierarchy level to select a sorting table from said at least two sorting tables.
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33. The apparatus according to claim 29 wherein the memory stores further executable instructions configured to, with the processor, cause the apparatus to use at least two sorting tables, and use the hierarchy level to select a sorting table from said at least two sorting tables. 35. The apparatus according to claim 33 , wherein each of said at least two sorting tables comprises a set of code words and a set of syntax elements, and wherein the memory stores further executable instructions configured to, with the processor, cause the apparatus to use the hierarchy level to select a sorting table from said at least two sorting tables; use said code word to select the syntax element; and swap the syntax element with another syntax element of said set of syntax elements in the selected sorting table.
| 0.7 |
10. The method for implementing email recipient templates as in claim 9 , further comprising receiving a selection of one of the displayed recipient templates.
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10. The method for implementing email recipient templates as in claim 9 , further comprising receiving a selection of one of the displayed recipient templates. 11. The method for implementing email recipient templates as in claim 10 , further comprising populating the to, cc, and/or bcc fields with email addresses from the selected recipient template.
| 0.935028 |
15. A system for multi-document aggregation, said system comprising: a processor; a data bus coupled to said processor; and a computer usable medium embodying computer program code, said computer usable medium being coupled to said data bus; and said computer program code comprising instructions executable by said processor and configured to: constructing a document redundancy graph from a document set, said document redundancy graph comprising a plurality of nodes wherein each node of said plurality of nodes represents a unique cluster of information and wherein said plurality of nodes comprise at least one redundant node comprising duplicate clusters of information extracted from a plurality of documents of said document set; determine a longest acyclic path in said document redundancy graph; displaying each node of said plurality of nodes of said longest acyclic path in a first column of a plurality of columns on a graphical user interface; displaying said each node in a position in said first column corresponding to a position in said longest acyclic path; displaying at least one node of a branching path in said document redundancy graph in an additional column of said plurality of columns in a position corresponding to a position in said document redundancy graph where said at least one node of said branching path branched from said longest acyclic path of said document redundancy graph on said graphical user interface; providing preference criteria for selecting from said redundant node at least one particular cluster of information; rendering on said graphical user interface said preference criteria; selecting at least one particular document from said at least one redundant node in accordance with a user selection of said preference criterion; and selecting said particular cluster of information from said selected at least one particular document for display.
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15. A system for multi-document aggregation, said system comprising: a processor; a data bus coupled to said processor; and a computer usable medium embodying computer program code, said computer usable medium being coupled to said data bus; and said computer program code comprising instructions executable by said processor and configured to: constructing a document redundancy graph from a document set, said document redundancy graph comprising a plurality of nodes wherein each node of said plurality of nodes represents a unique cluster of information and wherein said plurality of nodes comprise at least one redundant node comprising duplicate clusters of information extracted from a plurality of documents of said document set; determine a longest acyclic path in said document redundancy graph; displaying each node of said plurality of nodes of said longest acyclic path in a first column of a plurality of columns on a graphical user interface; displaying said each node in a position in said first column corresponding to a position in said longest acyclic path; displaying at least one node of a branching path in said document redundancy graph in an additional column of said plurality of columns in a position corresponding to a position in said document redundancy graph where said at least one node of said branching path branched from said longest acyclic path of said document redundancy graph on said graphical user interface; providing preference criteria for selecting from said redundant node at least one particular cluster of information; rendering on said graphical user interface said preference criteria; selecting at least one particular document from said at least one redundant node in accordance with a user selection of said preference criterion; and selecting said particular cluster of information from said selected at least one particular document for display. 16. The system of claim 15 , further comprising a user interface operably coupled to said processor; and wherein said computer program code is further configured to: displaying for each node of said plurality of nodes a portion of a unique cluster of information represented by said each node in said first or said additional column.
| 0.5 |
19. An article of manufacture comprising: computer executable instructions stored on non-transitory computer readable media, which, when executed by a computer, causes the computer to perform operations comprising: receiving data characterizing each of a plurality of documents within each of a plurality of document sets; grouping the plurality of documents into a plurality of stacks using one or more grouping algorithms, wherein key words are identified in each document and weights specified by a scorecard scoring model are assigned to variables corresponding to each key word, wherein a scoring algorithm, using corresponding variables and weights, provides a score for each document which is used by the grouping algorithm when grouping the documents; identifying a prime document for each stack, the prime document including attributes representative of the entire stack; providing data characterizing documents for each stack including at least the identified prime document to at least one human reviewer; receiving user-generated input from the human reviewer categorizing each provided document; providing data characterizing the user-generated input; evaluating, by at least one data processor, identified grouping errors using at least one of Z-test techniques and multiple regression techniques; determining, by at least one data processor based on the evaluating, a relative contribution of the variables used by the grouping algorithm to the grouping errors; and modifying, by at least one data processor, the grouping algorithm so that at least one weight assigned by the grouping algorithm off-sets the relative contribution of the variables used by the grouping algorithm to an error rate, wherein documents in subsequently received sets of documents are grouped using the modified grouping algorithm.
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19. An article of manufacture comprising: computer executable instructions stored on non-transitory computer readable media, which, when executed by a computer, causes the computer to perform operations comprising: receiving data characterizing each of a plurality of documents within each of a plurality of document sets; grouping the plurality of documents into a plurality of stacks using one or more grouping algorithms, wherein key words are identified in each document and weights specified by a scorecard scoring model are assigned to variables corresponding to each key word, wherein a scoring algorithm, using corresponding variables and weights, provides a score for each document which is used by the grouping algorithm when grouping the documents; identifying a prime document for each stack, the prime document including attributes representative of the entire stack; providing data characterizing documents for each stack including at least the identified prime document to at least one human reviewer; receiving user-generated input from the human reviewer categorizing each provided document; providing data characterizing the user-generated input; evaluating, by at least one data processor, identified grouping errors using at least one of Z-test techniques and multiple regression techniques; determining, by at least one data processor based on the evaluating, a relative contribution of the variables used by the grouping algorithm to the grouping errors; and modifying, by at least one data processor, the grouping algorithm so that at least one weight assigned by the grouping algorithm off-sets the relative contribution of the variables used by the grouping algorithm to an error rate, wherein documents in subsequently received sets of documents are grouped using the modified grouping algorithm. 31. An article as in claim 19 , wherein providing the data comprises one or more of: displaying the data, transmitting the data to a remote computing system, and persisting the data.
| 0.51083 |
1. A method of processing e-communication data by a computer system to identify one or more themes within the communication data, the method comprising: accessing, by a processing system of a computer system, a set of communication data stored in a storage system of the computer system; identifying, by the processing system, terms in the set of communication data, wherein a term is a word or short phrase; defining, by the processing system, relations in the set of communication data based on the terms, wherein a relation is a pair of terms that appear in proximity to one another; calculating, by the processing system, a relation score for each relation based on a frequency that the terms of the relation appear together in the set of communication data, the number of letters in the terms of the relation, and/or the proximity of the terms to one another, wherein relations that appear relatively frequently in the set of communication data and/or have terms with more letters are given a higher score, wherein the score is lowered for those relations whose terms appear relatively far apart in the set of communication data, wherein scoring each relation includes multiplying a number of times that the terms of the relation appear in the set of communication data by a number of total characters in the terms of the relation, and dividing by 1+an average distance between the terms of the relation as it appears in the set of communication data; identifying, by the processing system, themes in the set of communication data based on the relations, wherein a theme is a group of one or more relations that have similar meaning; and storing, by the processing system, the terms, the relations, and the themes in a database.
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1. A method of processing e-communication data by a computer system to identify one or more themes within the communication data, the method comprising: accessing, by a processing system of a computer system, a set of communication data stored in a storage system of the computer system; identifying, by the processing system, terms in the set of communication data, wherein a term is a word or short phrase; defining, by the processing system, relations in the set of communication data based on the terms, wherein a relation is a pair of terms that appear in proximity to one another; calculating, by the processing system, a relation score for each relation based on a frequency that the terms of the relation appear together in the set of communication data, the number of letters in the terms of the relation, and/or the proximity of the terms to one another, wherein relations that appear relatively frequently in the set of communication data and/or have terms with more letters are given a higher score, wherein the score is lowered for those relations whose terms appear relatively far apart in the set of communication data, wherein scoring each relation includes multiplying a number of times that the terms of the relation appear in the set of communication data by a number of total characters in the terms of the relation, and dividing by 1+an average distance between the terms of the relation as it appears in the set of communication data; identifying, by the processing system, themes in the set of communication data based on the relations, wherein a theme is a group of one or more relations that have similar meaning; and storing, by the processing system, the terms, the relations, and the themes in a database. 8. The method of claim 1 further comprising calculating a theme score for each theme by averaging the scores of each relation grouped into that theme, and eliminating low-scoring themes.
| 0.553657 |
17. The system of claim 15 , wherein the operations further comprise: filtering the candidate individuals according to one or more criteria, wherein the criteria comprise soft criteria, which indicate a nonconforming candidate individual is to remain as a candidate individual, and/or hard criteria, which indicate a nonconforming candidate individual is to be removed as a candidate individual.
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17. The system of claim 15 , wherein the operations further comprise: filtering the candidate individuals according to one or more criteria, wherein the criteria comprise soft criteria, which indicate a nonconforming candidate individual is to remain as a candidate individual, and/or hard criteria, which indicate a nonconforming candidate individual is to be removed as a candidate individual. 18. The system of claim 17 , wherein the operations further comprise: determining, for each candidate individual, a likelihood the candidate individual is the individual based on the one or more criteria; and removing one or more candidate individuals with respective likelihoods below a threshold.
| 0.87493 |
10. A computer program product for managing a flow model simulation, the computer program product comprising: a computer readable storage device; program instructions for associating annotated simulation settings with a source model to form an annotated source model in response to receiving the source model created in a non-native modeler, wherein the annotated simulation settings are derived from at least one of a set of user-defined simulation settings and default simulation settings; program instructions for transforming the annotated source model into an internal domain model using a set of links, wherein the set of links are generated using a set of link rules that comprise instruction that govern the creation of the set of links, the set of link rules customizable for the source model, and wherein the set of links maps a set of source model elements to a set of internal domain model elements of the internal domain model; program instructions for mapping results from a simulation of the internal domain model back to the source model to identify a context for the results, wherein the simulation is governed by the annotated simulation settings; program instructions for generating a target view model from the internal domain model, wherein the target view model comprises the results presented in the context of the source model; and wherein the program instructions are stored on the computer-readable storage device.
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10. A computer program product for managing a flow model simulation, the computer program product comprising: a computer readable storage device; program instructions for associating annotated simulation settings with a source model to form an annotated source model in response to receiving the source model created in a non-native modeler, wherein the annotated simulation settings are derived from at least one of a set of user-defined simulation settings and default simulation settings; program instructions for transforming the annotated source model into an internal domain model using a set of links, wherein the set of links are generated using a set of link rules that comprise instruction that govern the creation of the set of links, the set of link rules customizable for the source model, and wherein the set of links maps a set of source model elements to a set of internal domain model elements of the internal domain model; program instructions for mapping results from a simulation of the internal domain model back to the source model to identify a context for the results, wherein the simulation is governed by the annotated simulation settings; program instructions for generating a target view model from the internal domain model, wherein the target view model comprises the results presented in the context of the source model; and wherein the program instructions are stored on the computer-readable storage device. 14. The computer program product of claim 10 , wherein the program instructions for generating the view model further comprise: instructions for conforming the target view model to the source view model.
| 0.566569 |
1. A method for providing an alternative to the existing world wide web, known as a graphical user interface (GUI) web, comprising GUI browsers as alternatives to existing hypertext markup language (HTML) web browsers, the method comprising: providing a GUI web-browser with functionality to create, edit, and retrieve GUI documents as GUI web pages, the GUI web pages being an alternative to HTML web pages, the GUI web-browser comprising a page window configured to display the GUI documents as the GUI web pages; displaying, within the GUI web-browser, an empty page window for creating a GUI document in a GUI document display format, the GUI document being configured to display GUI elements programmatically adapted for use as presentation elements, the GUI elements being alternatives to HTML elements; placing at least one presentation element within the empty page window, wherein the at least one presentation element comprises an instance of a GUI class object and metadata; enabling editing of the at least one presentation element by providing editing tools configured to modify properties, functions, and events of the at least one presentation element and enabling the user to select from a plurality of properties, functions and events predefined by the GUI web-browser; and saving the GUI document as a GUI web page comprising the at least one presentation element, wherein saving the GUI document as the GUI web page comprises converting the GUI document from the GUI document display format to a GUI document stored format, the GUI document stored format comprising the metadata associated with the at least one presentation element, wherein the GUI document is configured to be loaded from the GUI document stored format and displayed in the GUI document display format as the GUI web page.
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1. A method for providing an alternative to the existing world wide web, known as a graphical user interface (GUI) web, comprising GUI browsers as alternatives to existing hypertext markup language (HTML) web browsers, the method comprising: providing a GUI web-browser with functionality to create, edit, and retrieve GUI documents as GUI web pages, the GUI web pages being an alternative to HTML web pages, the GUI web-browser comprising a page window configured to display the GUI documents as the GUI web pages; displaying, within the GUI web-browser, an empty page window for creating a GUI document in a GUI document display format, the GUI document being configured to display GUI elements programmatically adapted for use as presentation elements, the GUI elements being alternatives to HTML elements; placing at least one presentation element within the empty page window, wherein the at least one presentation element comprises an instance of a GUI class object and metadata; enabling editing of the at least one presentation element by providing editing tools configured to modify properties, functions, and events of the at least one presentation element and enabling the user to select from a plurality of properties, functions and events predefined by the GUI web-browser; and saving the GUI document as a GUI web page comprising the at least one presentation element, wherein saving the GUI document as the GUI web page comprises converting the GUI document from the GUI document display format to a GUI document stored format, the GUI document stored format comprising the metadata associated with the at least one presentation element, wherein the GUI document is configured to be loaded from the GUI document stored format and displayed in the GUI document display format as the GUI web page. 13. The method of claim 1 , wherein saving the GUI Document comprises: grouping the page window with its associated properties, grouping the at least one presentation element with its associated properties, assigning a common unique value to the page window group and to each corresponding presentation elements group associated with the page window group, and saving the grouped data in a file containing multiple displayed pages in stored format.
| 0.519113 |
1. A document retrieval apparatus comprising: a document storage unit for storing a document to be searched; a document size storage unit for storing a data size of the document such that the data size is associated with a document ID for identifying the document; a retrieval document size calculation unit for reading out from the document size storage unit the data size associated with the document ID indicating the document to be searched, and calculating a retrieval document size by adding up the read out data size(s); a prospect time calculation unit for calculating a first estimated time taken for a retrieval process by a first retrieval method and a second estimated time taken for the retrieval process by a second retrieval method, based on the retrieval document size; a retrieval method decision unit for comparing the first and second estimated times and deciding which retrieval method to use for performing the retrieval process, the first method or the second method; a retrieval key input unit for receiving an input of a first and second retrieval keys; an index storage unit for storing the retrieval key contained in the document and the document ID such that they are associated with each other; a retrieval action unit for performing a process of retrieving the document containing the retrieval key; and a retrieved document ID storage unit for storing a retrieved document ID indicating the document containing the retrieval key, and wherein the first retrieval method is an index scan method of retrieving the document ID associated with the retrieval key from the index storage unit; the second retrieval method is a text scan method of searching, for each of the documents stored in the document storage unit, whether or not the retrieval key is contained in the document; the retrieval action unit retrieves the document containing the first retrieval key in accordance with the first retrieval method, and stores in the retrieved document ID storage unit the retrieved document ID indicating the document containing the first retrieval key; the retrieval document size calculation unit reads out from the document size storage unit the data size associated with each of the retrieved document IDs stored in the retrieved document ID storage unit, and calculates the retrieval document size by adding up the read out data sizes; and the retrieval method decision unit compares the first and second estimated times and decides which retrieval method to use for performing the process of retrieving the document data containing the second retrieval key, the first method or the second method.
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1. A document retrieval apparatus comprising: a document storage unit for storing a document to be searched; a document size storage unit for storing a data size of the document such that the data size is associated with a document ID for identifying the document; a retrieval document size calculation unit for reading out from the document size storage unit the data size associated with the document ID indicating the document to be searched, and calculating a retrieval document size by adding up the read out data size(s); a prospect time calculation unit for calculating a first estimated time taken for a retrieval process by a first retrieval method and a second estimated time taken for the retrieval process by a second retrieval method, based on the retrieval document size; a retrieval method decision unit for comparing the first and second estimated times and deciding which retrieval method to use for performing the retrieval process, the first method or the second method; a retrieval key input unit for receiving an input of a first and second retrieval keys; an index storage unit for storing the retrieval key contained in the document and the document ID such that they are associated with each other; a retrieval action unit for performing a process of retrieving the document containing the retrieval key; and a retrieved document ID storage unit for storing a retrieved document ID indicating the document containing the retrieval key, and wherein the first retrieval method is an index scan method of retrieving the document ID associated with the retrieval key from the index storage unit; the second retrieval method is a text scan method of searching, for each of the documents stored in the document storage unit, whether or not the retrieval key is contained in the document; the retrieval action unit retrieves the document containing the first retrieval key in accordance with the first retrieval method, and stores in the retrieved document ID storage unit the retrieved document ID indicating the document containing the first retrieval key; the retrieval document size calculation unit reads out from the document size storage unit the data size associated with each of the retrieved document IDs stored in the retrieved document ID storage unit, and calculates the retrieval document size by adding up the read out data sizes; and the retrieval method decision unit compares the first and second estimated times and decides which retrieval method to use for performing the process of retrieving the document data containing the second retrieval key, the first method or the second method. 6. The document retrieval apparatus according to claim 1 , wherein: the retrieval key comprises a combination of a predetermined number of characters; and the index storage unit stores the document IDs, associating them with all of the combinations of the predetermined number of the characters contained in all of the documents to be searched.
| 0.701713 |
1. A method comprising: receiving, by one or more computing devices of a matching-engine system, from an administrator of the matching-engine system a set of physician-selection parameters comprising: a performance-score-range for physicians; and an experience-score-range for physicians; storing, by one or more of the computing devices, the parameters in a data store of the matching-engine system; receiving, by one or more of the computing devices, a search query from a client device of a user of the matching-engine system, the search query comprising a geographic location of the user and one or more of a user-specified symptom or a user-specified treatment; determining, by one or more of the computing devices, at least one base-concept based on the search query, the base-concept comprising a medical diagnosis or a medical procedure; identifying, by one or more of the computing devices, a set of one or more physicians to be recommended to the user based at least in part on: a geographic location of each of the one or more physicians; a performance-score associated with the at least one base-concept for each of the one or more physicians, wherein the performance-score is calculated based on a weighted aggregate of individual performance-scores for one or more sub-concepts of the base-concept, wherein the individual performance-scores are calculated by: (1) accessing one or more Current Procedural Terminology (CPT) codes from claims data received from the physician, wherein the CPT codes refer to a medical service provided by the physician in connection with the one or more sub-concepts; (2) determining one or more relative value units (RVUs) corresponding to the one or more CPT codes, wherein the RVUs corresponding to a CPT code represents a location-independent measure of overall resources used for the medical service; (3) calculating a physician-cost-factor for the physician associated with the one or more sub-concepts, wherein the physician-cost-factor is based on the RVUs corresponding to the medical service provided by the physician for the one or more sub-concepts; (4) accessing an average cost factor associated with the one or more sub-concepts for a plurality of physicians, wherein the physician and the plurality of physicians share a common specialty and common geographic location; and (5) comparing the physician-cost-factor with the average cost factor, wherein the individual performance-score for the physician for the one or more sub-concepts is increased if the physician-cost-factor is lower than the average cost factor; an experience-score associated with the at least one base-concept each of the one or more physicians; and the set of physician-selection parameters from the administrator; and sending, by one or more computing devices, a search-results page to a client device of the user, the search-results page comprising references to one or more of the physicians in the set of physicians.
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1. A method comprising: receiving, by one or more computing devices of a matching-engine system, from an administrator of the matching-engine system a set of physician-selection parameters comprising: a performance-score-range for physicians; and an experience-score-range for physicians; storing, by one or more of the computing devices, the parameters in a data store of the matching-engine system; receiving, by one or more of the computing devices, a search query from a client device of a user of the matching-engine system, the search query comprising a geographic location of the user and one or more of a user-specified symptom or a user-specified treatment; determining, by one or more of the computing devices, at least one base-concept based on the search query, the base-concept comprising a medical diagnosis or a medical procedure; identifying, by one or more of the computing devices, a set of one or more physicians to be recommended to the user based at least in part on: a geographic location of each of the one or more physicians; a performance-score associated with the at least one base-concept for each of the one or more physicians, wherein the performance-score is calculated based on a weighted aggregate of individual performance-scores for one or more sub-concepts of the base-concept, wherein the individual performance-scores are calculated by: (1) accessing one or more Current Procedural Terminology (CPT) codes from claims data received from the physician, wherein the CPT codes refer to a medical service provided by the physician in connection with the one or more sub-concepts; (2) determining one or more relative value units (RVUs) corresponding to the one or more CPT codes, wherein the RVUs corresponding to a CPT code represents a location-independent measure of overall resources used for the medical service; (3) calculating a physician-cost-factor for the physician associated with the one or more sub-concepts, wherein the physician-cost-factor is based on the RVUs corresponding to the medical service provided by the physician for the one or more sub-concepts; (4) accessing an average cost factor associated with the one or more sub-concepts for a plurality of physicians, wherein the physician and the plurality of physicians share a common specialty and common geographic location; and (5) comparing the physician-cost-factor with the average cost factor, wherein the individual performance-score for the physician for the one or more sub-concepts is increased if the physician-cost-factor is lower than the average cost factor; an experience-score associated with the at least one base-concept each of the one or more physicians; and the set of physician-selection parameters from the administrator; and sending, by one or more computing devices, a search-results page to a client device of the user, the search-results page comprising references to one or more of the physicians in the set of physicians. 2. The method of claim 1 , wherein each physician in the set is associated with: a performance-score within the performance-score-range; and an experience-score within the experience-score-range.
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34. The method of claim 33 , wherein extracting one or more features further comprises: identifying an associate word that is associated with the particular content word; determining whether the associate word belongs in a particular associate word group, wherein the particular associate word group is associated with another figurative usage likelihood; wherein a prediction of whether the particular content word is being used figuratively is based on the figurative usage likelihood and the another figurative usage likelihood.
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34. The method of claim 33 , wherein extracting one or more features further comprises: identifying an associate word that is associated with the particular content word; determining whether the associate word belongs in a particular associate word group, wherein the particular associate word group is associated with another figurative usage likelihood; wherein a prediction of whether the particular content word is being used figuratively is based on the figurative usage likelihood and the another figurative usage likelihood. 35. The method of claim 34 , wherein the associate word is in a same sentence as the particular content word.
| 0.944547 |
17. A system comprising: a processor of a machine; a user interface module to cause presentation of a message interface that is used, by a user, to report an issue affecting the user to a content submission system, the message interface including a short text field that receives at least one keyword that summarizes the issue being reported and a separate description field for textual input of a description of the issue being reported; and a search module to, in response to detection of completion of entry of the at least one keyword in the short text field, automatically, based on an auto-search feature being turned on and without receiving a selection of a button that triggers a search, perform, using the processor of the machine, the search of a content database for previously submitted content comprising one or more issues reported by other users that matches the at least one keyword that summarizes the issue being reported, and to cause display of a results list in proximity to the short text field on the message interface, the results list comprising a selectable title and a separately selectable link for each result in the results list that corresponds to the previously submitted content that matches the at least one keyword that summarizes the issue being reported, the previously submitted content being previously submitted messages reporting issues to the content submission system.
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17. A system comprising: a processor of a machine; a user interface module to cause presentation of a message interface that is used, by a user, to report an issue affecting the user to a content submission system, the message interface including a short text field that receives at least one keyword that summarizes the issue being reported and a separate description field for textual input of a description of the issue being reported; and a search module to, in response to detection of completion of entry of the at least one keyword in the short text field, automatically, based on an auto-search feature being turned on and without receiving a selection of a button that triggers a search, perform, using the processor of the machine, the search of a content database for previously submitted content comprising one or more issues reported by other users that matches the at least one keyword that summarizes the issue being reported, and to cause display of a results list in proximity to the short text field on the message interface, the results list comprising a selectable title and a separately selectable link for each result in the results list that corresponds to the previously submitted content that matches the at least one keyword that summarizes the issue being reported, the previously submitted content being previously submitted messages reporting issues to the content submission system. 20. The system of claim 17 , further comprising a notes module to: receive an indication of activation of a notes button; detect whether the at least one keyword is present in the short text field; based on the at least one keyword being present in the short text field, perform a search for notes that match the at least one keyword from the short text field; and based on the at least one keyword not being present in the short text field, performing the search for the notes using manually entered note search terms, the notes providing background or context for the previously submitted content linked to the notes.
| 0.593878 |
1. A recommendation method comprising: providing an ontology database comprising an ontology hierarchy structure with N hierarchy levels, wherein N is an integer, and each of the hierarchy levels comprises at least one entity; storing, through the ontology database, a plurality of j th user data respectively corresponding to a plurality of users, wherein each of the j th user data records at least one j th entity of the entities on a j th hierarchy level of the ontology hierarchy structure; generating a plurality of k th user data corresponding to the users according to the j th user data respectively, wherein each of the k th user data records at least one k th entity of the entities on a k th hierarchy level of the ontology hierarchy structure; clustering the k th user data; and recommending the entities in the ontology database to the users according to the clustering result, wherein the step of generating the k th user data corresponding to the users comprises: calculating a sparsity of the j th user data; and mapping the j th entity recorded in each of the j th user data to at least one of the k th entity recorded in each of the k th user data according to the sparsity of the j th user data; wherein a first calculating value is equal to a product of a quantity of the users and a quantity of the entities on the j th hierarchy level, a second calculating value is equal to a quantity of a sum of the j th entity recorded by each of the j th user data divided by the first calculating value, and the sparsity of the j th user data is equal to 1 subtracted by the second calculating value.
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1. A recommendation method comprising: providing an ontology database comprising an ontology hierarchy structure with N hierarchy levels, wherein N is an integer, and each of the hierarchy levels comprises at least one entity; storing, through the ontology database, a plurality of j th user data respectively corresponding to a plurality of users, wherein each of the j th user data records at least one j th entity of the entities on a j th hierarchy level of the ontology hierarchy structure; generating a plurality of k th user data corresponding to the users according to the j th user data respectively, wherein each of the k th user data records at least one k th entity of the entities on a k th hierarchy level of the ontology hierarchy structure; clustering the k th user data; and recommending the entities in the ontology database to the users according to the clustering result, wherein the step of generating the k th user data corresponding to the users comprises: calculating a sparsity of the j th user data; and mapping the j th entity recorded in each of the j th user data to at least one of the k th entity recorded in each of the k th user data according to the sparsity of the j th user data; wherein a first calculating value is equal to a product of a quantity of the users and a quantity of the entities on the j th hierarchy level, a second calculating value is equal to a quantity of a sum of the j th entity recorded by each of the j th user data divided by the first calculating value, and the sparsity of the j th user data is equal to 1 subtracted by the second calculating value. 5. The recommendation method as claimed in claim 1 , wherein the step of recommending the entities in the ontology database to the users according to the clustering result comprises: searching a k th frequent entity from the k th entity recorded by each of the k th user data in a cluster; searching a j th frequent entity from the entities on the j th hierarchy level according to the k th frequent entity; and recommending the j th frequent entity to one of the users corresponding to the k th user data in the cluster.
| 0.511338 |
1. A method of operating an interactive self-help service, comprising: providing an application script for implementing the interactive self-help service; providing a deployment platform on an IP network having a plurality of application servers and application resources distributed over the IP network able to execute the application script; providing a specification for preferred application resources needed for executing the application script; monitoring the plurality of application resources periodically for status of each from a first node on the network to maintain an updated centralized list of the application resources prioritized by performance; selecting an application server located at a second node from the plurality of application servers on the network to execute the application script; maintaining at the selected application server a local list of application resources previously servicing the selected application server, the local list including quality of service of the application resources from the second node; selecting a central view list of application resources by querying the centralized list by resource type to conform to a predefined specification and prioritized by performance; querying the local list to select a local view list of previously contacted resources prioritized by availability and indicating a degree of success of previous browser attempts for each previously contacted resource; and executing the application script by the selected application server with application resources located dynamically from a final prioritized list created based upon the central view list filtered by using the local view list.
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1. A method of operating an interactive self-help service, comprising: providing an application script for implementing the interactive self-help service; providing a deployment platform on an IP network having a plurality of application servers and application resources distributed over the IP network able to execute the application script; providing a specification for preferred application resources needed for executing the application script; monitoring the plurality of application resources periodically for status of each from a first node on the network to maintain an updated centralized list of the application resources prioritized by performance; selecting an application server located at a second node from the plurality of application servers on the network to execute the application script; maintaining at the selected application server a local list of application resources previously servicing the selected application server, the local list including quality of service of the application resources from the second node; selecting a central view list of application resources by querying the centralized list by resource type to conform to a predefined specification and prioritized by performance; querying the local list to select a local view list of previously contacted resources prioritized by availability and indicating a degree of success of previous browser attempts for each previously contacted resource; and executing the application script by the selected application server with application resources located dynamically from a final prioritized list created based upon the central view list filtered by using the local view list. 9. The method as in claim 1 , wherein the specification for preferred application resources needed for executing the application script includes application resources accessible by a specific network route.
| 0.5565 |
1. A computer implemented method in a data processing system for transforming source input data using a transformation macro, the computer implemented method comprising computer implemented steps of: executing, by the data processing system using the transformation macro, a transformation macro script; reading, by the data processing system using the transformation macro script, one or more transformation templates, wherein one or more input data source files are contained within the one or more transformation templates; reading, by the data processing system using the transformation macro script, the one or more input data source files contained within the one or more transformation templates; performing, by the data processing system using the transformation macro, logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files; determining, by the data processing system, whether constraints generated by the logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files are valid; responsive to a determination by the data processing system that the constraints generated by the logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files are valid, transforming, by the data processing system using the transformation macro, the one or more input data source files from a first file format into a second file format; and responsive to determining by the data processing system that transformation of the one or more input data source files from the first file format into the second file format is complete, outputting, by the data processing system, a transformation output.
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1. A computer implemented method in a data processing system for transforming source input data using a transformation macro, the computer implemented method comprising computer implemented steps of: executing, by the data processing system using the transformation macro, a transformation macro script; reading, by the data processing system using the transformation macro script, one or more transformation templates, wherein one or more input data source files are contained within the one or more transformation templates; reading, by the data processing system using the transformation macro script, the one or more input data source files contained within the one or more transformation templates; performing, by the data processing system using the transformation macro, logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files; determining, by the data processing system, whether constraints generated by the logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files are valid; responsive to a determination by the data processing system that the constraints generated by the logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files are valid, transforming, by the data processing system using the transformation macro, the one or more input data source files from a first file format into a second file format; and responsive to determining by the data processing system that transformation of the one or more input data source files from the first file format into the second file format is complete, outputting, by the data processing system, a transformation output. 5. The computer implemented method of claim 1 , wherein the transformation macro script is a modular transformation macro script, and wherein the modular transformation macro script is combined with other modular transformation macro scripts.
| 0.603497 |
12. A method for menu constructing of a mobile communication terminal using mobile flash, the method comprising steps of: storing configuration information of the mobile communication terminal in a memory section; loading a corresponding flash movie file based on a reproduction request of a flash movie; parsing the configuration information read from the memory section; mapping the flash movie with the parsed configuration information; and outputting the mapped contents through a display section.
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12. A method for menu constructing of a mobile communication terminal using mobile flash, the method comprising steps of: storing configuration information of the mobile communication terminal in a memory section; loading a corresponding flash movie file based on a reproduction request of a flash movie; parsing the configuration information read from the memory section; mapping the flash movie with the parsed configuration information; and outputting the mapped contents through a display section. 14. The method according to claim 12 , wherein the step of providing with the memory comprises a step of storing the configuration information in a form of an Extendible Markup Language (XML) document.
| 0.724766 |
6. The method of claim 5 , wherein linking comprises identifying a weighted set of words or phrases in each tessellated region classified as containing text; recognizing tessellated regions that share a weighted word or phrase; and establishing links between the recognized tessellated regions.
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6. The method of claim 5 , wherein linking comprises identifying a weighted set of words or phrases in each tessellated region classified as containing text; recognizing tessellated regions that share a weighted word or phrase; and establishing links between the recognized tessellated regions. 7. The method of claim 6 , wherein identifying a weighted word set comprises, for each tessellated region, computing relative occurrences of words or phrases as compared to a larger corpus.
| 0.875258 |
1. A non-transitory storage medium encoded with machine-readable computer program code for providing search and reference functions for a messaging system, the non-transitory storage medium including instructions for causing a computer to implement a method, comprising: receiving a request to search a data archive for reference information relating to at least one keyword selected by a messaging system user, said messaging system user actively engaged in composing a message or a response to a message, and wherein further, said at least one keyword is selected from a body of said message's text; searching said data archive; if a reference is found, presenting said reference to said messaging system user within said message; wherein said data archive includes information gathered from said messaging system user's message folder and at least one of: a local data storage system; and a shared online repository; and further comprising instructions for causing said computer to implement: integrating process software for providing said search and reference functions for a messaging system, said integrating process software further comprising: determining if said process software will execute on at least one server; identifying an address of said at least one server; checking said at least one server for operating systems, applications, and version numbers for validation with said process software, and identifying any missing software applications for said at least one server that are required for integration; updating said at least one server with respect to any operating system and application that is not validated for said process software, and providing any of said missing software applications for said at least one server required for said integration; identifying client addresses and checking client computers for operating systems, applications, and version numbers for validation with said process software, and identifying any software applications missing from said client computers that are required for integration; updating said client computers with respect to any operating system and application that is not validated for said process software, and providing any missing software application for said client computers required for said integration; and installing said process software on said client computers and said at least one server.
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1. A non-transitory storage medium encoded with machine-readable computer program code for providing search and reference functions for a messaging system, the non-transitory storage medium including instructions for causing a computer to implement a method, comprising: receiving a request to search a data archive for reference information relating to at least one keyword selected by a messaging system user, said messaging system user actively engaged in composing a message or a response to a message, and wherein further, said at least one keyword is selected from a body of said message's text; searching said data archive; if a reference is found, presenting said reference to said messaging system user within said message; wherein said data archive includes information gathered from said messaging system user's message folder and at least one of: a local data storage system; and a shared online repository; and further comprising instructions for causing said computer to implement: integrating process software for providing said search and reference functions for a messaging system, said integrating process software further comprising: determining if said process software will execute on at least one server; identifying an address of said at least one server; checking said at least one server for operating systems, applications, and version numbers for validation with said process software, and identifying any missing software applications for said at least one server that are required for integration; updating said at least one server with respect to any operating system and application that is not validated for said process software, and providing any of said missing software applications for said at least one server required for said integration; identifying client addresses and checking client computers for operating systems, applications, and version numbers for validation with said process software, and identifying any software applications missing from said client computers that are required for integration; updating said client computers with respect to any operating system and application that is not validated for said process software, and providing any missing software application for said client computers required for said integration; and installing said process software on said client computers and said at least one server. 2. The non-transitory storage medium of claim 1 , further comprising instructions for causing said computer to implement: in response to a request by said messaging system user, providing access to a recipient of said message to said shared online repository operable for allowing said recipient to: search for a reference within said shared online repository; and access references provided in said message.
| 0.609643 |
1. An electronic resource denotation, request and delivery system, comprising: a protocol through which electronic resources are each denoted by a resource alias unique throughout an interconnected network of two or more networks, each of said resource aliases comprising a string of characters forming a mnemonic independent of the physical location of, or path to said electronic resource, and not dependent on an identification of a naming authority governing the assignment of resource aliases for use on said interconnected network; location data associated with each of said resource aliases; a central registry accessible through said interconnected network for resolving said resource aliases into their respective associated location data; and at least one computer accessible through said interconnected network for requesting a resolution of a particular resource alias.
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1. An electronic resource denotation, request and delivery system, comprising: a protocol through which electronic resources are each denoted by a resource alias unique throughout an interconnected network of two or more networks, each of said resource aliases comprising a string of characters forming a mnemonic independent of the physical location of, or path to said electronic resource, and not dependent on an identification of a naming authority governing the assignment of resource aliases for use on said interconnected network; location data associated with each of said resource aliases; a central registry accessible through said interconnected network for resolving said resource aliases into their respective associated location data; and at least one computer accessible through said interconnected network for requesting a resolution of a particular resource alias. 24. The system of claim 1 wherein said resource alias further comprises a source alias prepended to said string of characters forming a mnemonic, said source alias comprising a string of characters forming a mnemonic denoting a provider of said electronic resource.
| 0.651303 |
17. An implant adapted to be implanted in a spine of a patient comprising: a body including a shield with a shield cavity, the shield cavity having a first end and a second end and a shield cavity axis; a deflection rod having a fixed end and a free end and a longitudinal axis, the deflection rod mounted in said shield cavity such that the fixed end is secured in the first end of the shield cavity, the free end extends out of the second end of the shield cavity, and the longitudinal axis is aligned with the shield cavity axis; an gap defined between said deflection rod and said shield, said gap extending from the second end of the shield cavity at least partway along the shield cavity towards the first end of the shield cavity; said gap being configured to allow bending of the deflection rod within the shield cavity to thereby allow deflection of the free end of the deflection rod away from alignment with the shield cavity axis in response to a load applied to the free end of the deflection rod; and wherein said deflection of the free end of the deflection rod away from alignment with the shield cavity axis is limited by contact between the deflection rod and the shield.
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17. An implant adapted to be implanted in a spine of a patient comprising: a body including a shield with a shield cavity, the shield cavity having a first end and a second end and a shield cavity axis; a deflection rod having a fixed end and a free end and a longitudinal axis, the deflection rod mounted in said shield cavity such that the fixed end is secured in the first end of the shield cavity, the free end extends out of the second end of the shield cavity, and the longitudinal axis is aligned with the shield cavity axis; an gap defined between said deflection rod and said shield, said gap extending from the second end of the shield cavity at least partway along the shield cavity towards the first end of the shield cavity; said gap being configured to allow bending of the deflection rod within the shield cavity to thereby allow deflection of the free end of the deflection rod away from alignment with the shield cavity axis in response to a load applied to the free end of the deflection rod; and wherein said deflection of the free end of the deflection rod away from alignment with the shield cavity axis is limited by contact between the deflection rod and the shield. 21. The implant of claim 17 , wherein said deflection rod has a first resistance to deflection over a first 0.06 inches of deflection and a second resistance to deflection over a further 0.04 inches of deflection and wherein the second resistance is more than double the first resistance.
| 0.606162 |
20. A system for processing posts in an activity stream, the system comprising: one or more processors; the one or more processors being configured to: receive a client type specifying a type of a client device; receive activity information from an activity source; receive an activity type; create a first protocol buffer using the activity type and the activity information; select embedded code from a library of embedded code based in part upon the client type and the activity type; add the embedded code to the first protocol buffer to create a type-specific protocol buffer; and send the type-specific protocol buffer to the client device for rendering of the activity information.
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20. A system for processing posts in an activity stream, the system comprising: one or more processors; the one or more processors being configured to: receive a client type specifying a type of a client device; receive activity information from an activity source; receive an activity type; create a first protocol buffer using the activity type and the activity information; select embedded code from a library of embedded code based in part upon the client type and the activity type; add the embedded code to the first protocol buffer to create a type-specific protocol buffer; and send the type-specific protocol buffer to the client device for rendering of the activity information. 24. The system of claim 20 , wherein the one or more processors are further configured to communicate with the activity source and provide activity information to a data type taxonomy.
| 0.764031 |
1. A system for providing recommendations to improve a query, comprising: a processor; and storage coupled to the processor, wherein the storage stores a computer program, and wherein the processor executes the computer program to perform operations, operations comprising: receiving a query with query keywords and selected categories; and in response to determining that the selected categories are ranked high with reference to query relevance indicator values for each of the selected categories, determining whether a lowest category level has been reached in the selected categories; in response to determining that the lowest category level has been reached, ranking individual services that are at the lowest category levels: and providing one or more high ranked services from the ranked individual services; and in response to determining that the lowest category level has not been reached, calculating a keyword relevance indicator of each keyword in the query for each subcategory of each of the selected categories, wherein the keyword relevance indicator for a keyword is calculated using a keyword frequency of the keyword and an inverse service frequency of a subcategory; calculating a query relevance indicator of the query with each subcategory using the retrieved keyword relevance indicators, wherein the query relevance indicator is generated based on a keyword relevance indicator of a keyword specified in the query and a keyword relevance indicator of a keyword in the subcategory that is not specified in the query; ranking each subcategory based on the query relevance indicators; and providing the ranked subcategories for use in selecting new categories to be submitted with the query.
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1. A system for providing recommendations to improve a query, comprising: a processor; and storage coupled to the processor, wherein the storage stores a computer program, and wherein the processor executes the computer program to perform operations, operations comprising: receiving a query with query keywords and selected categories; and in response to determining that the selected categories are ranked high with reference to query relevance indicator values for each of the selected categories, determining whether a lowest category level has been reached in the selected categories; in response to determining that the lowest category level has been reached, ranking individual services that are at the lowest category levels: and providing one or more high ranked services from the ranked individual services; and in response to determining that the lowest category level has not been reached, calculating a keyword relevance indicator of each keyword in the query for each subcategory of each of the selected categories, wherein the keyword relevance indicator for a keyword is calculated using a keyword frequency of the keyword and an inverse service frequency of a subcategory; calculating a query relevance indicator of the query with each subcategory using the retrieved keyword relevance indicators, wherein the query relevance indicator is generated based on a keyword relevance indicator of a keyword specified in the query and a keyword relevance indicator of a keyword in the subcategory that is not specified in the query; ranking each subcategory based on the query relevance indicators; and providing the ranked subcategories for use in selecting new categories to be submitted with the query. 6. The system of claim 1 , wherein the operations further comprise: providing recommendations regarding the query keywords for use in revising the query; and receiving a revised query based on the provided recommendations.
| 0.621131 |
7. A computer implemented method of forensic data analysis, the method comprising: extracting, with a data extraction module, unknown raw data from a plurality of raw data sources; providing the extracted unknown raw data to an interpreter module; receiving, at the interpreter module, the extracted unknown raw data from the data extraction module; storing a plurality of search packs wherein the search packs are adapted to reference other search packs from different platforms; accessing, at the interpreter module, one or more of the search packs each having associated suspect data features; determining which one or more search packs to send the unknown raw data to wherein the determination is based on categories of data; automatically identifying, using the interpreter module, suspect data from among the extracted raw data by applying a hash function to the extracted raw data to generate an extracted data hash value, and comparing the extracted data hash value to find identical and similar suspect data features; and generating, using the interpreter module, a report indicating any matches between the extracted data and any similar suspect data features.
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7. A computer implemented method of forensic data analysis, the method comprising: extracting, with a data extraction module, unknown raw data from a plurality of raw data sources; providing the extracted unknown raw data to an interpreter module; receiving, at the interpreter module, the extracted unknown raw data from the data extraction module; storing a plurality of search packs wherein the search packs are adapted to reference other search packs from different platforms; accessing, at the interpreter module, one or more of the search packs each having associated suspect data features; determining which one or more search packs to send the unknown raw data to wherein the determination is based on categories of data; automatically identifying, using the interpreter module, suspect data from among the extracted raw data by applying a hash function to the extracted raw data to generate an extracted data hash value, and comparing the extracted data hash value to find identical and similar suspect data features; and generating, using the interpreter module, a report indicating any matches between the extracted data and any similar suspect data features. 11. The method of claim 7 , wherein each search pack comprises a pre-established set of relevant data having a pre-determined pattern.
| 0.62024 |
1. A method of providing an ordered list of search results, comprising the steps of: receiving a term of a query; determining a geographical area associated with a requestor of the query; generating, with at least one processor, search results associated with the term and the geographical area, the search results including first search results relevant to the term and second search results relevant to the geographical area; and ordering the search results for display, the ordering of the search results comprising: weighting the first search results more than the second search results if a number of the first search results is less than a number of the second search results; weighting the second search results more than the first search results if a number of the first search results is more than a number of the second search results; and ordering the search results for display based on the weighting of the first search results and the weighting of the second search results; determining computer network information associated with the requestor; and determining the geographical area using the determined computer network information, wherein the computer network information comprises at least one of an Internet Protocol (IP) address associated with the requestor or a location of a service provider gateway of the requestor, and wherein the determining a geographical area includes determining the geographical area using the IP address associated with the requestor or the location of the service provider gateway of the requestor.
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1. A method of providing an ordered list of search results, comprising the steps of: receiving a term of a query; determining a geographical area associated with a requestor of the query; generating, with at least one processor, search results associated with the term and the geographical area, the search results including first search results relevant to the term and second search results relevant to the geographical area; and ordering the search results for display, the ordering of the search results comprising: weighting the first search results more than the second search results if a number of the first search results is less than a number of the second search results; weighting the second search results more than the first search results if a number of the first search results is more than a number of the second search results; and ordering the search results for display based on the weighting of the first search results and the weighting of the second search results; determining computer network information associated with the requestor; and determining the geographical area using the determined computer network information, wherein the computer network information comprises at least one of an Internet Protocol (IP) address associated with the requestor or a location of a service provider gateway of the requestor, and wherein the determining a geographical area includes determining the geographical area using the IP address associated with the requestor or the location of the service provider gateway of the requestor. 4. The method of claim 1 , wherein the determining a geographical area comprises determining the geographical area without soliciting geographic location information from the requester.
| 0.539739 |
19. A computer readable medium having computer-executable instructions that, when executed on one or more processors, performs the following: construct a table user interface (UI) for display within a document including text and a table, wherein the table supports the full spreadsheet functionality; create a cell table to hold data and at least one formula for the table UI; upon modification of the data, automatically recalculate the formula in the cell table to produce a new result; and provide a document behavior operation including one or more of spell checking, grammar checking, find, replace, and text formatting, across table boundaries, such that when invoked, document behavior operations that are applied to the text outside of the table are applied across a table boundary to text inside the table.
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19. A computer readable medium having computer-executable instructions that, when executed on one or more processors, performs the following: construct a table user interface (UI) for display within a document including text and a table, wherein the table supports the full spreadsheet functionality; create a cell table to hold data and at least one formula for the table UI; upon modification of the data, automatically recalculate the formula in the cell table to produce a new result; and provide a document behavior operation including one or more of spell checking, grammar checking, find, replace, and text formatting, across table boundaries, such that when invoked, document behavior operations that are applied to the text outside of the table are applied across a table boundary to text inside the table. 20. The computer medium of claim 19 , further comprising computer-executable instructions that, when executed on one or more processors, perform creation of a format table to hold information pertaining to a data format of the table UI.
| 0.592271 |
1. A computer-implemented method for extending a knowledge base, the method being executed using one or more processors and comprising: receiving an enterprise service signature (ESS) associated with an enterprise service (ES), the ESS being stored in a computer-readable repository, the ES comprising a callable service that provides business functionality, the ESS identifying the ES and comprising a concatenation of terms and a notation; segmenting, by the one or more processors, the ESS based on the notation to provide a segmented ESS comprising an array of terms; comparing, by the one or more processors, terms of the array of terms to metadata of a taxonomic scheme, the metadata comprising one or more neighboring entities of a respective term in the array of terms; identifying, by the one or more processors and based on the comparing, one or more known terms and one or more unknown terms from the segmented ESS, the one or more known terms matching the taxonomic scheme and the one or more unknown terms not being associated with the taxonomic scheme; determining, by the one or more processors, that at least one unknown term of the one or more unknown terms comprises at least one of a specialization and a new entity based on combining a cohesion value and a correlation value, the cohesion value being based on a number of times the at least one unknown term is used with one of the one or more known terms and the correlation value being based on a number of times the at least one unknown term is used with other known terms; and extending, by the one or more processors, the knowledge base in view of the at least one of the specialization and the new entity.
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1. A computer-implemented method for extending a knowledge base, the method being executed using one or more processors and comprising: receiving an enterprise service signature (ESS) associated with an enterprise service (ES), the ESS being stored in a computer-readable repository, the ES comprising a callable service that provides business functionality, the ESS identifying the ES and comprising a concatenation of terms and a notation; segmenting, by the one or more processors, the ESS based on the notation to provide a segmented ESS comprising an array of terms; comparing, by the one or more processors, terms of the array of terms to metadata of a taxonomic scheme, the metadata comprising one or more neighboring entities of a respective term in the array of terms; identifying, by the one or more processors and based on the comparing, one or more known terms and one or more unknown terms from the segmented ESS, the one or more known terms matching the taxonomic scheme and the one or more unknown terms not being associated with the taxonomic scheme; determining, by the one or more processors, that at least one unknown term of the one or more unknown terms comprises at least one of a specialization and a new entity based on combining a cohesion value and a correlation value, the cohesion value being based on a number of times the at least one unknown term is used with one of the one or more known terms and the correlation value being based on a number of times the at least one unknown term is used with other known terms; and extending, by the one or more processors, the knowledge base in view of the at least one of the specialization and the new entity. 8. The method of claim 1 , wherein extending the knowledge base comprises automatically generating an automata based on the at least one unknown term, the automata representing a naming convention of an ES.
| 0.53219 |
2. The method of claim 1 , further comprising evaluating the function with at least one object to provide an output.
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2. The method of claim 1 , further comprising evaluating the function with at least one object to provide an output. 3. The method of claim 2 , further comprising serializing the output and organizing the output for display on a graphical output device.
| 0.952131 |
11. A dialog system, comprising: a speech recognition unit receiving a user utterance including a proper name; a recognizer unit recognizing the proper name in the user utterance; a scoring unit determining a first confidence score for the recognized proper name; and a question formulation unit generating a first machine response the user utterance including an indirect confirmation question related to the proper name, wherein the first machine response does not repeat the proper name, if the first confidence score is below a defined threshold value, wherein the speech recognizer unit receives a user response to the indirect confirmation question, and the scoring unit modifies the first confidence score to generate a second confidence score based on the user response.
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11. A dialog system, comprising: a speech recognition unit receiving a user utterance including a proper name; a recognizer unit recognizing the proper name in the user utterance; a scoring unit determining a first confidence score for the recognized proper name; and a question formulation unit generating a first machine response the user utterance including an indirect confirmation question related to the proper name, wherein the first machine response does not repeat the proper name, if the first confidence score is below a defined threshold value, wherein the speech recognizer unit receives a user response to the indirect confirmation question, and the scoring unit modifies the first confidence score to generate a second confidence score based on the user response. 12. The system of claim 11 wherein the proper name comprises any part of speech describing a person, place or thing.
| 0.617906 |
1. A computer-implemented system that facilitates query comprehensions, comprising: a processor; and a memory communicatively coupled to the processor, the memory having stored therein computer-executable instructions configured to implement the query comprehension system including: a comprehension component that manages a scope of a control variable; and a transformation component that receives from a user a query that includes initialization data and a set of query clauses in a sequence characterized by a query expression, wherein the user can perform at least the following: input new control variables into the received user-inputted query, the control variables comprising unique local variables that are configured to represent a property or column of an individual data row in a collection as the user-inputted query evaluates, hide existing control variables in the user-inputted query that are determined to be out of scope when the hidden variables are no longer part of the user-inputted query, reveal hidden variables that are determined to be in scope when the previously hidden variables are now part of the user-inputted query and implement the existing control variables in a different syntactical order than that in which the new control variables were inputted in the user-inputted query, wherein the control variable of the user inputted query have no syntactical order restriction, and wherein: the initialization data includes a control variable and at least one of a collection or an expression; the transformation component resolves values of the control variable in scope for each query clause, and based upon a type of each query clause, respectively; the transformation component operates on each query clause in a manner that is independent of an ordering of the sequence; and the transformation component outputs the results of the transformation performed on the collection or expression based upon the query expression and based on the number of control variables in scope, wherein the format in which the results are output is variable depending on the number of control variables in scope.
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1. A computer-implemented system that facilitates query comprehensions, comprising: a processor; and a memory communicatively coupled to the processor, the memory having stored therein computer-executable instructions configured to implement the query comprehension system including: a comprehension component that manages a scope of a control variable; and a transformation component that receives from a user a query that includes initialization data and a set of query clauses in a sequence characterized by a query expression, wherein the user can perform at least the following: input new control variables into the received user-inputted query, the control variables comprising unique local variables that are configured to represent a property or column of an individual data row in a collection as the user-inputted query evaluates, hide existing control variables in the user-inputted query that are determined to be out of scope when the hidden variables are no longer part of the user-inputted query, reveal hidden variables that are determined to be in scope when the previously hidden variables are now part of the user-inputted query and implement the existing control variables in a different syntactical order than that in which the new control variables were inputted in the user-inputted query, wherein the control variable of the user inputted query have no syntactical order restriction, and wherein: the initialization data includes a control variable and at least one of a collection or an expression; the transformation component resolves values of the control variable in scope for each query clause, and based upon a type of each query clause, respectively; the transformation component operates on each query clause in a manner that is independent of an ordering of the sequence; and the transformation component outputs the results of the transformation performed on the collection or expression based upon the query expression and based on the number of control variables in scope, wherein the format in which the results are output is variable depending on the number of control variables in scope. 8. The system of claim 1 , the set of query clauses is not required to include an explicit termination query clause.
| 0.528052 |
1. A method to process a document, comprising: partitioning, with a tokenizer operating on at least one computer, document text separated by spaces into a plurality of tokens based on the spaces; identifying, with a token processing unit operating on at least one computer, tokens to be ignored and not considered; determining, with the token processing unit, that a first token considered of the plurality of tokens comprises a chemical name fragment, wherein determining comprises: examining syntax of the first token, examining context of the first token with respect to at least one adjacent token of the plurality of tokens, and taking into account the syntax and the context, applying to the first token a plurality of regular expressions, rules, and a plurality of dictionaries comprised of a prefix dictionary, and a suffix dictionary to recognize the chemical name fragments; adding, with the token processing unit, the recognized chemical name fragment to a vector of chemical name fragments, where the chemical name fragment is identified by a vector index variable; combining, with the token processing unit, the recognized chemical name fragment with at least one of the adjacent tokens that are determined to be a chemical name fragment into a complete chemical name, where combining comprises: initializing the chemical name fragment vector index variable, incrementing the chemical name fragment vector index variable, where the incrementing continues at least until no chemical name fragments remain; setting a string combination to include the chemical name fragments identified by the initialized and incremented chemical name fragment vector index variables, and adding the string combination to a vector c as the complete chemical name; assigning, with a sentence parser unit operating on at least one computer, the complete chemical name with one part of speech; and storing in a memory the complete chemical name assigned with the one part of speech.
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1. A method to process a document, comprising: partitioning, with a tokenizer operating on at least one computer, document text separated by spaces into a plurality of tokens based on the spaces; identifying, with a token processing unit operating on at least one computer, tokens to be ignored and not considered; determining, with the token processing unit, that a first token considered of the plurality of tokens comprises a chemical name fragment, wherein determining comprises: examining syntax of the first token, examining context of the first token with respect to at least one adjacent token of the plurality of tokens, and taking into account the syntax and the context, applying to the first token a plurality of regular expressions, rules, and a plurality of dictionaries comprised of a prefix dictionary, and a suffix dictionary to recognize the chemical name fragments; adding, with the token processing unit, the recognized chemical name fragment to a vector of chemical name fragments, where the chemical name fragment is identified by a vector index variable; combining, with the token processing unit, the recognized chemical name fragment with at least one of the adjacent tokens that are determined to be a chemical name fragment into a complete chemical name, where combining comprises: initializing the chemical name fragment vector index variable, incrementing the chemical name fragment vector index variable, where the incrementing continues at least until no chemical name fragments remain; setting a string combination to include the chemical name fragments identified by the initialized and incremented chemical name fragment vector index variables, and adding the string combination to a vector c as the complete chemical name; assigning, with a sentence parser unit operating on at least one computer, the complete chemical name with one part of speech; and storing in a memory the complete chemical name assigned with the one part of speech. 2. A method as in claim 1 , where the complete chemical name is assigned a noun phrase part of speech.
| 0.56354 |
8. A system, comprising: a processor coupled to a memory, the processor configured to execute computer-executable instructions stored in the memory that when executed, perform the following acts: receive a data analysis expression comprising a calculation and a relationship, from multiple relationships between data of two tables of a database, to employ with respect to the calculation; override a default relationship of the database with the relationship by setting the default relationship as active and other relationships of the multiple relationships as inactive; retrieve data from the two tables for the calculation based on the active relationship, wherein the active relationship enables acquisition of data based on a particular column of matching data in the two tables; initiate execution of the calculation on the data, wherein execution of the calculation comprises evaluating an expression specified by the calculation on the data retrieved from the two tables; restore the default relationship after execution of the calculation is complete by setting the default relationship as active and other relationships of the multiple relationships as inactive; and return a result of execution of the calculation.
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8. A system, comprising: a processor coupled to a memory, the processor configured to execute computer-executable instructions stored in the memory that when executed, perform the following acts: receive a data analysis expression comprising a calculation and a relationship, from multiple relationships between data of two tables of a database, to employ with respect to the calculation; override a default relationship of the database with the relationship by setting the default relationship as active and other relationships of the multiple relationships as inactive; retrieve data from the two tables for the calculation based on the active relationship, wherein the active relationship enables acquisition of data based on a particular column of matching data in the two tables; initiate execution of the calculation on the data, wherein execution of the calculation comprises evaluating an expression specified by the calculation on the data retrieved from the two tables; restore the default relationship after execution of the calculation is complete by setting the default relationship as active and other relationships of the multiple relationships as inactive; and return a result of execution of the calculation. 10. The system of claim 8 , the multiple relationships are assigned weighted priorities and an ambiguity is resolved based on the weighted priorities.
| 0.564112 |
1. A method, comprising: identifying, by a computing device, characteristics of a relational database; generating, by the computing device, tokens from the characteristics of the relational database; receiving, by the computing device, a search request containing a search term entered into a field of a user interface; identifying, by the computing device, a set of the tokens associated with the search term; automatically generating, by the computing device, a structured query based on the set of the tokens associated with the search term; using, by the computing device, the structured query to retrieve data in the relational database; classifying the tokens as non-numeric attributes and numeric measures; identifying a first one of the tokens associated with the search term; identifying the first one of the tokens as one of the non-numeric attributes; identifying a first table associated with the first one of the tokens containing the non-numeric attributes; searching for a second table linked to the first table containing numeric measures; displaying a second one of the tokens associated with the second table; and displaying the numeric measures from the second table in response to identifying the first one of the tokens as one of the non-numeric attributes.
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1. A method, comprising: identifying, by a computing device, characteristics of a relational database; generating, by the computing device, tokens from the characteristics of the relational database; receiving, by the computing device, a search request containing a search term entered into a field of a user interface; identifying, by the computing device, a set of the tokens associated with the search term; automatically generating, by the computing device, a structured query based on the set of the tokens associated with the search term; using, by the computing device, the structured query to retrieve data in the relational database; classifying the tokens as non-numeric attributes and numeric measures; identifying a first one of the tokens associated with the search term; identifying the first one of the tokens as one of the non-numeric attributes; identifying a first table associated with the first one of the tokens containing the non-numeric attributes; searching for a second table linked to the first table containing numeric measures; displaying a second one of the tokens associated with the second table; and displaying the numeric measures from the second table in response to identifying the first one of the tokens as one of the non-numeric attributes. 8. The method of claim 1 , further comprising: receiving a portion of the search request as an unstructured input; comparing the portion of the search request with the tokens; and suggesting some of the tokens for replacing the portion of the search request.
| 0.503554 |
1. A control apparatus for controlling electronic equipment and for designating and controlling an operation mode thereof, comprising: an acoustic-electric transducer for receiving spoken instructions from a user designating the operation mode and for outputting an electric speech signal in response thereto; speech recognition means receiving the electric speech signal output from the acoustic-electric transducer for recognizing words in the electric speech signal and outputting a signal corresponding to the recognized words; animation character generating means for producing a video signal of an animation character who is a message speaker that interacts with the user; video image display means for displaying the video signal from the animation character generating means; speech synthesizing means for synthesizing a speech signal of a message spoken by the animation character; speech outputting means for transmitting the speech signal from the speech synthesizing means in audible human sounds; and a microprocessor responsive to the output signal from the speech recognition means for producing an operation mode designation and control signal for designating the operation mode of the electronic equipment and controlling the electronic equipment to operate in the designated mode, an action control signal fed to the animation character generating means for controlling the action of the animation character, and a message signal fed to the speech synthesizing means instructing a message signal to be synthesized in the speech synthesizing means, wherein the microprocessor performs natural language or dialogue inference processing of the output signal from the speech recognition means.
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1. A control apparatus for controlling electronic equipment and for designating and controlling an operation mode thereof, comprising: an acoustic-electric transducer for receiving spoken instructions from a user designating the operation mode and for outputting an electric speech signal in response thereto; speech recognition means receiving the electric speech signal output from the acoustic-electric transducer for recognizing words in the electric speech signal and outputting a signal corresponding to the recognized words; animation character generating means for producing a video signal of an animation character who is a message speaker that interacts with the user; video image display means for displaying the video signal from the animation character generating means; speech synthesizing means for synthesizing a speech signal of a message spoken by the animation character; speech outputting means for transmitting the speech signal from the speech synthesizing means in audible human sounds; and a microprocessor responsive to the output signal from the speech recognition means for producing an operation mode designation and control signal for designating the operation mode of the electronic equipment and controlling the electronic equipment to operate in the designated mode, an action control signal fed to the animation character generating means for controlling the action of the animation character, and a message signal fed to the speech synthesizing means instructing a message signal to be synthesized in the speech synthesizing means, wherein the microprocessor performs natural language or dialogue inference processing of the output signal from the speech recognition means. 9. A control apparatus for controlling electronic equipment as defined in claim 1, wherein the acoustic-electric transducer includes a switch for designating a speech input state and in which the speech input is divided by turning the switch on and off.
| 0.585148 |
13. The method of claim 1 further comprising utilizing a plurality of fact checking implementations initially, wherein each fact checking implementation utilizes a different set of source information, and comparing results of each fact checking implementation, and iteratively eliminating a fact checking implementation of the plurality of fact checking implementations with a lowest confidence score until a single fact checking implementation remains.
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13. The method of claim 1 further comprising utilizing a plurality of fact checking implementations initially, wherein each fact checking implementation utilizes a different set of source information, and comparing results of each fact checking implementation, and iteratively eliminating a fact checking implementation of the plurality of fact checking implementations with a lowest confidence score until a single fact checking implementation remains. 15. The method of claim 13 wherein the single fact checking implementation determined by eliminating other fact checking implementations is utilized for a specific type of content and is reused for future content that is the same type of content as the specific type of content.
| 0.924424 |
7. A system for providing assertions regarding an item query, the system comprising: at least one data store configured to store assertions, wherein each assertion is representative of at least one search criterion, and wherein the at least one search criterion is determined based at least in part on a previous action of at least one user taken in response to results of a previously executed query, and wherein each assertion is selectable by an additional user to generate a new query based at least in part on modified set of search criteria corresponding to each assertion; and one or more processors in communication with the at least one data store, the one or more processors configured to: receive, from a user computing device, a query including search criteria; determine an assertion of the stored assertions that is relevant to the received query based at least in part on the search criteria; transmit, to the user computing device, a display page including results of the query and the assertion that is relevant to the query; receive a user selection of the assertion, wherein the user selection of the assertion corresponds to a user request to generate a new query based at least in part on modifying the search criteria included within the received query in accordance with the at least one search criterion represented by the assertion; generate the new query based at least in part on modifying the search criteria included within the received query in accordance with the at least one search criterion represented by the determined assertion; and transmit results of the new query to the user computing device.
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7. A system for providing assertions regarding an item query, the system comprising: at least one data store configured to store assertions, wherein each assertion is representative of at least one search criterion, and wherein the at least one search criterion is determined based at least in part on a previous action of at least one user taken in response to results of a previously executed query, and wherein each assertion is selectable by an additional user to generate a new query based at least in part on modified set of search criteria corresponding to each assertion; and one or more processors in communication with the at least one data store, the one or more processors configured to: receive, from a user computing device, a query including search criteria; determine an assertion of the stored assertions that is relevant to the received query based at least in part on the search criteria; transmit, to the user computing device, a display page including results of the query and the assertion that is relevant to the query; receive a user selection of the assertion, wherein the user selection of the assertion corresponds to a user request to generate a new query based at least in part on modifying the search criteria included within the received query in accordance with the at least one search criterion represented by the assertion; generate the new query based at least in part on modifying the search criteria included within the received query in accordance with the at least one search criterion represented by the determined assertion; and transmit results of the new query to the user computing device. 13. The system of claim 7 , wherein the previous action corresponds to at least one of searching for an item or acquiring an item.
| 0.599951 |
8. A computer-implemented method for summarizing the differences between network resources, the method comprising: under the control of a network computing component executing on one or more physical computing components of a network computing provider, the physical computing components configured to execute specific instructions, obtaining data regarding a measurement of differences between a plurality of versions of a plurality of network resources, wherein the plurality of network resources are related, and wherein the differences are differences between versions of a single network resource; causing the display of a plurality of objects, each object corresponding to one of the plurality of network resources, wherein each object represents the measurement of differences between the plurality of versions of the corresponding network resource; and causing the display of a plurality of connections, each connection graphically associating two or more objects with each other, wherein each connection represents a shared property of the network resources represented by each of the associated objects.
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8. A computer-implemented method for summarizing the differences between network resources, the method comprising: under the control of a network computing component executing on one or more physical computing components of a network computing provider, the physical computing components configured to execute specific instructions, obtaining data regarding a measurement of differences between a plurality of versions of a plurality of network resources, wherein the plurality of network resources are related, and wherein the differences are differences between versions of a single network resource; causing the display of a plurality of objects, each object corresponding to one of the plurality of network resources, wherein each object represents the measurement of differences between the plurality of versions of the corresponding network resource; and causing the display of a plurality of connections, each connection graphically associating two or more objects with each other, wherein each connection represents a shared property of the network resources represented by each of the associated objects. 10. The computer-implemented method of claim 8 , wherein each of the plurality of objects comprises a color representing the measurement of differences between the plurality of versions of the corresponding network resource.
| 0.522786 |
1. A method for ability enhancement, the method comprising: by a computer system, receiving data representing speech signals from a voice conference amongst multiple speakers, wherein the multiple speakers are remotely located from one another, wherein each of the multiple speakers uses a separate conferencing device to participate in the voice conference; determining speaker-related information associated with the multiple speakers, based on the data representing speech signals from the voice conference; recording conference history information based on the speaker-related information, by recording indications of topics discussed during the voice conference by: performing speech recognition to convert the data representing speech signals into text; analyzing the text to identify frequently used terms or phrases; and determining the topics discussed during the voice conference based on the frequently used terms or phrases; audibly notifying a user to view the conference history information on a display device, wherein the user is notified in a manner that is not audible to at least some of the multiple speakers; and presenting, on the display device, at least some of the conference history information to the user; translating an utterance of one of the multiple speakers in a first language into a message in a second language, based on the speaker-related information, wherein the speaker related information is determined by automatically determining the second and the first language comprising steps of: concurrently or simultaneously applying multiple speech recognizers and using GPS information indicating the speakers' locations; and recording the message in the second language as part of the conference history information.
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1. A method for ability enhancement, the method comprising: by a computer system, receiving data representing speech signals from a voice conference amongst multiple speakers, wherein the multiple speakers are remotely located from one another, wherein each of the multiple speakers uses a separate conferencing device to participate in the voice conference; determining speaker-related information associated with the multiple speakers, based on the data representing speech signals from the voice conference; recording conference history information based on the speaker-related information, by recording indications of topics discussed during the voice conference by: performing speech recognition to convert the data representing speech signals into text; analyzing the text to identify frequently used terms or phrases; and determining the topics discussed during the voice conference based on the frequently used terms or phrases; audibly notifying a user to view the conference history information on a display device, wherein the user is notified in a manner that is not audible to at least some of the multiple speakers; and presenting, on the display device, at least some of the conference history information to the user; translating an utterance of one of the multiple speakers in a first language into a message in a second language, based on the speaker-related information, wherein the speaker related information is determined by automatically determining the second and the first language comprising steps of: concurrently or simultaneously applying multiple speech recognizers and using GPS information indicating the speakers' locations; and recording the message in the second language as part of the conference history information. 33. The method of claim 1 , further comprising: performing the receiving data representing speech signals from a voice conference amongst multiple speakers, the determining speaker-related information associated with the multiple speakers, the recording conference history information based on the speaker-related information, and/or the presenting at least some of the conference history information on a general purpose computing device that is operated by the user.
| 0.541197 |
20. The computer readable storage medium of claim 19 , wherein the two or more alternative interpretations of user intent each specify a respective constrained selection task of identifying items of a respective selection domain based on one or more respective selection criteria.
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20. The computer readable storage medium of claim 19 , wherein the two or more alternative interpretations of user intent each specify a respective constrained selection task of identifying items of a respective selection domain based on one or more respective selection criteria. 21. The computer readable storage medium of claim 20 , wherein the one or more commonalities include a common constraint for the respective constrained selection tasks.
| 0.83215 |
4. The method of claim 3 , wherein the new feature-space speaker adaptation parameters include a first non-diagonal matrix, and wherein replacing the updated feature-space speaker adaptation parameters with the new feature-space speaker adaptation parameters comprises replacing the second diagonal matrix with the first non-diagonal matrix.
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4. The method of claim 3 , wherein the new feature-space speaker adaptation parameters include a first non-diagonal matrix, and wherein replacing the updated feature-space speaker adaptation parameters with the new feature-space speaker adaptation parameters comprises replacing the second diagonal matrix with the first non-diagonal matrix. 5. The method of claim 4 , further comprising: after replacing the second diagonal matrix with the first non-diagonal matrix, applying the non-diagonal matrix to a second subsequently-received feature vector; and updating the non-diagonal matrix based on the second subsequently-received feature vector.
| 0.863039 |
15. The computer-readable medium of claim 12 , wherein said second tier functionality is operable to enable said user to modify said default expression.
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15. The computer-readable medium of claim 12 , wherein said second tier functionality is operable to enable said user to modify said default expression. 17. The computer-readable medium of claim 15 , wherein said first tier functionality is operable to display a modified expression showing on-the-fly said group in said new position.
| 0.930587 |
1. A computer-implemented method for identifying similar documents, comprising: receiving document text for a current document, the current document including a plurality of metadata fields and corresponding portions of the document text; determining a first descriptiveness score for each word of the document text based on a first corpus; determining a prominence score for each word of the document text, the prominence score for a particular word being based on a non-compound likelihood for the particular word, the non-compound likelihood for the particular word being based on a probability that the particular word and a word that is adjacent to the particular word in the current document do not combine to form a word compound; modifying the first descriptiveness score for each word based on a weight assigned to the metadata field to which the word corresponds; determining a comparison metric for the current document based on the modified first descriptiveness score for each word and the prominence score for each word; finding, using a query processor, at least one potential document, wherein document text for each potential document includes at least one word from the current document; and analyzing each found potential document to identify at least one similar document as a function of a comparison metric for the respective potential document and the comparison metric for the current document.
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1. A computer-implemented method for identifying similar documents, comprising: receiving document text for a current document, the current document including a plurality of metadata fields and corresponding portions of the document text; determining a first descriptiveness score for each word of the document text based on a first corpus; determining a prominence score for each word of the document text, the prominence score for a particular word being based on a non-compound likelihood for the particular word, the non-compound likelihood for the particular word being based on a probability that the particular word and a word that is adjacent to the particular word in the current document do not combine to form a word compound; modifying the first descriptiveness score for each word based on a weight assigned to the metadata field to which the word corresponds; determining a comparison metric for the current document based on the modified first descriptiveness score for each word and the prominence score for each word; finding, using a query processor, at least one potential document, wherein document text for each potential document includes at least one word from the current document; and analyzing each found potential document to identify at least one similar document as a function of a comparison metric for the respective potential document and the comparison metric for the current document. 6. The method of claim 1 , wherein the modifying the first descriptiveness score for each word comprises modifying the first descriptiveness score of a particular word based on a comparison of the particular word to a corpus of first and last names of persons.
| 0.650381 |
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