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2. A method in a computing device for calculating a bid amount for a keyword, the method comprising: collecting, at one or more computer systems, conversion information for the keyword indicating financial benefit resulting from users selecting advertisements displayed with content that relates to the keyword, the financial benefit being organized into categories; determining, at the one or more computer systems, a category-specific advertising expense factor for each category; calculating, at the one or more computer systems, a category-specific product for each category, the category specific product calculated by multiplying the financial benefit for the category by the category-specific advertising expense factor determined for the category; generating, at the one or more computer systems, a summation of the calculated category-specific products; generating, at the one or more computer systems, a quotient, wherein the quotient is the summation of the category-specific products divided by a number of sessions with financial benefit; and generating, at the one or more computer systems, a bid amount for the keyword based at least in part on the quotient multiplied by a forecast conversion rate, the forecast conversion rate comprising a predicted percentage of clickthroughs associated with the keyword that results in a conversion.
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2. A method in a computing device for calculating a bid amount for a keyword, the method comprising: collecting, at one or more computer systems, conversion information for the keyword indicating financial benefit resulting from users selecting advertisements displayed with content that relates to the keyword, the financial benefit being organized into categories; determining, at the one or more computer systems, a category-specific advertising expense factor for each category; calculating, at the one or more computer systems, a category-specific product for each category, the category specific product calculated by multiplying the financial benefit for the category by the category-specific advertising expense factor determined for the category; generating, at the one or more computer systems, a summation of the calculated category-specific products; generating, at the one or more computer systems, a quotient, wherein the quotient is the summation of the category-specific products divided by a number of sessions with financial benefit; and generating, at the one or more computer systems, a bid amount for the keyword based at least in part on the quotient multiplied by a forecast conversion rate, the forecast conversion rate comprising a predicted percentage of clickthroughs associated with the keyword that results in a conversion. 4. The method of claim 2 wherein the financial benefit is profit generated from purchases of items within a category during a session initiated with the selection of an advertisement for the keyword and the category-specific advertising expense factor is a percent of profit to be spent on advertising for the category of the purchased item.
| 0.546226 |
1. A computer-implemented method for program code library selection in a networked computing environment, comprising: receiving a search results file in a library selection integrated development environment (IDE) from a library searching IDE, the search results file comprising at least one method and at least one class from a first program code file in the library searching IDE, and the search results file having a set of attributes; determining whether to perform a micro-benchmarking on the at least one method and the at least one class of the search results file, the determining being based on at least one of: a configuration of a second program code file in the library selection IDE, or a detected code pattern of the second program code file; performing, responsive to the determining, the micro-benchmarking on the at least one method and the at least one class, and storing an associated micro-benchmark time and an invocation timestamp in a computer storage device; calculating a set of code style similarity scores that indicate a similarity between the at least one method and the at least one class with the methods and classes of the second program code file based on code syntax similarity; and providing an ordered list of the methods and classes of the second program code file based on the set of code style similarity scores, the micro-benchmarking, and the set of attributes.
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1. A computer-implemented method for program code library selection in a networked computing environment, comprising: receiving a search results file in a library selection integrated development environment (IDE) from a library searching IDE, the search results file comprising at least one method and at least one class from a first program code file in the library searching IDE, and the search results file having a set of attributes; determining whether to perform a micro-benchmarking on the at least one method and the at least one class of the search results file, the determining being based on at least one of: a configuration of a second program code file in the library selection IDE, or a detected code pattern of the second program code file; performing, responsive to the determining, the micro-benchmarking on the at least one method and the at least one class, and storing an associated micro-benchmark time and an invocation timestamp in a computer storage device; calculating a set of code style similarity scores that indicate a similarity between the at least one method and the at least one class with the methods and classes of the second program code file based on code syntax similarity; and providing an ordered list of the methods and classes of the second program code file based on the set of code style similarity scores, the micro-benchmarking, and the set of attributes. 4. The computer-implemented method of claim 1 , the code pattern comprising a complex code pattern.
| 0.898167 |
1. A method for assigning an annotation to a variable and a statement in a source code of a software application, the method comprising: generating, by a processor, an intermediate representation of the source code by parsing the source code, wherein the source code comprises a plurality of variables; identifying one or more instances of definition of the variable of the plurality of variables present in the intermediate representation; identifying, one or more instances of use of the variable in the intermediate representation; categorizing, by the processor, the variable into a group of variables based on: a) the one or more instances of definition of the variable, b) the one or more instances of use of the variable, c) a description of the variable, and d) mathematical operators defining a correlation between the variable and one or more other variables of the plurality of variables, wherein the description of the variable indicates a nature of data stored in the variable, and wherein the group of variables comprises variables storing data of similar nature; creating a data description table of the plurality of variables, wherein the data description table comprises the variable and the description of the variable; creating, by the processor, a data dictionary of the plurality of variables, wherein the data dictionary comprises the group of variables and the description of the variables present in the group of variables; and assigning, by the processor, the annotation to the variable present in the statement of the source code based on the data description table and the data dictionary, thereby assigning the annotation to the statement in the source code of the software application.
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1. A method for assigning an annotation to a variable and a statement in a source code of a software application, the method comprising: generating, by a processor, an intermediate representation of the source code by parsing the source code, wherein the source code comprises a plurality of variables; identifying one or more instances of definition of the variable of the plurality of variables present in the intermediate representation; identifying, one or more instances of use of the variable in the intermediate representation; categorizing, by the processor, the variable into a group of variables based on: a) the one or more instances of definition of the variable, b) the one or more instances of use of the variable, c) a description of the variable, and d) mathematical operators defining a correlation between the variable and one or more other variables of the plurality of variables, wherein the description of the variable indicates a nature of data stored in the variable, and wherein the group of variables comprises variables storing data of similar nature; creating a data description table of the plurality of variables, wherein the data description table comprises the variable and the description of the variable; creating, by the processor, a data dictionary of the plurality of variables, wherein the data dictionary comprises the group of variables and the description of the variables present in the group of variables; and assigning, by the processor, the annotation to the variable present in the statement of the source code based on the data description table and the data dictionary, thereby assigning the annotation to the statement in the source code of the software application. 8. The method of claim 1 , further comprising creating a refined data dictionary from the data dictionary by eliminating false positives for the variables present in the data dictionary.
| 0.571892 |
13. A non-transitory machine-readable storage medium comprising instructions that, when accessed by a processing device, cause the processing device to: execute, by the processing device, a numeric conversion module as a front-end and back-end translation interface to an application executed by the processing device and compiled by a compiler, wherein the numeric conversion module is dedicated for use by the application and is not used by other applications executed by the processing device; receive, by the processing device during runtime of the application, a string array of numeric data in a local language other than English, wherein the numeric data is used in calculations performed by the during runtime of the application to generate calculated numerals that are not known in code of the application during compilation of the application by the compiler; convert, by the processing device during the runtime of the application, characters of the string array of numeric data from local language characters not in English alphabet digits and not representable within the 128 characters of an American Standard Code for Information Interchange (ASCII) format into English alphabet digits representable by the 128 characters of the ASCII format by utilizing a number conversion matrix; provide, by the processing device during the runtime of the application, the English alphabet digits in the ASCII format to a processing function of the application for use with the calculations of the application during the runtime of the application; perform, by the processing device during the runtime of an application, the processing function for the application to calculate numerals as English alphabet digits in the ASCII format; convert, by the processing device during the runtime of the application; the calculated numerals to translated numeric data in the local language other than English by utilizing the number conversion matrix; and provide the translated numeric data to an end user of the application during the runtime of the application without modifying the compiler to process the numeric data in the local language other than English.
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13. A non-transitory machine-readable storage medium comprising instructions that, when accessed by a processing device, cause the processing device to: execute, by the processing device, a numeric conversion module as a front-end and back-end translation interface to an application executed by the processing device and compiled by a compiler, wherein the numeric conversion module is dedicated for use by the application and is not used by other applications executed by the processing device; receive, by the processing device during runtime of the application, a string array of numeric data in a local language other than English, wherein the numeric data is used in calculations performed by the during runtime of the application to generate calculated numerals that are not known in code of the application during compilation of the application by the compiler; convert, by the processing device during the runtime of the application, characters of the string array of numeric data from local language characters not in English alphabet digits and not representable within the 128 characters of an American Standard Code for Information Interchange (ASCII) format into English alphabet digits representable by the 128 characters of the ASCII format by utilizing a number conversion matrix; provide, by the processing device during the runtime of the application, the English alphabet digits in the ASCII format to a processing function of the application for use with the calculations of the application during the runtime of the application; perform, by the processing device during the runtime of an application, the processing function for the application to calculate numerals as English alphabet digits in the ASCII format; convert, by the processing device during the runtime of the application; the calculated numerals to translated numeric data in the local language other than English by utilizing the number conversion matrix; and provide the translated numeric data to an end user of the application during the runtime of the application without modifying the compiler to process the numeric data in the local language other than English. 16. The non-transitory machine-readable storage medium of claim 13 , wherein the local language is Hindi.
| 0.781893 |
15. The system of claim 14 , wherein an identifier of the data item and the first temporal indicator assigned to the data item are stored in an indexed database table.
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15. The system of claim 14 , wherein an identifier of the data item and the first temporal indicator assigned to the data item are stored in an indexed database table. 18. The system of claim 15 , wherein the database table is a SQL SERVER table.
| 0.965062 |
6. A system according to claim 5 , wherein the unplaced spine group is rotated in a direction comprising at least one of a clockwise and a counter-clockwise direction.
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6. A system according to claim 5 , wherein the unplaced spine group is rotated in a direction comprising at least one of a clockwise and a counter-clockwise direction. 7. A system according to claim 6 , further comprising: a positioning module to move the unplaced spine group outwards away from the center ring when the rotation of the unplaced spine group exceeds at least one of a maximum and minimum angle measured from a central vector along which the most similar unique spine is placed.
| 0.832502 |
9. A method as defined in claim 7 , wherein said selecting step comprises displaying a color selection chart from which colors are selected and programmed to the selected key.
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9. A method as defined in claim 7 , wherein said selecting step comprises displaying a color selection chart from which colors are selected and programmed to the selected key. 10. A method as defined in claim 9 , wherein a color is programmed to a key from a color selection chart.
| 0.91976 |
18. A tangible computer-readable medium having stored thereon a plurality of instructions which, when executed by at least one processor, cause the at least one processor to: receive, from a user, a selection of a first control action associated with a first application stored in a mobile device; receive, from the user, input that identifies a word or a phrase to be used as a voice command corresponding to the first control action; associate the identified word or phrase with the first control action; receive voice input from the user; identify the voice input as corresponding to the identified word or phrase; and perform the first control action associated with the first application based on the identified voice input.
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18. A tangible computer-readable medium having stored thereon a plurality of instructions which, when executed by at least one processor, cause the at least one processor to: receive, from a user, a selection of a first control action associated with a first application stored in a mobile device; receive, from the user, input that identifies a word or a phrase to be used as a voice command corresponding to the first control action; associate the identified word or phrase with the first control action; receive voice input from the user; identify the voice input as corresponding to the identified word or phrase; and perform the first control action associated with the first application based on the identified voice input. 20. The tangible computer-readable medium of claim 18 , further including instructions for causing the at least one processor to: allow a user to select a word or phrase corresponding to each of a plurality of control actions associated with the first application.
| 0.723426 |
13. The system of claim 8 , wherein the content preview received from the IDE system and the content generation system is based at least in part on a tone associated with the potential real-world event.
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13. The system of claim 8 , wherein the content preview received from the IDE system and the content generation system is based at least in part on a tone associated with the potential real-world event. 14. The system of claim 13 , wherein the potential real-world event is selected from the following group: a business event, a current event, a historical event, a virtual event, a sports event, a player performance during an in-progress sporting event, a financial prediction, an internal reporting event.
| 0.943626 |
15. The system of claim 10 , wherein the phonotactic grammar is an N-gram phonotactic grammar.
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15. The system of claim 10 , wherein the phonotactic grammar is an N-gram phonotactic grammar. 16. The system of claim 15 , wherein the N-gram phonotactic grammar is unsmoothed, recognizing only N-grams which have been seen in data used to train the N-gram phonotactic grammar.
| 0.934721 |
1. A method for processing messages within the framework of an integrated messaging system, comprising: ascertaining an identification, gathering text data and voice data from an instantaneous message, processing the text data and voice data from the instantaneous message by a translation system and, analyzing the processed text data and voice data together with at least one of: at least one of sound data, image data, messages with other types of media in connection with the instantaneous message, and data derived from additional information sources; data stored within the framework of previous messages in a sender data area for at least one of acquired and ascertained sender data; and data of additional features from the owner data area for at least one of acquired and ascertained owner data, such analysis being implemented according to at least one of semantic, prosodic, phonetic and other analytical methods, and image processing methods, for the presence of information/data that are suitable to convey to the recipient both the message itself and the background information in connection with the message in the most authentic form possible, both the instantaneous message and the data derived from the message being evaluated according to predefined classification rules and assigned to different classes of a linking matrix configured as assignment matrix (n:m), and the data provided within the framework of the linking matrix being stored in at least one of an index database and in a memory area for information of individual messages.
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1. A method for processing messages within the framework of an integrated messaging system, comprising: ascertaining an identification, gathering text data and voice data from an instantaneous message, processing the text data and voice data from the instantaneous message by a translation system and, analyzing the processed text data and voice data together with at least one of: at least one of sound data, image data, messages with other types of media in connection with the instantaneous message, and data derived from additional information sources; data stored within the framework of previous messages in a sender data area for at least one of acquired and ascertained sender data; and data of additional features from the owner data area for at least one of acquired and ascertained owner data, such analysis being implemented according to at least one of semantic, prosodic, phonetic and other analytical methods, and image processing methods, for the presence of information/data that are suitable to convey to the recipient both the message itself and the background information in connection with the message in the most authentic form possible, both the instantaneous message and the data derived from the message being evaluated according to predefined classification rules and assigned to different classes of a linking matrix configured as assignment matrix (n:m), and the data provided within the framework of the linking matrix being stored in at least one of an index database and in a memory area for information of individual messages. 11. The method as recited in claim 1 , wherein the incoming messages are assigned to different message types, the data resulting from the different message types being processed according to predefined classification rules and assigned to different classes/categories via a linking matrix, and the data, having been assigned to the particular classes and/or categories, are assigned to an index database of the mailbox system operator and/or stored in corresponding classes in the memory area for supplementary information of individual messages of the mailbox of the individual mailbox owner.
| 0.819343 |
15. The computer system of claim 7 , wherein the output synthesizer further comprises a morphological synthesizer adapted to perform a morphological synthesis on the surface structure using morphological descriptions of the output language and construct the output sentence in the output language.
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15. The computer system of claim 7 , wherein the output synthesizer further comprises a morphological synthesizer adapted to perform a morphological synthesis on the surface structure using morphological descriptions of the output language and construct the output sentence in the output language. 16. The computer system of claim 15 , wherein the morphological synthesis is performed on lexical meanings of constituent cores of the surface structure.
| 0.95958 |
1. A method for comparing items of anonymized data, the method comprising: receiving a plurality of items of data, each item of the plurality of items of data comprising an anonymized ordered list of words, wherein each word of the anonymized ordered list of words is anonymized in a plurality of forms and is associated with a respective item of data, wherein the plurality of forms comprise: a respective word of the anonymized ordered list of words as the respective word originally appeared, a variation of the respective word, and a metaphone encoding of the respective word; comparing, by one or more processors, a first item of the plurality of items of data with a second item of the plurality of items of data by: comparing, by one or more processors, each of the plurality of forms of each word in the first item with the corresponding form of each corresponding word in the second item; scoring, by one or more processors, each comparison of each word in the first item with each respective word in the second item based on: a degree of matching between each of the plurality of forms of each word in the first item with the corresponding form of each corresponding word in the second item; a plurality of weights assigned to each corresponding form of the plurality of forms, wherein a first weight is assigned to the respective word of the anonymized ordered list of words as the respective word originally appeared, a second weight is assigned to the variation of the respective word, and a third weight is assigned to the metaphone encoding of the respective word; and wherein the first weight exceeds the second weight and the second weight exceeds the third weight; and computing, by one or more processors, a total score for the comparison of the first item and the second item based on the scoring.
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1. A method for comparing items of anonymized data, the method comprising: receiving a plurality of items of data, each item of the plurality of items of data comprising an anonymized ordered list of words, wherein each word of the anonymized ordered list of words is anonymized in a plurality of forms and is associated with a respective item of data, wherein the plurality of forms comprise: a respective word of the anonymized ordered list of words as the respective word originally appeared, a variation of the respective word, and a metaphone encoding of the respective word; comparing, by one or more processors, a first item of the plurality of items of data with a second item of the plurality of items of data by: comparing, by one or more processors, each of the plurality of forms of each word in the first item with the corresponding form of each corresponding word in the second item; scoring, by one or more processors, each comparison of each word in the first item with each respective word in the second item based on: a degree of matching between each of the plurality of forms of each word in the first item with the corresponding form of each corresponding word in the second item; a plurality of weights assigned to each corresponding form of the plurality of forms, wherein a first weight is assigned to the respective word of the anonymized ordered list of words as the respective word originally appeared, a second weight is assigned to the variation of the respective word, and a third weight is assigned to the metaphone encoding of the respective word; and wherein the first weight exceeds the second weight and the second weight exceeds the third weight; and computing, by one or more processors, a total score for the comparison of the first item and the second item based on the scoring. 5. The method of claim 1 , wherein computing the total score is further based on a value associated with unmatched words, based on the degree of matching, in the longer item of the first item and the second item.
| 0.742131 |
12. The system of claim 11 , the method comprising correcting at least some of the one or more mislabeled pairs.
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12. The system of claim 11 , the method comprising correcting at least some of the one or more mislabeled pairs. 16. The system of claim 12 , the method comprising modifying the pre-existing relevance ranking based upon at least some of the corrected pairs.
| 0.939602 |
9. The classification system of claim 1 , wherein said processor is further configured to weight said probability function of one attribute with respect to a probability function of at least one other attribute of said object.
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9. The classification system of claim 1 , wherein said processor is further configured to weight said probability function of one attribute with respect to a probability function of at least one other attribute of said object. 10. The classification system of claim 9 , wherein said weighting of a probability function comprises scaling probability functions of other attributes.
| 0.913147 |
1. A method of identifying a name and boundary of a neighborhood based on web documents, the method comprising: extracting, via one or more processors, n-grams appearing in a plurality of web documents and being of less than a threshold word count: obtaining a plurality of web documents, each web document being associated with a respective geographic location, the web documents including user reviews of local businesses associated with the respective geographic locations in the geographic information system, extracting n-grams from each of the web documents; associating, via the one or more processors, the n-grams with geographic locations associated with the web documents from which the n-grams were extracted, including associating each of the n-grams with a respective latitude and longitude coordinate of the web document from which the n-grams were extracted; identifying, via the one or more processors, a neighborhood by identifying a cluster of geographic locations associated with the n-grams, including: filtering from the n-grams stop-words, filtering from the n-grams phrases occurring in the web documents less than a threshold amount, filtering from the n-grams at least some n-grams that do not correspond with a cluster, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of clusters, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of geographic locations outside of a cluster; determining, via the one or more processors, a boundary for the neighborhood from the distribution of geographical locations in the cluster, including determining a convex hull of the cluster by identifying geographic locations of vertices of a polygon that contains at least a substantial portion of the cluster; determining, via the one or more processors, a name for the neighborhood from the n-gram, including: designating the n-gram as a candidate name for the geographic area defined by the polygon, identifying one or more candidate names for geographic areas at least partially overlapping the polygon, ranking the candidate names based on an amount of times the name appears in the web documents and the size of the geographic areas at least partially overlapping the polygon, and selecting the highest ranking candidate name as the name; and adding, via the one or more processors, the name and boundary of the neighborhood to a geographic information system, including storing the name in memory in a record that associates the name with the geographic area defined by the boundary.
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1. A method of identifying a name and boundary of a neighborhood based on web documents, the method comprising: extracting, via one or more processors, n-grams appearing in a plurality of web documents and being of less than a threshold word count: obtaining a plurality of web documents, each web document being associated with a respective geographic location, the web documents including user reviews of local businesses associated with the respective geographic locations in the geographic information system, extracting n-grams from each of the web documents; associating, via the one or more processors, the n-grams with geographic locations associated with the web documents from which the n-grams were extracted, including associating each of the n-grams with a respective latitude and longitude coordinate of the web document from which the n-grams were extracted; identifying, via the one or more processors, a neighborhood by identifying a cluster of geographic locations associated with the n-grams, including: filtering from the n-grams stop-words, filtering from the n-grams phrases occurring in the web documents less than a threshold amount, filtering from the n-grams at least some n-grams that do not correspond with a cluster, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of clusters, filtering from the n-grams at least some n-grams that correspond to more than a threshold amount of geographic locations outside of a cluster; determining, via the one or more processors, a boundary for the neighborhood from the distribution of geographical locations in the cluster, including determining a convex hull of the cluster by identifying geographic locations of vertices of a polygon that contains at least a substantial portion of the cluster; determining, via the one or more processors, a name for the neighborhood from the n-gram, including: designating the n-gram as a candidate name for the geographic area defined by the polygon, identifying one or more candidate names for geographic areas at least partially overlapping the polygon, ranking the candidate names based on an amount of times the name appears in the web documents and the size of the geographic areas at least partially overlapping the polygon, and selecting the highest ranking candidate name as the name; and adding, via the one or more processors, the name and boundary of the neighborhood to a geographic information system, including storing the name in memory in a record that associates the name with the geographic area defined by the boundary. 12. The method of claim 1 , comprising: receiving a search query including the name; identifying a geographic area defined by the boundary based on an association with the name in the geographic information system; ranking search results based on the geographic area; selecting an advertisement based on the name or the geographic area; and sending the advertisement and the search result.
| 0.5 |
13. A computer program product stored on a non-transitory tangible computer usable medium for analyzing speech, comprising: program code that when executed by a processor: converts inputted speech received from a speaker to text; displays the text in a textual interface; automatically generates feedback information, that comprises results of an analysis of the inputted speech and/or text, by automatically analyzing the inputted speech and/or text; and automatically outputs the feedback information as annotations in the textual interface, wherein the annotations are distinct from the inputted speech and text.
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13. A computer program product stored on a non-transitory tangible computer usable medium for analyzing speech, comprising: program code that when executed by a processor: converts inputted speech received from a speaker to text; displays the text in a textual interface; automatically generates feedback information, that comprises results of an analysis of the inputted speech and/or text, by automatically analyzing the inputted speech and/or text; and automatically outputs the feedback information as annotations in the textual interface, wherein the annotations are distinct from the inputted speech and text. 20. The computer program product of claim 13 , wherein the feedback information is displayed in the textual interface that displays highlighted text along with annotations.
| 0.674121 |
6. The method of claim 4 , wherein the first menu is selectable from a plurality of menus for setting a language for each of the OSD function, the audio function, and the caption function.
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6. The method of claim 4 , wherein the first menu is selectable from a plurality of menus for setting a language for each of the OSD function, the audio function, and the caption function. 7. The method of claim 6 , wherein the first menu corresponds to one selected from the group consisting of the OSD function menu, the audio function menu, and the caption function menu, and wherein the at least one other function corresponds to a set of menus including at least one of a remainder of the group.
| 0.83283 |
17. A computer implemented method for analyzing an externally generated document for use in a document management system of the type having a Native Template database including a list of templates for one or more types of documents having common characteristics and Conversion Database including a list of one or more data points associated with each listed document type, one or more descriptive text entries associated with each listed data point, and Proximity information which describes the location of the data point in relation to the Descriptive Text, the method comprising the steps of: (gg) setting up the system to determine how a specific variation of a document relates to a template. (hh) introducing the externally generated document into the system; (ii) analyzing the introduced document by selecting a template from the Native Template database relating to a document type that has characteristics in common with the introduced document, selecting a data point from the template, searching the introduced document for text associated with the selected data point and, if text associated with the selected data point is located, recording the data point and the location of the associated text in the Conversion Database, if text associated with the selected data point is not located, not recording any data; (jj) presenting the recorded data to the user for review; and (kk) approving, modifying or rejecting the presented data.
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17. A computer implemented method for analyzing an externally generated document for use in a document management system of the type having a Native Template database including a list of templates for one or more types of documents having common characteristics and Conversion Database including a list of one or more data points associated with each listed document type, one or more descriptive text entries associated with each listed data point, and Proximity information which describes the location of the data point in relation to the Descriptive Text, the method comprising the steps of: (gg) setting up the system to determine how a specific variation of a document relates to a template. (hh) introducing the externally generated document into the system; (ii) analyzing the introduced document by selecting a template from the Native Template database relating to a document type that has characteristics in common with the introduced document, selecting a data point from the template, searching the introduced document for text associated with the selected data point and, if text associated with the selected data point is located, recording the data point and the location of the associated text in the Conversion Database, if text associated with the selected data point is not located, not recording any data; (jj) presenting the recorded data to the user for review; and (kk) approving, modifying or rejecting the presented data. 22. The method of claim 17 wherein the step of setting up the system comprises the steps of: (ll) introducing a set-up document of the type associated with the template; (mm) presenting the user with the set-up document and template simultaneously; (nn) selecting a data point from the template; (oo) assigning the selected data point to a field in the Conversion Database; (pp) associating the text accompanying the selected data point with the selected data point in the assigned Conversion Database field; (qq) assigning a Data Type to the selected data point in the Conversion Database; (rr) storing a default set of Descriptive Text values and Proximities based on the context of the selected data point value; (ss) storing an additional user-specified set of Descriptive text values; (tt) assigning proximity information to each user-specified Descriptive Text value; and (uu) repeating steps (nn) through (tt) for each data point selected in the set-up document.
| 0.634022 |
1. A system for performing an ad hoc query comprising: a query service operating on a processor and configured to receive an ad hoc query in a domain-specific language; a query parsing service operating on the processor and configured to receive a validate request and a parse request from the query service and to return a query object to the query service; and a queryable interface operating on the processor and configured to receive the query object and to transmit the query object to one or more framework services for execution, wherein the ad hoc query contains one or more new key words and the query parsing service and the queryable interface are configured to add the one or more new key words if they are located in an associated model in the framework services.
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1. A system for performing an ad hoc query comprising: a query service operating on a processor and configured to receive an ad hoc query in a domain-specific language; a query parsing service operating on the processor and configured to receive a validate request and a parse request from the query service and to return a query object to the query service; and a queryable interface operating on the processor and configured to receive the query object and to transmit the query object to one or more framework services for execution, wherein the ad hoc query contains one or more new key words and the query parsing service and the queryable interface are configured to add the one or more new key words if they are located in an associated model in the framework services. 8. The system of claim 1 wherein the query object comprises a WHERE clause that is configured to specify one or more conditional expressions to filter objects that do not satisfy the conditional expressions.
| 0.5 |
1. One or more computer-readable storage memories that store executable instructions to provide search results, the executable instructions, when executed by a computer, causing the computer to perform acts comprising: receiving a query from a user; determining that the query is answerable with subjective or socially-derived information; comparing said query to a corpus of information to obtain objective results; comparing said query to a social graph to identify one or more people whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query; creating person results that comprise said one or more people and, for each of said one or more people, an explanation of each person's relevance to said query; providing, to said user, a set of results that comprise said objective results and said person results; and training a classifier to identify queries that call for subjective information using training data that comprises: a plurality of positive examples in which people were provided as search results and in which users who requested the results clicked on the people in the results; and a plurality of negative examples in which people were provided as search results and in which users who requested the results did not click on the people in the results; said determining that said query calls for subjective information being performed using said classifier, with said classifier having been trained on said training data.
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1. One or more computer-readable storage memories that store executable instructions to provide search results, the executable instructions, when executed by a computer, causing the computer to perform acts comprising: receiving a query from a user; determining that the query is answerable with subjective or socially-derived information; comparing said query to a corpus of information to obtain objective results; comparing said query to a social graph to identify one or more people whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query; creating person results that comprise said one or more people and, for each of said one or more people, an explanation of each person's relevance to said query; providing, to said user, a set of results that comprise said objective results and said person results; and training a classifier to identify queries that call for subjective information using training data that comprises: a plurality of positive examples in which people were provided as search results and in which users who requested the results clicked on the people in the results; and a plurality of negative examples in which people were provided as search results and in which users who requested the results did not click on the people in the results; said determining that said query calls for subjective information being performed using said classifier, with said classifier having been trained on said training data. 4. The one or more computer-readable storage memories of claim 1 , said query indicating a first geographic location, said aspect of relevance being based on a comparison of said first geographic locations with geographic locations of people in said social graph, said query being found to match a person who is associated with a second geographic location different from said first geographic location based on distance between said first geographic location and said second geographic location.
| 0.5 |
1. A method comprising: under control of one or more computing systems of a merchant website, the one or more computing systems configured with executable instructions, receiving, from a user of the merchant website and at the one or more computing systems, an image that illustrates an item having a corresponding item detail page within an electronic catalog; causing display of the image to the user by the one or more computing systems; receiving, from the user and at the one or more computing systems, a selection of the illustrated item; responsive to receiving the selection, causing display of a user interface by the one or more computing systems to allow the user to search the electronic catalog for the item; receiving, from the user and at the one or more computing systems, a selection of the item within the electronic catalog; and associating, by the one or more computing systems, the illustrated item with a link to the item detail page within the electronic catalog.
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1. A method comprising: under control of one or more computing systems of a merchant website, the one or more computing systems configured with executable instructions, receiving, from a user of the merchant website and at the one or more computing systems, an image that illustrates an item having a corresponding item detail page within an electronic catalog; causing display of the image to the user by the one or more computing systems; receiving, from the user and at the one or more computing systems, a selection of the illustrated item; responsive to receiving the selection, causing display of a user interface by the one or more computing systems to allow the user to search the electronic catalog for the item; receiving, from the user and at the one or more computing systems, a selection of the item within the electronic catalog; and associating, by the one or more computing systems, the illustrated item with a link to the item detail page within the electronic catalog. 3. A method as recited in claim 1 , wherein: the first selection comprises selecting an area of the image that borders the illustrated item; and the second selection comprises selecting the area of the image that borders the illustrated item.
| 0.56621 |
1. A computer-implemented method for digital search with task-enhanced search results, the method comprising: generating a search query based on interaction with a user; sending the search query to a search engine for an initial search; receiving initial search results from the search engine; predicting a current task being performed by the user at the time of the initial search, the current task being an action that the user is intending to perform at the time the search query is generated, wherein the current task corresponds to the search query without being specified by the search query, wherein predicting the current task includes associating with each of a plurality of tasks a probability that the current task is a particular task from among the plurality of tasks, wherein the associating uses past event records and associated task identifiers stored in a database, the associated task identifiers identifying the plurality of tasks from which the current task is predicted, and wherein the predicted current task is the particular task having a highest probability; computing task-related information from the predicted current task; filtering and ranking the initial search results based on the computed task-related information to produce enhanced search results; and presenting the enhanced search results to the user.
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1. A computer-implemented method for digital search with task-enhanced search results, the method comprising: generating a search query based on interaction with a user; sending the search query to a search engine for an initial search; receiving initial search results from the search engine; predicting a current task being performed by the user at the time of the initial search, the current task being an action that the user is intending to perform at the time the search query is generated, wherein the current task corresponds to the search query without being specified by the search query, wherein predicting the current task includes associating with each of a plurality of tasks a probability that the current task is a particular task from among the plurality of tasks, wherein the associating uses past event records and associated task identifiers stored in a database, the associated task identifiers identifying the plurality of tasks from which the current task is predicted, and wherein the predicted current task is the particular task having a highest probability; computing task-related information from the predicted current task; filtering and ranking the initial search results based on the computed task-related information to produce enhanced search results; and presenting the enhanced search results to the user. 12. The method of claim 1 further comprising calculating a similarity between keywords associated with the current task and words associated with a resource referenced in the initial search results.
| 0.56461 |
11. A non-transitory computer readable medium storing instructions that, when executed by a processor, perform a method for increasing the reliability of a circuit design by managing safe operating area assertion violations, the processor-implemented method comprising: transforming simulator output into descriptive data, regarding safe operating area assertion violations, wherein the descriptive data is compatible with a database; executing queries with the database on the descriptive data regarding the safe operating area assertion violations according to user input; and generating tangible query results regarding the safe operating area assertion violations for the circuit design to work for its intended purpose.
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11. A non-transitory computer readable medium storing instructions that, when executed by a processor, perform a method for increasing the reliability of a circuit design by managing safe operating area assertion violations, the processor-implemented method comprising: transforming simulator output into descriptive data, regarding safe operating area assertion violations, wherein the descriptive data is compatible with a database; executing queries with the database on the descriptive data regarding the safe operating area assertion violations according to user input; and generating tangible query results regarding the safe operating area assertion violations for the circuit design to work for its intended purpose. 13. The medium of claim 11 wherein the simulator output comprises numerical simulation results and safe operating area assertion violation messages.
| 0.539202 |
2. The method of claim 1 , wherein the domain model relates to a simple type or a complex type, the method further comprising: when a property for the domain model is of the simple type, populating the domain model with a value according to the document being represented; and when a property for the domain model is of the complex type, selectively adding another domain model as a value for the property according to the document being represented.
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2. The method of claim 1 , wherein the domain model relates to a simple type or a complex type, the method further comprising: when a property for the domain model is of the simple type, populating the domain model with a value according to the document being represented; and when a property for the domain model is of the complex type, selectively adding another domain model as a value for the property according to the document being represented. 4. The method of claim 2 , comprising: analyzing the set of domain models by determining values of properties from at least one domain model, the values extracted from the document represented by the domain model.
| 0.864865 |
1. A computer-readable memory storing a plurality of instructions for causing a processor to perform operations, the plurality of instructions comprising: instructions that cause the processor to determine that multiple portions of a continuous event processing (CEP) query can be executed concurrently relative to an event in an event stream, the instructions that cause the processor to determine that multiple portions of a continuous event processing (CEP) query can be executed concurrently relative to an event in an event stream comprising: instructions that cause the processor to split the CEP query into a plurality of separate operators; instructions that cause the processor to determine a separate ordering constraint for each particular operator within the plurality of separate operators; instructions that cause the processor to determine an ordering constraint for the CEP query based at least in part on the ordering constraints that the processor determined for the plurality of separate operators; and instructions that cause the processor to determine, based on the ordering constraint for the CEP query, whether the multiple portions of the CEP query can be executed in a concurrent manner; and instructions that cause the processor to execute the multiple portions of the CEP query concurrently against a first event received via the event stream, the instructions that cause the processor to execute the multiple portions of the CEP query concurrently against a first event received via the event stream comprising: instructions that cause the processor to spawn multiple threads of execution that concurrently process the multiple portions of the CEP query against the first event received via the event stream in response to determining that the multiple portions of the CEP query can be executed in a concurrent manner.
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1. A computer-readable memory storing a plurality of instructions for causing a processor to perform operations, the plurality of instructions comprising: instructions that cause the processor to determine that multiple portions of a continuous event processing (CEP) query can be executed concurrently relative to an event in an event stream, the instructions that cause the processor to determine that multiple portions of a continuous event processing (CEP) query can be executed concurrently relative to an event in an event stream comprising: instructions that cause the processor to split the CEP query into a plurality of separate operators; instructions that cause the processor to determine a separate ordering constraint for each particular operator within the plurality of separate operators; instructions that cause the processor to determine an ordering constraint for the CEP query based at least in part on the ordering constraints that the processor determined for the plurality of separate operators; and instructions that cause the processor to determine, based on the ordering constraint for the CEP query, whether the multiple portions of the CEP query can be executed in a concurrent manner; and instructions that cause the processor to execute the multiple portions of the CEP query concurrently against a first event received via the event stream, the instructions that cause the processor to execute the multiple portions of the CEP query concurrently against a first event received via the event stream comprising: instructions that cause the processor to spawn multiple threads of execution that concurrently process the multiple portions of the CEP query against the first event received via the event stream in response to determining that the multiple portions of the CEP query can be executed in a concurrent manner. 7. The computer-readable memory of claim 1 , wherein the plurality of instructions further comprise: instructions that cause the processor to merge, into a single shared operator, (a) a first operator that is used by a first CEP query that processes events in the event stream, and (b) a second operator that is used by a second CEP query that also processes events in the event stream, in response to determining that the first operator and the second operator both perform a particular type of operation; wherein the instructions that cause the processor to determine the separate ordering constraint for each particular operator within the plurality of separate operators comprise instructions that cause the processor to determine the ordering constraint for a third operator, which receives input from the shared operator, based at least in part on the ordering constraint of the shared operator; wherein the instructions that cause the processor to determine the separate ordering constraint for each particular operator within the plurality of separate operators comprise instructions that cause the processor to determine the ordering constraint for a fourth operator, which receives input from the shared operator, based at least in part on the ordering constraint of the shared operator; wherein the third operator is used by the first CEP query and is not used by the second CEP query; wherein the fourth operator is used by the second CEP query and is not used by the first CEP query.
| 0.5 |
3. The method for generating a code according to claim 1 , wherein, during the creation of the intermediate language model, a completely or partially accessible central data container is provided that enables an adaptation of the intermediate language model, and wherein the creation of the intermediate language model imposes predetermined limitations of the first plurality of predetermined parameters and information on the intermediate language model.
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3. The method for generating a code according to claim 1 , wherein, during the creation of the intermediate language model, a completely or partially accessible central data container is provided that enables an adaptation of the intermediate language model, and wherein the creation of the intermediate language model imposes predetermined limitations of the first plurality of predetermined parameters and information on the intermediate language model. 4. The method for generating a code according to claim 3 , wherein the first plurality of predetermined parameters and information is referenced in the central data container, and wherein the adaptation of the intermediate language model is carried out based on the first plurality of predetermined parameters and information for generating the code within the central data container.
| 0.845726 |
15. The system of claim 14 , wherein the feature vector generator is further configured to: select a first vocabulary term and a second vocabulary term of the plurality of vocabulary terms; identify a term frequency of the first vocabulary term within a web page of the plurality of web pages; identify a term frequency of the second vocabulary term within the web page of the plurality of web pages; identify an inverse document frequency (IDF) of the first vocabulary term and an IDF of the second vocabulary term from the N-gram file; calculate a weight for the first vocabulary term based on the IDF of the first and second vocabulary term and the term frequency of the first vocabulary term and the second vocabulary term; and calculate a weight for the second vocabulary term based on the IDF of the first and second vocabulary term and the term frequency of the first and second vocabulary term.
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15. The system of claim 14 , wherein the feature vector generator is further configured to: select a first vocabulary term and a second vocabulary term of the plurality of vocabulary terms; identify a term frequency of the first vocabulary term within a web page of the plurality of web pages; identify a term frequency of the second vocabulary term within the web page of the plurality of web pages; identify an inverse document frequency (IDF) of the first vocabulary term and an IDF of the second vocabulary term from the N-gram file; calculate a weight for the first vocabulary term based on the IDF of the first and second vocabulary term and the term frequency of the first vocabulary term and the second vocabulary term; and calculate a weight for the second vocabulary term based on the IDF of the first and second vocabulary term and the term frequency of the first and second vocabulary term. 16. The system of claim 15 , wherein the N-gram generator is further configured to: assign identification numbers to the first vocabulary term and the second vocabulary term.
| 0.940888 |
1. A computer-implemented method for confirming authorship of documents, performed on a server having at least one processor and memory storing at least one program for execution by the at least one processor to perform the method, comprising: accessing a first document hosted on a first website of a first domain, the first document being indirectly linked to a second document through at least one link in a chain of links, a respective link in the chain of links including a first predefined authorship attribute asserting authorship of a respective document including the respective link by a respective entity associated with a respective target document of the respective link; and conditionally confirming authorship of the first document by an entity associated with the second document when the second document includes a second link to the first website of the first domain, the second link including a second predefined authorship attribute indicating that the entity associated with the second document is an author of or contributor to content at the first website of the first domain.
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1. A computer-implemented method for confirming authorship of documents, performed on a server having at least one processor and memory storing at least one program for execution by the at least one processor to perform the method, comprising: accessing a first document hosted on a first website of a first domain, the first document being indirectly linked to a second document through at least one link in a chain of links, a respective link in the chain of links including a first predefined authorship attribute asserting authorship of a respective document including the respective link by a respective entity associated with a respective target document of the respective link; and conditionally confirming authorship of the first document by an entity associated with the second document when the second document includes a second link to the first website of the first domain, the second link including a second predefined authorship attribute indicating that the entity associated with the second document is an author of or contributor to content at the first website of the first domain. 13. The computer-implemented method of any of claims 1 - 12 , further comprising responsive to confirming authorship of the first document by the entity, associating the first document with the entity in a search index.
| 0.630045 |
1. A computer-implemented method for multicultural electronic communication management, the method comprising: initiating, by a user, an electronic communication configured to be transmitted to both a first intended recipient and a second intended recipient; identifying, based on a set of profile data, a first cultural indicator for the first intended recipient; identifying, based on the set of profile data, a second cultural indicator for the second intended recipient; detecting, using a natural language processing technique, a cultural element of the electronic communication; determining, based on both the first cultural indicator and the cultural element, a first cultural-version of the cultural element for the first intended recipient; determining, based on both the second cultural indicator and the cultural element, a second cultural-version of the cultural element for the second intended recipient; establishing, using both the first cultural-version and the second cultural-version, a cultural translation object in the electronic communication; and transmitting, in response to establishing the cultural translation object in the electronic communication, the electronic communication to both the first intended recipient and the second intended recipient.
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1. A computer-implemented method for multicultural electronic communication management, the method comprising: initiating, by a user, an electronic communication configured to be transmitted to both a first intended recipient and a second intended recipient; identifying, based on a set of profile data, a first cultural indicator for the first intended recipient; identifying, based on the set of profile data, a second cultural indicator for the second intended recipient; detecting, using a natural language processing technique, a cultural element of the electronic communication; determining, based on both the first cultural indicator and the cultural element, a first cultural-version of the cultural element for the first intended recipient; determining, based on both the second cultural indicator and the cultural element, a second cultural-version of the cultural element for the second intended recipient; establishing, using both the first cultural-version and the second cultural-version, a cultural translation object in the electronic communication; and transmitting, in response to establishing the cultural translation object in the electronic communication, the electronic communication to both the first intended recipient and the second intended recipient. 7. The method of claim 1 , wherein determining, based on both the first cultural indicator and the cultural element, the first cultural-version of the cultural element for the first intended recipient includes: analyzing, using a set of culture-oriented natural language processing techniques, the cultural element.
| 0.562405 |
15. A non-transitory computer readable medium storing computer program instructions for calculating a similarity score of a query set comprising a query set of tokens and a first database set comprising a first database set of tokens, wherein the first database set is one of a plurality of database sets in a data collection set, said computer program instructions defining the steps of: for each specific token in the query set, determining the number of database sets in the data collection set that contain the specific token; for each specific token in the query set, calculating an inverse document frequency (idf) weight based at least in part on the number of database sets that contain the specific token and on the total number of database sets in the data collection set; calculating a normalized length of the first database set; calculating a normalized length of the query set; and, calculating a similarity score based at least in part on the normalized length of the first database set, the normalized length of the query set, and the idf weight of each of the tokens in the query set.
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15. A non-transitory computer readable medium storing computer program instructions for calculating a similarity score of a query set comprising a query set of tokens and a first database set comprising a first database set of tokens, wherein the first database set is one of a plurality of database sets in a data collection set, said computer program instructions defining the steps of: for each specific token in the query set, determining the number of database sets in the data collection set that contain the specific token; for each specific token in the query set, calculating an inverse document frequency (idf) weight based at least in part on the number of database sets that contain the specific token and on the total number of database sets in the data collection set; calculating a normalized length of the first database set; calculating a normalized length of the query set; and, calculating a similarity score based at least in part on the normalized length of the first database set, the normalized length of the query set, and the idf weight of each of the tokens in the query set. 16. The non-transitory computer readable medium of claim 15 wherein said computer program instructions further comprise computer program instructions defining the step of: performing an improved no random access process.
| 0.620015 |
6. A computer-implemented method for electronic form generation, the method comprising: receiving, from a user, a selection of an electronically stored real estate form, wherein the electronically stored real estate form comprises a plurality of pages; retrieving an image of a first page of the plurality of pages of the real estate form from a first record in a first data store; causing a display of the image of the first page of the real estate form on a graphical display at a first image pixel density, the image of the first page comprising human-readable text and an answer area graphically proximate to the human-readable text; causing a display of a first canvas page of a plurality of canvas pages of an electronic canvas on the graphical display at a second image pixel density, wherein the first canvas page of the electronic canvas is separate from the image the first page of the real estate form and the second image pixel density of the first canvas page of the electronic canvas is higher than the first image pixel density of the image of the first page of the real estate form, wherein the second image pixel density of the first canvas of the electronic canvas is modifiable, and wherein the first canvas page of the electronic canvas overlaps at least a portion of the image of the first page of the real estate form; causing a display of a plurality of data entry field types on the graphical display, wherein the user can select at least one data entry field type among the plurality of data entry field types , and wherein the user can specify a placement position of the selected data entry field type on the first canvas page of the electronic canvas; receiving, from the user, a selection of a data entry field type of the plurality of data entry field types; receiving, from the user, a placement position of a data entry field of the selected data entry field type placed onto the first canvas page of the electronic canvas, wherein the placement position of the data entry field placed onto the first canvas page of the electronic canvas is a location within the bounds of the first canvas page of the electronic canvas, and wherein the placement position of the data entry field placed onto the first canvas page of the electronic canvas is graphically proximate to the answer area of the image of the first page of the real estate form; and storing in a second data store a second record, the second record comprising at least three distinct components: a first component providing an indication of the associated real estate form; a second component providing an indication of the data entry field type; and a third component providing the placement position of the data entry field placed onto the first canvas page of the electronic canvas that overlaps the image of the first page of the real estate form, wherein the placement position is stored as (i) a pair of coordinates indicative of a position of the placed data entry field relative to a lower left corner of the first canvas page of the electronic canvas and (ii) a page reference identifier corresponding to the first page of the real estate form, and wherein the pair of coordinates are based on the second image pixel density of the first canvas page of the electronic canvas.
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6. A computer-implemented method for electronic form generation, the method comprising: receiving, from a user, a selection of an electronically stored real estate form, wherein the electronically stored real estate form comprises a plurality of pages; retrieving an image of a first page of the plurality of pages of the real estate form from a first record in a first data store; causing a display of the image of the first page of the real estate form on a graphical display at a first image pixel density, the image of the first page comprising human-readable text and an answer area graphically proximate to the human-readable text; causing a display of a first canvas page of a plurality of canvas pages of an electronic canvas on the graphical display at a second image pixel density, wherein the first canvas page of the electronic canvas is separate from the image the first page of the real estate form and the second image pixel density of the first canvas page of the electronic canvas is higher than the first image pixel density of the image of the first page of the real estate form, wherein the second image pixel density of the first canvas of the electronic canvas is modifiable, and wherein the first canvas page of the electronic canvas overlaps at least a portion of the image of the first page of the real estate form; causing a display of a plurality of data entry field types on the graphical display, wherein the user can select at least one data entry field type among the plurality of data entry field types , and wherein the user can specify a placement position of the selected data entry field type on the first canvas page of the electronic canvas; receiving, from the user, a selection of a data entry field type of the plurality of data entry field types; receiving, from the user, a placement position of a data entry field of the selected data entry field type placed onto the first canvas page of the electronic canvas, wherein the placement position of the data entry field placed onto the first canvas page of the electronic canvas is a location within the bounds of the first canvas page of the electronic canvas, and wherein the placement position of the data entry field placed onto the first canvas page of the electronic canvas is graphically proximate to the answer area of the image of the first page of the real estate form; and storing in a second data store a second record, the second record comprising at least three distinct components: a first component providing an indication of the associated real estate form; a second component providing an indication of the data entry field type; and a third component providing the placement position of the data entry field placed onto the first canvas page of the electronic canvas that overlaps the image of the first page of the real estate form, wherein the placement position is stored as (i) a pair of coordinates indicative of a position of the placed data entry field relative to a lower left corner of the first canvas page of the electronic canvas and (ii) a page reference identifier corresponding to the first page of the real estate form, and wherein the pair of coordinates are based on the second image pixel density of the first canvas page of the electronic canvas. 17. The computer-implemented method of claim 6 , further comprising: determining that a rule is to be associated with the data entry field of the selected data entry field type placed onto the first canvas page of the electronic canvas; and in response to determining that a rule is to be associated with the data entry field of the selected data entry field type placed onto the first canvas page of the electronic canvas, adding the rule to the second record.
| 0.5 |
10. Computer hardware storage media having computer-executable instructions embodied thereon, that when executed, perform a method for presenting a web-accessible topic focused data mart, the method comprising: receiving health data from a data source comprising at least one of receiving internal health data collected by a health care facility and receiving public health data provided by a public agency; populating a topic focused data mart having at least a portion of the health data received from the data source, the topic focused data mart only comprising data relevant to a predetermined topic associated with the one topic focused data mart, the at least the portion of the health data being associated with the predetermined topic; associating the topic focused data mart with a web service; receiving demographic information from an Electronic Health Record (EHR) associated with a patient; querying the topic focused data mart based on the demographic information received from the EHR, the querying the topic focused data mart comprising querying only the at least the portion of the health data included in the topic focused data mart; and presenting context-specific data derived from the topic focused data mart in the EHR, the context-specific data being based on the demographic information, the receiving, querying, and presenting being performed without input from a clinician.
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10. Computer hardware storage media having computer-executable instructions embodied thereon, that when executed, perform a method for presenting a web-accessible topic focused data mart, the method comprising: receiving health data from a data source comprising at least one of receiving internal health data collected by a health care facility and receiving public health data provided by a public agency; populating a topic focused data mart having at least a portion of the health data received from the data source, the topic focused data mart only comprising data relevant to a predetermined topic associated with the one topic focused data mart, the at least the portion of the health data being associated with the predetermined topic; associating the topic focused data mart with a web service; receiving demographic information from an Electronic Health Record (EHR) associated with a patient; querying the topic focused data mart based on the demographic information received from the EHR, the querying the topic focused data mart comprising querying only the at least the portion of the health data included in the topic focused data mart; and presenting context-specific data derived from the topic focused data mart in the EHR, the context-specific data being based on the demographic information, the receiving, querying, and presenting being performed without input from a clinician. 13. The media of claim 10 , wherein the context-specific data is length of stay by condition.
| 0.728864 |
1. A method for processing a call, the method comprising: receiving a call from a caller over a communication network; determining a telephone number of the caller; accessing an electronic database to determine a stored language preference of the caller, the caller's stored language preference being associated with the caller's telephone number in the electronic database; routing the call to a predetermined destination based on the stored language preference of the caller in the electronic database; and routing the call to a default destination when the electronic database does not include a stored language preference of the caller.
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1. A method for processing a call, the method comprising: receiving a call from a caller over a communication network; determining a telephone number of the caller; accessing an electronic database to determine a stored language preference of the caller, the caller's stored language preference being associated with the caller's telephone number in the electronic database; routing the call to a predetermined destination based on the stored language preference of the caller in the electronic database; and routing the call to a default destination when the electronic database does not include a stored language preference of the caller. 11. The method of claim 1 , wherein a caller's stored language preference is entered into the electronic database by a caller using a dual tone multi frequency input.
| 0.692053 |
11. A processor-implemented method comprising the steps of: detecting a reference citation in a first electronic document; processing the reference citation to determine a plurality of links to a second electronic document identified by the reference citation, each of the plurality of links comprising a uniform resource identifier (URI) for directly accessing the second electronic document; selecting at least one of the plurality of links based on preference information; and displaying the selected at least one link and at least a portion of the first electronic document; wherein processing the reference citation to determine the plurality of links comprises: formulating a search query based on the reference citation; identifying a plurality of document portals, the plurality of document portals comprising a first subset of document portals for which a particular user is known to have a valid subscription and a second subset of document portals for which a particular user is not known to have a valid subscription; restricting the search query to the first subset of the plurality of document portals; executing the restricted search query; and in the event that executing the restricted search query fails, executing an unrestricted search query to search the second subset of the plurality of document portals.
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11. A processor-implemented method comprising the steps of: detecting a reference citation in a first electronic document; processing the reference citation to determine a plurality of links to a second electronic document identified by the reference citation, each of the plurality of links comprising a uniform resource identifier (URI) for directly accessing the second electronic document; selecting at least one of the plurality of links based on preference information; and displaying the selected at least one link and at least a portion of the first electronic document; wherein processing the reference citation to determine the plurality of links comprises: formulating a search query based on the reference citation; identifying a plurality of document portals, the plurality of document portals comprising a first subset of document portals for which a particular user is known to have a valid subscription and a second subset of document portals for which a particular user is not known to have a valid subscription; restricting the search query to the first subset of the plurality of document portals; executing the restricted search query; and in the event that executing the restricted search query fails, executing an unrestricted search query to search the second subset of the plurality of document portals. 18. The method of claim 11 wherein the step of detecting the reference citation in the first electronic document comprises parsing the first electronic document to identify a plurality of reference citations.
| 0.655364 |
2. A network device that is operative for generating extraction rules, comprising: including: a transceiver that is operative to communicate over a network; a memory that is operative to store at least instructions; and a processor device that is operative to execute instructions that enable actions, including: accessing in memory a set of events, each event identified by an associated time stamp; wherein each event in the set of events includes a portion of raw data from machine data; transmitting for display a user interface including a first event and a plurality of second events of the set of events; receiving data indicating a selection of a portion of text within the first event; automatically determining a field extraction rule that extracts as a value of a field the selection of the portion of text within the first event when the field extraction rule is applied to the first event; and transmitting for display an updated user interface that includes the second events and that indicates, for each of the second events, a value of the field for each second event that would be extracted by applying the extraction rule to the second event.
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2. A network device that is operative for generating extraction rules, comprising: including: a transceiver that is operative to communicate over a network; a memory that is operative to store at least instructions; and a processor device that is operative to execute instructions that enable actions, including: accessing in memory a set of events, each event identified by an associated time stamp; wherein each event in the set of events includes a portion of raw data from machine data; transmitting for display a user interface including a first event and a plurality of second events of the set of events; receiving data indicating a selection of a portion of text within the first event; automatically determining a field extraction rule that extracts as a value of a field the selection of the portion of text within the first event when the field extraction rule is applied to the first event; and transmitting for display an updated user interface that includes the second events and that indicates, for each of the second events, a value of the field for each second event that would be extracted by applying the extraction rule to the second event. 18. The network device of claim 2 , wherein the field extraction rule comprises a regular expression.
| 0.79558 |
16. The method of claim 14 , wherein obtaining a plurality of candidate corrected spellings for the entity name comprises: generating a name query from the entity name and the two or more context terms; and searching context-entity name data for the candidate corrected spellings responsive to the name query.
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16. The method of claim 14 , wherein obtaining a plurality of candidate corrected spellings for the entity name comprises: generating a name query from the entity name and the two or more context terms; and searching context-entity name data for the candidate corrected spellings responsive to the name query. 20. The method of claim 16 , wherein the entity name includes one or more parts and the name query further includes one or more related names for one of the parts of the entity name.
| 0.9469 |
1. A method, in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to specifically configure the processor to implement an automatic speech recognition system comprising an acoustic model and an external word embedding neural network language model, the method comprising: configuring the automatic speech recognition system with an external word embedding neural network language model that accepts as input a sequence of words and predicts a current word based on the sequence of words, wherein the external word embedding neural network language model combines an external embedding matrix to a history word embedding matrix and a prediction word embedding matrix of the external word embedding neural network language model; receiving as input an audio signal and generating a sequence of words based on the audio signal by the acoustic model; receiving the sequence of input words by the automatic speech recognition system from the acoustic model; applying a plurality of previous words in the sequence of input words as inputs to the external word embedding neural network language model in the automatic speech recognition system, wherein the external word embedding neural network language model generates a predicted current word based on the plurality of previous words; and processing, by the automatic speech recognition system, a current word in the sequence of input words based on the predicted current word generated by the external word embedding neural network language model, wherein processing the current word comprises recognizing a current spoken word in the audio signal based on the predicted current word.
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1. A method, in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to specifically configure the processor to implement an automatic speech recognition system comprising an acoustic model and an external word embedding neural network language model, the method comprising: configuring the automatic speech recognition system with an external word embedding neural network language model that accepts as input a sequence of words and predicts a current word based on the sequence of words, wherein the external word embedding neural network language model combines an external embedding matrix to a history word embedding matrix and a prediction word embedding matrix of the external word embedding neural network language model; receiving as input an audio signal and generating a sequence of words based on the audio signal by the acoustic model; receiving the sequence of input words by the automatic speech recognition system from the acoustic model; applying a plurality of previous words in the sequence of input words as inputs to the external word embedding neural network language model in the automatic speech recognition system, wherein the external word embedding neural network language model generates a predicted current word based on the plurality of previous words; and processing, by the automatic speech recognition system, a current word in the sequence of input words based on the predicted current word generated by the external word embedding neural network language model, wherein processing the current word comprises recognizing a current spoken word in the audio signal based on the predicted current word. 11. The method of claim 1 , wherein the external embedding neural language model is a 3-gram feed-forward neural network language model.
| 0.560899 |
1. A method in a computing system, having a processor and memory, comprising: causing by the computing system to be presented via a network connection device to each of a plurality of people: a plurality of unlikely questions, each of whose affirmative answer is accurate for only a small percentage of the population, a fabrication gauge question whose affirmative answer is accurate for a known percentage of the population regardless of whether it is answered accurately by people to whom it is posed, and at least one substantive question; accessing, via the memory, a statistical expectation attributed to an affirmative answer to the fabrication gauge question; for each of the plurality of people: receiving, by the computing system, responses to the posed questions provided by the person; storing, in the memory, an identifier for the person among a set of person identifiers, the identifier associated with the responses; calculating, by the processor, a first percentage of the plurality of people who answered the fabrication gauge question in the affirmative; determining by the processor that the calculated first percentage exceeds the statistical expectation; determining, with the processor, for each person identifier, a number of unlikely questions to which the identified person answered affirmatively; with the processor, discarding person identifiers from the set of person identifiers by: (a) identifying, among the set of person identifiers, a proper subset associated with the largest number of unlikely questions answered affirmatively; (b) storing, in the memory, an indication to discard one or more of the person identifiers in the proper subset; (c) calculating a second percentage of people associated with undiscarded person identifiers who answered the fabrication gauge question in the affirmative; and (d) iteratively repeating (a)-(c) until the second percentage is within a predetermined range of the known percentage; and reporting answers to the at least one substantive question for only people among the plurality of people whose person identifiers are undiscarded.
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1. A method in a computing system, having a processor and memory, comprising: causing by the computing system to be presented via a network connection device to each of a plurality of people: a plurality of unlikely questions, each of whose affirmative answer is accurate for only a small percentage of the population, a fabrication gauge question whose affirmative answer is accurate for a known percentage of the population regardless of whether it is answered accurately by people to whom it is posed, and at least one substantive question; accessing, via the memory, a statistical expectation attributed to an affirmative answer to the fabrication gauge question; for each of the plurality of people: receiving, by the computing system, responses to the posed questions provided by the person; storing, in the memory, an identifier for the person among a set of person identifiers, the identifier associated with the responses; calculating, by the processor, a first percentage of the plurality of people who answered the fabrication gauge question in the affirmative; determining by the processor that the calculated first percentage exceeds the statistical expectation; determining, with the processor, for each person identifier, a number of unlikely questions to which the identified person answered affirmatively; with the processor, discarding person identifiers from the set of person identifiers by: (a) identifying, among the set of person identifiers, a proper subset associated with the largest number of unlikely questions answered affirmatively; (b) storing, in the memory, an indication to discard one or more of the person identifiers in the proper subset; (c) calculating a second percentage of people associated with undiscarded person identifiers who answered the fabrication gauge question in the affirmative; and (d) iteratively repeating (a)-(c) until the second percentage is within a predetermined range of the known percentage; and reporting answers to the at least one substantive question for only people among the plurality of people whose person identifiers are undiscarded. 2. The method of claim 1 wherein the unlikely questions and fabrication gauge questions are caused to be posed in the same survey with substantive questions to which the people's responses are sought.
| 0.518182 |
7. A non-transitory computer readable medium encoded with software comprising computer executable instructions and when the software is executed operable to: receive a first customer service interaction including an identity and user inputted information; access a customer database with the identity to determine a username for an online service; download a posting from the online service associated with the username; filter information of the posting based on the user inputted information, wherein the filtering is according to at least two vectors, wherein a first vector of the at least two vectors includes two or more factors pertaining to the posting, and wherein a second vector of the at least two vectors includes two or more factors pertaining to the user inputted information; and assign a customer service agent to a second customer service interaction based on the filtered information of the posting.
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7. A non-transitory computer readable medium encoded with software comprising computer executable instructions and when the software is executed operable to: receive a first customer service interaction including an identity and user inputted information; access a customer database with the identity to determine a username for an online service; download a posting from the online service associated with the username; filter information of the posting based on the user inputted information, wherein the filtering is according to at least two vectors, wherein a first vector of the at least two vectors includes two or more factors pertaining to the posting, and wherein a second vector of the at least two vectors includes two or more factors pertaining to the user inputted information; and assign a customer service agent to a second customer service interaction based on the filtered information of the posting. 19. The non-transitory computer readable medium of claim 7 , wherein the first vector includes product information derived from the posting and the second vector includes product information derived from the user inputted information.
| 0.635838 |
1. A method comprising: modifying, using one or more processors, a query string of characters using a set of heuristics; performing, using one or more processors, a character-by-character comparison of the modified query string with at least one known string of characters in a corpus in order to locate an exact match for the modified query string; and responsive to not finding an exact match for the modified query string in the corpus, performing, by one or more processors, the following steps in order to locate an equivalent for the modified query string: forming a plurality of sub-strings of characters from the modified query string, the sub-strings having varying lengths such that at least two of the formed sub-strings differ in length, each sub-string comprising a composition of characters selected based on a frequency of occurrence of the composition in the modified query string; and using an information retrieval technique on the sub-strings formed from the modified query string to identify a known string of characters equivalent to the query string.
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1. A method comprising: modifying, using one or more processors, a query string of characters using a set of heuristics; performing, using one or more processors, a character-by-character comparison of the modified query string with at least one known string of characters in a corpus in order to locate an exact match for the modified query string; and responsive to not finding an exact match for the modified query string in the corpus, performing, by one or more processors, the following steps in order to locate an equivalent for the modified query string: forming a plurality of sub-strings of characters from the modified query string, the sub-strings having varying lengths such that at least two of the formed sub-strings differ in length, each sub-string comprising a composition of characters selected based on a frequency of occurrence of the composition in the modified query string; and using an information retrieval technique on the sub-strings formed from the modified query string to identify a known string of characters equivalent to the query string. 5. The method of claim 1 , wherein the set of heuristics comprises removing a portion of the query string.
| 0.668345 |
13. The method of claim 12 , wherein the mapping at least one element of each of the plurality of stages to the refined business outcome through the previous elements by the computing system to produce the marketing blueprint comprises: identifying one or more marketing strategies for each of the one or more elements of each previous stage of said plurality of stages.
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13. The method of claim 12 , wherein the mapping at least one element of each of the plurality of stages to the refined business outcome through the previous elements by the computing system to produce the marketing blueprint comprises: identifying one or more marketing strategies for each of the one or more elements of each previous stage of said plurality of stages. 14. The method of claim 13 , wherein the mapping at least one element of each of the plurality of stages to the refined business outcome through the previous elements by the computing system to produce the marketing blueprint further comprises: defining one or more milestones for each of the one or more marketing strategies.
| 0.930121 |
30. The method of claim 29 , wherein the additional table includes (i) a join key column, (ii) a key column, and (iii) for each scalar type of data in the map, a value column.
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30. The method of claim 29 , wherein the additional table includes (i) a join key column, (ii) a key column, and (iii) for each scalar type of data in the map, a value column. 31. The method of claim 30 , wherein the key column is a string type.
| 0.925553 |
27. The hardware-implemented system of claim 24 , wherein said sequential pattern determination module configured to determine one or more sequential patterns associated with the at least one subjective user state and the at least one objective occurrence comprises: a historical data referencing module configured to reference historical data.
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27. The hardware-implemented system of claim 24 , wherein said sequential pattern determination module configured to determine one or more sequential patterns associated with the at least one subjective user state and the at least one objective occurrence comprises: a historical data referencing module configured to reference historical data. 28. The hardware-implemented system of claim 27 , wherein said historical data referencing module configured to reference historical data comprises: a historical data referencing module configured to reference historical data indicative of at least a link between a subjective user state type and an objective occurrence type.
| 0.801571 |
7. A computer program product comprising a non-transitory computer readable medium having encoded thereon computer executable instructions, said computer executable instructions comprising instructions to: display, on a display, a composition field and a second field, the second field including text; receive an input for inclusion in the composition field; determine that a portion of the composition field is not visible on the display when the input is received, including the portion being moved off-screen from the display; in response to the determining, display an overlay, the overlay including an input area, wherein the overlay is a partially transparent overlay; display the input in the input area of the overlay; detect an insert event; and in response to detecting the insert event, insert the elements entered in the input area of the overlay into the composition field and remove the overlay from the display.
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7. A computer program product comprising a non-transitory computer readable medium having encoded thereon computer executable instructions, said computer executable instructions comprising instructions to: display, on a display, a composition field and a second field, the second field including text; receive an input for inclusion in the composition field; determine that a portion of the composition field is not visible on the display when the input is received, including the portion being moved off-screen from the display; in response to the determining, display an overlay, the overlay including an input area, wherein the overlay is a partially transparent overlay; display the input in the input area of the overlay; detect an insert event; and in response to detecting the insert event, insert the elements entered in the input area of the overlay into the composition field and remove the overlay from the display. 8. The computer program product of claim 7 , wherein the insert event is any one of a user-generated event, a system event, and a combination of the user-generated event and the system event.
| 0.610329 |
4. A computing device comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the computing device to perform operations, comprising: determining one or more segmentations for each search query in a collection of search queries, wherein each search query includes a plurality of terms, and wherein each segmentation identifies at least one potential phrase that includes at least one term that appears in the search query; determining, for each search query in the collection of search queries, a respective score for each of the one or more segmentations of the search query; selecting, for each search query in the collection of search queries, at least one segmentation having a best score from the one or more respective segmentations of the search query, wherein the at least one selected segmentation identifies at least one actual phrase that includes at least one term that appears in the search query; and storing the at least one selected segmentation for each search query in the collection of search queries as training data for training a predictive model.
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4. A computing device comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the computing device to perform operations, comprising: determining one or more segmentations for each search query in a collection of search queries, wherein each search query includes a plurality of terms, and wherein each segmentation identifies at least one potential phrase that includes at least one term that appears in the search query; determining, for each search query in the collection of search queries, a respective score for each of the one or more segmentations of the search query; selecting, for each search query in the collection of search queries, at least one segmentation having a best score from the one or more respective segmentations of the search query, wherein the at least one selected segmentation identifies at least one actual phrase that includes at least one term that appears in the search query; and storing the at least one selected segmentation for each search query in the collection of search queries as training data for training a predictive model. 16. The computing device of claim 4 , wherein storing the at least one selected segmentation for each search query in the collection of search queries as training data for training a predictive model further comprises: storing each search query in the collection of search queries as input data; and storing, for each search query in the collection of search queries, the at least one selected segmentation for the search query as output data.
| 0.593952 |
12. A computer readable storage medium encoding computer program code to configure an application on a system, the computer program code comprising functionality to: receive a request to configure the application from a client associated with the application, wherein the system is external to the client, and wherein the request comprises an application context describing a state of the application at runtime; obtain a rule comprising a conditional expression for configuring the application at runtime; parse the rule to extract a symbol and an operator; convert the conditional expression into a tree comprising the symbol and the operator; replace the symbol with a value from the application context using a domain map to find a context data source publishing the value; calculate a correct configuration for the application based on the application context by evaluating the tree after replacing the symbol; obtain an application object associated with a plurality of options for configuring the application; select an option of the plurality of options based on the correct configuration for the application; and send, from the system and in response to the request, an instance of the application object encapsulating the option to the client wherein the application object is used to set a configuration of the application to the correct configuration.
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12. A computer readable storage medium encoding computer program code to configure an application on a system, the computer program code comprising functionality to: receive a request to configure the application from a client associated with the application, wherein the system is external to the client, and wherein the request comprises an application context describing a state of the application at runtime; obtain a rule comprising a conditional expression for configuring the application at runtime; parse the rule to extract a symbol and an operator; convert the conditional expression into a tree comprising the symbol and the operator; replace the symbol with a value from the application context using a domain map to find a context data source publishing the value; calculate a correct configuration for the application based on the application context by evaluating the tree after replacing the symbol; obtain an application object associated with a plurality of options for configuring the application; select an option of the plurality of options based on the correct configuration for the application; and send, from the system and in response to the request, an instance of the application object encapsulating the option to the client wherein the application object is used to set a configuration of the application to the correct configuration. 20. The computer readable storage medium of claim 12 , wherein the plurality of options comprises at least one selected from a group consisting of a default list of accounts, a default list of inventory items, and a default list of customer types accessed by the application and available to a user of the application.
| 0.748626 |
15. The method of claim 13 wherein the correspondence test comprises comparing an identifier of the element with an identifier of a subclass of the class of the further entity group.
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15. The method of claim 13 wherein the correspondence test comprises comparing an identifier of the element with an identifier of a subclass of the class of the further entity group. 16. The method of claim 15 wherein comparing the identifier of the element with the identifier of the subclass comprises testing if any one of the following relations exists between identifiers of the element and the subclass: the identifiers are identical, the identifiers are synonymous, the identifiers are similar according to a first similarity test.
| 0.829502 |
15. The system of claim 13 , wherein the quote extraction module is further configured to: generate a list of topics for each of the individual items from the plurality of sentences; identify one or more common topics from the list of topics of each of the individual items; generate an overall list of topics discussed across all of the individual items from the plurality of sentences and assign each sentence in the plurality of sentences to one or more topics in the overall list of topics; and extract the one or more quotes from the sentences assigned to topics matching the one or more common topics.
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15. The system of claim 13 , wherein the quote extraction module is further configured to: generate a list of topics for each of the individual items from the plurality of sentences; identify one or more common topics from the list of topics of each of the individual items; generate an overall list of topics discussed across all of the individual items from the plurality of sentences and assign each sentence in the plurality of sentences to one or more topics in the overall list of topics; and extract the one or more quotes from the sentences assigned to topics matching the one or more common topics. 18. The system of claim 15 , wherein generating the overall list of topics discussed across all of the individual items from the plurality of sentences and assigning each sentence in the plurality of sentences to one or more topics in the overall list of topics comprises discovering the overall list of topics from the plurality of sentences and assigning the sentences to the topics utilizing latent Dirichlet allocation.
| 0.797018 |
13. A method executed on a computing device for determining document classification probabilistically through classification rule analysis, the method comprising: identifying patterns and evidences within content of documents, wherein each one of the evidences includes an aggregate of keyword matches that are in proximity; determining a confidence level of an affinity from a probability of at least one of the evidences being within a proximity window of a presence of the affinity, wherein the proximity window includes a window of the content used to scan the content for the affinity; constructing a classification rule based on an entity determined according to an analysis of the patterns and the affinity determined according to an analysis of the evidences; processing the content with the classification rule to collect returned results; and comparing the returned results to expected results to evaluate the classification rule against acceptance requirements.
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13. A method executed on a computing device for determining document classification probabilistically through classification rule analysis, the method comprising: identifying patterns and evidences within content of documents, wherein each one of the evidences includes an aggregate of keyword matches that are in proximity; determining a confidence level of an affinity from a probability of at least one of the evidences being within a proximity window of a presence of the affinity, wherein the proximity window includes a window of the content used to scan the content for the affinity; constructing a classification rule based on an entity determined according to an analysis of the patterns and the affinity determined according to an analysis of the evidences; processing the content with the classification rule to collect returned results; and comparing the returned results to expected results to evaluate the classification rule against acceptance requirements. 15. The method of claim 13 , further comprising: determining a confidence level of the entity from a probability of matching at least one of the patterns to indicate a presence of the entity.
| 0.726532 |
5. An apparatus for Ileo-Cecal Valve (ICV) detection in an input 3D computed tomography (CT) volume, comprising: means for detecting initial box candidates for the ICV based on an ICV orifice in said input 3D CT volume; and means for detecting a box bounding the ICV in said 3D CT volume by sequentially detecting possible locations, scales, and orientations of the box bounding the ICV using incremental parameter learning based on said initial box candidates.
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5. An apparatus for Ileo-Cecal Valve (ICV) detection in an input 3D computed tomography (CT) volume, comprising: means for detecting initial box candidates for the ICV based on an ICV orifice in said input 3D CT volume; and means for detecting a box bounding the ICV in said 3D CT volume by sequentially detecting possible locations, scales, and orientations of the box bounding the ICV using incremental parameter learning based on said initial box candidates. 6. The apparatus of claim 5 , wherein said means for detecting initial box candidates for the ICV comprises: means for detecting a number of ICV orifice candidate voxels in said 3D CT volume using a trained 3D point detector; means for aligning an orientation of a 3D box centered at each orifice candidate voxel with a gradient vector at that orifice candidate voxel, wherein a scale of each 3D box is fixed; means for generating a set testing boxes by rotating the orientation of the 3D box centered at each orifice candidate voxel; and means for detecting a number of said testing boxes as initial box candidates using a trained 3D box detector.
| 0.627353 |
1. A computer-implemented method for searching information in a system including an information database that stores information contents and a metadata database that stores metadata describing the information contents, the method comprising: detecting an intention of an information searcher by using a result of a syntax analysis of keywords inputted by the information searcher; extracting a plurality of metadata which describe information contents meeting the detected intention of the information searcher from the metadata stored in the metadata database; generating an editor in a table form in which the plurality of metadata extracted from the metadata stored in the metadata database are paired with a plurality of metadata fields of the editor and displaying the generated editor to the information searcher; receiving a plurality of metadata items inputted by the information searcher through the plurality of metadata fields of the editor; determining a search directory for searching contents in the information database according to the detected intention of the information searcher; searching information contents having metadata corresponding to the plurality of metadata items inputted through the plurality of metadata fields of the editor from the information database; comparing the plurality of metadata items inputted through the plurality of metadata fields of the editor with the searched metadata corresponding to the searched information contents; selecting, among the searched information contents, information contents having a degree of coincidence exceeding a pre-defined threshold based on a comparison result; and displaying the selected information contents.
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1. A computer-implemented method for searching information in a system including an information database that stores information contents and a metadata database that stores metadata describing the information contents, the method comprising: detecting an intention of an information searcher by using a result of a syntax analysis of keywords inputted by the information searcher; extracting a plurality of metadata which describe information contents meeting the detected intention of the information searcher from the metadata stored in the metadata database; generating an editor in a table form in which the plurality of metadata extracted from the metadata stored in the metadata database are paired with a plurality of metadata fields of the editor and displaying the generated editor to the information searcher; receiving a plurality of metadata items inputted by the information searcher through the plurality of metadata fields of the editor; determining a search directory for searching contents in the information database according to the detected intention of the information searcher; searching information contents having metadata corresponding to the plurality of metadata items inputted through the plurality of metadata fields of the editor from the information database; comparing the plurality of metadata items inputted through the plurality of metadata fields of the editor with the searched metadata corresponding to the searched information contents; selecting, among the searched information contents, information contents having a degree of coincidence exceeding a pre-defined threshold based on a comparison result; and displaying the selected information contents. 5. The method of claim 1 , wherein the inputted keywords are one of a word unit, a phrase unit and a sentence unit.
| 0.757857 |
9. A computer implemented method for storing and accessing information in a database of annotated author documents comprising the steps of: responding to a selection by an evaluator of an author and a particular document by displaying the selected document in a first window of a graphical user interface; displaying in a second window of the graphical user interface a tag list of tags with a predetermined set of tags from which the evaluator can choose, wherein the tag list with a predetermined set of tags is a list of goals and the tagged portion of the document is annotated by a goal selected by the evaluator from the set of goals by the respective tag and a weight, if selected; receiving a selection by the evaluator of a portion of the displayed document by an evaluator; receiving a selection by the evaluator of one or more tags from the list of tags; associating one or more selected tags with the selected portion of the displayed document; saving the document and one or more tags in the database as an annotated document; displaying in a third window a weight; prompting the evaluator to select a quality weight and an importance weight to be assigned to the goal; and associating selected quality and importance weights with the tag.
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9. A computer implemented method for storing and accessing information in a database of annotated author documents comprising the steps of: responding to a selection by an evaluator of an author and a particular document by displaying the selected document in a first window of a graphical user interface; displaying in a second window of the graphical user interface a tag list of tags with a predetermined set of tags from which the evaluator can choose, wherein the tag list with a predetermined set of tags is a list of goals and the tagged portion of the document is annotated by a goal selected by the evaluator from the set of goals by the respective tag and a weight, if selected; receiving a selection by the evaluator of a portion of the displayed document by an evaluator; receiving a selection by the evaluator of one or more tags from the list of tags; associating one or more selected tags with the selected portion of the displayed document; saving the document and one or more tags in the database as an annotated document; displaying in a third window a weight; prompting the evaluator to select a quality weight and an importance weight to be assigned to the goal; and associating selected quality and importance weights with the tag. 10. The computer implemented method, as in claim 9, where in response to an evaluator selecting a report process and selecting authors and documents from the database, further comprising the steps of: retrieving goals for the selected authors and documents; multiplying quality and importance weights assigned to each the retrieved goals; accumulating products of quality and importance weights; computing normalized sums of accumulated products of quality and importance weights; and generating a report of goals by category showing normalized sums of accumulated products of quality and importance weights to indicate how well goals are being met.
| 0.5 |
26. A computer system as in claim 25 in which the another operating system comprises one of a Windows operating system and an Apple operating system.
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26. A computer system as in claim 25 in which the another operating system comprises one of a Windows operating system and an Apple operating system. 27. A computer as in claim 26 in which said documents reside as respective time ordered streams in at least one server and a number of personal computers selectively communicating with each other and with the server, and said processing system causes one of the personal computers to search a number of said respective streams in order to create a time-ordered substream.
| 0.922722 |
10. The method of claim 9 , further comprising: determining, based on the data, a lexicon that includes a plurality of entries, wherein a given entry in the lexicon includes text in the first-language matched with a phonemic representation that includes one or more phonemes of the second-language, and wherein the phonemic representation is indicative of a pronunciation of the text in the first-language according to the speech sounds of the second-language; and identifying, from within the lexicon, the given entry having the phonemic representation that corresponds to the pronunciation of the linguistic content indicated in the input, wherein determining the linguistic content is based on the text in the identified given entry.
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10. The method of claim 9 , further comprising: determining, based on the data, a lexicon that includes a plurality of entries, wherein a given entry in the lexicon includes text in the first-language matched with a phonemic representation that includes one or more phonemes of the second-language, and wherein the phonemic representation is indicative of a pronunciation of the text in the first-language according to the speech sounds of the second-language; and identifying, from within the lexicon, the given entry having the phonemic representation that corresponds to the pronunciation of the linguistic content indicated in the input, wherein determining the linguistic content is based on the text in the identified given entry. 11. The method of claim 10 , wherein determining the lexicon comprises receiving the lexicon from an external computing device.
| 0.821203 |
5. The computer-implemented method of claim 2 , further comprising receiving a selection from the displayed preferred category values.
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5. The computer-implemented method of claim 2 , further comprising receiving a selection from the displayed preferred category values. 6. The computer-implemented method of claim 5 , wherein, upon receipt of the selection from the displayed category values, a second set of the data entries associated with the selected category value is provided for display.
| 0.929994 |
28. A method for automatically extracting relations between concepts included in electronic text, comprising: accessing, by a program executing on a computer, a semantic network, wherein the semantic network comprises a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets; wherein the semantic network further includes semantic information comprising at least one of: an expanded set of semantic relation links representing: hierarchical semantic relations, synset/corpus semantic relations verb/subject semantic relations, verb/direct object semantic relations, and fine grain/coarse grain semantic relationship; a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language; and performing, by the program, semantic disambiguation on the electronic text using the semantic network and the at least one of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference of the electronic text.
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28. A method for automatically extracting relations between concepts included in electronic text, comprising: accessing, by a program executing on a computer, a semantic network, wherein the semantic network comprises a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets; wherein the semantic network further includes semantic information comprising at least one of: an expanded set of semantic relation links representing: hierarchical semantic relations, synset/corpus semantic relations verb/subject semantic relations, verb/direct object semantic relations, and fine grain/coarse grain semantic relationship; a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language; and performing, by the program, semantic disambiguation on the electronic text using the semantic network and the at least one of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference of the electronic text. 32. The method of claim 28 wherein The method is used for electronic searches as a semantic-based ranking method for a search engine in which documents returned from a keyword search are analyzed to identify concepts contained in the documents and then ranked using a specific relevance that a concept has inside the documents.
| 0.531142 |
1. A method for performing a search for content in an electronic database using a tuple index with separately indexed tuple word combinations, the method comprising: creating the tuple index comprising a plurality of tuples, wherein each tuple comprises three or more terms found within electronic content, wherein at least two tuples in the tuple index include two terms in common and one different term; receiving a search request that includes two or more search terms; creating one or more tuples from the two or more search terms including creating a first sequence identifier to represent a first tuple created from the two or more search terms; performing a search for documents of the electronic content that match the search request by comparing the one or more tuples created from the two or more search terms to the plurality of tuples in the tuple index; and providing a plurality of documents as results of the performed search including ranking two or more documents in the results based on the two or more documents each containing the first tuple, but having a different sequence identifier associated with the first tuple such that a document containing the first tuple and a sequence identifier that matches the first sequence identifier is ranked higher than a document containing the first tuple and a sequence identifier that does not match the first sequence identifier.
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1. A method for performing a search for content in an electronic database using a tuple index with separately indexed tuple word combinations, the method comprising: creating the tuple index comprising a plurality of tuples, wherein each tuple comprises three or more terms found within electronic content, wherein at least two tuples in the tuple index include two terms in common and one different term; receiving a search request that includes two or more search terms; creating one or more tuples from the two or more search terms including creating a first sequence identifier to represent a first tuple created from the two or more search terms; performing a search for documents of the electronic content that match the search request by comparing the one or more tuples created from the two or more search terms to the plurality of tuples in the tuple index; and providing a plurality of documents as results of the performed search including ranking two or more documents in the results based on the two or more documents each containing the first tuple, but having a different sequence identifier associated with the first tuple such that a document containing the first tuple and a sequence identifier that matches the first sequence identifier is ranked higher than a document containing the first tuple and a sequence identifier that does not match the first sequence identifier. 3. A method as recited in claim 1 , wherein the one or more search terms are received from a remote computing system.
| 0.575407 |
1. A system for obtaining solution suggestions for problems, the system comprising: at least one processor and at least one storage medium including an electronic model of a system or process, wherein the electronic model includes components of the system or process and relationships between the components; a problem analysis tool that analyzes the components and the relationships between the components of the electronic model to identify a problem to be solved, generates a problem statement representing the problem, and generates a machine representation of a problem statement; a query formatter that reformulates the machine representation into a natural language query or Boolean query and automatically submits the query to at least one knowledge base; and the at least one knowledge base comprising at least one database comprising problem solutions and returning a set of solution suggestions responsive to the query.
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1. A system for obtaining solution suggestions for problems, the system comprising: at least one processor and at least one storage medium including an electronic model of a system or process, wherein the electronic model includes components of the system or process and relationships between the components; a problem analysis tool that analyzes the components and the relationships between the components of the electronic model to identify a problem to be solved, generates a problem statement representing the problem, and generates a machine representation of a problem statement; a query formatter that reformulates the machine representation into a natural language query or Boolean query and automatically submits the query to at least one knowledge base; and the at least one knowledge base comprising at least one database comprising problem solutions and returning a set of solution suggestions responsive to the query. 13. The system of claim 1 , wherein: the problem analysis tool performs a root cause analysis of the electronic model to generate a directed graph having one or more nodes, wherein each node represents a problem statement and has a node edge that represents a cause-effect relationship; and the query formatter translates the one or more nodes into the natural language query.
| 0.513747 |
1. A physically embodied computer readable-media having embedded computer executable instructions for discerning a term for a misspelled entry, the instructions performing steps comprising: creating a phonetic residue of the misspelled entry; comparing the phonetic residue of the misspelled entry to created phonetic residues of one or more terms in a dictionary of terms; and selecting those terms in the dictionary of terms that have a phonetic residue that substantially matches the phonetic residue of the misspelled entry whereby a selected entry is discerned as a term for the misspelled entry; wherein the phonetic residue of the misspelled entry and the phonetic residues of the dictionary of terms are created by at least removing all phonetic information provided by non-leading vowels of the misspelled entry and terms in the dictionary of terms, respectively.
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1. A physically embodied computer readable-media having embedded computer executable instructions for discerning a term for a misspelled entry, the instructions performing steps comprising: creating a phonetic residue of the misspelled entry; comparing the phonetic residue of the misspelled entry to created phonetic residues of one or more terms in a dictionary of terms; and selecting those terms in the dictionary of terms that have a phonetic residue that substantially matches the phonetic residue of the misspelled entry whereby a selected entry is discerned as a term for the misspelled entry; wherein the phonetic residue of the misspelled entry and the phonetic residues of the dictionary of terms are created by at least removing all phonetic information provided by non-leading vowels of the misspelled entry and terms in the dictionary of terms, respectively. 17. The computer readable-media as recited in claim 1 , wherein a selected term is provided to a search engine.
| 0.612245 |
1. A computer system, including a repository, comprising: a.) first means for transforming a first distinctive representation of business model information into an OMG compliant UML representation of at least a portion of a business model and storing said representation in said repository in the form of a set of object classes, said first means for transforming including: 1) a representation of a business model between one of said distinctive representations and said UML representation of said business model; and 2) means for creating bi-directional mapping between elements of said method of representation of a business model by said one of the distinctive representations and the method of representation of said business model by said UML representation; b.) means for modifying said UML representation of said business model; c.) means for modifying a distinctive representation of said business model to reflect the modification in said UML representation of said business model; and d.)second means for transforming said UML representation into a second distinctive representation of at least a portion of said business model.
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1. A computer system, including a repository, comprising: a.) first means for transforming a first distinctive representation of business model information into an OMG compliant UML representation of at least a portion of a business model and storing said representation in said repository in the form of a set of object classes, said first means for transforming including: 1) a representation of a business model between one of said distinctive representations and said UML representation of said business model; and 2) means for creating bi-directional mapping between elements of said method of representation of a business model by said one of the distinctive representations and the method of representation of said business model by said UML representation; b.) means for modifying said UML representation of said business model; c.) means for modifying a distinctive representation of said business model to reflect the modification in said UML representation of said business model; and d.)second means for transforming said UML representation into a second distinctive representation of at least a portion of said business model. 2. The system of claim 1 wherein business model information comprises at least portion of a business model.
| 0.659746 |
12. A method, comprising: receiving, by a server computing device from a client computing device over a network, a network request for a network page; associating, by the server computing device, one of a plurality of user accounts with the network request; retrieving, by the server computing device, the network page from a network page server over the network; calculating, by the server computing device, for a document, a plurality of component scores including a readability score, a word count, or a timeliness score, wherein the readability score is calculated by applying a readability test to the network page, wherein the readability score is based at least in part on a word complexity, a word diversity, or a sentence length; determining, by the server computing device, a plurality of weights to be multiplied to the plurality of component scores based at least in part on configuration data associated with the user account, each of the plurality of user accounts associated with configuration data; calculating, by the server computing device, a dynamic threshold value as a function of a plurality of quality scores of other network pages; generating, by the server computing device, a quality score for the network page by applying the plurality of weights to the plurality of component scores; and encoding, by the server computing device, for rendering by the client computing device a report embodying at least the quality score within a user interface component distinct from the network page, wherein responsive to the quality score of the network page falling below the dynamic threshold value, the report provides at least one suggested modification to the network page to improve the quality score.
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12. A method, comprising: receiving, by a server computing device from a client computing device over a network, a network request for a network page; associating, by the server computing device, one of a plurality of user accounts with the network request; retrieving, by the server computing device, the network page from a network page server over the network; calculating, by the server computing device, for a document, a plurality of component scores including a readability score, a word count, or a timeliness score, wherein the readability score is calculated by applying a readability test to the network page, wherein the readability score is based at least in part on a word complexity, a word diversity, or a sentence length; determining, by the server computing device, a plurality of weights to be multiplied to the plurality of component scores based at least in part on configuration data associated with the user account, each of the plurality of user accounts associated with configuration data; calculating, by the server computing device, a dynamic threshold value as a function of a plurality of quality scores of other network pages; generating, by the server computing device, a quality score for the network page by applying the plurality of weights to the plurality of component scores; and encoding, by the server computing device, for rendering by the client computing device a report embodying at least the quality score within a user interface component distinct from the network page, wherein responsive to the quality score of the network page falling below the dynamic threshold value, the report provides at least one suggested modification to the network page to improve the quality score. 16. The method of claim 12 , further comprising determining, by the server computing device, the modification to the network page to increase the quality score of the network page.
| 0.599638 |
17. An information system, comprising: a content database to store context-sensitive content items; a content suggestion module implemented using a processor, the content suggestion module configured for selection of suggested content from the context-sensitive content in the content database, the context-sensitive content being relevant to attainment of an overall goal that is attempted by a human subject, wherein the overall goal is attained in connection with changes to human behavior by the human subject in a plurality of real-world activities, and wherein to select the suggested content, the content suggestion module is configured to: establish a filter and a weight for narrowing the selection of context-sensitive content using a condition relevant to the attainment of the overall goal, the condition provided from a profile of the human subject, wherein the profile tracks a behavior characteristic of the human subject affecting the attainment of the overall goal by the human subject; match the context-sensitive content to the human subject according to the condition, by applying the filter to exclude content from the context-sensitive content not satisfying the condition; and prioritize the context-sensitive content to the human subject according to the condition, by applying the weight to produce the selection of the suggested content from the context-sensitive content having a largest prioritization for the condition and having a relevance match to the profile of the human subject; and a content delivery module implemented using the processor, the content delivery module configured to electronically provide the selection of the suggested content based on timing, and modify content of the selection of the suggested content to increase relevance to the human subject; wherein the selection of the suggested content includes one or more suggested actions for performance by the human subject, the one or more suggested actions relevant to the attainment of the overall goal by the human subject.
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17. An information system, comprising: a content database to store context-sensitive content items; a content suggestion module implemented using a processor, the content suggestion module configured for selection of suggested content from the context-sensitive content in the content database, the context-sensitive content being relevant to attainment of an overall goal that is attempted by a human subject, wherein the overall goal is attained in connection with changes to human behavior by the human subject in a plurality of real-world activities, and wherein to select the suggested content, the content suggestion module is configured to: establish a filter and a weight for narrowing the selection of context-sensitive content using a condition relevant to the attainment of the overall goal, the condition provided from a profile of the human subject, wherein the profile tracks a behavior characteristic of the human subject affecting the attainment of the overall goal by the human subject; match the context-sensitive content to the human subject according to the condition, by applying the filter to exclude content from the context-sensitive content not satisfying the condition; and prioritize the context-sensitive content to the human subject according to the condition, by applying the weight to produce the selection of the suggested content from the context-sensitive content having a largest prioritization for the condition and having a relevance match to the profile of the human subject; and a content delivery module implemented using the processor, the content delivery module configured to electronically provide the selection of the suggested content based on timing, and modify content of the selection of the suggested content to increase relevance to the human subject; wherein the selection of the suggested content includes one or more suggested actions for performance by the human subject, the one or more suggested actions relevant to the attainment of the overall goal by the human subject. 22. The information system of claim 17 , further comprising: a feedback module configured to receive feedback from the human subject about one or more suggested actions presented to the human subject from the suggested content.
| 0.631267 |
11. An apparatus for searching audio files in a portable audio player in combination with an automobile audio system, comprising: means for reading meta-tag data associated with each audio file and producing voice data files for information retrieved from the meta-tag data; means for creating a play list that lists the voice data files produced based on the meta-tag data in an predetermined order where each of the voice data files and audio files is accompanied by address data; means for storing the play list and the audio files in the portable audio player; means for connecting the portable audio player with the automobile audio system for sending the voice data files in the play list and the audio files to the automobile audio system and receiving command signals from the automobile audio system; means for generating speech sounds that successively and automatically read aloud the data in the voice data files in the play list by the automobile audio system in a predetermined order and speed; means for accepting user's commands made in response to the speech sounds where the user's commands are transmitted through the automobile audio system to the portable audio player; and means for searching an audio file in the portable audio player based on the user's commands; wherein the speech sounds generated from the automobile audio system include a series of information on audio files so that a particular audio file is specified when both the information on the particular audio file is announced by the speech sounds and the user's commands are issued.
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11. An apparatus for searching audio files in a portable audio player in combination with an automobile audio system, comprising: means for reading meta-tag data associated with each audio file and producing voice data files for information retrieved from the meta-tag data; means for creating a play list that lists the voice data files produced based on the meta-tag data in an predetermined order where each of the voice data files and audio files is accompanied by address data; means for storing the play list and the audio files in the portable audio player; means for connecting the portable audio player with the automobile audio system for sending the voice data files in the play list and the audio files to the automobile audio system and receiving command signals from the automobile audio system; means for generating speech sounds that successively and automatically read aloud the data in the voice data files in the play list by the automobile audio system in a predetermined order and speed; means for accepting user's commands made in response to the speech sounds where the user's commands are transmitted through the automobile audio system to the portable audio player; and means for searching an audio file in the portable audio player based on the user's commands; wherein the speech sounds generated from the automobile audio system include a series of information on audio files so that a particular audio file is specified when both the information on the particular audio file is announced by the speech sounds and the user's commands are issued. 16. An apparatus for searching an audio file as defined in claim 11 , wherein said meta-tag data includes at least an artist name and a title of music that associated with each of the audio files.
| 0.61561 |
32. The invention as set forth in claim 31, wherein the minimum total cost is a least number of bits required to represent each data set.
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32. The invention as set forth in claim 31, wherein the minimum total cost is a least number of bits required to represent each data set. 33. The invention as set forth in claim 32, wherein the total cost is a total encoding cost of each decoding context associated with each data set plus the cost of representing codebooks for each of decoding context.
| 0.804007 |
1. An input method for completing a missing text or a phrase on a display of a device terminal, comprising: receiving an input of a plurality of words as a first phrase or a first sentence through key entries for displaying on the device terminal; receiving an input of a first punctuation, wherein the first punctuation follows after the first phrase or the first sentence; receiving an input of a plurality of words as a second phrase or a second sentence through key entries for displaying on the device terminal, wherein the second phrase or the second sentence follows after the first punctuation; detecting a first location of a cursor on the display of the device terminal, wherein the first location of the cursor is positioned after an end of the second phrase or the second sentence; identifying by the device terminal, one or more words within only the second phrase or the second sentence which is located between the first punctuation and the first location of the cursor; using the identified one or more words within only the second phrase or the second sentence as a first previous text or a first previous phrase, querying for a first next text or a first next phrase from a word library in a memory of the device terminal, wherein the first next text or the first next phrase is associated in context with the first previous text or the first previous phrase; outputting on the display of the device terminal, the associated first next text or first next phrase which appends after the end of the second phrase or the second sentence; detecting a second location of the cursor on the display of the device terminal after the associated first next text or first next phrase is outputted, wherein the second location of the cursor is positioned before the first location of the cursor, and wherein the second location of the cursor is positioned after the first punctuation; identifying by the device terminal, one or more words within only a third phrase or a third sentence which is located between the first punctuation and the second location of the cursor; using the identified one or more words within only the third phrase or the third sentence as a second previous text or a second previous phrase, querying for a second next text or a second next phrase from the word library in the memory of the device terminal, wherein the second next text or the second next phrase is associated in context with the second previous text or the second previous phrase; and outputting on the display of the device terminal, the associated second next text or second next phrase which appends after the end of the third phrase or the third sentence.
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1. An input method for completing a missing text or a phrase on a display of a device terminal, comprising: receiving an input of a plurality of words as a first phrase or a first sentence through key entries for displaying on the device terminal; receiving an input of a first punctuation, wherein the first punctuation follows after the first phrase or the first sentence; receiving an input of a plurality of words as a second phrase or a second sentence through key entries for displaying on the device terminal, wherein the second phrase or the second sentence follows after the first punctuation; detecting a first location of a cursor on the display of the device terminal, wherein the first location of the cursor is positioned after an end of the second phrase or the second sentence; identifying by the device terminal, one or more words within only the second phrase or the second sentence which is located between the first punctuation and the first location of the cursor; using the identified one or more words within only the second phrase or the second sentence as a first previous text or a first previous phrase, querying for a first next text or a first next phrase from a word library in a memory of the device terminal, wherein the first next text or the first next phrase is associated in context with the first previous text or the first previous phrase; outputting on the display of the device terminal, the associated first next text or first next phrase which appends after the end of the second phrase or the second sentence; detecting a second location of the cursor on the display of the device terminal after the associated first next text or first next phrase is outputted, wherein the second location of the cursor is positioned before the first location of the cursor, and wherein the second location of the cursor is positioned after the first punctuation; identifying by the device terminal, one or more words within only a third phrase or a third sentence which is located between the first punctuation and the second location of the cursor; using the identified one or more words within only the third phrase or the third sentence as a second previous text or a second previous phrase, querying for a second next text or a second next phrase from the word library in the memory of the device terminal, wherein the second next text or the second next phrase is associated in context with the second previous text or the second previous phrase; and outputting on the display of the device terminal, the associated second next text or second next phrase which appends after the end of the third phrase or the third sentence. 4. The input method according to claim 1 , wherein the querying for the second next text or the second next phrase from the word library in the memory of the device terminal, comprises: querying from the word library for all expressions and sentences comprising the second previous text or the second previous phrase, and using an expression or a sentence that exists in the found expressions and sentences but does not exist in the second previous text or the second previous phrase as the second next text or the second next phrase.
| 0.532274 |
6. The method of claim 5 , wherein the updating the plurality of survey questions by removing questions satisfied by response answers from the selected set of experts comprises: determining that a question has been satisfied with a satisfactory answer upon receiving a total number of responses that meets a threshold number of responses; or determining that a question has been satisfied with a satisfactory answer if an answer to a question is within a threshold variance of correlation to the expected answer.
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6. The method of claim 5 , wherein the updating the plurality of survey questions by removing questions satisfied by response answers from the selected set of experts comprises: determining that a question has been satisfied with a satisfactory answer upon receiving a total number of responses that meets a threshold number of responses; or determining that a question has been satisfied with a satisfactory answer if an answer to a question is within a threshold variance of correlation to the expected answer. 7. The method of claim 6 , further comprising: determining that a question has been satisfied with a satisfactory answer upon receiving a response from a non-outlier expert and a response from an outlier expert.
| 0.931211 |
1. A computer-implemented method for searching a corpus of documents, the method comprising: defining a query as a twig comprising a root annotation operator having an associated tag specifying a span and having an associated expression indicative of one or more terms whose occurrence within the span will satisfy the query; recursively selecting an object from a group of objects that consists of the tag and the expression, and advancing through the corpus using the selected object until a candidate document is found that contains the tag and satisfies the expression; evaluating the candidate document to determine whether the one or more terms indicated by the expression occur within the span in the candidate document so as to satisfy the annotation operator; and retrieving the candidate document from the corpus upon determining that the annotation operator is satisfied.
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1. A computer-implemented method for searching a corpus of documents, the method comprising: defining a query as a twig comprising a root annotation operator having an associated tag specifying a span and having an associated expression indicative of one or more terms whose occurrence within the span will satisfy the query; recursively selecting an object from a group of objects that consists of the tag and the expression, and advancing through the corpus using the selected object until a candidate document is found that contains the tag and satisfies the expression; evaluating the candidate document to determine whether the one or more terms indicated by the expression occur within the span in the candidate document so as to satisfy the annotation operator; and retrieving the candidate document from the corpus upon determining that the annotation operator is satisfied. 6. The method according to claim 1 , wherein advancing through the corpus comprises creating an index of tags and words occurring in the documents in the corpus, and using the index to find the candidate documents.
| 0.678955 |
31. A non-transitory computer readable storage device storing a computer program product comprising machine-readable instructions that, when executed, cause a computer system to carry out operations comprising: receiving, by the computer system, data entered at a user interface provided on a display of a user device from a first user associated with a pre-determined user group, the data comprising an identification of a) a source language and b) a target language to which translation from the source language is requested; determining, by the computer system, that one or more second users of the pre-determined user group is associated with the source language and associated with the target language, each of the second users being a candidate to perform a translation from the source language to the target language, based on accessing a data repository that stores language capabilities of users within the pre-determined user group, the language capabilities of the users within the pre-determined user group being determined automatically based on mining a corpus of electronic documents associated with the pre-determined user group; and transmitting, by the computer system, an identification of the one or more second users, each of whom is a candidate to perform a translation from the source language to the target language, to the user device for display on the user interface; wherein the display of the identification of the one or more second users is based on a permission that allows a corresponding second user to be identified to one or more other users in the pre-determined user group.
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31. A non-transitory computer readable storage device storing a computer program product comprising machine-readable instructions that, when executed, cause a computer system to carry out operations comprising: receiving, by the computer system, data entered at a user interface provided on a display of a user device from a first user associated with a pre-determined user group, the data comprising an identification of a) a source language and b) a target language to which translation from the source language is requested; determining, by the computer system, that one or more second users of the pre-determined user group is associated with the source language and associated with the target language, each of the second users being a candidate to perform a translation from the source language to the target language, based on accessing a data repository that stores language capabilities of users within the pre-determined user group, the language capabilities of the users within the pre-determined user group being determined automatically based on mining a corpus of electronic documents associated with the pre-determined user group; and transmitting, by the computer system, an identification of the one or more second users, each of whom is a candidate to perform a translation from the source language to the target language, to the user device for display on the user interface; wherein the display of the identification of the one or more second users is based on a permission that allows a corresponding second user to be identified to one or more other users in the pre-determined user group. 33. The computer readable storage device of claim 31 , wherein the language capabilities of the users within the pre-determined user group are determined based on: identifying a particular language from the electronic documents of the corpus; identifying one or more users associated with the electronic documents; and storing the particular language as a language capability of the identified one or more users.
| 0.5 |
16. A non-transitory, computer-readable storage medium storing instructions, an execution of which in a computer system causes the computer system to perform operations comprising: receiving event data associated with network activities, wherein the event data comprises machine data; evaluating event data based on a machine learning model utilizing historical data pertaining to evaluations of past events; identifying at least one anomaly automatically determined from machine learning on the event data; identifying at least one threat automatically determined from machine learning on the event data and the identified at least one anomaly, wherein a threat is associated with each identified anomaly that, individually or in combination, triggered the determination of the threat; and upon selection by a user, via a graphical user interface, of an identified threat, generating a kill chain view associated with the threat, wherein the kill chain view includes a plurality of stages, and, for each stage, the kill chain view lists each type of identified anomaly associated with each stage of the kill chain and the number of anomalies of each type, wherein the listing of comprises a link for each anomaly type; upon selection by the user, via a graphical user interface, of the link for a selected anomaly type, generating a listing of all anomalies of the selected type, including a link for each anomaly; upon selection by the user of the link for a selected anomaly, generating a prompt to tag the anomaly for subsequent tracking; and upon receiving input from the user regarding the identified threat based upon the anomalies in the generated kill chain view, providing feedback for training the machine learning model.
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16. A non-transitory, computer-readable storage medium storing instructions, an execution of which in a computer system causes the computer system to perform operations comprising: receiving event data associated with network activities, wherein the event data comprises machine data; evaluating event data based on a machine learning model utilizing historical data pertaining to evaluations of past events; identifying at least one anomaly automatically determined from machine learning on the event data; identifying at least one threat automatically determined from machine learning on the event data and the identified at least one anomaly, wherein a threat is associated with each identified anomaly that, individually or in combination, triggered the determination of the threat; and upon selection by a user, via a graphical user interface, of an identified threat, generating a kill chain view associated with the threat, wherein the kill chain view includes a plurality of stages, and, for each stage, the kill chain view lists each type of identified anomaly associated with each stage of the kill chain and the number of anomalies of each type, wherein the listing of comprises a link for each anomaly type; upon selection by the user, via a graphical user interface, of the link for a selected anomaly type, generating a listing of all anomalies of the selected type, including a link for each anomaly; upon selection by the user of the link for a selected anomaly, generating a prompt to tag the anomaly for subsequent tracking; and upon receiving input from the user regarding the identified threat based upon the anomalies in the generated kill chain view, providing feedback for training the machine learning model. 22. The computer-readable storage medium of claim 16 , wherein the input received from the user indicates whether the identified threat or an anomaly associated with the threat is accurate or false.
| 0.822355 |
9. A system for enforcing parental-control policies on user-generated content comprising: a detection module programmed to: identify a web document, the web document comprising user-generated content that is not authored by an entity that publishes and/or hosts the web document; identify a subset of links in the web document that are related to the user-generated content in the web document by: 1) parsing the web document to identify a set of links in the web document; 2) identifying, within the set of links, one or more links which are related to the user-generated content by determining that the one or more links refer to the user-generated content, by determining that the user-generated content includes the one or more links, and/or by determining that the one or more links refer to a content-generating user responsible for generating the user-generated content; 3) excluding, from the subset of links, one or more links identified in the set of links that were not determined to be related to the user-generated content in the web document; 4) including, in the subset of links, the one or more links that were determined to be related to the user-generated content in the web document; a rating module programmed to: for each link in the subset of links: identify a target web document of the link; determine a parental-control rating for the link based on the target web document; generate a composite rating of the web document based, at least in part, on the parental-control rating of each link in the subset of links; enforce the parental control policy based on the composite rating of the web document; one or more processors configured to execute the detection module and the rating module.
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9. A system for enforcing parental-control policies on user-generated content comprising: a detection module programmed to: identify a web document, the web document comprising user-generated content that is not authored by an entity that publishes and/or hosts the web document; identify a subset of links in the web document that are related to the user-generated content in the web document by: 1) parsing the web document to identify a set of links in the web document; 2) identifying, within the set of links, one or more links which are related to the user-generated content by determining that the one or more links refer to the user-generated content, by determining that the user-generated content includes the one or more links, and/or by determining that the one or more links refer to a content-generating user responsible for generating the user-generated content; 3) excluding, from the subset of links, one or more links identified in the set of links that were not determined to be related to the user-generated content in the web document; 4) including, in the subset of links, the one or more links that were determined to be related to the user-generated content in the web document; a rating module programmed to: for each link in the subset of links: identify a target web document of the link; determine a parental-control rating for the link based on the target web document; generate a composite rating of the web document based, at least in part, on the parental-control rating of each link in the subset of links; enforce the parental control policy based on the composite rating of the web document; one or more processors configured to execute the detection module and the rating module. 10. The system of claim 9 , wherein the rating module enforces the parental-control policy by blocking access to the web document.
| 0.566351 |
12. A system comprising: at least one processor; and memory that comprises instructions that, when executed by the at least one processor, cause the at least one processor to generate a computer-readable index, wherein generating the computer-readable index comprises: locating a table in source code of a page, the table comprises an attribute identity of an entity and an attribute value for the attribute identity and the entity, wherein the table is free of an identity of the entity; responsive to locating the table in the source code of the web page, inferring the identity of the entity, wherein inferring the identity of the entity comprises: determining that a title of the page and a header of the page comprise a same keyword; and inferring that the keyword is at least a portion of the identity of the entity based upon the keyword being included in both the title of the page and the header of the page; and responsive to inferring the identity of the entity, in the computer-readable index, indexing the attribute value by the entity identity and the attribute identity.
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12. A system comprising: at least one processor; and memory that comprises instructions that, when executed by the at least one processor, cause the at least one processor to generate a computer-readable index, wherein generating the computer-readable index comprises: locating a table in source code of a page, the table comprises an attribute identity of an entity and an attribute value for the attribute identity and the entity, wherein the table is free of an identity of the entity; responsive to locating the table in the source code of the web page, inferring the identity of the entity, wherein inferring the identity of the entity comprises: determining that a title of the page and a header of the page comprise a same keyword; and inferring that the keyword is at least a portion of the identity of the entity based upon the keyword being included in both the title of the page and the header of the page; and responsive to inferring the identity of the entity, in the computer-readable index, indexing the attribute value by the entity identity and the attribute identity. 13. The system of claim 12 , wherein inferring the identity of the entity further comprises: performing a comparison between queries issued to a search engine to locate the page and keywords in at least one of the title, the header, or content of the page; and inferring the entity identity based upon the comparison.
| 0.604721 |
2. The computer program product of claim 1 wherein the terminology content comprises concepts that are associated with at least one terminology code system.
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2. The computer program product of claim 1 wherein the terminology content comprises concepts that are associated with at least one terminology code system. 3. The computer program product of claim 2 wherein the seed concept has a coded data type.
| 0.958413 |
15. A method according to claim 14 , wherein locating a first layout strings file and a second layout strings file from a plurality of layout strings files includes locating the one of the plurality of layout strings files storing the first layout string in a selected language.
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15. A method according to claim 14 , wherein locating a first layout strings file and a second layout strings file from a plurality of layout strings files includes locating the one of the plurality of layout strings files storing the first layout string in a selected language. 16. A method according to claim 15 , wherein locating a first LIF and a second LIF from a plurality of layout information files includes locating a layout information file dependent on the selected language specifying how the first content is to be presented to the user.
| 0.858301 |
8. A system for automatically constructing wrappers across a plurality of domains, the system comprising: a memory; and a processor coupled to the memory, the processor configured to: create a first wrapper in a first domain using a first set of training data, the first set of training data created from a subset of documents in the first domain; apply the first wrapper to each page in the first domain to extract additional training data; combine the first set of training data with the additional training data to generate a first target string; search other domains in the plurality of domains to determine if any of the other domains comprises documents having portions of the first target string; and create a second wrapper for at least one of the other domains in the plurality of domains from the first target string.
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8. A system for automatically constructing wrappers across a plurality of domains, the system comprising: a memory; and a processor coupled to the memory, the processor configured to: create a first wrapper in a first domain using a first set of training data, the first set of training data created from a subset of documents in the first domain; apply the first wrapper to each page in the first domain to extract additional training data; combine the first set of training data with the additional training data to generate a first target string; search other domains in the plurality of domains to determine if any of the other domains comprises documents having portions of the first target string; and create a second wrapper for at least one of the other domains in the plurality of domains from the first target string. 14. The system of claim 8 , wherein the first target string follows a known set of variations across the plurality of domains.
| 0.736861 |
22. The speech synthesizer of claim 21 wherein one of said control signals is produced by said input means whenever a phoneme requiring vocal energy is to be generated, and said suppression means is adapted to effect the bandwidths of said resonant filters only when said one control signal is produced.
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22. The speech synthesizer of claim 21 wherein one of said control signals is produced by said input means whenever a phoneme requiring vocal energy is to be generated, and said suppression means is adapted to effect the bandwidths of said resonant filters only when said one control signal is produced. 23. The speech synthesizer of claim 22 wherein said one control signal comprises a vocal amplitude control signal.
| 0.896208 |
7. The article of manufacture of claim 5 further comprising: getting and setting said classfile by referring to a name of a construct within said set of configuration data that contains both said identity of said classfile and said identity of said serializer.
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7. The article of manufacture of claim 5 further comprising: getting and setting said classfile by referring to a name of a construct within said set of configuration data that contains both said identity of said classfile and said identity of said serializer. 8. The article of manufacture of claim 7 further comprising: getting and setting said serializer by referring to said name.
| 0.903214 |
1. A method, comprising: determining, using a first sentiment model having a current list of keywords and respective weights, respective sentiment results for a plurality of posts, wherein the determining is performed using a processing device; receiving, via a user interface, sentiment feedback for the respective sentiment results; displaying a first set of posts which are in the plurality of posts and have a sentiment feedback not matching the respective sentiment results; displaying: keywords which appear in the first set of posts; and the keywords' respective weights; receiving a first change including at least one of: a first proposed change to a respective weight of one or more of the keywords; a first proposed deletion of one or more of the keywords; or a first proposed new keyword and a respective weight of the first proposed new keyword; maintaining unchanged the current list of keywords and respective weights while creating a proposed list of keywords and respective weights by applying the first change to the current list of keywords and respective weights; analyzing the first set of posts, using the proposed list of keywords and respective weights; enabling identifying overfitting by displaying sentiment results for the first set of posts produced using the proposed list of keywords and respective weights; receiving a second change including at least one of: a second proposed change to a respective weight of one or more of the keywords; a second proposed deletion of one or more of the keywords; or a second proposed new keyword and a respective weight of the second proposed new keyword; updating the proposed list of keywords and respective weights by applying the second change to the proposed list of keywords and respective weights; after applying the second change to the proposed list of keywords and respective weights, re-analyzing the first set of posts using the proposed list of keywords and respective weights; enabling identifying overfitting by displaying sentiment results for the first set of posts produced using the proposed list of keywords and respective weights; and creating a second sentiment model by replacing the current list of keywords and respective weights with the second proposed list of keywords and respective weights.
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1. A method, comprising: determining, using a first sentiment model having a current list of keywords and respective weights, respective sentiment results for a plurality of posts, wherein the determining is performed using a processing device; receiving, via a user interface, sentiment feedback for the respective sentiment results; displaying a first set of posts which are in the plurality of posts and have a sentiment feedback not matching the respective sentiment results; displaying: keywords which appear in the first set of posts; and the keywords' respective weights; receiving a first change including at least one of: a first proposed change to a respective weight of one or more of the keywords; a first proposed deletion of one or more of the keywords; or a first proposed new keyword and a respective weight of the first proposed new keyword; maintaining unchanged the current list of keywords and respective weights while creating a proposed list of keywords and respective weights by applying the first change to the current list of keywords and respective weights; analyzing the first set of posts, using the proposed list of keywords and respective weights; enabling identifying overfitting by displaying sentiment results for the first set of posts produced using the proposed list of keywords and respective weights; receiving a second change including at least one of: a second proposed change to a respective weight of one or more of the keywords; a second proposed deletion of one or more of the keywords; or a second proposed new keyword and a respective weight of the second proposed new keyword; updating the proposed list of keywords and respective weights by applying the second change to the proposed list of keywords and respective weights; after applying the second change to the proposed list of keywords and respective weights, re-analyzing the first set of posts using the proposed list of keywords and respective weights; enabling identifying overfitting by displaying sentiment results for the first set of posts produced using the proposed list of keywords and respective weights; and creating a second sentiment model by replacing the current list of keywords and respective weights with the second proposed list of keywords and respective weights. 3. The method of claim 1 , wherein the received sentiment feedback is in a form of negative actual sentiment, indifferent actual sentiment, or positive actual sentiment.
| 0.915591 |
7. A testing method, comprising: presenting to a user a test question, said test question indicating a task to be performed using a computer application and prompting the user to perform the task using the computer application to create a computer graphic responsive to the test question displayed on a computer screen; automatically taking a snapshot of at least a portion of the computer screen containing the computer graphic responsive to the test question, and combining this snapshot with received text to create a page comprising the received text and the snapshot represented in a common internet language; and storing the page in an electronic database as an answer to the test question.
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7. A testing method, comprising: presenting to a user a test question, said test question indicating a task to be performed using a computer application and prompting the user to perform the task using the computer application to create a computer graphic responsive to the test question displayed on a computer screen; automatically taking a snapshot of at least a portion of the computer screen containing the computer graphic responsive to the test question, and combining this snapshot with received text to create a page comprising the received text and the snapshot represented in a common internet language; and storing the page in an electronic database as an answer to the test question. 15. The method according to claim 7 , further comprising the step of selectively limiting access to the page based on an authorization.
| 0.758162 |
1. A method for routing a facsimile, comprising: receiving text of a facsimile in a computer readable format; ascertaining one or more of a significance and a relevance of at least a portion of the text by ascertaining a position of one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyzing the text of the facsimile for at least one of a meaning and a context of the text; routing the facsimile or text thereof to one or more destinations based on the analysis; initiating a business process based on the analysis; detecting a problem with the business process; generating a notification of the problem; and notifying one or more entities of the problem, wherein the routing utilizes an outgoing communication device.
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1. A method for routing a facsimile, comprising: receiving text of a facsimile in a computer readable format; ascertaining one or more of a significance and a relevance of at least a portion of the text by ascertaining a position of one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyzing the text of the facsimile for at least one of a meaning and a context of the text; routing the facsimile or text thereof to one or more destinations based on the analysis; initiating a business process based on the analysis; detecting a problem with the business process; generating a notification of the problem; and notifying one or more entities of the problem, wherein the routing utilizes an outgoing communication device. 9. The method as recited in claim 1 , wherein at least one of the destinations corresponds to a recipient other than an intended recipient of the facsimile.
| 0.61128 |
13. An article, comprising: a computer readable medium comprising non-transitory stored instructions that enable a machine to: receive a document from a user having an associated security access profile; generate a security label to be stored as an attribute of the document, the security label comprising: a clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of the plurality of clearance components determined based on the security access profile associated with the user; and a secondary security component selected from an authorized subset of a plurality of secondary security components, the authorized subset of the plurality of secondary security components determined based on the clearance component of the security label and the security access profile associated with the user; store the document in a document repository storing a plurality of documents each having an associated security label; determine whether a third-party user is authorized access the document based on a comparison of a security access profile of the third-party user and the security label associated with the document; allow, when a determination that the third-party user is authorized to access the document based on the comparison of the security access profile of the third-party/user and the security label associated with the document, the third-party user to access the document; receive an edited version of the document from the third-party user, the edited version of the document having an associated updated security label, the updated security label comprising: an updated clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of a plurality of clearance components determined based on the security access profile associated with the third-party user; and one or more updated secondary security components selected from a subset of a plurality of secondary security components, the subset of a plurality of secondary security components determined based on the updated clearance component of the updated security label and the security access profile associated with the third-party user; and store the edited version of the document in the document repository storing the plurality of documents each having an associated security label.
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13. An article, comprising: a computer readable medium comprising non-transitory stored instructions that enable a machine to: receive a document from a user having an associated security access profile; generate a security label to be stored as an attribute of the document, the security label comprising: a clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of the plurality of clearance components determined based on the security access profile associated with the user; and a secondary security component selected from an authorized subset of a plurality of secondary security components, the authorized subset of the plurality of secondary security components determined based on the clearance component of the security label and the security access profile associated with the user; store the document in a document repository storing a plurality of documents each having an associated security label; determine whether a third-party user is authorized access the document based on a comparison of a security access profile of the third-party user and the security label associated with the document; allow, when a determination that the third-party user is authorized to access the document based on the comparison of the security access profile of the third-party/user and the security label associated with the document, the third-party user to access the document; receive an edited version of the document from the third-party user, the edited version of the document having an associated updated security label, the updated security label comprising: an updated clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of a plurality of clearance components determined based on the security access profile associated with the third-party user; and one or more updated secondary security components selected from a subset of a plurality of secondary security components, the subset of a plurality of secondary security components determined based on the updated clearance component of the updated security label and the security access profile associated with the third-party user; and store the edited version of the document in the document repository storing the plurality of documents each having an associated security label. 15. The software of claim 13 , operable to: generate a first interface to be displayed to the user, the first interface comprising a clearance component field comprising one or more clearance components of the subset of authorized clearance components to the user; receive from the user a selection of an authorized clearance component from the one or more clearance components of the subset of authorized clearance components; determine, in response to the selection of the clearance component of the security label by the user, the one or more authorized subsets of secondary security components from the plurality of secondary security components based on the selected clearance component of the security label and the security access profile associated with the user; and generate a second interface to be displayed to the user, the second interface comprising one or more secondary security component fields, each secondary security component field comprising one or more secondary security components of a subset of authorized secondary security components.
| 0.571759 |
52. The system of claim 51 wherein the operations further comprise: updating a confidence score for the second user based on the accuracy of the translation correction, the confidence score representing a likelihood that the second user will provide an accurate translation of a text message at a later time.
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52. The system of claim 51 wherein the operations further comprise: updating a confidence score for the second user based on the accuracy of the translation correction, the confidence score representing a likelihood that the second user will provide an accurate translation of a text message at a later time. 53. The system of claim 52 wherein the operations further comprise: revoking the second user's translation privileges when the confidence score falls below a threshold value.
| 0.931502 |
89. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the personally identifiable information comprises e-mail addresses; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender.
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89. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the personally identifiable information comprises e-mail addresses; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender. 94. The method of claim 89 wherein the first activity information is generated by activity at a Web site.
| 0.647078 |
19. The system of claim 18 , wherein the system further comprises a data store having stored within it a set of context-specific parameters, the set of context-specific parameters comprising, for each context, a weighting factor for each language model.
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19. The system of claim 18 , wherein the system further comprises a data store having stored within it a set of context-specific parameters, the set of context-specific parameters comprising, for each context, a weighting factor for each language model. 20. The system of claim 19 , wherein the context-specific parameters are recipient-specific parameters.
| 0.908038 |
7. The method of claim 1 , wherein modifying the second plurality of query results based on the information associated with the tracked navigation of the user through the first plurality of query results comprises: identifying one or more additional search terms within the information associated with the tracked navigation of the user through the first plurality of query results; supplementing the second set of one or more search terms from the user with the one or more additional search terms; and using the supplemented search terms to modify the second plurality of query results.
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7. The method of claim 1 , wherein modifying the second plurality of query results based on the information associated with the tracked navigation of the user through the first plurality of query results comprises: identifying one or more additional search terms within the information associated with the tracked navigation of the user through the first plurality of query results; supplementing the second set of one or more search terms from the user with the one or more additional search terms; and using the supplemented search terms to modify the second plurality of query results. 8. The method of claim 7 , wherein the one or more additional search terms are located in different electronic documents within the first plurality of query results.
| 0.825683 |
10. The system of claim 9 wherein: the first job ticket comprises an AFP Form Map; and the server is further operable to extract the second job ticket from within a Medium Map of the AFP Form Map.
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10. The system of claim 9 wherein: the first job ticket comprises an AFP Form Map; and the server is further operable to extract the second job ticket from within a Medium Map of the AFP Form Map. 11. The system of claim 10 wherein: the server is further operable to extract the second job ticket from within a Medium Map that includes a tag identifying the language of the second job ticket as JDF.
| 0.859102 |
11. A computer program product for identifying content in a document, the computer program product comprising: a computer readable storage medium, wherein the computer readable storage medium is not a signal, wherein the computer readable storage medium includes program instructions that when executed by a computer cause the computer to carry out the steps of: identifying within each document of a plurality of open documents, by a computing device, content corresponding to a particular subject matter category; in response to the computing device opening an additional document, identifying within the additional document, by the computer device, additional content corresponding to the particular subject matter category; providing, within the additional document, an indicator that visually distinguishes the identified additional content from the other content within the additional document; in response to the computing device opening a second additional document and content of the second additional document not corresponding to the particular subject matter category, determining a new subject matter category corresponding to the content of the second additional document; determining a majority of the plurality of open documents of the computing device relate to similar subject matter, wherein the particular subject matter category relates to the similar subject matter; in response to determining that the majority of the plurality of open documents of the computing device relate to the similar subject matter, assigning a weight to the similar subject matter and the new subject matter category, wherein the similar subject matter is more heavily weighted than the new subject matter category; and providing indicators that visually distinguish documents relating to the similar subject matter category from documents relating to the new subject matter category.
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11. A computer program product for identifying content in a document, the computer program product comprising: a computer readable storage medium, wherein the computer readable storage medium is not a signal, wherein the computer readable storage medium includes program instructions that when executed by a computer cause the computer to carry out the steps of: identifying within each document of a plurality of open documents, by a computing device, content corresponding to a particular subject matter category; in response to the computing device opening an additional document, identifying within the additional document, by the computer device, additional content corresponding to the particular subject matter category; providing, within the additional document, an indicator that visually distinguishes the identified additional content from the other content within the additional document; in response to the computing device opening a second additional document and content of the second additional document not corresponding to the particular subject matter category, determining a new subject matter category corresponding to the content of the second additional document; determining a majority of the plurality of open documents of the computing device relate to similar subject matter, wherein the particular subject matter category relates to the similar subject matter; in response to determining that the majority of the plurality of open documents of the computing device relate to the similar subject matter, assigning a weight to the similar subject matter and the new subject matter category, wherein the similar subject matter is more heavily weighted than the new subject matter category; and providing indicators that visually distinguish documents relating to the similar subject matter category from documents relating to the new subject matter category. 12. The computer program product of claim 11 , wherein the plurality of open documents and the additional document comprise one or more of word processing documents, spreadsheets, text editing files, presentation documents or web browser pages.
| 0.657895 |
1. A voice messaging system for converting an audio voice message from a caller into text, the voice messaging system comprising: a plurality of conversion resources for converting the audio voice message into the text for an intended recipient, the plurality of conversion resources comprising: at least one automatic speech recognition (ASR) system to automatically recognize at least some of the audio voice message and generate a plurality of candidate words or phrases; and a computer implemented lattice sub-system that generates a lattice of possible words or phrases, enabling an operator to view one or more candidate words or phrases and to either select one of the one or more candidate words or phrases, or, by entering one or more characters of a different word or phrase, to trigger the lattice sub-system to provide at least one alternative word or phrase, wherein the lattice sub-system automatically differentiates between parts of the message based on whether the lattice sub-system determines parts of the message to be important or unimportant.
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1. A voice messaging system for converting an audio voice message from a caller into text, the voice messaging system comprising: a plurality of conversion resources for converting the audio voice message into the text for an intended recipient, the plurality of conversion resources comprising: at least one automatic speech recognition (ASR) system to automatically recognize at least some of the audio voice message and generate a plurality of candidate words or phrases; and a computer implemented lattice sub-system that generates a lattice of possible words or phrases, enabling an operator to view one or more candidate words or phrases and to either select one of the one or more candidate words or phrases, or, by entering one or more characters of a different word or phrase, to trigger the lattice sub-system to provide at least one alternative word or phrase, wherein the lattice sub-system automatically differentiates between parts of the message based on whether the lattice sub-system determines parts of the message to be important or unimportant. 21. The system of claim 1 further comprising a mobile telephone for displaying the text converted from the audio voice message.
| 0.539207 |
11. A method for forming a pronounceable security password according to claim 9, further comprising the steps: discarding said second pronounceable word segment if the transition number of said corresponding word segment is less than said second threshold transition number; selecting a third one of said plurality of first word segment portions, wherein selection of any one of said plurality of first word segment portions is of substantially equal probability; selecting a third one of said plurality of second word segment portions from the set of second word segment portions associated with said third selected first word segment portion, wherein selection of any one of said second word segment portions within said associated set of second word segment portions is of substantially equal probability; combining said third selected first word segment portion and said third selected second word segment portion to form a substitute second pronounceable word segment; and combining said first pronounceable word segment and said substitute second pronounceable word segment to form a substitute portion of the password; wherein said generated pronounceable security password includes said substitute second pronounceable word segment only if consecutive characters of said substitute password portion fail to correspond to those of said plurality of first word segment portions having a transition number less than said second threshold transition number.
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11. A method for forming a pronounceable security password according to claim 9, further comprising the steps: discarding said second pronounceable word segment if the transition number of said corresponding word segment is less than said second threshold transition number; selecting a third one of said plurality of first word segment portions, wherein selection of any one of said plurality of first word segment portions is of substantially equal probability; selecting a third one of said plurality of second word segment portions from the set of second word segment portions associated with said third selected first word segment portion, wherein selection of any one of said second word segment portions within said associated set of second word segment portions is of substantially equal probability; combining said third selected first word segment portion and said third selected second word segment portion to form a substitute second pronounceable word segment; and combining said first pronounceable word segment and said substitute second pronounceable word segment to form a substitute portion of the password; wherein said generated pronounceable security password includes said substitute second pronounceable word segment only if consecutive characters of said substitute password portion fail to correspond to those of said plurality of first word segment portions having a transition number less than said second threshold transition number. 12. A method for forming a pronounceable security password according to claim 11, further comprising the step of determining if consecutive characters of said substitute portion of the password correspond to a first word segment portion, within said plurality of first word segment portions, and if the transition number of said corresponding first word segment portion is less than said second threshold transition number.
| 0.745427 |
1. A system for analyzing entity performance, the system comprising: a memory that stores a set of instructions; one or more processors configured to execute the set of instructions that cause the one or more processors to: receive a request from a user computer via a network with one or more filter selections; access a data structure in the memory, the data structure comprising a plurality of categories of information showing interactions related to multiple entities; identify a set of categories of the plurality of categories within the data structure based on the one or more filter selections, the set of categories within the data structure includes location information related to at least one of the multiple entities, wherein the plurality of the categories of the data structure include at least one of: an interaction number category, a consuming entity identification category, a consuming entity location category, a provisioning entity identification category, a provisioning entity location category, a type of provisioning entity category, an interaction amount category, and a time of interaction category; determine the location information of the at least one of the multiple entities to update the data structure, wherein the location information is determined based on a computed affinity score that is based on computed travel times so that the affinity score can have an inverse proportionality with computed travel times such that a higher affinity score can have a lower travel time, wherein the computed affinity score is used to estimate the location information within an estimated area location for the provisioning entity without an identified location information, wherein the determining includes verifying that a populated category of the plurality of categories is valid data that signifies the location information; update the data structure with the determined location information within the area location; process the location information of the identified set of categories to analyze a performance of one or more entities of the multiple entities in accordance with the one or more filter selections; and provide the processed location information to display the performance of the one or more entities on a graphical user interface of the user computer.
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1. A system for analyzing entity performance, the system comprising: a memory that stores a set of instructions; one or more processors configured to execute the set of instructions that cause the one or more processors to: receive a request from a user computer via a network with one or more filter selections; access a data structure in the memory, the data structure comprising a plurality of categories of information showing interactions related to multiple entities; identify a set of categories of the plurality of categories within the data structure based on the one or more filter selections, the set of categories within the data structure includes location information related to at least one of the multiple entities, wherein the plurality of the categories of the data structure include at least one of: an interaction number category, a consuming entity identification category, a consuming entity location category, a provisioning entity identification category, a provisioning entity location category, a type of provisioning entity category, an interaction amount category, and a time of interaction category; determine the location information of the at least one of the multiple entities to update the data structure, wherein the location information is determined based on a computed affinity score that is based on computed travel times so that the affinity score can have an inverse proportionality with computed travel times such that a higher affinity score can have a lower travel time, wherein the computed affinity score is used to estimate the location information within an estimated area location for the provisioning entity without an identified location information, wherein the determining includes verifying that a populated category of the plurality of categories is valid data that signifies the location information; update the data structure with the determined location information within the area location; process the location information of the identified set of categories to analyze a performance of one or more entities of the multiple entities in accordance with the one or more filter selections; and provide the processed location information to display the performance of the one or more entities on a graphical user interface of the user computer. 2. The system of claim 1 , wherein at least one of the computed travel times includes a computed travel time between two provisioning entities.
| 0.865169 |
25. A computer system comprising: a non-transitory computer readable storage medium on which is provided a language model database to store a plurality of language models corresponding to a plurality of languages, each language model including information usable to determine a score reflecting a probability that a document is in the language corresponding to that language model, the language model database being further to store an impostor profile associated with each of the plurality of languages, wherein the impostor profile for each of the plurality of languages includes a parameter set comprising values characterizing a score distribution expected for documents in that language when scored using the respective language models of one or more impostor languages in an impostor set associated with that language; and control logic coupled to the language model database to compute, for at least some of the plurality of languages, a document score for a test document, the document score being computed based on at least some of the language models stored in the language model data store, and to select a most likely language for the test document based on the computed document scores, wherein document scores are also computed for the impostor languages in the impostor set associated with the most likely language, the control logic being further to compare the document scores computed for the impostor languages in the impostor set associated with the most likely language to the impostor profile for the most likely language and to determine whether the test document is in the most likely language or in no language based at least in part on a result of comparing the document scores.
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25. A computer system comprising: a non-transitory computer readable storage medium on which is provided a language model database to store a plurality of language models corresponding to a plurality of languages, each language model including information usable to determine a score reflecting a probability that a document is in the language corresponding to that language model, the language model database being further to store an impostor profile associated with each of the plurality of languages, wherein the impostor profile for each of the plurality of languages includes a parameter set comprising values characterizing a score distribution expected for documents in that language when scored using the respective language models of one or more impostor languages in an impostor set associated with that language; and control logic coupled to the language model database to compute, for at least some of the plurality of languages, a document score for a test document, the document score being computed based on at least some of the language models stored in the language model data store, and to select a most likely language for the test document based on the computed document scores, wherein document scores are also computed for the impostor languages in the impostor set associated with the most likely language, the control logic being further to compare the document scores computed for the impostor languages in the impostor set associated with the most likely language to the impostor profile for the most likely language and to determine whether the test document is in the most likely language or in no language based at least in part on a result of comparing the document scores. 26. The computer system of claim 25 further comprising: a document information data store configured to store information about a plurality of documents including the test document, wherein the control logic is further configured to store, in the document information data store, language information for the test document, the language information including a result of the determination.
| 0.504343 |
10. An apparatus for maintaining a collection of test scripts, the apparatus comprising: an input adapted to receive test scripts and application data; a memory adapted to store data; and a processor adapted to: identify at least one common test script module present within at least two unmodularized test scripts, wherein the at least one common test script module is contained within each of the at least two unmodularized test scripts, and wherein each of the at least two unmodularized test scripts are associated with a common application; divide, by at least in part comparing a task coverage of a portion of the at least two unmodularized test scripts to a respective task coverage of one or more common test script modules stored in a module library, the at least two unmodularized test scripts into a set of modularized test scripts that comprises the at least one common test script module; receive an update to the common application; and update the at least one common test script module in response to the update of the common application, whereby updating the at least one common test script module causes a corresponding update to the at least two unmodularized test scripts.
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10. An apparatus for maintaining a collection of test scripts, the apparatus comprising: an input adapted to receive test scripts and application data; a memory adapted to store data; and a processor adapted to: identify at least one common test script module present within at least two unmodularized test scripts, wherein the at least one common test script module is contained within each of the at least two unmodularized test scripts, and wherein each of the at least two unmodularized test scripts are associated with a common application; divide, by at least in part comparing a task coverage of a portion of the at least two unmodularized test scripts to a respective task coverage of one or more common test script modules stored in a module library, the at least two unmodularized test scripts into a set of modularized test scripts that comprises the at least one common test script module; receive an update to the common application; and update the at least one common test script module in response to the update of the common application, whereby updating the at least one common test script module causes a corresponding update to the at least two unmodularized test scripts. 11. The apparatus according to claim 10 , wherein the processor is further adapted to: storing the at least one common script module in a module library; and determining that a task coverage of the at least one common test script module is one of greater than and not within a task coverage of the one or more of the modules stored in the module library, wherein the identifying comprises identifying the at least one common test script module, based upon the determining, to be one of the modules stored in the module library.
| 0.5 |
1. A system for converting user-selected printed text to a synthesized image sequence, comprising: processing electronics configured to receive an image of text over a network, the text being a passage from a source text, to translate the text of the image of text into a machine readable format, and, in response to receiving the image: to determine the source text from the text; to search for and to receive, from a source other than the image of text, auxiliary information comprising another passage within the source text; and to generate model information based on the auxiliary information and the text translated into the machine readable format.
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1. A system for converting user-selected printed text to a synthesized image sequence, comprising: processing electronics configured to receive an image of text over a network, the text being a passage from a source text, to translate the text of the image of text into a machine readable format, and, in response to receiving the image: to determine the source text from the text; to search for and to receive, from a source other than the image of text, auxiliary information comprising another passage within the source text; and to generate model information based on the auxiliary information and the text translated into the machine readable format. 12. The system of claim 1 , wherein the processing electronics are further configured to generate a synthesized image sequence based on the model information.
| 0.553459 |
1. A method for controlling a display device, comprising: setting an operational language of the display device, the operational language being at least one language provided by a manufacturer of the display device; receiving a request from a user to display a manual; receiving a request from the user to select a first language different from the set operational language for displaying the manual; reading one or more images from one or more files corresponding to a page of the manual in which the one or more images are to be included; reading first language data to be displayed with the one or more images, the first language data corresponding to the selected first language; reading display location information for the one or more images and the first language data; reading link information for combining the one or more images for display with the first language data corresponding to the page of the manual; combining the one or more images and first language data for simultaneous display at predetermined locations within a same screen corresponding to the page of the manual based on the link information, wherein the one or more images and the first language data are stored separately, and wherein the manual guides a user in controlling an operation of the display device; receiving additional language data from a network; and combining the additional language data with the one or more read images or one or more new images for simultaneous display at predetermined locations within another page of the manual.
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1. A method for controlling a display device, comprising: setting an operational language of the display device, the operational language being at least one language provided by a manufacturer of the display device; receiving a request from a user to display a manual; receiving a request from the user to select a first language different from the set operational language for displaying the manual; reading one or more images from one or more files corresponding to a page of the manual in which the one or more images are to be included; reading first language data to be displayed with the one or more images, the first language data corresponding to the selected first language; reading display location information for the one or more images and the first language data; reading link information for combining the one or more images for display with the first language data corresponding to the page of the manual; combining the one or more images and first language data for simultaneous display at predetermined locations within a same screen corresponding to the page of the manual based on the link information, wherein the one or more images and the first language data are stored separately, and wherein the manual guides a user in controlling an operation of the display device; receiving additional language data from a network; and combining the additional language data with the one or more read images or one or more new images for simultaneous display at predetermined locations within another page of the manual. 9. The method of claim 1 , wherein selecting the first language for the manual different from the operational language of the display device does not change the operational language of the display device.
| 0.586368 |
11. At least one non-transitory computer readable medium storing instruction that, when executed by at least one processor, performs a method of communication comprising: receiving an audio message from a caller to a recipient; transcribing the audio voice message to produce text; providing a text message including the text and a link comprising information that links to a conversion system capable of converting speech to text and an identifier indicating a destination for a reply message, such that when the recipient selects the link, the recipient is connected to the conversion system to speak the reply message that is automatically transcribed into a reply text message and provided to the destination associated with the identifier; and transmitting the text message to a mobile device of the recipient.
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11. At least one non-transitory computer readable medium storing instruction that, when executed by at least one processor, performs a method of communication comprising: receiving an audio message from a caller to a recipient; transcribing the audio voice message to produce text; providing a text message including the text and a link comprising information that links to a conversion system capable of converting speech to text and an identifier indicating a destination for a reply message, such that when the recipient selects the link, the recipient is connected to the conversion system to speak the reply message that is automatically transcribed into a reply text message and provided to the destination associated with the identifier; and transmitting the text message to a mobile device of the recipient. 12. The at least one non-transitory computer readable medium of claim 11 , further comprising: receiving a communication to connect in response to the recipient selecting the link; prompting the recipient to provide speech input subsequent to connecting; receiving speech input from the recipient; transcribing the speech input from the recipient to text; and automatically transmitting a text message including the text to the destination identified by the identifier in the link.
| 0.5 |
6. A non-transitory computer readable storage medium having embodied thereon a program which, when executed by a computer, causes the computer to execute a method of generating a unified modeling language (UML) activity diagram of a UML task object, the method comprising: receiving a command to modify a node of a UML class diagram of the UML task object, the UML class diagram defining at least one subtask node that is associated with the UML task object, the at least one subtask node including the node, and the node defining a set of steps performed by a subtask of the node; and automatically generating the UML activity diagram to selectively include the node in the UML activity diagram or selectively omit the node from the UML activity diagram, based on the command, the UML activity diagram defining a subset of a complete ordered set of a plurality of steps, subtasks, decision blocks, and transitions between the steps, subtasks, and decision blocks performed by the UML task object, wherein the command to modify the node of the class diagram indicates at least one of to include a first node to the class diagram and to omit a second node from the class diagram, and wherein the command indicates to include the first node to the class diagram, wherein the generating comprises including the first node in the generated UML activity diagram.
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6. A non-transitory computer readable storage medium having embodied thereon a program which, when executed by a computer, causes the computer to execute a method of generating a unified modeling language (UML) activity diagram of a UML task object, the method comprising: receiving a command to modify a node of a UML class diagram of the UML task object, the UML class diagram defining at least one subtask node that is associated with the UML task object, the at least one subtask node including the node, and the node defining a set of steps performed by a subtask of the node; and automatically generating the UML activity diagram to selectively include the node in the UML activity diagram or selectively omit the node from the UML activity diagram, based on the command, the UML activity diagram defining a subset of a complete ordered set of a plurality of steps, subtasks, decision blocks, and transitions between the steps, subtasks, and decision blocks performed by the UML task object, wherein the command to modify the node of the class diagram indicates at least one of to include a first node to the class diagram and to omit a second node from the class diagram, and wherein the command indicates to include the first node to the class diagram, wherein the generating comprises including the first node in the generated UML activity diagram. 7. The non-transitory computer readable storage medium according to claim 6 , wherein the command indicates to omit the second node from the class diagram, and wherein the generating comprises omitting the second node from the class diagram.
| 0.514403 |
36. The computer-implemented process of claim 21 , wherein said associating comprises accessing mapping information stored in a medium, said mapping information identifying said attribute of data that are to be associated with said search attribute.
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36. The computer-implemented process of claim 21 , wherein said associating comprises accessing mapping information stored in a medium, said mapping information identifying said attribute of data that are to be associated with said search attribute. 37. The computer-implemented process of claim 36 , wherein said process further comprising inputting said mapping information in said medium.
| 0.897838 |
5. The computerized system of claim 1 , wherein the statistical machine translation engine is configured to translate between each of a plurality of language pairs, each language pair having a source language and a target language; wherein the monolingual parallel corpus is one of a plurality of monolingual parallel corpora that the phrasal decoder is trained on, each of the monolingual parallel corpora being for a target language in one of the language pairs, and each of the monolingual parallel corpora including a machine translation output and a corresponding target human translation output; and wherein the target human translation output for each monolingual parallel corpora is from a corresponding bilingual parallel corpus for one of the language pairs.
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5. The computerized system of claim 1 , wherein the statistical machine translation engine is configured to translate between each of a plurality of language pairs, each language pair having a source language and a target language; wherein the monolingual parallel corpus is one of a plurality of monolingual parallel corpora that the phrasal decoder is trained on, each of the monolingual parallel corpora being for a target language in one of the language pairs, and each of the monolingual parallel corpora including a machine translation output and a corresponding target human translation output; and wherein the target human translation output for each monolingual parallel corpora is from a corresponding bilingual parallel corpus for one of the language pairs. 6. The computerized system of claim 5 , wherein the language pairs are typologically different language pairs.
| 0.850845 |
14. A machine-readable storage device with instruction stored thereon, the instructions when executed operable to cause a computerized mobile device to: receive an indication of a first user input comprising an actuation of a graphical element, the actuation being associated with a voice input operation, the first user input being detected at a presence-sensitive display; responsive to receiving the indication of the first user input and prior to a termination of the actuation: initiate the voice input operation; receive, using the voice input operation, an indication of a user-spoken search phrase comprising one or more search terms; output for display, the one or more candidate text search phrases determined based at least in part on the spoken phrase; receive an indication of a gesture sliding from a first area of a presence-sensitive display associated with the one or more candidate text search phrases to a second area of the presence-sensitive display associated with at least one icon; receive an indication of a second user input indicating the termination of the actuation, wherein the second user input indicates a completion of the user-spoken search phrase; and responsive to receiving the indication of the second user inputs perform an action associated with the at least one icon using the one or more terms in the spoken phrase.
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14. A machine-readable storage device with instruction stored thereon, the instructions when executed operable to cause a computerized mobile device to: receive an indication of a first user input comprising an actuation of a graphical element, the actuation being associated with a voice input operation, the first user input being detected at a presence-sensitive display; responsive to receiving the indication of the first user input and prior to a termination of the actuation: initiate the voice input operation; receive, using the voice input operation, an indication of a user-spoken search phrase comprising one or more search terms; output for display, the one or more candidate text search phrases determined based at least in part on the spoken phrase; receive an indication of a gesture sliding from a first area of a presence-sensitive display associated with the one or more candidate text search phrases to a second area of the presence-sensitive display associated with at least one icon; receive an indication of a second user input indicating the termination of the actuation, wherein the second user input indicates a completion of the user-spoken search phrase; and responsive to receiving the indication of the second user inputs perform an action associated with the at least one icon using the one or more terms in the spoken phrase. 16. The machine-readable medium of claim 14 , the instructions when executed further operable to cause the computerized mobile device to: output for display one or more candidate text phrases derived from the spoken search phrase; receive an indication of a third user input indicating which of the one or more candidate text phrases is an intended phrase; and perform the action using the intended phrase.
| 0.54797 |
5. The computer-implemented method of claim 1 , wherein said reconciliation tool is further configured for highlighting said flagged objects in a user interface of said document creation application to indicate the presence of an object having a field value.
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5. The computer-implemented method of claim 1 , wherein said reconciliation tool is further configured for highlighting said flagged objects in a user interface of said document creation application to indicate the presence of an object having a field value. 8. The computer-implemented method of claim 5 , wherein said reconciliation tool is further configured for annotating objects flagged with field values with comments regarding said objects.
| 0.946488 |
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