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7. A computer-implemented method for evaluating a broker, comprising the steps of: extracting data from an broker price opinion performed by the broker; in a computer processor or microprocessor, evaluating the extracted data against a plurality of rules applicable to the type of broker price opinion, wherein each rule is assigned a particular weight; and automatically calculating in a computer processor or microprocessor a broker price opinion score based on the evaluation, wherein the broker price opinion score is calculated by summing the total of each rule that is triggered multiplied by the weight assigned to that rule, according to the following formula: Score = K 1 + ⅇ ∑ j = 1 N ⢠w jj ⢠r j / Γ where N rules are evaluated, K is a constant, F is a constant, w is the weight of a rule, and r is a variable that defaults to 0 but takes on the value 1 if the rule triggers or fires.
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7. A computer-implemented method for evaluating a broker, comprising the steps of: extracting data from an broker price opinion performed by the broker; in a computer processor or microprocessor, evaluating the extracted data against a plurality of rules applicable to the type of broker price opinion, wherein each rule is assigned a particular weight; and automatically calculating in a computer processor or microprocessor a broker price opinion score based on the evaluation, wherein the broker price opinion score is calculated by summing the total of each rule that is triggered multiplied by the weight assigned to that rule, according to the following formula: Score = K 1 + ⅇ ∑ j = 1 N ⢠w jj ⢠r j / Γ where N rules are evaluated, K is a constant, F is a constant, w is the weight of a rule, and r is a variable that defaults to 0 but takes on the value 1 if the rule triggers or fires. 8. The method of claim 7 , wherein the rules address whether the broker price opinion complies with an applicable standard.
| 0.630556 |
1. A method for arranging content in an electronic page, the method comprising: identifying a plurality of objects on the electronic page; forming a membrane for each identified object by setting a geometric shape around each identified object, wherein forming the membrane comprises generating guidelines for each identified object, wherein generating the guidelines further comprises associating a gravity distance with each of the generated guidelines; receiving an entry of an insertion point in the electronic page; and aligning the insertion point based on at least one of the guidelines, wherein aligning the insertion point based on at least one of the guidelines comprises: determining a plurality of guidelines from the generated guidelines having the gravity distance extending to the point of insertion, and selecting a dominant guideline from the plurality of guidelines, wherein selecting the dominant guideline comprises: determining a guideline hierarchy associated with each of the plurality of guidelines based on the gravity distance associated with each of the plurality of guidelines and a position of the insertion point relative to each of the plurality of guidelines, and selecting the dominant guideline from the plurality of guidelines based on the determined guideline hierarchy; and aligning the insertion point relative to the selected dominant guideline.
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1. A method for arranging content in an electronic page, the method comprising: identifying a plurality of objects on the electronic page; forming a membrane for each identified object by setting a geometric shape around each identified object, wherein forming the membrane comprises generating guidelines for each identified object, wherein generating the guidelines further comprises associating a gravity distance with each of the generated guidelines; receiving an entry of an insertion point in the electronic page; and aligning the insertion point based on at least one of the guidelines, wherein aligning the insertion point based on at least one of the guidelines comprises: determining a plurality of guidelines from the generated guidelines having the gravity distance extending to the point of insertion, and selecting a dominant guideline from the plurality of guidelines, wherein selecting the dominant guideline comprises: determining a guideline hierarchy associated with each of the plurality of guidelines based on the gravity distance associated with each of the plurality of guidelines and a position of the insertion point relative to each of the plurality of guidelines, and selecting the dominant guideline from the plurality of guidelines based on the determined guideline hierarchy; and aligning the insertion point relative to the selected dominant guideline. 12. The method of claim 1 , wherein associating the gravity distance with each of the generated guidelines comprises associating the gravity distance according to one of the following: a preset system parameter, a user preference, and the electronic page needs.
| 0.5 |
5. An instructional globe comprising a globe-shaped body forming a representation of the earth by a number of information-laden, spherical surface appendages, and wherein said appendages comprise spherical surface segments and wherein there are cues on the surface of the globe having a profile corresponding in configuration to said specific ones of said spherical surface segments, wherein there are attaching means for removably attaching said segments to the globe-shaped body in manners and positions to visually or tactically reinforce the geographical concepts of the world, wherein said cues comprise a plurality of indentations and wherein each of said spherical surface segments in geometrically similar in outline to a corresponding indentation.
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5. An instructional globe comprising a globe-shaped body forming a representation of the earth by a number of information-laden, spherical surface appendages, and wherein said appendages comprise spherical surface segments and wherein there are cues on the surface of the globe having a profile corresponding in configuration to said specific ones of said spherical surface segments, wherein there are attaching means for removably attaching said segments to the globe-shaped body in manners and positions to visually or tactically reinforce the geographical concepts of the world, wherein said cues comprise a plurality of indentations and wherein each of said spherical surface segments in geometrically similar in outline to a corresponding indentation. 13. An instructional globe according to claim 5 wherein said spherical segments are further subdivided in subsegments having geographically significant shapes.
| 0.75105 |
1. A method for communicating control information, comprising: determining a first movement of a first device wearable by a user based on a first set of data received from the first device by way of an antenna, wherein the first set of data relates to the first movement of the first device; determining a second movement of a second device wearable by the user based on a second set of data received from the second device by way of the antenna, wherein the second set of data relates to the second movement of the second device, wherein the first and second movements occur simultaneously, and wherein the second wearable device is separate from and not integrated with the first wearable device; generating a first set of possibly performed gestures based on the first movement; generating a second set of possibly performed gestures based on the second movement; inferring, from the first and second sets of possibly performed gestures, that the first movement is representative of an intended command and the second movement is not representative of the intended command; and transmitting information based on the inference and wherein inferring that the first movement is representative of the intended command and the second movement is not representative of the intended command is based on the first and second sets of possibly performed gestures indicating that the first and second movements are in substantially the same direction.
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1. A method for communicating control information, comprising: determining a first movement of a first device wearable by a user based on a first set of data received from the first device by way of an antenna, wherein the first set of data relates to the first movement of the first device; determining a second movement of a second device wearable by the user based on a second set of data received from the second device by way of the antenna, wherein the second set of data relates to the second movement of the second device, wherein the first and second movements occur simultaneously, and wherein the second wearable device is separate from and not integrated with the first wearable device; generating a first set of possibly performed gestures based on the first movement; generating a second set of possibly performed gestures based on the second movement; inferring, from the first and second sets of possibly performed gestures, that the first movement is representative of an intended command and the second movement is not representative of the intended command; and transmitting information based on the inference and wherein inferring that the first movement is representative of the intended command and the second movement is not representative of the intended command is based on the first and second sets of possibly performed gestures indicating that the first and second movements are in substantially the same direction. 4. The method of claim 1 , wherein generating the second set of possibly performed gestures comprises determining the second movement as being gesture-related.
| 0.826087 |
10. An apparatus for performing calculations of a electronic device, comprising: a display unit displaying input characters in a character input window; and a control unit checking whether an arithmetic expression is present in the displayed input characters, calculating the arithmetic expression when the arithmetic expression is present in the displayed input characters, and controlling the display unit to display a result of the calculation.
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10. An apparatus for performing calculations of a electronic device, comprising: a display unit displaying input characters in a character input window; and a control unit checking whether an arithmetic expression is present in the displayed input characters, calculating the arithmetic expression when the arithmetic expression is present in the displayed input characters, and controlling the display unit to display a result of the calculation. 14. The apparatus of claim 10 , wherein the control unit controls the display unit to present the identified arithmetic expression in a manner distinct from the remaining portion of the displayed input characters.
| 0.563734 |
9. A computer-implemented method for converting content of a target for use with a text-to-speech engine, said method comprising: at a computer comprising a computer program to implement processing operations: receiving data that defines content of a Website; processing the data to, identify a context identifier from among the content; separate the content into relevant content and miscellaneous content; locate a target term in the relevant content; use the context identifier to identify a substitution unit for the target term; and generate a spoken content input that can be utilized by a text-to-speech generator to generate spoken content, the spoken content input comprising a replacement unit corresponding to the substitution unit, wherein the substitution unit is selected from a repository with entries that are arranged in tables in accordance with a prioritized scheme, wherein the prioritized scheme defines a position amongst the tables for the substitution unit, wherein the position in the tables is assigned based on a specificity characteristic that describes a relative inclusivity of the substitution unit as compared to other substitution units, and wherein the position defines a level of priority for the identified token.
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9. A computer-implemented method for converting content of a target for use with a text-to-speech engine, said method comprising: at a computer comprising a computer program to implement processing operations: receiving data that defines content of a Website; processing the data to, identify a context identifier from among the content; separate the content into relevant content and miscellaneous content; locate a target term in the relevant content; use the context identifier to identify a substitution unit for the target term; and generate a spoken content input that can be utilized by a text-to-speech generator to generate spoken content, the spoken content input comprising a replacement unit corresponding to the substitution unit, wherein the substitution unit is selected from a repository with entries that are arranged in tables in accordance with a prioritized scheme, wherein the prioritized scheme defines a position amongst the tables for the substitution unit, wherein the position in the tables is assigned based on a specificity characteristic that describes a relative inclusivity of the substitution unit as compared to other substitution units, and wherein the position defines a level of priority for the identified token. 15. A computer-implemented method according to claim 9 , wherein the tables are associated with the context identifier.
| 0.626351 |
13. A non-transitory computer-readable storage medium having stored therein a plurality of instructions executable by a computer, the plurality of instructions comprising code sections for performing steps of: selecting a multimedia program for presentation, the multimedia program having a plurality of segments; classifying each segment of the plurality of segments according to associated content; for each given segment of the plurality of segments, retrieving a data entry template based, at least in part, upon the classification of the given segment; for each given segment of the plurality of segments, populating a data entry database via the data entry template corresponding to the given segment; generating a data stream via the data entry database, wherein a timing of the data stream is configured to coincide with a timing of the plurality of segments upon presentation by a multimedia system; generating at least one query grammar, wherein the at least one query grammar is programmed to interpret commands to access content in the data stream; simultaneously transmitting, to the multimedia system, the content associated with at least one of the plurality of segments, one or more of the at least one query grammar, and the data stream; monitoring a user interface element to detect an input query; determining whether the input query is valid according to the at least one query grammar; and responsive to the determination that the input query is valid, retrieving content associated with the input query, including any updated information for the data stream.
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13. A non-transitory computer-readable storage medium having stored therein a plurality of instructions executable by a computer, the plurality of instructions comprising code sections for performing steps of: selecting a multimedia program for presentation, the multimedia program having a plurality of segments; classifying each segment of the plurality of segments according to associated content; for each given segment of the plurality of segments, retrieving a data entry template based, at least in part, upon the classification of the given segment; for each given segment of the plurality of segments, populating a data entry database via the data entry template corresponding to the given segment; generating a data stream via the data entry database, wherein a timing of the data stream is configured to coincide with a timing of the plurality of segments upon presentation by a multimedia system; generating at least one query grammar, wherein the at least one query grammar is programmed to interpret commands to access content in the data stream; simultaneously transmitting, to the multimedia system, the content associated with at least one of the plurality of segments, one or more of the at least one query grammar, and the data stream; monitoring a user interface element to detect an input query; determining whether the input query is valid according to the at least one query grammar; and responsive to the determination that the input query is valid, retrieving content associated with the input query, including any updated information for the data stream. 15. The computer-readable storage medium of claim 13 , wherein the content in the data stream is arranged according to an order of the plurality of segments.
| 0.587613 |
3. The system of claim 1 , wherein the operations further comprise receiving a second user gesture input through the user interface that indicates that the user would like to view a transaction history associated with the selected contact.
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3. The system of claim 1 , wherein the operations further comprise receiving a second user gesture input through the user interface that indicates that the user would like to view a transaction history associated with the selected contact. 5. The system of claim 3 , wherein the second user gesture input comprises a horizontal swipe input to the left.
| 0.905224 |
5. A method for determining a solution to a problem using on-line documentation, comprising the steps of: forming a questionless case-based knowledge base, said questionless case-based knowledge base comprised of a series of questionless case structures stored in memory, each said questionless case structure comprised of a title, a description of a particular problem and a solution to said particular problem; determining a natural language description of said problem, said natural language description of said problem comprised of one or more strings of alpha-numeric characters; inputting, to a search engine, said one or more strings of alpha-numeric characters which describe said natural language description of said problem, one alpha-numeric character at a time; conducting first, second and third searches of said questionless case-based knowledge base each time one of said alpha-numeric characters is input into said search engine; said first search of said questionless case-based knowledge base searching for questionless case structures which contain at least one word, or a portion thereof, which exactly matches one of said strings of alpha-numeric characters previously input into said search engine; said second search of said questionless case-based knowledge base searching for questionless case structures which contain at least one word, or a portion thereof, which exactly matches three consecutive characters of one of said alpha-numeric character strings previously input into said search engine; said third search of said questionless case-based knowledge base searching for questionless case structures which contain a numeric representation which differs from a numeric representation forming part of one of said alpha-numeric character strings previously input into said search engine by less than a pre-determined value; determining which of said matching questionless case structures contains a most probable solution to said problem; and selecting, for review, said matching questionless case structures determined to contain the most probable solution to said problem.
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5. A method for determining a solution to a problem using on-line documentation, comprising the steps of: forming a questionless case-based knowledge base, said questionless case-based knowledge base comprised of a series of questionless case structures stored in memory, each said questionless case structure comprised of a title, a description of a particular problem and a solution to said particular problem; determining a natural language description of said problem, said natural language description of said problem comprised of one or more strings of alpha-numeric characters; inputting, to a search engine, said one or more strings of alpha-numeric characters which describe said natural language description of said problem, one alpha-numeric character at a time; conducting first, second and third searches of said questionless case-based knowledge base each time one of said alpha-numeric characters is input into said search engine; said first search of said questionless case-based knowledge base searching for questionless case structures which contain at least one word, or a portion thereof, which exactly matches one of said strings of alpha-numeric characters previously input into said search engine; said second search of said questionless case-based knowledge base searching for questionless case structures which contain at least one word, or a portion thereof, which exactly matches three consecutive characters of one of said alpha-numeric character strings previously input into said search engine; said third search of said questionless case-based knowledge base searching for questionless case structures which contain a numeric representation which differs from a numeric representation forming part of one of said alpha-numeric character strings previously input into said search engine by less than a pre-determined value; determining which of said matching questionless case structures contains a most probable solution to said problem; and selecting, for review, said matching questionless case structures determined to contain the most probable solution to said problem. 7. A method for determining a solution to a problem according to claim 5 wherein the step of selecting one of said matching case structures which contains the most probable solution to said problem further comprises the steps of: assigning first, second and third weights to matches respectively determined by said first, second and third searches; determining a composite score for said matching questionless case structures based upon both number and type of matches detected; ranking said matching questionless case structures by said composite scores; and selecting said questionless case structure having the highest ranking for review.
| 0.5 |
1. A method for automatically recognizing Arabic text, comprising: building an Arabic corpus comprising Arabic text files and ground truths corresponding to each of the Arabic text files, wherein the Arabic text files include Arabic texts written in different writing styles; storing writing-style indices in association with the Arabic text files by a computer, wherein each of the writing-style indices indicates that one of the Arabic text files is written in one of the writing styles; acquiring a text image containing a line of Arabic characters; digitizing the line of the Arabic characters to form a two-dimensional array of pixels each associated with a pixel value, wherein the pixel value is expressed in a binary number; dividing the line of the Arabic characters into a plurality of line images; defining a plurality of cells in one of the plurality of line images, wherein each of the plurality of cells comprises a group of adjacent pixels; serializing pixel values of pixels in each of the plurality of cells in one of the plurality of line images to form a binary cell number; forming a text feature vector according to binary cell numbers obtained from the plurality of cells in one of the plurality of line images; training a Hidden Markov Model using the Arabic text files and ground truths in the Arabic corpus in accordance with the writing-style indices in association with the Arabic text files; and feeding the text feature vector into the Hidden Markov Model to recognize the line of Arabic characters.
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1. A method for automatically recognizing Arabic text, comprising: building an Arabic corpus comprising Arabic text files and ground truths corresponding to each of the Arabic text files, wherein the Arabic text files include Arabic texts written in different writing styles; storing writing-style indices in association with the Arabic text files by a computer, wherein each of the writing-style indices indicates that one of the Arabic text files is written in one of the writing styles; acquiring a text image containing a line of Arabic characters; digitizing the line of the Arabic characters to form a two-dimensional array of pixels each associated with a pixel value, wherein the pixel value is expressed in a binary number; dividing the line of the Arabic characters into a plurality of line images; defining a plurality of cells in one of the plurality of line images, wherein each of the plurality of cells comprises a group of adjacent pixels; serializing pixel values of pixels in each of the plurality of cells in one of the plurality of line images to form a binary cell number; forming a text feature vector according to binary cell numbers obtained from the plurality of cells in one of the plurality of line images; training a Hidden Markov Model using the Arabic text files and ground truths in the Arabic corpus in accordance with the writing-style indices in association with the Arabic text files; and feeding the text feature vector into the Hidden Markov Model to recognize the line of Arabic characters. 11. The method of claim 1 , wherein the pixel values in the two-dimensional array of pixels are expressed in single-bit binary numbers.
| 0.591657 |
22. In a method for automated linguistic expression substitution on a digital data processor, the improvement wherein said digital data processor executes steps comprising A. accepting into said digital data processor a suspect expression signal representative of a linguistic expression consisting of characters, B. accepting into said digital data processor an alternate expression signal representative of a permissible linguistic expression consisting of characters, C. comparing within said digital data processor said suspect expression signal with said alternate expression signal and producing a disparity signal numerically representative of differences between a spelling of the linguistic expression represented by said suspect expression signals and a spelling of the linguistic expression represented by said alternate expression signal, said comparing step including the step of producing said disparity signal to be numerically representative of the type and magnitude of differences between said suspect expression signal and said alternate expression signal, said comparing step further including the steps of responding to the detection of transposition, character deletion, unmatched character, and character length disparity types for producing a signal indicative of the numerically-weighted structural significance of that detected type, and D. evaluating within said digital data processor a numerical value represented by said disparity signal for determining whether said alternate expression signal is substitutable for said suspect expression signal and for producing an output signal indicative thereof.
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22. In a method for automated linguistic expression substitution on a digital data processor, the improvement wherein said digital data processor executes steps comprising A. accepting into said digital data processor a suspect expression signal representative of a linguistic expression consisting of characters, B. accepting into said digital data processor an alternate expression signal representative of a permissible linguistic expression consisting of characters, C. comparing within said digital data processor said suspect expression signal with said alternate expression signal and producing a disparity signal numerically representative of differences between a spelling of the linguistic expression represented by said suspect expression signals and a spelling of the linguistic expression represented by said alternate expression signal, said comparing step including the step of producing said disparity signal to be numerically representative of the type and magnitude of differences between said suspect expression signal and said alternate expression signal, said comparing step further including the steps of responding to the detection of transposition, character deletion, unmatched character, and character length disparity types for producing a signal indicative of the numerically-weighted structural significance of that detected type, and D. evaluating within said digital data processor a numerical value represented by said disparity signal for determining whether said alternate expression signal is substitutable for said suspect expression signal and for producing an output signal indicative thereof. 25. In a method for automated linguistic expression substitution on a digital data processor according to claim 22, the improvement in which said comparing step further comprises the step of detecting a disparity type representative of unmatched characters, with respect to said alternate expression signal, within said suspect expression signal.
| 0.618702 |
1. A method, comprising: monitoring an application to identify invocations of an instrumented component; determining a response time of each invocation of the instrumented component; determining an average of the response times in an X minute period; determining a severity of the average of the response times in the X minutes period; determining a rolling average of the response times in a Y minute period, where X and Y and numbers and Y>X; determining a severity of the rolling average; preparing a first web feed document for a first user type comprising, in a first <item> element, the average of the response times in the X minutes period and the severity of the average of the response times, the preparing the first web feed document comprises replacing placeholder elements in a <title> element of the first <item> element with the average of the response times and the severity of the average of the response times; and preparing a second web feed document for a second user type comprising, in a second <item> element, the rolling average of the response times in the Y minute period and the severity of the rolling average, the preparing the second web feed document comprises replacing placeholder elements in a <title> element of the second <item> element with the rolling average and the severity of the rolling average.
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1. A method, comprising: monitoring an application to identify invocations of an instrumented component; determining a response time of each invocation of the instrumented component; determining an average of the response times in an X minute period; determining a severity of the average of the response times in the X minutes period; determining a rolling average of the response times in a Y minute period, where X and Y and numbers and Y>X; determining a severity of the rolling average; preparing a first web feed document for a first user type comprising, in a first <item> element, the average of the response times in the X minutes period and the severity of the average of the response times, the preparing the first web feed document comprises replacing placeholder elements in a <title> element of the first <item> element with the average of the response times and the severity of the average of the response times; and preparing a second web feed document for a second user type comprising, in a second <item> element, the rolling average of the response times in the Y minute period and the severity of the rolling average, the preparing the second web feed document comprises replacing placeholder elements in a <title> element of the second <item> element with the rolling average and the severity of the rolling average. 8. The method of claim 1 , wherein: the first web feed document is prepared every X minutes.
| 0.750422 |
1. A method comprising: receiving, by a production manager computer, at a time before closing a media production, cue metadata defining a plurality of music cues for the media production, wherein a first part of the cue metadata is received from a first computer and a second part of the cue metadata is received from a second computer that is different than the first computer, wherein the first part of the cue metadata includes a first plurality of timecodes for the plurality of music cues and the second part of the cue metadata includes a second plurality of timecodes for the plurality of music cues, wherein the first part of the cue metadata is received by the first computer via a first graphical user interface displayed by the first computer and the second part of the cue metadata is received by the second computer via a second graphical user interface displayed by the second computer; storing, by the production manager computer, one or more records in a database based on the cue metadata, wherein the database stores both the first plurality of timecodes for the plurality of music cues and the second plurality of timecodes for the plurality of music cues; generating, by the production manager computer, a cue data set based on the one or more records; causing, by the production manager computer, display of the cue data set; wherein the method is performed by one or more computing devices.
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1. A method comprising: receiving, by a production manager computer, at a time before closing a media production, cue metadata defining a plurality of music cues for the media production, wherein a first part of the cue metadata is received from a first computer and a second part of the cue metadata is received from a second computer that is different than the first computer, wherein the first part of the cue metadata includes a first plurality of timecodes for the plurality of music cues and the second part of the cue metadata includes a second plurality of timecodes for the plurality of music cues, wherein the first part of the cue metadata is received by the first computer via a first graphical user interface displayed by the first computer and the second part of the cue metadata is received by the second computer via a second graphical user interface displayed by the second computer; storing, by the production manager computer, one or more records in a database based on the cue metadata, wherein the database stores both the first plurality of timecodes for the plurality of music cues and the second plurality of timecodes for the plurality of music cues; generating, by the production manager computer, a cue data set based on the one or more records; causing, by the production manager computer, display of the cue data set; wherein the method is performed by one or more computing devices. 6. The method of claim 1 , further comprising the production management computer sending the cue data set to a third party computer.
| 0.748466 |
2. The method of claim 1 , wherein the first feature score, the second feature score, and the merged feature score are of a plurality of possible values for each respective score, wherein the plurality of merging techniques comprise: (i) weighting the merged feature score based on the first feature score, (ii) weighting the merged feature score based on the second feature score, (iii) not considering the first feature score upon determining the first feature score does not exceed a minimum weight threshold for the first feature score, (iv) considering the first feature score upon determining the first feature score exceeds the minimum weight threshold for the first feature score, (v) not considering the second feature score upon determining the second feature score does not exceed a minimum weight threshold for the second feature score, and (vi) considering the second feature score upon determining the second feature score exceed the minimum weight threshold for the second feature score, wherein computing the first feature score merges the first set of features of the plurality of items of evidence, wherein computing the second feature score merges the second set of features of the plurality of items of evidence, wherein the plurality of features comprise: (i) a quality, (ii) a relevance, (iii) a sentiment, and (iv) a source of each candidate answer and each item of evidence, wherein computing the second feature score for a first item of evidence of the plurality of items of evidence based on the first feature score of the first item of evidence comprises: not considering the first feature score of the first item of evidence when computing the second feature score for the first item of evidence upon determining that the first feature score of the first item of evidence does not exceed the minimum weight threshold for the first feature score; and weighting the second feature score of the first item of evidence based on the first feature score of the first item of evidence upon determining that the first feature score of the first item of evidence exceeds the minimum weight threshold for the first feature score.
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2. The method of claim 1 , wherein the first feature score, the second feature score, and the merged feature score are of a plurality of possible values for each respective score, wherein the plurality of merging techniques comprise: (i) weighting the merged feature score based on the first feature score, (ii) weighting the merged feature score based on the second feature score, (iii) not considering the first feature score upon determining the first feature score does not exceed a minimum weight threshold for the first feature score, (iv) considering the first feature score upon determining the first feature score exceeds the minimum weight threshold for the first feature score, (v) not considering the second feature score upon determining the second feature score does not exceed a minimum weight threshold for the second feature score, and (vi) considering the second feature score upon determining the second feature score exceed the minimum weight threshold for the second feature score, wherein computing the first feature score merges the first set of features of the plurality of items of evidence, wherein computing the second feature score merges the second set of features of the plurality of items of evidence, wherein the plurality of features comprise: (i) a quality, (ii) a relevance, (iii) a sentiment, and (iv) a source of each candidate answer and each item of evidence, wherein computing the second feature score for a first item of evidence of the plurality of items of evidence based on the first feature score of the first item of evidence comprises: not considering the first feature score of the first item of evidence when computing the second feature score for the first item of evidence upon determining that the first feature score of the first item of evidence does not exceed the minimum weight threshold for the first feature score; and weighting the second feature score of the first item of evidence based on the first feature score of the first item of evidence upon determining that the first feature score of the first item of evidence exceeds the minimum weight threshold for the first feature score. 3. The method of claim 2 , wherein the first merging technique comprises a combination of at least two of the plurality of merging techniques, the method further comprising: computing a merged feature score of each of the plurality of candidate answers based on the first merging technique, wherein the merged feature scores of the plurality of candidate answers are used to select one of the plurality of candidate answers as a correct response to a question presented to the question answering system.
| 0.719807 |
1. A computer-implemented method comprising: receiving, by a directory server, a query for an attribute associated with a Lightweight Directory Access Protocol (LDAP) entry, wherein the attribute is stored in a repository and contains a plurality of pairs of values, with each pair containing an attribute value and a corresponding version number stored as a subtype of the attribute; determining, by the directory server, whether the query includes a version number of the attribute; in response to a determination that the query includes a version number, returning a first attribute value that corresponds to the version number in the query; in response to a determination that the query includes a predetermined symbol, returning all versions of the attribute; and in response to a determination that the query does not include a version number or the predetermined symbol, returning a second attribute value that corresponds to a current version of the attribute.
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1. A computer-implemented method comprising: receiving, by a directory server, a query for an attribute associated with a Lightweight Directory Access Protocol (LDAP) entry, wherein the attribute is stored in a repository and contains a plurality of pairs of values, with each pair containing an attribute value and a corresponding version number stored as a subtype of the attribute; determining, by the directory server, whether the query includes a version number of the attribute; in response to a determination that the query includes a version number, returning a first attribute value that corresponds to the version number in the query; in response to a determination that the query includes a predetermined symbol, returning all versions of the attribute; and in response to a determination that the query does not include a version number or the predetermined symbol, returning a second attribute value that corresponds to a current version of the attribute. 2. The method of claim 1 further comprising: maintaining a revision history for changes made to the attribute associated with the LDAP entry in an LDAP repository.
| 0.772853 |
1. A method performed by one or more server devices, the method comprising: providing, to an entity, a first interface that includes information identifying each of a plurality of documents, the information including: access statistics, for each document of the plurality of documents, that relate to previous accesses of the document by one or more users, where the access statistics include an indication of an average number of different pages per document, of the plurality of documents, accessed per user, of the one or more users, and fields that define presentation parameters applied to each of the plurality of documents, where the presentation parameters, applied to a first document of the plurality of documents, are different than the presentation parameters applied to a second document of the plurality of documents, where the fields, for one of the plurality of documents, include: a field that allows the entity to define a quantity of content, of the one of the plurality of one or more documents, that is to be presented to a user when the user accesses the one of the plurality of documents, where the quantity is greater than zero and less than a full content of the particular document one of the plurality of documents, a field that allows the entity to list one or more particular advertisements, of a plurality of advertisements, that are to be blocked when presenting the one of the plurality of documents to the user, and least one of: a field that allows the entity to define one or more portions of the one of the plurality of documents to be provided to the user for purchase, where the one or more portions of one of the plurality of documents to be provided to the user for purchase are less than the full content of the one of the plurality of documents, or a field that allows the entity to define whether images, included in the one of the plurality of documents, are to be viewable to the user when presenting the one of the plurality of documents to the user, the providing being performed by one or more processors associated with the one or more server devices; presenting, using one or more processors associated with the one or more server devices, a second interface based on selection, by the entity, of one or more of the plurality of documents, where the second interface includes information identifying the one or more of the plurality of documents, the information identifying the one or more of the plurality of documents including the presentation parameters, associated with the fields, corresponding to the one or more of the plurality of documents; receiving, from the entity and via the second interface, modifications to the presentation parameters, associated with the fields, corresponding to the one or more of the plurality of documents, the receiving being performed by one or more processors associated with the one or more server devices; and applying, using one or more processors associated with the one or more server devices, the modified presentation parameters, the modified presentation parameters to the one or more of the plurality of documents.
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1. A method performed by one or more server devices, the method comprising: providing, to an entity, a first interface that includes information identifying each of a plurality of documents, the information including: access statistics, for each document of the plurality of documents, that relate to previous accesses of the document by one or more users, where the access statistics include an indication of an average number of different pages per document, of the plurality of documents, accessed per user, of the one or more users, and fields that define presentation parameters applied to each of the plurality of documents, where the presentation parameters, applied to a first document of the plurality of documents, are different than the presentation parameters applied to a second document of the plurality of documents, where the fields, for one of the plurality of documents, include: a field that allows the entity to define a quantity of content, of the one of the plurality of one or more documents, that is to be presented to a user when the user accesses the one of the plurality of documents, where the quantity is greater than zero and less than a full content of the particular document one of the plurality of documents, a field that allows the entity to list one or more particular advertisements, of a plurality of advertisements, that are to be blocked when presenting the one of the plurality of documents to the user, and least one of: a field that allows the entity to define one or more portions of the one of the plurality of documents to be provided to the user for purchase, where the one or more portions of one of the plurality of documents to be provided to the user for purchase are less than the full content of the one of the plurality of documents, or a field that allows the entity to define whether images, included in the one of the plurality of documents, are to be viewable to the user when presenting the one of the plurality of documents to the user, the providing being performed by one or more processors associated with the one or more server devices; presenting, using one or more processors associated with the one or more server devices, a second interface based on selection, by the entity, of one or more of the plurality of documents, where the second interface includes information identifying the one or more of the plurality of documents, the information identifying the one or more of the plurality of documents including the presentation parameters, associated with the fields, corresponding to the one or more of the plurality of documents; receiving, from the entity and via the second interface, modifications to the presentation parameters, associated with the fields, corresponding to the one or more of the plurality of documents, the receiving being performed by one or more processors associated with the one or more server devices; and applying, using one or more processors associated with the one or more server devices, the modified presentation parameters, the modified presentation parameters to the one or more of the plurality of documents. 8. The method of claim 1 , where the presentation parameters relate to access limitations applied to the plurality of one or more documents when the plurality of one or more documents are accessed by the one or more users.
| 0.712972 |
1. A method for conversing comprising: establishing a plurality of conference areas wherein each conference area supports a language and is operated in parallel with other conference areas such that each conference area contains the same messages in the same order, said plurality of conference areas managed by an online service conference manager that manages translations of messages from each conference area for broadcast of translated messages to other conference areas; connecting a first plurality of computer users to a first conference area, wherein said computers users are connected to said first conference area according to said computer users specified preference for a first language; connecting a second plurality of computer users to a second conference area, wherein said computers users are connected to said second conference area according to said computer users specified preference for a second language; electronically receiving, at said online service conference manager, text communications in said first language, said text communications originating from spoken communications by computer users currently connected to said first conference area for said first language; automatically polling for untranslated text communications from said first conference area, said polling performed by a polling server; automatically transmitting said untranslated text communications from said polling server to said online service conference manager, automatically translating at said online service conference manager said untranslated text communications in said first language to translated text communications in a second language when said online service conference manager receives untranslated text communications from said polling server; automatically transmitting said translated text communications to said second conference area for said second language; and automatically broadcasting said translated text communications from said online service conference manager to said computer users currently connected to said second conference area.
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1. A method for conversing comprising: establishing a plurality of conference areas wherein each conference area supports a language and is operated in parallel with other conference areas such that each conference area contains the same messages in the same order, said plurality of conference areas managed by an online service conference manager that manages translations of messages from each conference area for broadcast of translated messages to other conference areas; connecting a first plurality of computer users to a first conference area, wherein said computers users are connected to said first conference area according to said computer users specified preference for a first language; connecting a second plurality of computer users to a second conference area, wherein said computers users are connected to said second conference area according to said computer users specified preference for a second language; electronically receiving, at said online service conference manager, text communications in said first language, said text communications originating from spoken communications by computer users currently connected to said first conference area for said first language; automatically polling for untranslated text communications from said first conference area, said polling performed by a polling server; automatically transmitting said untranslated text communications from said polling server to said online service conference manager, automatically translating at said online service conference manager said untranslated text communications in said first language to translated text communications in a second language when said online service conference manager receives untranslated text communications from said polling server; automatically transmitting said translated text communications to said second conference area for said second language; and automatically broadcasting said translated text communications from said online service conference manager to said computer users currently connected to said second conference area. 4. The method of claim 1 wherein said text communications are automatically translated from said first language to said second language in accordance with a machine translator.
| 0.611461 |
1. A system, comprising: at least one processor; and memory device including instructions that, when executed by the at least one processor, cause the system to: obtain an image including text; process the image with a text recognition algorithm to produce text string data, the text string data including at least two options for at least one portion of the text string, each of the at least two options having a respective confidence value; process the text string data using a rule decision tree, the rule decision tree including a plurality of hierarchical nodes, at least a portion of the hierarchical nodes corresponding to a respective semantic boosting rule, wherein processing the text string using the decision tree includes, for at least one node of the nodes in the decision tree: determine that a pre-condition is satisfied for the semantic boosting rule, for a first node of the decision tree, with respect to the text string; apply the semantic boosting rule for the first node to the text string in response to determining that the pre-condition is satisfied, the applying of the semantic boosting rule causing in at least one confidence value for the text string to be adjusted and a refined version of the text string to be generated; and upon receiving the refined version of the text string, provide the refined version as recognized text for the image.
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1. A system, comprising: at least one processor; and memory device including instructions that, when executed by the at least one processor, cause the system to: obtain an image including text; process the image with a text recognition algorithm to produce text string data, the text string data including at least two options for at least one portion of the text string, each of the at least two options having a respective confidence value; process the text string data using a rule decision tree, the rule decision tree including a plurality of hierarchical nodes, at least a portion of the hierarchical nodes corresponding to a respective semantic boosting rule, wherein processing the text string using the decision tree includes, for at least one node of the nodes in the decision tree: determine that a pre-condition is satisfied for the semantic boosting rule, for a first node of the decision tree, with respect to the text string; apply the semantic boosting rule for the first node to the text string in response to determining that the pre-condition is satisfied, the applying of the semantic boosting rule causing in at least one confidence value for the text string to be adjusted and a refined version of the text string to be generated; and upon receiving the refined version of the text string, provide the refined version as recognized text for the image. 3. The system of claim 1 , wherein the instructions when executed further cause the system to: determine that at least the refined version of the text string corresponds to actionable text; and present an interface element that, when selected, initiates a process for performing an action associated with the actionable text.
| 0.541463 |
14. A system for verification of soft error resilience of devices from design data for a logic design, comprising: a computer processing system having memory and processing facilities for processing data with a computer program for analysis of failure rates of devices from said design data; a fault injection and exercising environment for inducing faults in devices from said design data; and said computer program for analysis of failure rates of devices from said design data being stored in said memory of said computer processing system and upon execution of said computer program and exercise of said fault injection and exercising environment for said design data, said computer program provides a Soft Error Rate (SER) rate value for devices of said design data for verification of soft error resilience of the devices from said design data, and further provides selection of a statistically relevant set of SER sensitive logic devices from the design data for the analysis, the statistically relevant set of SER sensitive logic devices formed by successively filtering the design data through a series of heuristic rule-based device identifiers that group and annotate the SER sensitive logic devices by parsing a netlist representing the logic design for identification nomenclature, device type and connectivity, and selects, groups and associates related devices for testing according to a list of predetermined SER sensitive device types, and reduces a number of the devices in the SER sensitive device test set based on symmetry of structures joined to a common bus and further reduces flow device vectors to scalars.
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14. A system for verification of soft error resilience of devices from design data for a logic design, comprising: a computer processing system having memory and processing facilities for processing data with a computer program for analysis of failure rates of devices from said design data; a fault injection and exercising environment for inducing faults in devices from said design data; and said computer program for analysis of failure rates of devices from said design data being stored in said memory of said computer processing system and upon execution of said computer program and exercise of said fault injection and exercising environment for said design data, said computer program provides a Soft Error Rate (SER) rate value for devices of said design data for verification of soft error resilience of the devices from said design data, and further provides selection of a statistically relevant set of SER sensitive logic devices from the design data for the analysis, the statistically relevant set of SER sensitive logic devices formed by successively filtering the design data through a series of heuristic rule-based device identifiers that group and annotate the SER sensitive logic devices by parsing a netlist representing the logic design for identification nomenclature, device type and connectivity, and selects, groups and associates related devices for testing according to a list of predetermined SER sensitive device types, and reduces a number of the devices in the SER sensitive device test set based on symmetry of structures joined to a common bus and further reduces flow device vectors to scalars. 16. The system according to claim 14 wherein design data for a device to be tested with an induced logic state fault is assigned a value weighting attribute for the specific device characteristics of the device to determine when to test the device and how to include the test result in the SER rate.
| 0.518551 |
25. A method for converting a textual passage to a synthesized image sequence, comprising: receiving, at processing electronics of a mobile phone, an image of text from a camera of the mobile phone, the text being a passage from a source text; translating the text of the image of text into a machine readable format; receiving auxiliary information; transmitting the text in the machine readable format and the auxiliary information to a remote server; receiving from the remote server model information based on the text in the machine readable format and the auxiliary information; generating the synthesized image sequence based on the model information; and displaying the synthesized image sequence using a display of the mobile phone.
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25. A method for converting a textual passage to a synthesized image sequence, comprising: receiving, at processing electronics of a mobile phone, an image of text from a camera of the mobile phone, the text being a passage from a source text; translating the text of the image of text into a machine readable format; receiving auxiliary information; transmitting the text in the machine readable format and the auxiliary information to a remote server; receiving from the remote server model information based on the text in the machine readable format and the auxiliary information; generating the synthesized image sequence based on the model information; and displaying the synthesized image sequence using a display of the mobile phone. 34. The method of claim 25 , wherein the mobile phone is configured to receive the auxiliary information from a second mobile phone.
| 0.684066 |
1. A method for performing dual mode speech recognition, comprising: receiving a spoken query from a user; processing the spoken query, including: sending the spoken query to a local recognition system on a mobile device; transmitting the spoken query to a remote recognition system via a communications link; and setting a latency timer period to a preset timeout value; in the event that the spoken query is not recognized by either the local recognition system or the remote recognition system within the latency timer period, choosing recognition failure as a final result; in the event that the spoken query is recognized by both the local recognition system and the remote recognition system within the latency timer period, obtaining a recognition result and associated recognition score from both the local recognition system and the remote recognition system and choosing the recognition result associated with the higher recognition score as the final result; in the event that the spoken query is recognized by only the local recognition within the latency timer period, obtaining a recognition result from the local recognition system, and choosing the local recognition result as the final result; in the event that the spoken query is recognized by only the remote recognition system within the latency timer period, obtaining a recognition result from the remote recognition system, and choosing the remote recognition result as the final result; taking action on behalf of the user based on the final result.
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1. A method for performing dual mode speech recognition, comprising: receiving a spoken query from a user; processing the spoken query, including: sending the spoken query to a local recognition system on a mobile device; transmitting the spoken query to a remote recognition system via a communications link; and setting a latency timer period to a preset timeout value; in the event that the spoken query is not recognized by either the local recognition system or the remote recognition system within the latency timer period, choosing recognition failure as a final result; in the event that the spoken query is recognized by both the local recognition system and the remote recognition system within the latency timer period, obtaining a recognition result and associated recognition score from both the local recognition system and the remote recognition system and choosing the recognition result associated with the higher recognition score as the final result; in the event that the spoken query is recognized by only the local recognition within the latency timer period, obtaining a recognition result from the local recognition system, and choosing the local recognition result as the final result; in the event that the spoken query is recognized by only the remote recognition system within the latency timer period, obtaining a recognition result from the remote recognition system, and choosing the remote recognition result as the final result; taking action on behalf of the user based on the final result. 2. The method of claim 1 , wherein: the local recognition system maintains a client vocabulary programmed to describe words or phrases available to be recognized.
| 0.54524 |
1. A method for automatically transcribing a customer service telephone conversation between an arbitrary number of speakers, the method comprising: receiving data corresponding to the telephone conversation, wherein the received data comprises audio data and metadata that identifies one or more of the speakers in the audio data; separating the audio data into frames; analyzing the frames to identify utterances, wherein each utterance comprises a plurality of frames; performing blind diarization of the audio data to differentiate speakers, wherein the blind diarization comprises: representing each utterance as a utterance model based on acoustic features of each utterance, clustering the utterance models, creating speaker models from each of the clusters, constructing a hidden Markov model from the speaker models, and decoding the hidden Markov model to differentiate speakers of each utterance; tagging homogeneous speaker segments in the telephone conversation with a tag unique for each speaker; performing speaker diarization to replace one or more of the tags with a speaker's identity, wherein the speaker diarization comprises: comparing the homogeneous speaker segments in the telephone conversation to one or more models retrieved from a database wherein the one or more models retrieved correspond to the one or more speakers identified in the metadata, and based on the comparison, identifying one or more of the speakers; and transcribing the conversation to obtain a text representation of the conversation, wherein each spoken part of the conversation is labeled with either the speaker's identity or the tag associated with the speaker.
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1. A method for automatically transcribing a customer service telephone conversation between an arbitrary number of speakers, the method comprising: receiving data corresponding to the telephone conversation, wherein the received data comprises audio data and metadata that identifies one or more of the speakers in the audio data; separating the audio data into frames; analyzing the frames to identify utterances, wherein each utterance comprises a plurality of frames; performing blind diarization of the audio data to differentiate speakers, wherein the blind diarization comprises: representing each utterance as a utterance model based on acoustic features of each utterance, clustering the utterance models, creating speaker models from each of the clusters, constructing a hidden Markov model from the speaker models, and decoding the hidden Markov model to differentiate speakers of each utterance; tagging homogeneous speaker segments in the telephone conversation with a tag unique for each speaker; performing speaker diarization to replace one or more of the tags with a speaker's identity, wherein the speaker diarization comprises: comparing the homogeneous speaker segments in the telephone conversation to one or more models retrieved from a database wherein the one or more models retrieved correspond to the one or more speakers identified in the metadata, and based on the comparison, identifying one or more of the speakers; and transcribing the conversation to obtain a text representation of the conversation, wherein each spoken part of the conversation is labeled with either the speaker's identity or the tag associated with the speaker. 5. The method according to claim 1 , wherein the received data comprises metadata that identifies a customer service agent in the telephone conversation.
| 0.612483 |
17. A non-transitory computer-readable storage medium comprising instructions that, when executed by a computer processor of a device, cause the device to perform a method of speech recognition comprising: processing a speech input to produce a sequence of representative speech vectors; and performing a first recognition pass using a first acoustic model to produce at least one intermediate recognition hypothesis corresponding to the speech input; performing a second recognition pass using a second acoustic model to re-evaluate the at least one intermediate recognition hypothesis and produce a final recognition result corresponding to the speech input; and wherein the second recognition pass is a generic recognition pass that is based on a generic speech recognition arrangement using generic acoustic modeling of a broad general class of input speech and wherein the first recognition pass is an adapted recognition pass that is based on a speech adapted arrangement using pre-adapted acoustic modeling of a specific sub-class of the general class of input speech.
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17. A non-transitory computer-readable storage medium comprising instructions that, when executed by a computer processor of a device, cause the device to perform a method of speech recognition comprising: processing a speech input to produce a sequence of representative speech vectors; and performing a first recognition pass using a first acoustic model to produce at least one intermediate recognition hypothesis corresponding to the speech input; performing a second recognition pass using a second acoustic model to re-evaluate the at least one intermediate recognition hypothesis and produce a final recognition result corresponding to the speech input; and wherein the second recognition pass is a generic recognition pass that is based on a generic speech recognition arrangement using generic acoustic modeling of a broad general class of input speech and wherein the first recognition pass is an adapted recognition pass that is based on a speech adapted arrangement using pre-adapted acoustic modeling of a specific sub-class of the general class of input speech. 27. The method according to claim 17 , wherein the first recognition pass occurs prior to the second recognition pass.
| 0.784226 |
16. A non-transitory computer readable medium having instructions stored thereon, wherein the instructions, when executed by a processor, cause the processor to for each source file in a first collection of source files: parse the respective source file to extract one or more chemical structures, compare the one or more chemical structures to chemical structures stored in at least one dictionary, wherein comparing the one or more chemical structures comprises identifying one or more matching chemical structures, and each dictionary of the at least one dictionary comprises a hierarchical listing of chemical structures; associate, with the respective source file, the one or more matching chemical structures; generate a first virtual relational network comprising the source files in the first collection, wherein the first virtual network comprises: one or more nodes, wherein each node of the one or more nodes represents a particular matching chemical structure of the one or more matching chemical structures associated with a particular source file of the source files in the first collection, and one or more links, wherein each link represents a connection between a pair of nodes, wherein each node of the pair of nodes is associated with a common chemical structure; and compare the first virtual relational network to a second virtual relational network, wherein comparing comprises identifying at least one of a) one or more nodes and b) one or more links common to both the first virtual relational network and the second virtual relational network, wherein the second virtual relational network is created from a second collection of source files different than the first collection of source files; and the first virtual relational network and the second virtual relational network share at least one common dictionary, wherein the at least one dictionary comprises the at least one common dictionary.
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16. A non-transitory computer readable medium having instructions stored thereon, wherein the instructions, when executed by a processor, cause the processor to for each source file in a first collection of source files: parse the respective source file to extract one or more chemical structures, compare the one or more chemical structures to chemical structures stored in at least one dictionary, wherein comparing the one or more chemical structures comprises identifying one or more matching chemical structures, and each dictionary of the at least one dictionary comprises a hierarchical listing of chemical structures; associate, with the respective source file, the one or more matching chemical structures; generate a first virtual relational network comprising the source files in the first collection, wherein the first virtual network comprises: one or more nodes, wherein each node of the one or more nodes represents a particular matching chemical structure of the one or more matching chemical structures associated with a particular source file of the source files in the first collection, and one or more links, wherein each link represents a connection between a pair of nodes, wherein each node of the pair of nodes is associated with a common chemical structure; and compare the first virtual relational network to a second virtual relational network, wherein comparing comprises identifying at least one of a) one or more nodes and b) one or more links common to both the first virtual relational network and the second virtual relational network, wherein the second virtual relational network is created from a second collection of source files different than the first collection of source files; and the first virtual relational network and the second virtual relational network share at least one common dictionary, wherein the at least one dictionary comprises the at least one common dictionary. 17. The computer readable medium of claim 16 , wherein the one or more chemical structures are contained within embedded objects.
| 0.586861 |
1. A method comprising: evaluating, by a rule engine executed by a processing device, facts in a working memory stored on a data storage device against a rule with repetitions; and creating, by the rule engine, a multi-dimensional tuple to hold a set of the facts that matches the rule, the multi-dimensional tuple comprising a plurality of elements, wherein each of the plurality of elements comprises a complex index, and wherein each of the plurality of elements is a single fact or a tree structure for holding a plurality of facts of a repetition group that matches the rule with repetitions.
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1. A method comprising: evaluating, by a rule engine executed by a processing device, facts in a working memory stored on a data storage device against a rule with repetitions; and creating, by the rule engine, a multi-dimensional tuple to hold a set of the facts that matches the rule, the multi-dimensional tuple comprising a plurality of elements, wherein each of the plurality of elements comprises a complex index, and wherein each of the plurality of elements is a single fact or a tree structure for holding a plurality of facts of a repetition group that matches the rule with repetitions. 8. The method of claim 1 , further comprising: using, by the rule engine, an accumulate node as a repeat node; and inserting, by the rule engine, the repeat node into a Rete network to evaluate the rule with repetitions.
| 0.793843 |
7. A non-transitory computer-readable storage medium encoded with computer-executable instructions for retrieving information from a semantic database having a plurality of semantic data in response to a query, which in response to execution by a computing device, causes the computing device to: translate each of the plurality of semantic data to a first-order logic formula constructed by one or more atomic symbols and operators; select a first semantic data as a hub in an offline environment from the plurality of semantic data, wherein the first semantic data is resolved with a number of semantic data based on a resolution rule, and the number of the semantic data resolved with the hub is greater than a threshold, wherein a first standard formula transformed from the translated first-order logic formula of the first semantic data is resolved with a second standard formula transformed from the translated first-order logic formula of any of the number of semantic data, and further wherein one atomic symbol of the atomic symbols exists in the first standard formula and the negation of the atomic symbol exists in the second standard formula; calculate the semantic data set by calculating in a first level of a searching approach, a first resolvent of (1) the hub and (2) a second semantic data which directly links to the hub based on a resolution rule, and in response to the second semantic data being resolved with the hub, selecting the second semantic data as a part of the semantic data set in the offline environment; calculate the semantic data set by calculating in a second level of the searching approach, a second resolvent of (1) the semantic data set resulted in the first level of the searching approach and (2) a third semantic data which is within a predetermined distance from the hub, and in response to the third semantic data being resolved with any semantic data of the semantic data set resulted in the first level of the searching approach, selecting the third semantic data as a part of the semantic data set in the offline environment, wherein the calculating of the semantic data set is continuously executed in a background of the semantic database until a particular calculation limit is reached; index the semantic data set in the offline environment; modify the semantic database to include the indexed semantic data set in the offline environment; and retrieve information from the semantic data set in an online environment in response to the query.
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7. A non-transitory computer-readable storage medium encoded with computer-executable instructions for retrieving information from a semantic database having a plurality of semantic data in response to a query, which in response to execution by a computing device, causes the computing device to: translate each of the plurality of semantic data to a first-order logic formula constructed by one or more atomic symbols and operators; select a first semantic data as a hub in an offline environment from the plurality of semantic data, wherein the first semantic data is resolved with a number of semantic data based on a resolution rule, and the number of the semantic data resolved with the hub is greater than a threshold, wherein a first standard formula transformed from the translated first-order logic formula of the first semantic data is resolved with a second standard formula transformed from the translated first-order logic formula of any of the number of semantic data, and further wherein one atomic symbol of the atomic symbols exists in the first standard formula and the negation of the atomic symbol exists in the second standard formula; calculate the semantic data set by calculating in a first level of a searching approach, a first resolvent of (1) the hub and (2) a second semantic data which directly links to the hub based on a resolution rule, and in response to the second semantic data being resolved with the hub, selecting the second semantic data as a part of the semantic data set in the offline environment; calculate the semantic data set by calculating in a second level of the searching approach, a second resolvent of (1) the semantic data set resulted in the first level of the searching approach and (2) a third semantic data which is within a predetermined distance from the hub, and in response to the third semantic data being resolved with any semantic data of the semantic data set resulted in the first level of the searching approach, selecting the third semantic data as a part of the semantic data set in the offline environment, wherein the calculating of the semantic data set is continuously executed in a background of the semantic database until a particular calculation limit is reached; index the semantic data set in the offline environment; modify the semantic database to include the indexed semantic data set in the offline environment; and retrieve information from the semantic data set in an online environment in response to the query. 12. The non-transitory computer-readable storage medium of claim 7 , further containing additional instructions, which in response to execution by the computing device, causes the computing device to locate the semantic data set by comparing a query to the hub.
| 0.513081 |
16. A non-transitory computer-readable storage device comprising computer-readable instructions, which when executed by one or more processors of an electronic device, causes the one or more processors to: receive input representing user instruction to provide a reminder in the future, the instruction identifying an entity; and after receiving the input: detect, by a microphone of the electronic device, an audio input; identify, in the detected audio input, a voice corresponding to the entity; and in response to identifying the voice, provide the reminder.
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16. A non-transitory computer-readable storage device comprising computer-readable instructions, which when executed by one or more processors of an electronic device, causes the one or more processors to: receive input representing user instruction to provide a reminder in the future, the instruction identifying an entity; and after receiving the input: detect, by a microphone of the electronic device, an audio input; identify, in the detected audio input, a voice corresponding to the entity; and in response to identifying the voice, provide the reminder. 19. The non-transitory computer-readable storage medium of claim 16 , wherein providing the reminder comprises causing the reminder to be provided on an external electronic device associated with the entity.
| 0.677748 |
14. A non-transitory computer readable storage medium for facilitating business-to-business personal connections by enhancing Internet search results, the non-transitory computer readable storage medium storing instructions that when executed by a processor cause a computing device to perform acts comprising: registering one or more selling entities by establishing a selling entity account for each of the one or more selling entities in a business-to-business connectivity service, wherein each of the one or more selling entities corresponds to a single individual associated with one or more companies and wherein each individual is associated with only one selling entity; registering one or more buying entities by establishing a buying entity account for each of the one or more buying entities in a business-to-business connectivity service, wherein each of the one or more buying entities corresponds to a single individual; receiving one or more search query terms from a searching user; determining, based on the one or more search query terms, a first set of search results generated by an Internet search engine that queries the World Wide Web, that are relevant relative to the search query terms; selecting, from the first set, a second set of one or more search results, wherein each search result in the second set is selected in response to a determination that it comprises a Uniform Resource Locator (URL) that has been previously registered in association with at least one selling entity account in the business-to-business connectivity service; ranking the one or more search results in the second set based on at least one of: one or more ratings that are based on input from one or more buying entities or, a filter score that is based on filter criteria specified by a submitter of the search query terms when the submitter of the search query terms is a buying entity; generating, for presentation, seller-specific information for each of the search results that are in the second set of search results, wherein seller specific information comprises the name of a selling entity, the company associated with each selling entity, and one or both of a product or service that each selling entity is associated with; and presenting seller-specific information in connection with only those search results for which seller-specific information was generated.
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14. A non-transitory computer readable storage medium for facilitating business-to-business personal connections by enhancing Internet search results, the non-transitory computer readable storage medium storing instructions that when executed by a processor cause a computing device to perform acts comprising: registering one or more selling entities by establishing a selling entity account for each of the one or more selling entities in a business-to-business connectivity service, wherein each of the one or more selling entities corresponds to a single individual associated with one or more companies and wherein each individual is associated with only one selling entity; registering one or more buying entities by establishing a buying entity account for each of the one or more buying entities in a business-to-business connectivity service, wherein each of the one or more buying entities corresponds to a single individual; receiving one or more search query terms from a searching user; determining, based on the one or more search query terms, a first set of search results generated by an Internet search engine that queries the World Wide Web, that are relevant relative to the search query terms; selecting, from the first set, a second set of one or more search results, wherein each search result in the second set is selected in response to a determination that it comprises a Uniform Resource Locator (URL) that has been previously registered in association with at least one selling entity account in the business-to-business connectivity service; ranking the one or more search results in the second set based on at least one of: one or more ratings that are based on input from one or more buying entities or, a filter score that is based on filter criteria specified by a submitter of the search query terms when the submitter of the search query terms is a buying entity; generating, for presentation, seller-specific information for each of the search results that are in the second set of search results, wherein seller specific information comprises the name of a selling entity, the company associated with each selling entity, and one or both of a product or service that each selling entity is associated with; and presenting seller-specific information in connection with only those search results for which seller-specific information was generated. 15. The non-transitory computer readable medium of claim 14 , wherein the searching user is a buying entity and determining the first set of search results is further determined based one at least one of or a combination of the following: a set of attributes submitted by the searching user, which describe the searching user's capacity as a buyer; a set of filter criteria submitted by the searching user which indicate characteristics of selling entities that describe a selling entity's capacity as a seller; or at least one previous experience of the searching user with one or more selling entities and at least one previous experience of one or more other buying entities in a trusted buyer network associated with the searching user.
| 0.5 |
3. The method as claimed in claim 1 , wherein adjusting the threshold score value comprises comparing a target performance in relation to the motor task with an actual performance, and lowering the threshold score value if there is a deficit of the actual performance compared to the target performance, and increasing the threshold score value if there is a surplus in the actual performance compared to the target performance.
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3. The method as claimed in claim 1 , wherein adjusting the threshold score value comprises comparing a target performance in relation to the motor task with an actual performance, and lowering the threshold score value if there is a deficit of the actual performance compared to the target performance, and increasing the threshold score value if there is a surplus in the actual performance compared to the target performance. 5. The method as claimed in claim 3 , further comprising obtaining a default threshold score value, R 0 , for a first session, k=1, from a calibration process.
| 0.812007 |
11. A method for translating gestures in a virtual world, comprising: receiving an input from a first user representing an input gesture to be made by a first avatar to a second avatar in the virtual world; translating, using a processor, the input gesture input, by the first user, based at least in part on one or more environmental, cultural or social factors to generate at least one translated gesture; outputting on a first display a depiction of the gesture input by the first user as being made by the first avatar to the second avatar; and outputting on a second display the translated gesture as being made by the first avatar to the second avatar, wherein the first display is separate from the second display.
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11. A method for translating gestures in a virtual world, comprising: receiving an input from a first user representing an input gesture to be made by a first avatar to a second avatar in the virtual world; translating, using a processor, the input gesture input, by the first user, based at least in part on one or more environmental, cultural or social factors to generate at least one translated gesture; outputting on a first display a depiction of the gesture input by the first user as being made by the first avatar to the second avatar; and outputting on a second display the translated gesture as being made by the first avatar to the second avatar, wherein the first display is separate from the second display. 13. The method of claim 11 , wherein translating the input gesture input by the first user to generate at least one translated gesture comprises translating the input gesture based on at least one translation gesture associated with the second avatar.
| 0.695161 |
16. The testing harness of claim 15 , wherein the TTCN-3 format communications operations include message-based and signature-based communication operations, and the communications operations are mapped into a SystemVerilog mailbox system.
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16. The testing harness of claim 15 , wherein the TTCN-3 format communications operations include message-based and signature-based communication operations, and the communications operations are mapped into a SystemVerilog mailbox system. 17. The testing harness of claim 16 , further comprising: an unbounded SystemVerilog mailbox object, created for each port, the unbounded mailbox object used via message exchange between port instances to enable the communications operations.
| 0.769536 |
1. A method for reviewing software source code, the method comprising: receiving, by a computer, a changeset object containing information that identifies text changes made to source code statements in a source code module; creating, by the computer, a workflow of the source code module after the text changes identified in the changeset, wherein the workflow identifies execution paths among logical groupings of source code statements in the source code module; identifying, by the computer, logical groupings of source code statements in the workflow that contain text changes identified in the changeset; generating, by the computer, an integrated graphical user interface (GUI) that will: display source code statements in the source code module with a visual indication of the identified text changes; display the workflow with a visual indication of the logical groupings of source code statements in the source code module that contain the text changes identified in the changeset; visually indicate logical groupings in the workflow that contain text changes that are selected by a user in the displayed source code statements; visually indicate source code statements in the displayed source code statements that are contained in a selected logical grouping in the workflow; link comments, entered by the user, that are associated with a source code statement in the displayed source code statements to the logical groupings in the workflow that contain the associated source code statements; link comments, entered by the user, that are associated with a logical grouping in the workflow to the source code statements in the displayed source code statements that contain the associated logical grouping; visually indicate the linked logical groupings when a source code statement in the displayed source code statements is selected; and visually indicate the linked source code statements when a logical grouping in the workflow is selected.
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1. A method for reviewing software source code, the method comprising: receiving, by a computer, a changeset object containing information that identifies text changes made to source code statements in a source code module; creating, by the computer, a workflow of the source code module after the text changes identified in the changeset, wherein the workflow identifies execution paths among logical groupings of source code statements in the source code module; identifying, by the computer, logical groupings of source code statements in the workflow that contain text changes identified in the changeset; generating, by the computer, an integrated graphical user interface (GUI) that will: display source code statements in the source code module with a visual indication of the identified text changes; display the workflow with a visual indication of the logical groupings of source code statements in the source code module that contain the text changes identified in the changeset; visually indicate logical groupings in the workflow that contain text changes that are selected by a user in the displayed source code statements; visually indicate source code statements in the displayed source code statements that are contained in a selected logical grouping in the workflow; link comments, entered by the user, that are associated with a source code statement in the displayed source code statements to the logical groupings in the workflow that contain the associated source code statements; link comments, entered by the user, that are associated with a logical grouping in the workflow to the source code statements in the displayed source code statements that contain the associated logical grouping; visually indicate the linked logical groupings when a source code statement in the displayed source code statements is selected; and visually indicate the linked source code statements when a logical grouping in the workflow is selected. 2. The method of claim 1 , wherein the linked comments include specific line comments, general global document comments, added workflow branches and elements, deleted workflow branches and elements, and modified workflow branches and elements.
| 0.856471 |
15. A non-transitory processor-readable medium storing computer code representing instructions to cause a process for detecting and classifying via an image processor license plates displayed in images captured by an image capturing unit, said computer code comprising code to: capture an image of a vehicle utilizing an image-capturing unit that communicates with an image processor; locate a license plate region in said image of said vehicle after said capture of said image with said image-capturing unit by extracting a set of candidate regions from said image utilizing a weak classifier of said image processor; rank said set of candidate regions utilizing a secondary strong classifier of said image processor; and classify said image according to a confidence driven classification based on classification criteria determined by said weak classifier and said secondary strong classifier, thereby automatically identifying and eliminating un-readable images from human review.
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15. A non-transitory processor-readable medium storing computer code representing instructions to cause a process for detecting and classifying via an image processor license plates displayed in images captured by an image capturing unit, said computer code comprising code to: capture an image of a vehicle utilizing an image-capturing unit that communicates with an image processor; locate a license plate region in said image of said vehicle after said capture of said image with said image-capturing unit by extracting a set of candidate regions from said image utilizing a weak classifier of said image processor; rank said set of candidate regions utilizing a secondary strong classifier of said image processor; and classify said image according to a confidence driven classification based on classification criteria determined by said weak classifier and said secondary strong classifier, thereby automatically identifying and eliminating un-readable images from human review. 19. The processor-readable medium of claim 15 wherein said code to classify said image according to a confidence driven classification based on classification criteria determined by said weak classifier and said secondary strong classifier, further comprises code to: classify said image according to a confidence driven classification to exclude said image from review based on classification criteria determined by said weak classifier and said secondary strong classifier.
| 0.559744 |
1. A search engine stored on a non-transitory computer useable storage medium for execution by a computer for searching images located on remotely connected machines and extracting data from said images, said search engine comprising: means for receiving a query from a user; means for using the query to search an index collection of one or more charts for one or more chart types, each of the charts indexed by a set of attributes, and at least one of the attributes comprising a chart type determined through a classifier; the classifier for identifying images comprising image features characteristic of a particular numerically generated image type, the images comprising one or more charts selected from a plurality of known charts consisting of column charts, bar charts, line charts, pie charts, scatter charts, area charts, surface charts, and three-dimensional charts, wherein the classifier determines a chart type for an image from among the plurality of known charts; means for extracting numerical data from the one or more charts based on the chart type determined by the classifier, the numerical data represented graphically in the one or more charts; and means for presenting identified images and extracted numerical data to said user in response to said query.
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1. A search engine stored on a non-transitory computer useable storage medium for execution by a computer for searching images located on remotely connected machines and extracting data from said images, said search engine comprising: means for receiving a query from a user; means for using the query to search an index collection of one or more charts for one or more chart types, each of the charts indexed by a set of attributes, and at least one of the attributes comprising a chart type determined through a classifier; the classifier for identifying images comprising image features characteristic of a particular numerically generated image type, the images comprising one or more charts selected from a plurality of known charts consisting of column charts, bar charts, line charts, pie charts, scatter charts, area charts, surface charts, and three-dimensional charts, wherein the classifier determines a chart type for an image from among the plurality of known charts; means for extracting numerical data from the one or more charts based on the chart type determined by the classifier, the numerical data represented graphically in the one or more charts; and means for presenting identified images and extracted numerical data to said user in response to said query. 5. A search engine as in claim 1 wherein the image features comprise horizontal lines, vertical lines, percentage of white area, circular arcs and text.
| 0.573991 |
1. A method of providing call center functionality at a representative station, the representative station including a computer and a telephone, said method comprising the steps of: establishing a data communications link between a system computer and the station computer; receiving computer log-in information from the station computer via the data communications link; establishing a voice communications link between the station telephone and a telecommunications switch; receiving telephone log-in information from the station telephone via the voice communications link; establishing a link between the system computer and the switch such that call control commands provided from the station computer are transmitted to the switch via the system computer to control telephone calls that are received at the switch.
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1. A method of providing call center functionality at a representative station, the representative station including a computer and a telephone, said method comprising the steps of: establishing a data communications link between a system computer and the station computer; receiving computer log-in information from the station computer via the data communications link; establishing a voice communications link between the station telephone and a telecommunications switch; receiving telephone log-in information from the station telephone via the voice communications link; establishing a link between the system computer and the switch such that call control commands provided from the station computer are transmitted to the switch via the system computer to control telephone calls that are received at the switch. 3. The method of claim 1, wherein said step of receiving computer log-in information comprises the steps of: receiving at the system computer a computer log-in ID and password from the station computer; and authenticating the computer log-in ID and password.
| 0.776372 |
8. A non-transitory computer-readable storage medium that stores a computer program, the computer program including instructions that, when executed by a computer, cause the computer to perform operations comprising: accessing a database of business objects that include enterprise data, the business objects including data tables that relate semantic labels to the enterprise data applying one or more rules that use the semantic labels to select enterprise data corresponding to the semantic labels; using the selected enterprise data to determine modeling parameters that relate a semantic-label input set to a semantic-label output set, the semantic-label input set and the semantic-label output set each including at least one of the semantic labels; using the modeling parameters to generate a simulation table that predicts an operational range of at least one business object corresponding to at least one of the semantic labels; and augmenting the at least one business object in the database by including the simulation table in the at least one business object.
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8. A non-transitory computer-readable storage medium that stores a computer program, the computer program including instructions that, when executed by a computer, cause the computer to perform operations comprising: accessing a database of business objects that include enterprise data, the business objects including data tables that relate semantic labels to the enterprise data applying one or more rules that use the semantic labels to select enterprise data corresponding to the semantic labels; using the selected enterprise data to determine modeling parameters that relate a semantic-label input set to a semantic-label output set, the semantic-label input set and the semantic-label output set each including at least one of the semantic labels; using the modeling parameters to generate a simulation table that predicts an operational range of at least one business object corresponding to at least one of the semantic labels; and augmenting the at least one business object in the database by including the simulation table in the at least one business object. 9. The non-transitory computer-readable storage medium of claim 8 , wherein the modeling parameters define a neural network that relates the semantic-label input set to the semantic-label output set.
| 0.735493 |
1. A method of developing one or more application programs that cooperate to manage a distributed system comprising one or more servers, wherein at least one application program is associated with each server, the method including the steps: a) defining one or more managed objects associated with the distributed system in an object-oriented resource definition language and storing the definition of the one or more managed objects in one or more resource definition language files, wherein the definition of the one or more managed objects is based on an existing design and hierarchical structure of the distributed system, wherein parent-child relationships between the one or more managed objects are identified in the one or more resource definition language files using the object-oriented resource definition language to define the one or more managed objects in relation to the hierarchical structure of the distributed system; b) parsing the one or more resource definition language files to ensure conformity with the object-oriented resource definition language and creating an intermediate representation of the distributed system from the one or more conforming resource definition language files; c) processing the intermediate representation of the distributed system to form one or more programming language classes, one or more database definition files, and one or more script files; d) providing a reusable asset center framework to facilitate development of the one or more application programs, the reusable asset center including an SNMP agent framework that provides SNMP interface functionality to at least one of the one or more application programs, wherein the SNMP agent framework includes an SNMP table management object framework class that converts SNMP requests to managed object framework commands and an SNMP table class that includes procedures for accessing and chancing data in tables; and e) building the one or more application programs from at least the one or more programming language classes, one or more database definition files, one or more script files, and the reusable asset framework.
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1. A method of developing one or more application programs that cooperate to manage a distributed system comprising one or more servers, wherein at least one application program is associated with each server, the method including the steps: a) defining one or more managed objects associated with the distributed system in an object-oriented resource definition language and storing the definition of the one or more managed objects in one or more resource definition language files, wherein the definition of the one or more managed objects is based on an existing design and hierarchical structure of the distributed system, wherein parent-child relationships between the one or more managed objects are identified in the one or more resource definition language files using the object-oriented resource definition language to define the one or more managed objects in relation to the hierarchical structure of the distributed system; b) parsing the one or more resource definition language files to ensure conformity with the object-oriented resource definition language and creating an intermediate representation of the distributed system from the one or more conforming resource definition language files; c) processing the intermediate representation of the distributed system to form one or more programming language classes, one or more database definition files, and one or more script files; d) providing a reusable asset center framework to facilitate development of the one or more application programs, the reusable asset center including an SNMP agent framework that provides SNMP interface functionality to at least one of the one or more application programs, wherein the SNMP agent framework includes an SNMP table management object framework class that converts SNMP requests to managed object framework commands and an SNMP table class that includes procedures for accessing and chancing data in tables; and e) building the one or more application programs from at least the one or more programming language classes, one or more database definition files, one or more script files, and the reusable asset framework. 2. The method as set forth in claim 1 wherein the distributed system is a network.
| 0.642403 |
6. The method of claim 3 , wherein said creating the sequence of synthesized poses further comprises: identifying a collection of nearest neighbor feature vectors for each of the plurality of samples of the query stroke, wherein the collection of nearest neighbor feature vectors for each sample of the query stroke comprises two or more feature vectors for respective samples of one or more reference strokes that are most similar to the feature vector constructed for the sample of the query stroke; and wherein said identifying a best neighbor feature vector for each of the plurality of samples of the query stroke comprises selecting one of the nearest neighbor feature vectors from each of the collections of nearest neighbor feature vectors.
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6. The method of claim 3 , wherein said creating the sequence of synthesized poses further comprises: identifying a collection of nearest neighbor feature vectors for each of the plurality of samples of the query stroke, wherein the collection of nearest neighbor feature vectors for each sample of the query stroke comprises two or more feature vectors for respective samples of one or more reference strokes that are most similar to the feature vector constructed for the sample of the query stroke; and wherein said identifying a best neighbor feature vector for each of the plurality of samples of the query stroke comprises selecting one of the nearest neighbor feature vectors from each of the collections of nearest neighbor feature vectors. 7. The method of claim 6 , wherein said selecting one of the nearest neighbor feature vectors from each of the collections of nearest neighbor feature vectors comprises applying dynamic programming to the collections of nearest neighbor feature vectors to determine the lowest cost sequence of nearest neighbor feature vectors.
| 0.836503 |
1. A computer-implemented method comprising: displaying, in a user interface, first objects displaying respective first characters, each first character being a consonant of a language script, wherein the first objects are arranged circumferentially to define an interior region in which no other objects displaying characters are displayed; receiving a single selection of one of the first objects that displays one of the first characters, wherein the single selection causes the displayed one of the first characters to be a selected first character; and in response to receiving the single selection, displaying, in the user interface within the interior region, and while continuing to display the first objects, other, second objects displaying respective other single characters of the language script, each other, single character being a combination of the consonant of the selected first character, and a dependent vowel marker that, according to a language rule, is valid for the consonant of the selected first character.
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1. A computer-implemented method comprising: displaying, in a user interface, first objects displaying respective first characters, each first character being a consonant of a language script, wherein the first objects are arranged circumferentially to define an interior region in which no other objects displaying characters are displayed; receiving a single selection of one of the first objects that displays one of the first characters, wherein the single selection causes the displayed one of the first characters to be a selected first character; and in response to receiving the single selection, displaying, in the user interface within the interior region, and while continuing to display the first objects, other, second objects displaying respective other single characters of the language script, each other, single character being a combination of the consonant of the selected first character, and a dependent vowel marker that, according to a language rule, is valid for the consonant of the selected first character. 10. The method of claim 1 , further comprising: displaying, in the user interface, an additional object displaying an additional character that is a vowel of the language script; receiving a selection of the additional object; and in response to receiving the selection of the additional object, displaying, in the user interface and within the interior region, other, additional objects that display additional characters that are all the vowels of the language script.
| 0.515928 |
1. An integrated messaging system, comprising: a messaging server coupled to at least one network; and an integrated communication server in communication with networks of different types, and further in communication with the messaging server, the integrated communication server comprising a filter/transcribe module, the filter/transcribe module configured to: receive a voicemail message from a first network; perform a filtering operation on the voicemail message from a caller to a user comprising searching for predetermined words; perform a rough transcription of the voicemail message; generate an email message containing the rough transcription; receive a request from the user to provide a refined transcription of the voicemail message; request the refined transcription to be performed, wherein requesting comprises sending an audio file of the voice message, via one of the networks, to an entity to perform the refined transcription.
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1. An integrated messaging system, comprising: a messaging server coupled to at least one network; and an integrated communication server in communication with networks of different types, and further in communication with the messaging server, the integrated communication server comprising a filter/transcribe module, the filter/transcribe module configured to: receive a voicemail message from a first network; perform a filtering operation on the voicemail message from a caller to a user comprising searching for predetermined words; perform a rough transcription of the voicemail message; generate an email message containing the rough transcription; receive a request from the user to provide a refined transcription of the voicemail message; request the refined transcription to be performed, wherein requesting comprises sending an audio file of the voice message, via one of the networks, to an entity to perform the refined transcription. 12. The integrated messaging system of claim 1 , wherein the filter/transcribe module is further configured to receive the refined transcription from the entity; and substitute the refined transcription for the rough transcription in the email.
| 0.613473 |
1. A computer-implemented method for executing program code, the method comprising: receiving a source code file that includes computer code in a host language integrated with inset computer code in a domain specific language, the domain specific language being different from the host language; reading the source code file; responsive to reading computer code in the host language, invoking a set of computing instructions indicated by the computer code in accordance with the host language by interpreting a computing instruction indicated by the computer code as an operation in the host language; and responsive to reading inset computer code in the domain specific language, invoking a set of computing instructions indicated by the inset computer code in accordance with the domain specific language by performing operations including: selecting a domain specific language specification for the inset computer code, the domain specific language specification including instructions written in the host language for executing the inset computer code by relating tokens that include strings of characters from the domain specific language to corresponding tokens that include strings of characters from the host language and relating at least one grammatical rule for operations on tokens from the domain specific language to at least one corresponding grammatical rule for operations on tokens from the host language, and using the domain specific language specification to process the inset computer code.
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1. A computer-implemented method for executing program code, the method comprising: receiving a source code file that includes computer code in a host language integrated with inset computer code in a domain specific language, the domain specific language being different from the host language; reading the source code file; responsive to reading computer code in the host language, invoking a set of computing instructions indicated by the computer code in accordance with the host language by interpreting a computing instruction indicated by the computer code as an operation in the host language; and responsive to reading inset computer code in the domain specific language, invoking a set of computing instructions indicated by the inset computer code in accordance with the domain specific language by performing operations including: selecting a domain specific language specification for the inset computer code, the domain specific language specification including instructions written in the host language for executing the inset computer code by relating tokens that include strings of characters from the domain specific language to corresponding tokens that include strings of characters from the host language and relating at least one grammatical rule for operations on tokens from the domain specific language to at least one corresponding grammatical rule for operations on tokens from the host language, and using the domain specific language specification to process the inset computer code. 4. The method of claim 1 , wherein the host language is an interpreted language, and a line of the inset computer code in the domain specific language is interpreted as a result of the processing based on the instructions written in the host language from the domain specific language specification.
| 0.81685 |
2. The method of claim 1 , wherein the determining hierarchical relationships further comprises generating a classification tree for a subject, the classification tree specifying subset relationships among the set of subscription queries via hierarchical levels and nodes; wherein each node in a left branch of a parent node at a specified level in the classification tree is a subset of the parent node; and wherein further, subscription queries that are not classified as either of a subset and a superset of the parent node are placed in an empty leaf node by traversing the classification tree for a first available empty leaf node.
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2. The method of claim 1 , wherein the determining hierarchical relationships further comprises generating a classification tree for a subject, the classification tree specifying subset relationships among the set of subscription queries via hierarchical levels and nodes; wherein each node in a left branch of a parent node at a specified level in the classification tree is a subset of the parent node; and wherein further, subscription queries that are not classified as either of a subset and a superset of the parent node are placed in an empty leaf node by traversing the classification tree for a first available empty leaf node. 4. The method of claim 2 , wherein each of the nodes in the classification tree is associated with at least one of the subscription client systems based upon respective subscription queries.
| 0.882598 |
13. A computer program product comprising a computer-readable storage medium containing computer program code for: receiving, from a requesting user of a social networking system, a request for a content item associated with one or more comments, each comment representing information provided a social networking system user; calculating an interest score for each of the comments associated with the content item, the interest score representing a measure of the requesting user's interest in a comment; selecting a comment for presentation to the requesting user based at least in part on the calculated interest scores; responsive to the selected comment having a plurality of replies to the comment, calculating for each of the plurality of replies an interest score representing a measure of the requesting user's interest in the reply, each of the plurality of replies by a user of the social networking system; selecting a subset of replies from the plurality of replies based at least in part on the interest scores; determining an order to present the subset of replies based at least in part on the interest scores calculated for the subset of replies; presenting the selected comment and the selected subset of replies in the determined order in association with the selected comment to the requesting user along with the associated content item; and responsive to receiving a request from the requesting user to view the plurality of replies, presenting the plurality of replies in a chronological order based on a time associated with each of the plurality of replies.
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13. A computer program product comprising a computer-readable storage medium containing computer program code for: receiving, from a requesting user of a social networking system, a request for a content item associated with one or more comments, each comment representing information provided a social networking system user; calculating an interest score for each of the comments associated with the content item, the interest score representing a measure of the requesting user's interest in a comment; selecting a comment for presentation to the requesting user based at least in part on the calculated interest scores; responsive to the selected comment having a plurality of replies to the comment, calculating for each of the plurality of replies an interest score representing a measure of the requesting user's interest in the reply, each of the plurality of replies by a user of the social networking system; selecting a subset of replies from the plurality of replies based at least in part on the interest scores; determining an order to present the subset of replies based at least in part on the interest scores calculated for the subset of replies; presenting the selected comment and the selected subset of replies in the determined order in association with the selected comment to the requesting user along with the associated content item; and responsive to receiving a request from the requesting user to view the plurality of replies, presenting the plurality of replies in a chronological order based on a time associated with each of the plurality of replies. 15. The computer program product of claim 13 , wherein selecting the comment for presentation to the requesting user based at least in part on the calculated interest scores comprises: selecting a number of comments having highest interest scores from the calculated interest scores.
| 0.567374 |
1. A computer-implemented method for expansion of rare queries to improve advertisement results, the method comprising: receiving a query from a user by a search engine; determining that the query does not match an entry in an ad query lookup table stored in data storage of the search engine; retrieving one or more expanded queries located within a query feature index whose features relate to one or more features of the received query, wherein the query feature index is stored in a database of the data storage and comprises a plurality of expanded queries; wherein retrieving comprises: representing the features as vectors; weighting the vectors of the received query based on a number of times corresponding respective features occur in the query and on an inverse document frequency for corresponding respective features in an ad corpus, to more heavily weight the rare queries; and using a vector space-based retrieval approach for retrieving the expanded queries; generating, in real time and by the search engine, an ad query comprising an expanded version of the received query based on features of the retrieved expanded queries; and selecting one or more advertisements based on the generated ad query, wherein the one or more advertisements are displayed to the user in response to the query received from the user.
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1. A computer-implemented method for expansion of rare queries to improve advertisement results, the method comprising: receiving a query from a user by a search engine; determining that the query does not match an entry in an ad query lookup table stored in data storage of the search engine; retrieving one or more expanded queries located within a query feature index whose features relate to one or more features of the received query, wherein the query feature index is stored in a database of the data storage and comprises a plurality of expanded queries; wherein retrieving comprises: representing the features as vectors; weighting the vectors of the received query based on a number of times corresponding respective features occur in the query and on an inverse document frequency for corresponding respective features in an ad corpus, to more heavily weight the rare queries; and using a vector space-based retrieval approach for retrieving the expanded queries; generating, in real time and by the search engine, an ad query comprising an expanded version of the received query based on features of the retrieved expanded queries; and selecting one or more advertisements based on the generated ad query, wherein the one or more advertisements are displayed to the user in response to the query received from the user. 3. The method of claim 1 , wherein features of the received and expanded queries comprise one or more of unigrams, phrases, and semantic classes.
| 0.705439 |
1. A document generation system for producing a document from information derived from an information repository, comprising: a source of code representing a document template including, data fields containing placeholder items to be replaced by desired data items, and also including a repetition identifier indicating one of said data fields is to be replicated to provide a group of data fields to be replaced by a plurality of said desired data items; a source of document generation control information supporting insertion of said desired data items derived from said information repository in said data fields; and a document processor for applying said control information in replacing template document data field placeholder items with desired data items, to produce a generated document.
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1. A document generation system for producing a document from information derived from an information repository, comprising: a source of code representing a document template including, data fields containing placeholder items to be replaced by desired data items, and also including a repetition identifier indicating one of said data fields is to be replicated to provide a group of data fields to be replaced by a plurality of said desired data items; a source of document generation control information supporting insertion of said desired data items derived from said information repository in said data fields; and a document processor for applying said control information in replacing template document data field placeholder items with desired data items, to produce a generated document. 7. The system according to claim 1 , wherein said document processor processes template document data, excluding said desired data items inserted in said placeholder items, by incorporating said template document data in said generated document and said generated document is compatible with Extensible Stylesheet Language (XSL).
| 0.636199 |
11. A computer system of determining an impact of an event identified in a first topic map meta-model will have on at least one asset identified in a second topic map meta-model representative as a weight comprising a computer comprising at least one processor, one or more memories, one or more computer readable storage media having program instructions executable by the computer to perform the program instructions comprising: creating, by the computer a third topic map meta-model which maps at least one asset from the second topic map meta-model to an event from the first topic map meta-model, the third topic map meta-model comprising: a topic map representation of assets of the second topic map meta-model, the second topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of assets; a topic map representation of events of the first topic map meta-model, the first topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of events; identifying, by the computer, identification of at least one association mapped between an event identified in the first topic map meta-model and at least one asset identified in the second topic map meta-model; and assigning, by the computer, weight associated with the identification to the at least one association between an event identified in a first topic map meta-model and an asset identified in a second topic map meta-model in various scopes; receiving, by the computer, a query input from a user identifying an event; obtaining, by the computer, from the query input, at least an identification of an association between at least one asset and an event in the third topic map meta-model; searching, by the computer, the third topic map meta-model for the identification from the query input; displaying, by the computer, all weights assigned to the association between the event in the first topic map meta-model and at least one asset of the second topic map meta-model in at least one scope to the user.
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11. A computer system of determining an impact of an event identified in a first topic map meta-model will have on at least one asset identified in a second topic map meta-model representative as a weight comprising a computer comprising at least one processor, one or more memories, one or more computer readable storage media having program instructions executable by the computer to perform the program instructions comprising: creating, by the computer a third topic map meta-model which maps at least one asset from the second topic map meta-model to an event from the first topic map meta-model, the third topic map meta-model comprising: a topic map representation of assets of the second topic map meta-model, the second topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of assets; a topic map representation of events of the first topic map meta-model, the first topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of events; identifying, by the computer, identification of at least one association mapped between an event identified in the first topic map meta-model and at least one asset identified in the second topic map meta-model; and assigning, by the computer, weight associated with the identification to the at least one association between an event identified in a first topic map meta-model and an asset identified in a second topic map meta-model in various scopes; receiving, by the computer, a query input from a user identifying an event; obtaining, by the computer, from the query input, at least an identification of an association between at least one asset and an event in the third topic map meta-model; searching, by the computer, the third topic map meta-model for the identification from the query input; displaying, by the computer, all weights assigned to the association between the event in the first topic map meta-model and at least one asset of the second topic map meta-model in at least one scope to the user. 14. The computer system of claim 11 , wherein the weights are stored in a data structure.
| 0.62409 |
7. A computer implemented method according to claim 6 further comprising the steps of: (d2e11) when any said at least one undesirable terms are not returned from said recursive comparison subroutine, passing control to said step (d2e7); and (d2e12) when said determining step (d2e7) result is no, passing control to said blocking step (e) with an OK indication.
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7. A computer implemented method according to claim 6 further comprising the steps of: (d2e11) when any said at least one undesirable terms are not returned from said recursive comparison subroutine, passing control to said step (d2e7); and (d2e12) when said determining step (d2e7) result is no, passing control to said blocking step (e) with an OK indication. 8. A computer implemented method according to claim 7 wherein blocking step (e) further comprises the steps of: (e1) when no said at least one undesirable terms have been returned from said processing step (d), determining if any said OK indication or any said replacement string has been returned; (e2) when said determining step (e1) result is said OK indication, posting the content to the communication forum; (e3) when said determining step (e1) result is said replacement string, replacing all or part of the content with said replacement string yielding an altered content; (e4) determining if a notify user option has been selected; (e5) when said determining step (e4) result is yes, notifying the user that all or part of the content has been replaced; (e6) posting said altered content to the communication forum; and (e7) when said determining step (e4) result is no, posting said altered content to the communication forum without notifying the user.
| 0.871942 |
10. The method of claim 9 wherein sid output string displaying step further comprises the steps of: (a) selecting a display plane of said display means from a series of said display planes provided thereby for the display of said output string, said display planes being partially overlapping so as to perceptually appear sequentially posteriorly positioned with respect to a first given display plane, the criteria for selecting said display plane comprising: (i) that said display plane be posteriorly positioned with respect to said first given display plane; (ii) that said display plane be least obscurring of previously selected display planes; and (iii) that said display plane itself is not obscurred by said previously selected display planes; and (b) passing said output string to said display means such that said output string is perceptually displayed on said selected display plane.
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10. The method of claim 9 wherein sid output string displaying step further comprises the steps of: (a) selecting a display plane of said display means from a series of said display planes provided thereby for the display of said output string, said display planes being partially overlapping so as to perceptually appear sequentially posteriorly positioned with respect to a first given display plane, the criteria for selecting said display plane comprising: (i) that said display plane be posteriorly positioned with respect to said first given display plane; (ii) that said display plane be least obscurring of previously selected display planes; and (iii) that said display plane itself is not obscurred by said previously selected display planes; and (b) passing said output string to said display means such that said output string is perceptually displayed on said selected display plane. 11. The method of claim 10 wherein the step of receiving an input string further includes the step of passing said input string to said display means such that said input string is perceptually displayed on said first given display plane.
| 0.699733 |
7. A system, comprising: one or more processors; a non-transitory computer-readable storage medium containing instructions configured to cause the one or more processors to perform operations, including: receiving a search query, wherein the search query is received by a software component; parsing the search query into keywords and non-keywords; identifying a category for each keyword in the search query; grouping the keywords according to category, wherein categories include a file type, wherein metadata associated with a file type includes one or more parameters, wherein a parameter specifies a rule, and wherein grouping the keywords includes linking keywords in the same category using a Boolean OR; generating a machine interpreted search query by linking the grouped keywords with the non-keywords using a Boolean AND; and transmitting the machine interpreted search query, wherein when the machine interpreted search query is received by another software component, the machine interpreted search query is used to perform a search.
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7. A system, comprising: one or more processors; a non-transitory computer-readable storage medium containing instructions configured to cause the one or more processors to perform operations, including: receiving a search query, wherein the search query is received by a software component; parsing the search query into keywords and non-keywords; identifying a category for each keyword in the search query; grouping the keywords according to category, wherein categories include a file type, wherein metadata associated with a file type includes one or more parameters, wherein a parameter specifies a rule, and wherein grouping the keywords includes linking keywords in the same category using a Boolean OR; generating a machine interpreted search query by linking the grouped keywords with the non-keywords using a Boolean AND; and transmitting the machine interpreted search query, wherein when the machine interpreted search query is received by another software component, the machine interpreted search query is used to perform a search. 10. The system of claim 7 , wherein a rule specifies one or more words that match one or more keywords within a category.
| 0.800231 |
9. An interactive server for providing a response according to an utterance type of a user voice, the interactive server comprising: at least one memory configured to store instructions; at least one processor configured to execute the stored instructions to implement: an input interface configured to receive data corresponding to a user voice from a user terminal; a determiner comprising: a probability calculator configured to calculate a probability of the utterance type of the user voice being a search utterance type using the received data and a search language model established based on search utterances, and calculate a probability of the utterance type of the user voice being a chatting utterance type using the received data and a chatting language model established based on chatting utterances; a disparity calculator configured to calculate a disparity value between the probability of the utterance type of the user voice being the search utterance type and the probability of the utterance type of the user voice being the chatting utterance type; and an utterance type determiner configured to: in response to the disparity value being less than a predetermined value, determine that the utterance type of the user voice is an integrated utterance type, in response to the disparity value exceeding the predetermined value and the probability of the utterance type of the user voice being the search utterance type being greater than the probability of the utterance type of the user voice being the chatting utterance type, determine that the utterance type of the user voice is the search utterance type, and in response to the disparity value exceeding the predetermined value and the probability of the utterance type of the user voice being the search utterance type being less than the probability of the utterance type of the user voice being the chatting utterance type, determine that the utterance type of the user voice is the chatting utterance type; a response generator configured to, in response to determining that the utterance type of the user voice is the integrated utterance type, generate a search response and a chatting response in response to the user voice, and generate an integrated response by modifying at least one from among the search response and the chatting response and combining the search response and the chatting response; and a transmitter configured to transmit the integrated response to the user terminal.
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9. An interactive server for providing a response according to an utterance type of a user voice, the interactive server comprising: at least one memory configured to store instructions; at least one processor configured to execute the stored instructions to implement: an input interface configured to receive data corresponding to a user voice from a user terminal; a determiner comprising: a probability calculator configured to calculate a probability of the utterance type of the user voice being a search utterance type using the received data and a search language model established based on search utterances, and calculate a probability of the utterance type of the user voice being a chatting utterance type using the received data and a chatting language model established based on chatting utterances; a disparity calculator configured to calculate a disparity value between the probability of the utterance type of the user voice being the search utterance type and the probability of the utterance type of the user voice being the chatting utterance type; and an utterance type determiner configured to: in response to the disparity value being less than a predetermined value, determine that the utterance type of the user voice is an integrated utterance type, in response to the disparity value exceeding the predetermined value and the probability of the utterance type of the user voice being the search utterance type being greater than the probability of the utterance type of the user voice being the chatting utterance type, determine that the utterance type of the user voice is the search utterance type, and in response to the disparity value exceeding the predetermined value and the probability of the utterance type of the user voice being the search utterance type being less than the probability of the utterance type of the user voice being the chatting utterance type, determine that the utterance type of the user voice is the chatting utterance type; a response generator configured to, in response to determining that the utterance type of the user voice is the integrated utterance type, generate a search response and a chatting response in response to the user voice, and generate an integrated response by modifying at least one from among the search response and the chatting response and combining the search response and the chatting response; and a transmitter configured to transmit the integrated response to the user terminal. 10. The interactive server as claimed in claim 9 , wherein the response generator is configured to, in response to determining that the utterance type of the user voice is the search utterance type, generate a search response to the user voice, and in response to determining that the utterance type of the user voice is the chatting utterance type, generate a chatting response to the user voice, wherein the transmitter is configured to transmit one of the search response and the chatting response to the user terminal.
| 0.59678 |
12. A computer-implemented method of comparing two or more documents, comprising: linguistically analyzing a plurality of documents to identify at least one term group in each document, each term group comprising a main term and at least one subordinate term semantically related to the main term; generating a semantic vector associated with each document, the semantic vector comprising a plurality of components, each component including: a term group as a scalar in the document; a frequency value relating to a number of occurrences of the term group; and processing the semantic vector by a digital computer; and comparing a semantic vector of an identified document to the semantic vector for each document in the plurality of documents to determine at least one document semantically similar to the identified document using a defined metric, wherein said metric measures the semantic distance between documents as a function of at least the frequency values included in the semantic vectors for the documents, and wherein said metric is related to: Sqrt(f1 2 +f2 2 +f3 2 +f4 2 + +f(N−1) 2 fN 2 )*100n 2 wherein f is a difference in frequency of a common term between the plurality of documents and n is the number of terms those documents have in common.
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12. A computer-implemented method of comparing two or more documents, comprising: linguistically analyzing a plurality of documents to identify at least one term group in each document, each term group comprising a main term and at least one subordinate term semantically related to the main term; generating a semantic vector associated with each document, the semantic vector comprising a plurality of components, each component including: a term group as a scalar in the document; a frequency value relating to a number of occurrences of the term group; and processing the semantic vector by a digital computer; and comparing a semantic vector of an identified document to the semantic vector for each document in the plurality of documents to determine at least one document semantically similar to the identified document using a defined metric, wherein said metric measures the semantic distance between documents as a function of at least the frequency values included in the semantic vectors for the documents, and wherein said metric is related to: Sqrt(f1 2 +f2 2 +f3 2 +f4 2 + +f(N−1) 2 fN 2 )*100n 2 wherein f is a difference in frequency of a common term between the plurality of documents and n is the number of terms those documents have in common. 21. The method of claim 12 , wherein the weighting factor comprises a plurality of different weighting factors and each of the different weighting factors relates to the importance of the main term or a subordinate term in the term group.
| 0.550223 |
20. A system for generating metadata relating to a media object, the system comprising: a content analysis module configured to determine input data, the input data comprising content data determined by analyzing content of the media object; a machine learning module, configured to generate new metadata responsive to the input data; and metadata storage, configured to receive the new metadata and store the new metadata as well as a correspondence between the new metadata and the media object.
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20. A system for generating metadata relating to a media object, the system comprising: a content analysis module configured to determine input data, the input data comprising content data determined by analyzing content of the media object; a machine learning module, configured to generate new metadata responsive to the input data; and metadata storage, configured to receive the new metadata and store the new metadata as well as a correspondence between the new metadata and the media object. 26. The system of claim 20 , wherein the media object is a book, and the content comprises body text.
| 0.624298 |
1. A computer-implemented method for initializing an application's user interface components, the method comprising: connecting, by a computing device, an application view defined in semantic application logic to events generated when a user interacts with a visual display of the computing device, wherein connecting the application view to events generated when a user interacts with a visual display of the computing device includes: registering a listener on a document object model (DOM) object used by a Web browser to render the application view; and inserting a unique identifier in the DOM object to associate a graphical element with the runtime object; using, by the computing device, the semantic application logic to render graphical elements of at least one user interface component, wherein to render the graphical elements of the at least one user interface component includes: transforming the semantic application logic into a format for parsing and rendering; rendering, by a rendering component used by a client-side component executed by the computing device, graphical elements of the at least one user interface component; and presenting, by the visual display of the computing device, the rendered graphical elements of the at least one user interface component; instantiating, by the client-side component executed by the computing device, a runtime object that provides computational logic of the user interface component, wherein the semantic application logic used to visually render the at least one user interface component is defined independently from the computational logic of the runtime object and can be modified to change the visual rendering of the at least one user interface component without affecting functions of the runtime object; and initializing, by the computing device, the computational logic of the runtime object on the visual rendering of the at least one user interface component.
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1. A computer-implemented method for initializing an application's user interface components, the method comprising: connecting, by a computing device, an application view defined in semantic application logic to events generated when a user interacts with a visual display of the computing device, wherein connecting the application view to events generated when a user interacts with a visual display of the computing device includes: registering a listener on a document object model (DOM) object used by a Web browser to render the application view; and inserting a unique identifier in the DOM object to associate a graphical element with the runtime object; using, by the computing device, the semantic application logic to render graphical elements of at least one user interface component, wherein to render the graphical elements of the at least one user interface component includes: transforming the semantic application logic into a format for parsing and rendering; rendering, by a rendering component used by a client-side component executed by the computing device, graphical elements of the at least one user interface component; and presenting, by the visual display of the computing device, the rendered graphical elements of the at least one user interface component; instantiating, by the client-side component executed by the computing device, a runtime object that provides computational logic of the user interface component, wherein the semantic application logic used to visually render the at least one user interface component is defined independently from the computational logic of the runtime object and can be modified to change the visual rendering of the at least one user interface component without affecting functions of the runtime object; and initializing, by the computing device, the computational logic of the runtime object on the visual rendering of the at least one user interface component. 4. The method as recited in claim 1 , wherein connecting an application view to events generated when a user interacts with a visual display of a computing device includes determining if a previously created dialog still maintained in memory was reassigned to the application view.
| 0.506274 |
3. The method of claim 1 , wherein selecting the one or more fragments from the series of fragments of the web page comprises: determining the measure of similarity between the plurality of bookmarking tags and each fragment in the series of fragments of the web page, wherein the plurality of bookmarking tags is a plurality of social bookmarking tags; calculating a score for each fragment in the series of fragments of the web page based at least in part on the measure of similarity between the plurality of social bookmarking tags and the fragment; and selecting one or more fragments from the series of fragments of the web page based at least in part on the score associated with each fragment in the series of fragments of the web page.
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3. The method of claim 1 , wherein selecting the one or more fragments from the series of fragments of the web page comprises: determining the measure of similarity between the plurality of bookmarking tags and each fragment in the series of fragments of the web page, wherein the plurality of bookmarking tags is a plurality of social bookmarking tags; calculating a score for each fragment in the series of fragments of the web page based at least in part on the measure of similarity between the plurality of social bookmarking tags and the fragment; and selecting one or more fragments from the series of fragments of the web page based at least in part on the score associated with each fragment in the series of fragments of the web page. 4. The method of claim 3 , wherein calculating a score for each fragment in the series of fragments of the web page based at least in part on the measure of similarity between the plurality of social bookmarking tags and the fragment comprises: calculating a score for each fragment in the series of fragments of the web page based on the measure of similarity between the plurality of social bookmarking tags and the fragment and one or more of: a measure of similarity between a title associated with the web page and the fragment; a measure of similarity between a Uniform Resource Locator (URL) associated with the web page and the fragment; a measure of similarity between search terms used to identify the web page and the fragment; and a weighting factor associated with the position of the fragment in the series of fragments of the web page.
| 0.649224 |
19. The program product of claim 17 , wherein said constructing said inverted index comprises: generating a full path token and a full path token posting list associated therewith by said inverted index, said full path token posting list including a plurality of identifiers representing said plurality of documents, wherein an identifier of said plurality of identifiers represents said document and includes a payload value, said payload value identifying a full path of said document in said tree structure, and said payload value including a set of full path indicators provided by a scheme that uniquely labels each sibling node of said tree structure.
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19. The program product of claim 17 , wherein said constructing said inverted index comprises: generating a full path token and a full path token posting list associated therewith by said inverted index, said full path token posting list including a plurality of identifiers representing said plurality of documents, wherein an identifier of said plurality of identifiers represents said document and includes a payload value, said payload value identifying a full path of said document in said tree structure, and said payload value including a set of full path indicators provided by a scheme that uniquely labels each sibling node of said tree structure. 20. The program product of claim 19 , wherein said method further comprises: building a hierarchy of a plurality of counters, each counter being associated with a node of said plurality of nodes of said tree structure, wherein a counter of said plurality of counters is indexed by said set of full path indicators; and updating a value stored in said counter, said value indicating a count of one or more documents of said plurality of documents, said one or more documents categorized by a sub-category of a category or sub-category indicated by a constraint of said plurality of constraints.
| 0.822052 |
1. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations comprising: receiving user feedback for each of one or more social posts presented to a user, each social post presented in association with a sentiment assigned to the social post, the user feedback for each social post regarding the sentiment assigned to the social post; generating sentiment tuning data from the user feedback; generating a new set of sentiment indicators from user provided sentiment indicators of the sentiment tuning data; applying the new set of sentiment indicators, generated from the sentiment tuning data, to new social posts to determine sentiments for the new social posts, wherein the applying comprises: identifying designated expressive symbols of the new set of sentiment indicators in the new social posts, the new set of sentiment indicators comprising assignments between the designated expressive symbols and designated sentiments; and determining assignments of the sentiments to the new social posts based on the assignments between the designated expressive symbols and the designated sentiments; and presenting the new social posts in association with the sentiments assigned to the new social posts.
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1. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations comprising: receiving user feedback for each of one or more social posts presented to a user, each social post presented in association with a sentiment assigned to the social post, the user feedback for each social post regarding the sentiment assigned to the social post; generating sentiment tuning data from the user feedback; generating a new set of sentiment indicators from user provided sentiment indicators of the sentiment tuning data; applying the new set of sentiment indicators, generated from the sentiment tuning data, to new social posts to determine sentiments for the new social posts, wherein the applying comprises: identifying designated expressive symbols of the new set of sentiment indicators in the new social posts, the new set of sentiment indicators comprising assignments between the designated expressive symbols and designated sentiments; and determining assignments of the sentiments to the new social posts based on the assignments between the designated expressive symbols and the designated sentiments; and presenting the new social posts in association with the sentiments assigned to the new social posts. 6. The one or more computer storage media of claim 1 , wherein the sentiments correspond to at least one of positive sentiment, negative sentiment, and neutral sentiment.
| 0.738325 |
16. A system for recording media for a contact center comprising: a processor; a memory, wherein the first memory has stored thereon instructions that, when executed by the processor, cause the processor to: receive a request for a telephony call from a first communication device; invoke a rule based on an attribute of the telephony call, wherein the rule identifies a condition for recording the call; determine whether the condition for recording the call is satisfied; in response to determining that the condition for recording the call is satisfied, establish a first call path with a recording system instead of a second call path, wherein the recording system is configured to receive media transmitted by the first communication device via the first call path instead of the second call path, bridge a media path between the first communication and a second communication device, and record the media in a storage device; and in response to determining that the condition for recording the call is not satisfied, establish the second call path with the second communication device without establishing the first call path, wherein the media transmitted by the first communication device is for being received via the second call path instead of the first call path.
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16. A system for recording media for a contact center comprising: a processor; a memory, wherein the first memory has stored thereon instructions that, when executed by the processor, cause the processor to: receive a request for a telephony call from a first communication device; invoke a rule based on an attribute of the telephony call, wherein the rule identifies a condition for recording the call; determine whether the condition for recording the call is satisfied; in response to determining that the condition for recording the call is satisfied, establish a first call path with a recording system instead of a second call path, wherein the recording system is configured to receive media transmitted by the first communication device via the first call path instead of the second call path, bridge a media path between the first communication and a second communication device, and record the media in a storage device; and in response to determining that the condition for recording the call is not satisfied, establish the second call path with the second communication device without establishing the first call path, wherein the media transmitted by the first communication device is for being received via the second call path instead of the first call path. 18. The system of claim 16 , wherein the recording system is further configured to capture metadata associated with the call, store the captured metadata in association with the recorded media, and provide the recorded media and metadata to a requesting device over the wide area network.
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4. The computer-implemented method of claim 2 , wherein building the phonetic model further comprises: preparing a library of source words comprising pronounceable words and non-pronounceable words; and providing the library of source words to a learning model algorithm to train the learning model algorithm to determine characteristics of pronounceable and characteristics of non-pronounceable words.
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4. The computer-implemented method of claim 2 , wherein building the phonetic model further comprises: preparing a library of source words comprising pronounceable words and non-pronounceable words; and providing the library of source words to a learning model algorithm to train the learning model algorithm to determine characteristics of pronounceable and characteristics of non-pronounceable words. 6. The computer-implemented method of claim 4 , wherein preparing the library comprises: building an attribute relationship file format (ARFF) based on the library of source words; and associating one or more attributes of pronounceable words and non-pronounceable words with the ARFF.
| 0.771084 |
1. A method, comprising: generating, by one or more computing devices in response to input, a digital sketch comprising one or more panels, one or more sketches each at least in part included in a respective one of the one or more panels, and one or more textual elements each included in a respective one of the panels, said generating the digital sketch comprising: generating the one or more panels according to panel input specifying a border for each of the one or more panels on a page; generating the one or more sketches according to drawing input specifying one or more strokes on the page, at least a portion of the one or more strokes being drawn in at least one of the one or more panels; erasing a portion of the border for at least one of the panels according to an erase input; determining for each of the one or more panels, based on a windowing algorithm, which of the one or more strokes or portions of the one or more strokes are to be displayed in the digital sketch and which of the one or more strokes or portions of the one or more strokes are hidden in the digital sketch, the windowing algorithm recognizing the erased portion of the border and said determining that the one or more strokes or portions of the strokes that pass through the erased portion of the border are to be displayed and the one or more strokes or portions of the strokes that do not pass through the erased portion of the border are to be hidden from display, and for a panel, the windowing algorithm performing: determining at least one of the strokes crosses the border of the panel; splitting each stroke that crosses the border of the panel to generate at least two separate strokes from the respective stroke; marking each stroke that lies inside the border of the panel to be displayed; determining at least one remaining unmarked stroke that intersects a marked stroke; and marking each remaining unmarked stroke that intersects a marked stroke as to be displayed and additional remaining unmarked strokes are hidden from display.
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1. A method, comprising: generating, by one or more computing devices in response to input, a digital sketch comprising one or more panels, one or more sketches each at least in part included in a respective one of the one or more panels, and one or more textual elements each included in a respective one of the panels, said generating the digital sketch comprising: generating the one or more panels according to panel input specifying a border for each of the one or more panels on a page; generating the one or more sketches according to drawing input specifying one or more strokes on the page, at least a portion of the one or more strokes being drawn in at least one of the one or more panels; erasing a portion of the border for at least one of the panels according to an erase input; determining for each of the one or more panels, based on a windowing algorithm, which of the one or more strokes or portions of the one or more strokes are to be displayed in the digital sketch and which of the one or more strokes or portions of the one or more strokes are hidden in the digital sketch, the windowing algorithm recognizing the erased portion of the border and said determining that the one or more strokes or portions of the strokes that pass through the erased portion of the border are to be displayed and the one or more strokes or portions of the strokes that do not pass through the erased portion of the border are to be hidden from display, and for a panel, the windowing algorithm performing: determining at least one of the strokes crosses the border of the panel; splitting each stroke that crosses the border of the panel to generate at least two separate strokes from the respective stroke; marking each stroke that lies inside the border of the panel to be displayed; determining at least one remaining unmarked stroke that intersects a marked stroke; and marking each remaining unmarked stroke that intersects a marked stroke as to be displayed and additional remaining unmarked strokes are hidden from display. 8. The method as recited in claim 1 , wherein the panel input specifying the border for each of the one or more panels on the page is freeform sketching input.
| 0.603429 |
1. A method programmed in a non-transitory memory of a device comprising: a. automatically fact checking an email to determine a factual accuracy of the email by comparing, with the device, the email with source information, wherein fact checking occurs after the email is sent; and b. automatically indicating a status of the email based on a result of the comparison of the email with the source information.
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1. A method programmed in a non-transitory memory of a device comprising: a. automatically fact checking an email to determine a factual accuracy of the email by comparing, with the device, the email with source information, wherein fact checking occurs after the email is sent; and b. automatically indicating a status of the email based on a result of the comparison of the email with the source information. 6. The method of claim 1 wherein the source information comprises a plurality of sources, and each source of the plurality of sources has a reliability rating.
| 0.751852 |
13. A recommendation system for generating recommendations of alternative unique items, the recommendation system comprising: an items information database configured to store data relating to unique items; a penalty computation engine configured to calculate a dissimilarity penalty, the dissimilarity penalty at least partially generated based on a magnitude of dissimilarity between a plurality of selected items and an alternative item; a recommendation compilation engine configured to generate a recommendation of alternative unique items, wherein the recommendation compilation engine is configured to electronically communicate with the penalty computation engine to calculate dissimilarity penalties for each of a plurality of alternative unique items, the recommendation of alternative unique items comprising a ranking of at least a portion of the plurality of alternative unique items, the ranking based at least partially on the calculated dissimilarity penalties; and one or more computers configured to operate the recommendation compilation engine, wherein the one or more computers comprises a computer processor and an electronic storage medium.
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13. A recommendation system for generating recommendations of alternative unique items, the recommendation system comprising: an items information database configured to store data relating to unique items; a penalty computation engine configured to calculate a dissimilarity penalty, the dissimilarity penalty at least partially generated based on a magnitude of dissimilarity between a plurality of selected items and an alternative item; a recommendation compilation engine configured to generate a recommendation of alternative unique items, wherein the recommendation compilation engine is configured to electronically communicate with the penalty computation engine to calculate dissimilarity penalties for each of a plurality of alternative unique items, the recommendation of alternative unique items comprising a ranking of at least a portion of the plurality of alternative unique items, the ranking based at least partially on the calculated dissimilarity penalties; and one or more computers configured to operate the recommendation compilation engine, wherein the one or more computers comprises a computer processor and an electronic storage medium. 17. The recommendation system of claim 13 , wherein the penalty computation engine calculates the dissimilarity penalty based on attributes of the alternative item compared to attributes of the plurality of selected items.
| 0.727358 |
1. A computerized method of analyzing a plurality of documents, comprising: collecting and filtering terms from a plurality of documents; identifying a term-frequency vector for each of the documents; identifying a term-frequency matrix using the term-frequency vector, wherein rows of the term-frequency matrix comprise values for the term-frequency vectors; projecting the term-frequency matrix onto a lower dimensional space using latent semantic analysis, to create a transformed term matrix; developing a correlation matrix comprising columns and rows corresponding to terms of the transformed term matrix, and a plurality of elements each having a correlation value indicating a statistical relationship exclusively between two of the terms; converting the correlation values to distance values; creating a concept graph of connected components using the distance values that are greater than or less than a concept threshold, where each connected component is a concept set of terms that corresponds to a concept; and clustering documents that contain the terms of the concept set together.
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1. A computerized method of analyzing a plurality of documents, comprising: collecting and filtering terms from a plurality of documents; identifying a term-frequency vector for each of the documents; identifying a term-frequency matrix using the term-frequency vector, wherein rows of the term-frequency matrix comprise values for the term-frequency vectors; projecting the term-frequency matrix onto a lower dimensional space using latent semantic analysis, to create a transformed term matrix; developing a correlation matrix comprising columns and rows corresponding to terms of the transformed term matrix, and a plurality of elements each having a correlation value indicating a statistical relationship exclusively between two of the terms; converting the correlation values to distance values; creating a concept graph of connected components using the distance values that are greater than or less than a concept threshold, where each connected component is a concept set of terms that corresponds to a concept; and clustering documents that contain the terms of the concept set together. 13. The method of claim 1 , wherein the concept threshold is less than or equal to 1, and terms that have correlation higher than the concept threshold form the vertices of the concept graph.
| 0.53336 |
17. One or more non-transitory computer-readable storage media encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: obtaining a collection of training documents, the training documents including a group of positive documents and a group of negative documents, wherein the positive documents are training documents identified as being longform documents and the negative documents are training documents identified as not being longform documents; extracting a plurality of features from the training documents, wherein the plurality of features are associated with a plurality of different feature types that represent lexical or textual content of the training documents that are indicative of a document's writing style; generating a longform document classifier trained using feature instances extracted from the training documents, wherein the generated longform document classifier is trained such that input documents are classified as being longform documents or classified as not being longform documents; applying the longform document classifier to a corpus of documents; annotating an information retrieval index with an output classification for each document of the corpus of documents; and using the annotated index to provide search results identifying longform documents in response to a search query.
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17. One or more non-transitory computer-readable storage media encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: obtaining a collection of training documents, the training documents including a group of positive documents and a group of negative documents, wherein the positive documents are training documents identified as being longform documents and the negative documents are training documents identified as not being longform documents; extracting a plurality of features from the training documents, wherein the plurality of features are associated with a plurality of different feature types that represent lexical or textual content of the training documents that are indicative of a document's writing style; generating a longform document classifier trained using feature instances extracted from the training documents, wherein the generated longform document classifier is trained such that input documents are classified as being longform documents or classified as not being longform documents; applying the longform document classifier to a corpus of documents; annotating an information retrieval index with an output classification for each document of the corpus of documents; and using the annotated index to provide search results identifying longform documents in response to a search query. 19. The one or more non-transitory computer readable media of claim 17 , wherein the one or more features include a parts of speech n-gram feature that indicates aspects of common sentence structures in the documents.
| 0.542824 |
2. The method of claim 1 , further comprising: using the mapping table to recreate the attribute hierarchy when a significant change occurs in the physical hierarchy or the attribute hierarchy.
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2. The method of claim 1 , further comprising: using the mapping table to recreate the attribute hierarchy when a significant change occurs in the physical hierarchy or the attribute hierarchy. 10. The method of claim 2 , wherein a record in a new level is a dummy record that indicates a missing value for a corresponding attribute hierarchy field.
| 0.941302 |
23. A computer-implemented method of forecasting future observations in a sequence of time series data, comprising: storing, in a memory communicatively coupled to a processor, computer-executable instructions for performing the method of making predictions relative to the time series data, the predictions related to nontrivial extractions of implicit, previously unknown information obtained by data mining within large amounts of data; executing the instructions on the processor, wherein the instructions result in data mining within the large amounts of data; according to the instructions being executed: performing a greedy search to grow a model corresponding to the set of time series data represented by a decision graph having at least one non-trivial linear regression at leaves of the decision graph, the greedy search algorithm being performed iteratively relative to respective leaves of the model for a subset of potential regressors, wherein the potential regressors are arranged in the subset in a descending order of their correlation to a predicted variable; computing a Bayesian score for the model and, wherein the performance of the greedy search further comprising splitting a leaf node of the model into a pair of additional leaves, each of the additional leaves including at least one linear regression on at least one variable of a set of potential regressors and the performance of the greedy search further comprising merging at least two leaf nodes of the decision graph provided that the merging improves the Bayesian score for the model and the decision graph is a regression decision graph model comprising a plurality of leaves and at least one non-leaf node, the at least one non-leaf node being associated with a Boolean function for one of a plurality of variables having a split value, at least one non-root node of the regression decision graph model having more than one parent in the regression decision graph model, at least two leaves of the regression decision graph model being associated with at least one linear regression on at least one of the variables so as to provide a piecewise linear regression decision graph model; repeating the performance of the greedy search and computation of the Bayesian score so long as the model score improves; if the model score does not improve, terminating the modification and computation, and providing a model having a model structure corresponding to a decision graph having a fixed number of leaves that include at least one non-trivial linear regression; modifying a regressor variable at one of the leaves of the decision graph to provide a submodel; computing a Bayesian score for the submodel; repeating the modifying and computation of the Bayesian score for the submodel so long as the score of the submodel improves; if the score of the submodel does not improve relative to a previous score of the submodel, providing the submodel with the highest model score as the regression model that best models future observations of the time series data; and employing the best regression model to generate the future observations of the time series data.
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23. A computer-implemented method of forecasting future observations in a sequence of time series data, comprising: storing, in a memory communicatively coupled to a processor, computer-executable instructions for performing the method of making predictions relative to the time series data, the predictions related to nontrivial extractions of implicit, previously unknown information obtained by data mining within large amounts of data; executing the instructions on the processor, wherein the instructions result in data mining within the large amounts of data; according to the instructions being executed: performing a greedy search to grow a model corresponding to the set of time series data represented by a decision graph having at least one non-trivial linear regression at leaves of the decision graph, the greedy search algorithm being performed iteratively relative to respective leaves of the model for a subset of potential regressors, wherein the potential regressors are arranged in the subset in a descending order of their correlation to a predicted variable; computing a Bayesian score for the model and, wherein the performance of the greedy search further comprising splitting a leaf node of the model into a pair of additional leaves, each of the additional leaves including at least one linear regression on at least one variable of a set of potential regressors and the performance of the greedy search further comprising merging at least two leaf nodes of the decision graph provided that the merging improves the Bayesian score for the model and the decision graph is a regression decision graph model comprising a plurality of leaves and at least one non-leaf node, the at least one non-leaf node being associated with a Boolean function for one of a plurality of variables having a split value, at least one non-root node of the regression decision graph model having more than one parent in the regression decision graph model, at least two leaves of the regression decision graph model being associated with at least one linear regression on at least one of the variables so as to provide a piecewise linear regression decision graph model; repeating the performance of the greedy search and computation of the Bayesian score so long as the model score improves; if the model score does not improve, terminating the modification and computation, and providing a model having a model structure corresponding to a decision graph having a fixed number of leaves that include at least one non-trivial linear regression; modifying a regressor variable at one of the leaves of the decision graph to provide a submodel; computing a Bayesian score for the submodel; repeating the modifying and computation of the Bayesian score for the submodel so long as the score of the submodel improves; if the score of the submodel does not improve relative to a previous score of the submodel, providing the submodel with the highest model score as the regression model that best models future observations of the time series data; and employing the best regression model to generate the future observations of the time series data. 25. The method of claim 23 , a next regressor of the set of potential regressors being added to the subset of potential regressors for each subsequent iteration at a respective leaf so long as the model improved relative to a preceding iteration.
| 0.537369 |
1. A method for compiling data, the method comprising: receiving an input query in a first language; translating the input query to a nested relational algebra (NRA) in the form of a first intermediate representation (IR), wherein the first IR comprises a high-level functional language including algebraic operators; implementing a set of algorithms of the algebraic operators to compile at least some of the first IR into a second IR, wherein the second IR comprises a hybrid language which utilizes a data-flow language and a set of lower-level extensions, and wherein the second IR is optimized by utilizing a set of specific optimizations targeting a part of the second IR that was compiled from a set of algebraic operators of the first IR, wherein the first IR is optimized by utilizing a set of functional optimizations on a set of non-algebra portions of the first IR, wherein the second IR is further optimized by utilizing a set of data-flow optimizations; and compiling at least one of: the first IR and the second IR, into a low-level code.
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1. A method for compiling data, the method comprising: receiving an input query in a first language; translating the input query to a nested relational algebra (NRA) in the form of a first intermediate representation (IR), wherein the first IR comprises a high-level functional language including algebraic operators; implementing a set of algorithms of the algebraic operators to compile at least some of the first IR into a second IR, wherein the second IR comprises a hybrid language which utilizes a data-flow language and a set of lower-level extensions, and wherein the second IR is optimized by utilizing a set of specific optimizations targeting a part of the second IR that was compiled from a set of algebraic operators of the first IR, wherein the first IR is optimized by utilizing a set of functional optimizations on a set of non-algebra portions of the first IR, wherein the second IR is further optimized by utilizing a set of data-flow optimizations; and compiling at least one of: the first IR and the second IR, into a low-level code. 2. The method of claim 1 , wherein all of the first IR is compiled into the second IR.
| 0.590521 |
6. The method of claim 5 , wherein the production system further includes a production plan cache and wherein the backup system further includes a backup plan cache, the method further comprising: receiving, by the first DBMS and prior to the first query access plan satisfaction determination, a second request to execute the query; generating, by the first DBMS and in response to the receiving the second request to execute the query, the first query access plan based on statistics for the production database; storing, in response to the first query access plan satisfaction determination, the first query access plan to the production plan cache; and obtaining, in response to the receiving the second request to execute the query, a first result set for the query by implementing, by the first DBMS, the first query access plan on the production database, wherein the second query access is stored to the backup plan cache.
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6. The method of claim 5 , wherein the production system further includes a production plan cache and wherein the backup system further includes a backup plan cache, the method further comprising: receiving, by the first DBMS and prior to the first query access plan satisfaction determination, a second request to execute the query; generating, by the first DBMS and in response to the receiving the second request to execute the query, the first query access plan based on statistics for the production database; storing, in response to the first query access plan satisfaction determination, the first query access plan to the production plan cache; and obtaining, in response to the receiving the second request to execute the query, a first result set for the query by implementing, by the first DBMS, the first query access plan on the production database, wherein the second query access is stored to the backup plan cache. 7. The method of claim 6 , wherein the production system performs the generating the second query access plan, wherein the optimizer of the first DBMS performs the failure determination and the second query access plan satisfaction determination, and wherein the generating the second query access plan is based on the statistics for the production database.
| 0.717163 |
6. The computer-readable storage medium of claim 1 , further comprising updating the source data value upon a target change to the target property.
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6. The computer-readable storage medium of claim 1 , further comprising updating the source data value upon a target change to the target property. 9. The computer-readable storage medium of claim 6 , wherein updating the source data value is performed explicitly by an application.
| 0.951126 |
41. A computing device, comprising: force sensing means for sensing a force applied to a case of the computing device; means for receiving an electrical signal from the force sensing means; means for comparing the received electrical signal to each of a plurality of reference signal templates; means for calculating cross-correlation values of the received electrical signal and each of the plurality of reference signal templates; means for determining a best match reference signal template for the received electrical signal based on the cross-correlation values; means for identifying a functionality associated with the best match reference signal template; and means for implementing the identified functionality on the computing device.
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41. A computing device, comprising: force sensing means for sensing a force applied to a case of the computing device; means for receiving an electrical signal from the force sensing means; means for comparing the received electrical signal to each of a plurality of reference signal templates; means for calculating cross-correlation values of the received electrical signal and each of the plurality of reference signal templates; means for determining a best match reference signal template for the received electrical signal based on the cross-correlation values; means for identifying a functionality associated with the best match reference signal template; and means for implementing the identified functionality on the computing device. 48. The computing device of claim 41 , wherein means for comparing the received electrical signal with a reference signal template, and means for determining whether the received electrical signal matches the reference signal template comprises: means for performing a hidden Markov model test on the received electrical signal from the force sensing means.
| 0.686061 |
7. The method of claim 1 , further including a spelling teacher application software program, for allowing a teacher or instructor to add non misspelled words to said word database.
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7. The method of claim 1 , further including a spelling teacher application software program, for allowing a teacher or instructor to add non misspelled words to said word database. 9. The method of claim 7 , wherein said non misspelled words entered by said teacher further include a sentence showing proper usage of said non misspelled words.
| 0.894325 |
7. A system comprising: one or more computer processors configured to: receive a request to access a cache entry in a shared cache, the request referencing a synonym for the cache entry, a cache directory of the shared cache comprising, for each cache entry of the shared cache, a first-ranked synonym slot for storing a most recently used synonym for the cache entry and a second-ranked synonym slot for storing a second most recently used synonym for the cache entry; and based on receiving the request: write contents of the first-ranked synonym slot for the cache entry to the second-ranked synonym slot for the cache entry; and write the synonym referenced in the request to the first-ranked synonym slot for the cache entry.
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7. A system comprising: one or more computer processors configured to: receive a request to access a cache entry in a shared cache, the request referencing a synonym for the cache entry, a cache directory of the shared cache comprising, for each cache entry of the shared cache, a first-ranked synonym slot for storing a most recently used synonym for the cache entry and a second-ranked synonym slot for storing a second most recently used synonym for the cache entry; and based on receiving the request: write contents of the first-ranked synonym slot for the cache entry to the second-ranked synonym slot for the cache entry; and write the synonym referenced in the request to the first-ranked synonym slot for the cache entry. 12. The system of claim 7 , the one or more processors further configured to: receive an other request for an other cache entry, wherein the other request references an other synonym; determine that the other synonym matches a synonym stored in the second-ranked synonym slot of the other cache entry; and swap the synonyms in the first-ranked synonym slot and the second-ranked synonym slot of the other cache entry, responsive to determining that the other synonym matches the synonym stored in the second-ranked synonym slot of the other cache entry.
| 0.615953 |
49. A non-transitory computer-readable medium having stored thereon computer-executable instructions that, in response to execution by a computing system, cause the computing system to: receive multiple annotations from different authors for particular content in a digital work; store the annotations in association with the digital work; provide a list of abbreviated versions of the annotations to a user desiring to access one or more of the annotations, wherein the list presents the annotations in an order determined by reference to a criterion; receive an authorization credential from the user desiring to access one or more of the annotations; and if the authorization credential is valid, provide a full version of the one or more annotations of the digital work to the user in context with regard to the digital work.
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49. A non-transitory computer-readable medium having stored thereon computer-executable instructions that, in response to execution by a computing system, cause the computing system to: receive multiple annotations from different authors for particular content in a digital work; store the annotations in association with the digital work; provide a list of abbreviated versions of the annotations to a user desiring to access one or more of the annotations, wherein the list presents the annotations in an order determined by reference to a criterion; receive an authorization credential from the user desiring to access one or more of the annotations; and if the authorization credential is valid, provide a full version of the one or more annotations of the digital work to the user in context with regard to the digital work. 52. The computer-readable medium of claim 49 , wherein the criterion is a date of receipt of each of the annotations.
| 0.586999 |
1. In a computing environment, a method performed at least in part on at least one processor, the method comprising: receiving feature data corresponding to location-related information of an individual visit, the location-related information associated with a first computing device, the feature data including user demographics data of a person associated with the first computing device and at least one of arrival day of week, arrival time of day, visit midpoint time of day, departure time of day, duration of visit, season of year, holiday data, and nearby business features; computing an inference of a semantic label for a place represented by the location-related information for the individual visit using a semantic label classifier and the received feature data, the inference of the semantic label based at least in part on the user demographics data, such that the inferred semantic label for the place is customized to the person associated with the user demographics data and the individual visit; and associating the inferred semantic label with the place represented by the location-related information for the individual visit; and automatically performing an action at the first computing device or at another computing device based on the inferred semantic label.
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1. In a computing environment, a method performed at least in part on at least one processor, the method comprising: receiving feature data corresponding to location-related information of an individual visit, the location-related information associated with a first computing device, the feature data including user demographics data of a person associated with the first computing device and at least one of arrival day of week, arrival time of day, visit midpoint time of day, departure time of day, duration of visit, season of year, holiday data, and nearby business features; computing an inference of a semantic label for a place represented by the location-related information for the individual visit using a semantic label classifier and the received feature data, the inference of the semantic label based at least in part on the user demographics data, such that the inferred semantic label for the place is customized to the person associated with the user demographics data and the individual visit; and associating the inferred semantic label with the place represented by the location-related information for the individual visit; and automatically performing an action at the first computing device or at another computing device based on the inferred semantic label. 10. The method of claim 1 , further comprising: receiving user feedback based on the automatically performed action; and training the semantic label classifier at least in part using the received user feedback.
| 0.625489 |
18. The electronic system of claim 17 , wherein the operations further comprise: receiving, by the one or more computer systems, a request for information; and applying the supervised labeling model to the request for information to determine a label for the request.
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18. The electronic system of claim 17 , wherein the operations further comprise: receiving, by the one or more computer systems, a request for information; and applying the supervised labeling model to the request for information to determine a label for the request. 19. The electronic system of claim 18 , wherein the operations further comprise: determining that a confidence level for a relevance of information in the cross-channel cluster is less than a threshold level; and generating a message that identifies information in the cross-channel cluster that is likely to address the request for information.
| 0.820251 |
1. A computer implemented method of generating a plurality of specialty-oriented document databases or indices from a master index of terms within a subject matter area, said method comprising steps of assigning one or more specialties to each document, wherein said step of assigning one or more specialties is carried out by an expert in said one or more specialties, assigning a limited number of terms from said master index or codes corresponding to said terms to each document, wherein said step of assigning one or more terms or codes is carried out separately from said step of assigning one or more specialties of said plurality of specialties by an expert in said one or more specialties, said expert being a person, and wherein said step of assigning a limited number of terms or codes is based on primary relevance of material described as determined by said expert, merging results of said step of assigning one or more specialties and results of said step of assigning a limited number of terms or codes, using a computer, to form respective specialty-oriented document databases comprising said documents or respective specialty-oriented indices comprising said terms or codes corresponding to documents using terms or codes from said master index assigned to documents and which are assigned to respective specialties by said step of assigning one or more specialties to each document, wherein said method generates said plurality of specialty-oriented databases or indices of said documents which are accessible from said databases or indices in accordance with terms or codes assigned in said step of assigning a limited number of terms or codes to said documents.
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1. A computer implemented method of generating a plurality of specialty-oriented document databases or indices from a master index of terms within a subject matter area, said method comprising steps of assigning one or more specialties to each document, wherein said step of assigning one or more specialties is carried out by an expert in said one or more specialties, assigning a limited number of terms from said master index or codes corresponding to said terms to each document, wherein said step of assigning one or more terms or codes is carried out separately from said step of assigning one or more specialties of said plurality of specialties by an expert in said one or more specialties, said expert being a person, and wherein said step of assigning a limited number of terms or codes is based on primary relevance of material described as determined by said expert, merging results of said step of assigning one or more specialties and results of said step of assigning a limited number of terms or codes, using a computer, to form respective specialty-oriented document databases comprising said documents or respective specialty-oriented indices comprising said terms or codes corresponding to documents using terms or codes from said master index assigned to documents and which are assigned to respective specialties by said step of assigning one or more specialties to each document, wherein said method generates said plurality of specialty-oriented databases or indices of said documents which are accessible from said databases or indices in accordance with terms or codes assigned in said step of assigning a limited number of terms or codes to said documents. 9. The method as recited in claim 1 , wherein terms or codes assigned to each document are limited in number to 1 to 10.
| 0.570661 |
2. A computer implemented method comprising: a SQL/XML compiler rewriting a XQuery query that includes a XQuery function to generate a rewritten query, wherein said XQuery query applies XML data to said XQuery function, wherein rewriting said XQuery query includes: during compile time, said SQL/XML compiler determining that said XML data is dynamically typed; and in response to determining that said XML data is dynamically typed, said SQL/XML compiler replacing said XQuery function with an SQL polymorphic function that is able to handle a range of XML data types and performs type checking when computed at run time, said rewritten query applying said XML data to said SQL polymorphic function and typing said XML data as XMLType, wherein said method is performed by one or more computing devices.
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2. A computer implemented method comprising: a SQL/XML compiler rewriting a XQuery query that includes a XQuery function to generate a rewritten query, wherein said XQuery query applies XML data to said XQuery function, wherein rewriting said XQuery query includes: during compile time, said SQL/XML compiler determining that said XML data is dynamically typed; and in response to determining that said XML data is dynamically typed, said SQL/XML compiler replacing said XQuery function with an SQL polymorphic function that is able to handle a range of XML data types and performs type checking when computed at run time, said rewritten query applying said XML data to said SQL polymorphic function and typing said XML data as XMLType, wherein said method is performed by one or more computing devices. 4. The method of claim 2 , wherein said SQL polymorphic function is configured to perform: type checking, and one or more operations the execution of which depends on a result of type checking.
| 0.657244 |
15. An apparatus, comprising: one or more processors; and memory storing computer-readable instructions that, when executed by the one or more processors, cause the apparatus to: receive a request for a font file; determine whether the request is valid; in response to determining that the request is valid, embed a first watermark in the font file at least by inserting one or more zero-length vectors at one or more locations in the font file; and serve the font file.
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15. An apparatus, comprising: one or more processors; and memory storing computer-readable instructions that, when executed by the one or more processors, cause the apparatus to: receive a request for a font file; determine whether the request is valid; in response to determining that the request is valid, embed a first watermark in the font file at least by inserting one or more zero-length vectors at one or more locations in the font file; and serve the font file. 16. The apparatus of claim 15 , wherein the memory further stores computer-readable instructions that, when executed by the one or more processors, cause the apparatus to: embed a second watermark in the font file at least by inserting one or more data tables into one or more data structures of the font file, wherein the one or more data tables include a customer identifier.
| 0.502706 |
8. A computing device comprising one or more processors configured to: receive one or more indications of user input of a character string that comprises one or more non-punctuation characters and a plurality of instances of a generic punctuation mark character, the generic punctuation mark character being a stand-in for, and different than, any punctuation mark in a plurality of non-generic punctuation marks, the plurality of non-generic punctuation marks including a comma, a period, a colon, a semicolon, a question mark, a hyphen, a forward slash, a backslash, and an exclamation point; output the character string for display; responsive to receiving an indication that the user has finished entering the character string, for each respective instance of the generic punctuation mark character of the plurality of instances of the generic punctuation mark characters in the character string, output a plurality of punctuation marks for display, wherein each of the plurality of punctuation marks is one of the plurality of non-generic punctuation marks; receive an indication of a user selection of a respective punctuation mark from among the plurality of punctuation marks; and responsive to receiving the indication of the user selection of the respective punctuation mark from among the plurality of punctuation marks, output, for display, a respective version of the character string including the respective punctuation mark in place of the respective instance of the generic punctuation mark character.
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8. A computing device comprising one or more processors configured to: receive one or more indications of user input of a character string that comprises one or more non-punctuation characters and a plurality of instances of a generic punctuation mark character, the generic punctuation mark character being a stand-in for, and different than, any punctuation mark in a plurality of non-generic punctuation marks, the plurality of non-generic punctuation marks including a comma, a period, a colon, a semicolon, a question mark, a hyphen, a forward slash, a backslash, and an exclamation point; output the character string for display; responsive to receiving an indication that the user has finished entering the character string, for each respective instance of the generic punctuation mark character of the plurality of instances of the generic punctuation mark characters in the character string, output a plurality of punctuation marks for display, wherein each of the plurality of punctuation marks is one of the plurality of non-generic punctuation marks; receive an indication of a user selection of a respective punctuation mark from among the plurality of punctuation marks; and responsive to receiving the indication of the user selection of the respective punctuation mark from among the plurality of punctuation marks, output, for display, a respective version of the character string including the respective punctuation mark in place of the respective instance of the generic punctuation mark character. 11. The computing device of claim 8 , wherein: the one or more processors are configured to determine a respective ranked set of suggested non-generic punctuation marks for each of the plurality of instances of the generic punctuation mark character in the character string; and the one or more processors the configured to output, for display, a respective suggestion element for each of the plurality of instances of the generic punctuation mark character that includes a highest-ranked non-generic punctuation mark of the respective ranked set of suggested non-generic punctuation marks.
| 0.588605 |
1. A method performed by data processing apparatus, the method comprising: obtaining a group of similar images for a particular image, wherein each similar image is associated with one or more n-grams; determining an overall score for each of the n-grams, wherein for each n-gram the overall score is based at least in part on: i) a combination of image specific scores for the n-gram for images in the group of similar images and ii) the number of similar images in the group of similar images; and selecting one of the n-grams as a textual description of the particular image according at least in part on the overall scores for the n-grams and the respective n-gram order of each of the n-grams representing a number of tokens in the n-gram.
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1. A method performed by data processing apparatus, the method comprising: obtaining a group of similar images for a particular image, wherein each similar image is associated with one or more n-grams; determining an overall score for each of the n-grams, wherein for each n-gram the overall score is based at least in part on: i) a combination of image specific scores for the n-gram for images in the group of similar images and ii) the number of similar images in the group of similar images; and selecting one of the n-grams as a textual description of the particular image according at least in part on the overall scores for the n-grams and the respective n-gram order of each of the n-grams representing a number of tokens in the n-gram. 4. The method of claim 1 , wherein each image-specific score for a particular n-gram is calculated based on image affinity calculated between similar images associated with the n-gram.
| 0.74965 |
7. The system of claim 6 , wherein the graphical user interface engine is configured to generate the graphical user interface screens based on the information contained in at least one of a Display table, a Shape table, a Range table and a Query table, the hierarchical model further comprising: an Nclass_Group table configured to comprise information defining a group of node_classes within a Node_Class table that build a pool of nodes within a mapping; a Domain table configured to comprise information defining data element types that belong to a node, data element types that belong to a mapping, and data structures stored within the hierarchical model; an Attribute table configured to comprise operational data associated with a node and operational data associated with a mapping; the Display table configured to comprise information defining a graphical representation of a specific view of the hierarchical model; the Shape table configured to comprise one or more graphical parameters defining how node information is displayed, wherein the node information comprises the specification of a position, a size, a shape, and a background; the Range table configured to comprise color information corresponding to shapes for displaying a shape as part of a query result; and the Query table configured to comprise display information defining how a result of an SQL statement executed on the hierarchical model is displayed.
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7. The system of claim 6 , wherein the graphical user interface engine is configured to generate the graphical user interface screens based on the information contained in at least one of a Display table, a Shape table, a Range table and a Query table, the hierarchical model further comprising: an Nclass_Group table configured to comprise information defining a group of node_classes within a Node_Class table that build a pool of nodes within a mapping; a Domain table configured to comprise information defining data element types that belong to a node, data element types that belong to a mapping, and data structures stored within the hierarchical model; an Attribute table configured to comprise operational data associated with a node and operational data associated with a mapping; the Display table configured to comprise information defining a graphical representation of a specific view of the hierarchical model; the Shape table configured to comprise one or more graphical parameters defining how node information is displayed, wherein the node information comprises the specification of a position, a size, a shape, and a background; the Range table configured to comprise color information corresponding to shapes for displaying a shape as part of a query result; and the Query table configured to comprise display information defining how a result of an SQL statement executed on the hierarchical model is displayed. 8. The system of claim 7 , wherein the system further comprises a scenario engine configured to generate a visual representation of the structured, hierarchical model into a database and/or for generating a plurality of scenarios or ongoing variations of the structured, hierarchical model.
| 0.665051 |
1. An apparatus for the input of symbols, comprising: a plurality of keys for inputting symbols, said plurality of keys having both: a) a digit, and b) at least one punctuation symbol assigned to the keys, said keys characterized in that, for each key having a digit and a punctuation symbol assigned to it: the punctuation symbols and digits are overlapped in fonts and the at least one punctuation symbol associated with the key is morphically similar to the digit assigned to the key, wherein the at least one punctuation symbol is assigned to the key based upon at least the punctuation symbol being morphically similar to the digit assigned to the key, such that: the punctuation symbol and digit occupy substantially the same keypad surface real estate when the punctuation symbols and digits are overlapped in fonts, wherein said at least one punctuation symbol and said digit being presented at a same time.
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1. An apparatus for the input of symbols, comprising: a plurality of keys for inputting symbols, said plurality of keys having both: a) a digit, and b) at least one punctuation symbol assigned to the keys, said keys characterized in that, for each key having a digit and a punctuation symbol assigned to it: the punctuation symbols and digits are overlapped in fonts and the at least one punctuation symbol associated with the key is morphically similar to the digit assigned to the key, wherein the at least one punctuation symbol is assigned to the key based upon at least the punctuation symbol being morphically similar to the digit assigned to the key, such that: the punctuation symbol and digit occupy substantially the same keypad surface real estate when the punctuation symbols and digits are overlapped in fonts, wherein said at least one punctuation symbol and said digit being presented at a same time. 6. The apparatus of claim 1 , wherein said apparatus comprises at least one key that inputs a set of said symbols comprising: a digit correlated to a number “5”, and wherein said punctuation symbol is a hyphen.
| 0.758906 |
1. A computer implemented method for automated dictionary population, comprising: providing a processor executing instructions for: receiving a message containing words; parsing the words of the message; comparing each word to entries of at least one dictionary to identify new words that are not in said at least one dictionary; storing said new words in a supplementary word list; and parsing a group of adjacent words, wherein if none of said ad adjacent words are found in said at least one dictionary, storing said adjacent words with additional information that allows them to remain linked.
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1. A computer implemented method for automated dictionary population, comprising: providing a processor executing instructions for: receiving a message containing words; parsing the words of the message; comparing each word to entries of at least one dictionary to identify new words that are not in said at least one dictionary; storing said new words in a supplementary word list; and parsing a group of adjacent words, wherein if none of said ad adjacent words are found in said at least one dictionary, storing said adjacent words with additional information that allows them to remain linked. 2. The method of claim 1 , further comprising: identifying phrases from the parsed words by identifying phrase markers, wherein the phrase markers include at least one of italicized word groups, quoted word groups, bolded word groups, capitalized word groups, and word groups containing more than one new word.
| 0.754098 |
25. A method of automating the preparation of a voice application, comprising: annotating a voice Extensible Markup Language (XML) application with one or more audio tags, wherein each audio tag includes at least one voice property; associating a text string to be spoken in the voice application with a corresponding audio tag; parsing via a processor the application to locate the corresponding audio tag; passing the text string and the corresponding audio tag to a database of audio files; and if an audio file having content matching the text string and at least one voice property included in the associated audio tag is located in the database of audio files, replacing the text string with a file name of the located audio file automatically; and if an audio file having content matching the text string and the at least one voice property is not located in the database of audio files, determining whether a plurality of audio files are located in the database of audio files that match the at least one voice property and that partially match the text string, and replacing the text string with a file name representing the combination of the plurality of audio files after passing the file name representing the combination of the audio files to a developer for review and receiving developer confirmation.
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25. A method of automating the preparation of a voice application, comprising: annotating a voice Extensible Markup Language (XML) application with one or more audio tags, wherein each audio tag includes at least one voice property; associating a text string to be spoken in the voice application with a corresponding audio tag; parsing via a processor the application to locate the corresponding audio tag; passing the text string and the corresponding audio tag to a database of audio files; and if an audio file having content matching the text string and at least one voice property included in the associated audio tag is located in the database of audio files, replacing the text string with a file name of the located audio file automatically; and if an audio file having content matching the text string and the at least one voice property is not located in the database of audio files, determining whether a plurality of audio files are located in the database of audio files that match the at least one voice property and that partially match the text string, and replacing the text string with a file name representing the combination of the plurality of audio files after passing the file name representing the combination of the audio files to a developer for review and receiving developer confirmation. 26. The method of claim 25 , wherein replacing the text string with a file name of the located audio file includes replacing the text string with a file name of the located audio file that has content matching the text string and a default voice property.
| 0.615746 |
14. A system, comprising: one or more processors; memory; one or more programs stored in the memory to be executed by the one or more processors, the one or more programs comprising: instructions for determining a correlation, for each search context of a plurality of search contexts, for each scoring primitive of a plurality of scoring primitives, and for a set of previously executed search queries that are consistent with the search context, between the scoring primitive and actual user selections of results of the previously executed search queries by a plurality of users; instructions for performing machine learning, for each search context, on the correlations to identify a predicted performance function comprising a weighted subset of the scoring primitives that meet predefined predictive quality criteria, wherein the identified predicted performance function is associated with the search context; and instructions for receiving and executing a user submitted search query, submitted by a user, to produce a set of search results, including associating the user submitted search query with a respective search context of the plurality of search contexts, and ordering at least a portion of the search results in accordance with the identified predicted performance function for the search context associated with the user submitted search query.
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14. A system, comprising: one or more processors; memory; one or more programs stored in the memory to be executed by the one or more processors, the one or more programs comprising: instructions for determining a correlation, for each search context of a plurality of search contexts, for each scoring primitive of a plurality of scoring primitives, and for a set of previously executed search queries that are consistent with the search context, between the scoring primitive and actual user selections of results of the previously executed search queries by a plurality of users; instructions for performing machine learning, for each search context, on the correlations to identify a predicted performance function comprising a weighted subset of the scoring primitives that meet predefined predictive quality criteria, wherein the identified predicted performance function is associated with the search context; and instructions for receiving and executing a user submitted search query, submitted by a user, to produce a set of search results, including associating the user submitted search query with a respective search context of the plurality of search contexts, and ordering at least a portion of the search results in accordance with the identified predicted performance function for the search context associated with the user submitted search query. 21. The system of claim 14 , wherein ordering at least a subset of the search results includes evaluating the identified predicted performance function, for each of a plurality of the search results, using one or more parameters of a user profile of the user.
| 0.597993 |
18. The device of claim 10 , wherein the processor is further configured to: determine a respective pronunciation of one or more parts of a username in the network address based on a determination that the one or more parts comprises one or more of: a recognized word from a spoken language, a first name, a last name, and a diminutive variation of the first name.
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18. The device of claim 10 , wherein the processor is further configured to: determine a respective pronunciation of one or more parts of a username in the network address based on a determination that the one or more parts comprises one or more of: a recognized word from a spoken language, a first name, a last name, and a diminutive variation of the first name. 19. The device of claim 18 , wherein the processor is further configured to determine the respective pronunciation of the one or more parts by one or more of: generating the respective pronunciation of the one or more parts, each pronounced as a whole, and generating speech of the respective pronunciation of the one or more parts utilizing the audio waveform generator; and, generating a respective tokenized representation pronunciation of the one or more parts, each pronounced as a whole, suitable for interpretation by the text-to-speech engine.
| 0.864014 |
13. The method of claim 8 wherein the first increment value is greater than the second increment value.
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13. The method of claim 8 wherein the first increment value is greater than the second increment value. 14. The method of claim 13 wherein, in the first scoring model, the first increment value for the substitute term is less than or equal to an increment value for the query term.
| 0.941176 |
1. A processor implemented method for finding documents which relate to a portion of a temporal document, comprising: (a) initiating a signal of interest at any time during the temporal document; (b) capturing content between the time the content is present in the temporal document and the time of initiating the signal of interest; (c) finding the related documents based upon the content captured between the time the content is presented in the temporal document and the time of initiating the signal of interest by use of information retrieval techniques, including related documents not previously associated with the content captured; and (d) selecting the related documents from among a collection of documents which may be accessed through the Internet, by utilizing databases comprising information about the collection; wherein the related documents are accessed through the Internet, and wherein the related documents are selected from the collection according to the scores achieved when evaluating documents in the collection according to a formula giving scores to documents depending upon the occurrence in the documents of terms which occur in the content captured.
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1. A processor implemented method for finding documents which relate to a portion of a temporal document, comprising: (a) initiating a signal of interest at any time during the temporal document; (b) capturing content between the time the content is present in the temporal document and the time of initiating the signal of interest; (c) finding the related documents based upon the content captured between the time the content is presented in the temporal document and the time of initiating the signal of interest by use of information retrieval techniques, including related documents not previously associated with the content captured; and (d) selecting the related documents from among a collection of documents which may be accessed through the Internet, by utilizing databases comprising information about the collection; wherein the related documents are accessed through the Internet, and wherein the related documents are selected from the collection according to the scores achieved when evaluating documents in the collection according to a formula giving scores to documents depending upon the occurrence in the documents of terms which occur in the content captured. 2. The method of claim 1 , wherein the temporal document is video or audio material.
| 0.562865 |
13. A non-transitory machine-readable storage medium having instructions recorded therein for at least one processor of an in-vehicle audio system, execution of the instructions by the at least one processor causing the in-vehicle audio system to perform a method comprising: receiving a command to add one or more items of audio content to a medium of a storage device of the in-vehicle audio system, each respective item of the audio content having a word or a phrase associated therewith; and compiling at least a portion of a vocabulary dictionary of a speech recognition component of the in-vehicle audio system to update the vocabulary dictionary by adding, to the vocabulary dictionary, phonetics corresponding to at least one word or at least one phrase associated with the one or more items of audio content to be added, the vocabulary dictionary being arranged as a plurality of portions, each of the plurality of portions being capable of compiling separately, wherein: the compiling is started while the one or more items of the audio content are being added to the medium of the storage device, the compiling is completed before the one or more items of the audio content are completely added to the medium of the storage device, after completion of the compiling, the speech recognition component is capable of recognizing at least one word or at least one phrase associated with any one or more items of audio content added to the vocabulary dictionary, speech recognition control is available after the compiler completes compiling the vocabulary dictionary, and the speech recognition control related to each respective item of the audio content added to the medium of the storage device becomes available after completion of adding the audio content to the medium of the storage device, and the method further comprises: receiving a second command to delete at least one item of the audio content from the medium of the storage device; detecting an ignition off event as a result of turning off an ignition of a vehicle including the in-vehicle audio system; initiating a shutdown process of the in-vehicle audio system upon the detecting an ignition off event; and compiling, during the shutdown process, at least a second portion of the vocabulary dictionary to update the vocabulary dictionary by deleting, from the vocabulary dictionary, phonetics corresponding to at least one word or at least one phrase associated with the at least item of the audio content to be deleted.
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13. A non-transitory machine-readable storage medium having instructions recorded therein for at least one processor of an in-vehicle audio system, execution of the instructions by the at least one processor causing the in-vehicle audio system to perform a method comprising: receiving a command to add one or more items of audio content to a medium of a storage device of the in-vehicle audio system, each respective item of the audio content having a word or a phrase associated therewith; and compiling at least a portion of a vocabulary dictionary of a speech recognition component of the in-vehicle audio system to update the vocabulary dictionary by adding, to the vocabulary dictionary, phonetics corresponding to at least one word or at least one phrase associated with the one or more items of audio content to be added, the vocabulary dictionary being arranged as a plurality of portions, each of the plurality of portions being capable of compiling separately, wherein: the compiling is started while the one or more items of the audio content are being added to the medium of the storage device, the compiling is completed before the one or more items of the audio content are completely added to the medium of the storage device, after completion of the compiling, the speech recognition component is capable of recognizing at least one word or at least one phrase associated with any one or more items of audio content added to the vocabulary dictionary, speech recognition control is available after the compiler completes compiling the vocabulary dictionary, and the speech recognition control related to each respective item of the audio content added to the medium of the storage device becomes available after completion of adding the audio content to the medium of the storage device, and the method further comprises: receiving a second command to delete at least one item of the audio content from the medium of the storage device; detecting an ignition off event as a result of turning off an ignition of a vehicle including the in-vehicle audio system; initiating a shutdown process of the in-vehicle audio system upon the detecting an ignition off event; and compiling, during the shutdown process, at least a second portion of the vocabulary dictionary to update the vocabulary dictionary by deleting, from the vocabulary dictionary, phonetics corresponding to at least one word or at least one phrase associated with the at least item of the audio content to be deleted. 16. The non-transitory machine-readable storage medium of claim 13 , wherein the method further comprises: copying the one or more items of audio content from a second medium to the medium of the storage device.
| 0.546437 |
1. A document audit trail system comprising: data communication means, the data communication means including document data input means adapted for receiving document data representative of historical characteristics of an associated document, which document includes an indicia; conversion means adapted for converting between document data and indicia data representative of a visual representation of an encoding thereof; the data communication means further includes means adapted for communicating the indicia data with an associated document processing device comprising at least one of a printed device, scanning device, copying device, facsimile machine, multifunctional peripheral, and client application; means adapted for receiving a document processing instruction representative of a user-specified document processing operation for the associated document; means adapted for generating document data in accordance with a received document processing instruction; sensing means adapted for sensing a property of an indicia of the associated document, which property includes data corresponding to a history of at least one document processing operation performed on the associated document; means adapted for generating updated property data in accordance with a sensed property of the indicia in accordance with generated document data; means adapted for applying a modified indicia, inclusive of encoded information relating to the user-specified document processing operation and updated property data, to the associated document in accordance with indicia data received from the sensing means; and rendering means adapted for generating a tangible document output corresponding to received document data, which tangible document data includes the modified indicia.
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1. A document audit trail system comprising: data communication means, the data communication means including document data input means adapted for receiving document data representative of historical characteristics of an associated document, which document includes an indicia; conversion means adapted for converting between document data and indicia data representative of a visual representation of an encoding thereof; the data communication means further includes means adapted for communicating the indicia data with an associated document processing device comprising at least one of a printed device, scanning device, copying device, facsimile machine, multifunctional peripheral, and client application; means adapted for receiving a document processing instruction representative of a user-specified document processing operation for the associated document; means adapted for generating document data in accordance with a received document processing instruction; sensing means adapted for sensing a property of an indicia of the associated document, which property includes data corresponding to a history of at least one document processing operation performed on the associated document; means adapted for generating updated property data in accordance with a sensed property of the indicia in accordance with generated document data; means adapted for applying a modified indicia, inclusive of encoded information relating to the user-specified document processing operation and updated property data, to the associated document in accordance with indicia data received from the sensing means; and rendering means adapted for generating a tangible document output corresponding to received document data, which tangible document data includes the modified indicia. 3. The document audit trail system of claim 1 wherein the indicia applied to the associated document is in the form of a barcode.
| 0.637031 |
10. A system for self-assembling software components, the system comprising: a processor; a memory coupled to the processor; a set of language components executed in the memory by the processor that each defines at least one part of at least one language runnable on a computer by associating a piece of grammar of the at least one language with at least one software component that implements the piece of grammar; a dependency analyzer executed in the memory by the processor that attempts to run the set of language components against at least one section of code and discovers from at least one unrecognized syntactic appearance that at least one language component needed to run the at least one section of code is not available; a first processing unit to provide the at least one section of the code to request access to the at least one language component that the dependency analyzer discovered; a second processing unit to access and/or receive the at least one requested language component in view of the at least one section of the code; and a third processing unit to perform a self-assemble of the first set of language components with the received at least one language component.
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10. A system for self-assembling software components, the system comprising: a processor; a memory coupled to the processor; a set of language components executed in the memory by the processor that each defines at least one part of at least one language runnable on a computer by associating a piece of grammar of the at least one language with at least one software component that implements the piece of grammar; a dependency analyzer executed in the memory by the processor that attempts to run the set of language components against at least one section of code and discovers from at least one unrecognized syntactic appearance that at least one language component needed to run the at least one section of code is not available; a first processing unit to provide the at least one section of the code to request access to the at least one language component that the dependency analyzer discovered; a second processing unit to access and/or receive the at least one requested language component in view of the at least one section of the code; and a third processing unit to perform a self-assemble of the first set of language components with the received at least one language component. 11. The system of claim 10 wherein the dependency analyzer fails to match the at least one section of the code, and the at least one requested language component implements a subset of the at least one language used by the at least one section of code.
| 0.537422 |
13. A method for preparing a display document for analysis comprising: extracting character data from said display document, wherein a language of said character data in said display document is unknown when said character data is extracted; determining a first order associated with processing of said character data and a second order associated with a logical order of said character data; determining whether said first order is different from said second order; and reversing at least a portion of said character data in response to said determination that said first order is different from said second order; wherein determining the second order comprises identifying a punctuation character that is position dependent such that a space character will appear on only one side of the punctuation character, where the side of the punctuation character on which the space character appears depends on said second order; and comparing characters around said punctuation character data against a rule to determine said second order.
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13. A method for preparing a display document for analysis comprising: extracting character data from said display document, wherein a language of said character data in said display document is unknown when said character data is extracted; determining a first order associated with processing of said character data and a second order associated with a logical order of said character data; determining whether said first order is different from said second order; and reversing at least a portion of said character data in response to said determination that said first order is different from said second order; wherein determining the second order comprises identifying a punctuation character that is position dependent such that a space character will appear on only one side of the punctuation character, where the side of the punctuation character on which the space character appears depends on said second order; and comparing characters around said punctuation character data against a rule to determine said second order. 14. The method of claim 13 , wherein said second order is determined by identifying, in said character data, a full stop character and then determining on which side of said full stop character a space character appears.
| 0.605004 |
11. One or more computer-readable media comprising computer-executable instructions for integrating spreadsheet functionality into tables used in word processing and markup language documents, the computer-executable instructions comprising instructions for: integrating spreadsheet functionality into tables used in word processing and markup language documents; creating a spreadsheet object, a grid object, and a table object to manage one or more tables in a document; referencing content in a first of the tables from a second of the tables, the content of the first table being nested within a cell of the second table within the document and each of the first table and the second table supporting a plurality of spreadsheet functionalities; independently managing one or more nested tables using each table's own underlying set, at least one underlying set comprising the spreadsheet object, the grid object, and the table object; displaying the nested first table as enclosed in the cell of the second table; and providing automatic universal recalculation in response to a change in a value in one or more tables in the document.
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11. One or more computer-readable media comprising computer-executable instructions for integrating spreadsheet functionality into tables used in word processing and markup language documents, the computer-executable instructions comprising instructions for: integrating spreadsheet functionality into tables used in word processing and markup language documents; creating a spreadsheet object, a grid object, and a table object to manage one or more tables in a document; referencing content in a first of the tables from a second of the tables, the content of the first table being nested within a cell of the second table within the document and each of the first table and the second table supporting a plurality of spreadsheet functionalities; independently managing one or more nested tables using each table's own underlying set, at least one underlying set comprising the spreadsheet object, the grid object, and the table object; displaying the nested first table as enclosed in the cell of the second table; and providing automatic universal recalculation in response to a change in a value in one or more tables in the document. 14. The one or more computer-readable media as recited in claim 11 , wherein providing automatic universal recalculation comprises instructions for: reevaluating normal formulas only when dependencies change; reevaluating semi-calculation formulas every time a recalculation is performed; and never evaluating non-calculation formulas.
| 0.53858 |
11. A system comprising: a processor; and a non-transitory computer-readable medium having encoded thereon a sequence of instructions which, when loaded and executed by the processor, causes the processor to implement: a structure generation module configured to retrieve, from a memory, a global structure and a plurality of candidate answers therein; a computation module including: (i) a first computation unit configured to compute a first probability of a candidate answer based on a local structure of the candidate answer within the global structure; (ii) a second computation unit configured to compute a second probability of the candidate answer based on content of the candidate answer given content of a query; and (iii) a third computation unit configured to compute a third probability of the candidate answer based on context of the candidate answer given the content of the query; and a combination module configured to provide a combined probability for the candidate answer as a function of the first probability, second probability, and third probability.
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11. A system comprising: a processor; and a non-transitory computer-readable medium having encoded thereon a sequence of instructions which, when loaded and executed by the processor, causes the processor to implement: a structure generation module configured to retrieve, from a memory, a global structure and a plurality of candidate answers therein; a computation module including: (i) a first computation unit configured to compute a first probability of a candidate answer based on a local structure of the candidate answer within the global structure; (ii) a second computation unit configured to compute a second probability of the candidate answer based on content of the candidate answer given content of a query; and (iii) a third computation unit configured to compute a third probability of the candidate answer based on context of the candidate answer given the content of the query; and a combination module configured to provide a combined probability for the candidate answer as a function of the first probability, second probability, and third probability. 19. The system of claim 11 , wherein the structure generation module is further configured retrieve input data with a particular structure and generating the global structure automatically based on the input data by parsing the particular structure.
| 0.656627 |
15. The method as described in claim 14 wherein said second plurality of entities are mapped by importing schemas of databases for said entities into said global attribute object model and correlating relationships between related entities.
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15. The method as described in claim 14 wherein said second plurality of entities are mapped by importing schemas of databases for said entities into said global attribute object model and correlating relationships between related entities. 18. A method as described in claim 15 wherein said first entity in said unified entity-relationship system is mapped a plurality of times to a corresponding individual entity within a plurality of subsumed entity-relationship systems.
| 0.882716 |
12. The method of claim 10 further comprising: storing, in the memory, probe match scores obtained by performing a voice matching operation between the probe and the templates of the biometric corpus; clustering the probe match scores into K clusters; and selecting templates corresponding to ones of the K clusters having probe match scores that exceed M as the first templates.
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12. The method of claim 10 further comprising: storing, in the memory, probe match scores obtained by performing a voice matching operation between the probe and the templates of the biometric corpus; clustering the probe match scores into K clusters; and selecting templates corresponding to ones of the K clusters having probe match scores that exceed M as the first templates. 13. The method of claim 12 wherein the clustering comprises: setting K=1; performing a clustering process; and repeating the clustering process with K incremented by 1 each time until in each of the K clusters a difference between a maximum probe match score and a minimum probe match score is less than about ten times a difference between a maximum probe match score and a minimum probe match score in all the probe match scores.
| 0.866908 |
1. A computer-based method for processing one or more citations within a document, the method comprising: identifying in an electronic document an unformatted citation; parsing the identified unformatted citation and determining one or more citation terms; querying one or more citation libraries to find possible matching citations, each possible matching citation comprising at least a portion of the one or more citation terms; presenting for selecting a set of possible matching citations; and inserting a formatted citation based on a selected one of the set of possible matching citations into the document.
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1. A computer-based method for processing one or more citations within a document, the method comprising: identifying in an electronic document an unformatted citation; parsing the identified unformatted citation and determining one or more citation terms; querying one or more citation libraries to find possible matching citations, each possible matching citation comprising at least a portion of the one or more citation terms; presenting for selecting a set of possible matching citations; and inserting a formatted citation based on a selected one of the set of possible matching citations into the document. 5. The method of claim 1 wherein inserting comprises inserting links to citation data that forms the formatted citation.
| 0.713667 |
1. A computer system for providing responses to requests, the system configured to deploy code to execute multiple commands and provide answers resulting from the commands, the computer system comprising: a broker; a router; a service pack store; and a service pack stored in the service pack store, the service pack including: a plurality of service worker modules, wherein at least two service worker modules are configured to process a request differently from each other; and a plurality of routes, each route associating a service worker module and a location; wherein the broker is configured to download the service pack from the service pack store, distribute the service worker modules to a plurality of locations, and store a command sequence corresponding to each route within the router; wherein the router is configured to receive a plurality of requests and distribute each request according to the command sequences; wherein the service worker modules are each configured to determine an answer based on each request; and wherein the router is configured to receive the answers for each request from the service worker modules and provide a response output for each request based on at least one of the answers.
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1. A computer system for providing responses to requests, the system configured to deploy code to execute multiple commands and provide answers resulting from the commands, the computer system comprising: a broker; a router; a service pack store; and a service pack stored in the service pack store, the service pack including: a plurality of service worker modules, wherein at least two service worker modules are configured to process a request differently from each other; and a plurality of routes, each route associating a service worker module and a location; wherein the broker is configured to download the service pack from the service pack store, distribute the service worker modules to a plurality of locations, and store a command sequence corresponding to each route within the router; wherein the router is configured to receive a plurality of requests and distribute each request according to the command sequences; wherein the service worker modules are each configured to determine an answer based on each request; and wherein the router is configured to receive the answers for each request from the service worker modules and provide a response output for each request based on at least one of the answers. 13. The computer system of claim 1 , wherein the broker includes a service logger that intercepts logging messages from service worker modules attached to the broker and writes them to the log store.
| 0.541636 |
13. The data storage and/or retrieval system of claim 1 , wherein the plurality of entity type data tunnels comprise a plurality of collective data tunnels, the plurality of attribute data tunnels comprise a plurality of collective data tunnels, and the plurality of data cells of said collective data tunnels are collective data cells, wherein each of the collective data cells contain data which is characterised as one of identity, measurement, enumeration or opacity.
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13. The data storage and/or retrieval system of claim 1 , wherein the plurality of entity type data tunnels comprise a plurality of collective data tunnels, the plurality of attribute data tunnels comprise a plurality of collective data tunnels, and the plurality of data cells of said collective data tunnels are collective data cells, wherein each of the collective data cells contain data which is characterised as one of identity, measurement, enumeration or opacity. 14. The data storage and/or retrieval of claim 13 , wherein a collective data cell characterised as one of identity comprises a sequence of bits that denote an identity such that certainty of equivalence of identity for the attribute instance corresponding to said collective data cell can be determined by comparison of said bits in like sequence order.
| 0.903884 |
15. The system of claim 14 , wherein the primary vocabulary application is a generic vocabulary application, and the multiple secondary vocabulary applications are third-party provided vocabulary applications, the first speech recognition pass is based on the primary vocabulary application and the second speech recognition pass is based on the multiple secondary vocabulary applications, and each of the third-party provided vocabulary applications comprise vocabulary that is specific to a third-party provider.
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15. The system of claim 14 , wherein the primary vocabulary application is a generic vocabulary application, and the multiple secondary vocabulary applications are third-party provided vocabulary applications, the first speech recognition pass is based on the primary vocabulary application and the second speech recognition pass is based on the multiple secondary vocabulary applications, and each of the third-party provided vocabulary applications comprise vocabulary that is specific to a third-party provider. 16. The system of claim 15 , wherein the classifier is configured to classify recognized and unrecognized words using the first classification process and the second classification process based on employing a processor for performing at least one of binary classification, use of feature vectors, linear classification and non-linear classification.
| 0.826167 |
13. A method executed in an image processing apparatus, comprising: converting input image data to a bitmap data format; extracting, from the input image data, feature information of an object of interest in the input image data of the bitmap data format; referring to a dictionary and determining a similarity between feature information of an object registered in the dictionary and the feature information of the object of interest extracted in the extraction step, wherein in the dictionary, feature information of a plurality of objects are stored, each feature information is classified into one of a plurality of object-groups, and each feature information is associated with the image data in which an object represented by the feature information is included; registering, in the dictionary, the feature information of the object of interest extracted from the input image; determining whether a number of common images between an object-group of interest in the plurality of object-groups and object-groups other than the object-group of interest satisfies a predetermined criterion; and if the number of common images does not satisfy the predetermined criterion, updating the dictionary so that the feature information included in the object-group of interest is unusable when the dictionary is used for determining.
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13. A method executed in an image processing apparatus, comprising: converting input image data to a bitmap data format; extracting, from the input image data, feature information of an object of interest in the input image data of the bitmap data format; referring to a dictionary and determining a similarity between feature information of an object registered in the dictionary and the feature information of the object of interest extracted in the extraction step, wherein in the dictionary, feature information of a plurality of objects are stored, each feature information is classified into one of a plurality of object-groups, and each feature information is associated with the image data in which an object represented by the feature information is included; registering, in the dictionary, the feature information of the object of interest extracted from the input image; determining whether a number of common images between an object-group of interest in the plurality of object-groups and object-groups other than the object-group of interest satisfies a predetermined criterion; and if the number of common images does not satisfy the predetermined criterion, updating the dictionary so that the feature information included in the object-group of interest is unusable when the dictionary is used for determining. 15. The method according to claim 13 , wherein use of the feature of information included in the object-group of interest is inhibited by deleting, from the dictionary, the feature information.
| 0.764563 |
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