patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|---|---|---|
7,551,187 | 1 | 3 | 1. A computer system that facilitates free form digital inking, comprising: a pen-based microprocessor device and an application program, the application program is recorded on a computer-readable medium and capable of execution by a computer, the application program comprising: an input device for activating an inking region within a zoom window; an annotation management component that generates the zoom window comprising the inking region for an underlying digital document; and a navigation component that manually and automatically re-positions and re-sizes the zoom window and the inking region relative to the digital document, the re-position and re-size of the zoom window and the inking region occurs at least as an annotation of the digital document is entered in the inking region during an annotation event based at least in part on an amount of annotation information entered and displayed in the inking region, the size of the zoom window corresponds to the size of the inking region. | 1. A computer system that facilitates free form digital inking, comprising: a pen-based microprocessor device and an application program, the application program is recorded on a computer-readable medium and capable of execution by a computer, the application program comprising: an input device for activating an inking region within a zoom window; an annotation management component that generates the zoom window comprising the inking region for an underlying digital document; and a navigation component that manually and automatically re-positions and re-sizes the zoom window and the inking region relative to the digital document, the re-position and re-size of the zoom window and the inking region occurs at least as an annotation of the digital document is entered in the inking region during an annotation event based at least in part on an amount of annotation information entered and displayed in the inking region, the size of the zoom window corresponds to the size of the inking region. 3. The system of claim 1 , wherein the inking region is generated in connection with animation that makes it appear the inking region grows out of the digital document. | 0.626667 |
8,126,698 | 9 | 15 | 9. A method for translating messages, the method comprising: storing, in a message storage unit, a first message, a second message, and a third message, wherein the same content is respectively described in the first message and the second message in a first language and a second language that are different from each other; generating a first syntactic tree that represents a hierarchical structure of words and phrases included in the first message and a second syntactic tree that represents a hierarchical structure of words and phrases included in the second message by an operation of a CPU, by reading the first and second messages from the message storage unit and parsing the first and second messages; determining by the operation of the CPU whether a representation of a phrase represented by a certain subtree included in the first syntactic tree matches a representation of a phrase represented by a subtree, corresponding to the certain subtree, in the second syntactic tree, and, on the condition that the representations match each other, determining that the phrase is a phrase that need not be translated; and outputting, in a process of generating a fourth message described in a fourth language by translating a third message described in a third language by the operation of the CPU, the phrase that need not be translated and is included in the third message, as represented in the third message, the phrase being put in the fourth message after the translation. | 9. A method for translating messages, the method comprising: storing, in a message storage unit, a first message, a second message, and a third message, wherein the same content is respectively described in the first message and the second message in a first language and a second language that are different from each other; generating a first syntactic tree that represents a hierarchical structure of words and phrases included in the first message and a second syntactic tree that represents a hierarchical structure of words and phrases included in the second message by an operation of a CPU, by reading the first and second messages from the message storage unit and parsing the first and second messages; determining by the operation of the CPU whether a representation of a phrase represented by a certain subtree included in the first syntactic tree matches a representation of a phrase represented by a subtree, corresponding to the certain subtree, in the second syntactic tree, and, on the condition that the representations match each other, determining that the phrase is a phrase that need not be translated; and outputting, in a process of generating a fourth message described in a fourth language by translating a third message described in a third language by the operation of the CPU, the phrase that need not be translated and is included in the third message, as represented in the third message, the phrase being put in the fourth message after the translation. 15. The method of claim 9 , wherein the storing step comprises storing a plurality of messages in which the same content is described in a plurality of languages that are different from each other; and further comprising selecting, as the third language, a language, to which the highest priority is assigned, from languages of messages stored in the message storage unit in an order of priorities in association with the fourth language, and generates the fourth message described in the fourth language by translating the third message described in the third language. | 0.78294 |
8,494,900 | 15 | 16 | 15. The computer-implemented method of claim 12 further comprising: determining, with the computer system, a measure of confidence of ad scores for the document set; and adjusting, with the computer system, the document set score using the determined measure of confidence to generate a new document set score. | 15. The computer-implemented method of claim 12 further comprising: determining, with the computer system, a measure of confidence of ad scores for the document set; and adjusting, with the computer system, the document set score using the determined measure of confidence to generate a new document set score. 16. The computer-implemented method of claim 15 wherein the determined measure of confidence of ad scores is a function of a standard deviation of the ad scores for the document set. | 0.5 |
9,798,785 | 13 | 17 | 13. The apparatus of claim 9 , wherein the information regarding application or non-application of the search preference for the dynamic search according to the user's location comprises location information and time-zone information of the user. | 13. The apparatus of claim 9 , wherein the information regarding application or non-application of the search preference for the dynamic search according to the user's location comprises location information and time-zone information of the user. 17. The apparatus of claim 13 , wherein the server is further configured to: filter the arranged external search result using a prioritized preference, and forward the final search result including the filtered external search result to the requesting client. | 0.518587 |
7,813,929 | 16 | 18 | 16. A computer program product according to claim 13 , wherein the word substitution model derives probabilities by a log-linear combination of one or more feature functions. | 16. A computer program product according to claim 13 , wherein the word substitution model derives probabilities by a log-linear combination of one or more feature functions. 18. A computer program product according to claim 16 , wherein the feature functions are defined in terms of associations between a source word and a sequence of target words. | 0.5 |
9,858,919 | 6 | 7 | 6. A computer program product for adapting deep neural network acoustic models for automatic speech recognition, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: providing a deep neural network acoustic model; receiving audio data including one or more utterances of a speaker; extracting a plurality of speech recognition features from the one or more utterances of the speaker; creating a speaker identity vector for the speaker based on the speech recognition features extracted from the one or more utterances of the speaker; performing, by the processor, an automatic speech recognition using the speech recognition features extracted from the one or more utterances of the speaker and the speaker identity vector by executing the deep neural network acoustic model; and adapting the deep neural network acoustic model executing on a computer system the processor performing the automatic speech recognition using the speech recognition features extracted from the one or more utterances of the speaker and the speaker identity vector, wherein adapting the deep neural network acoustic model further comprises concatenating the speaker identity vector to each of the speech recognition features extracted from the one or more utterances of the speakers to form an input to the deep neural network acoustic model. | 6. A computer program product for adapting deep neural network acoustic models for automatic speech recognition, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: providing a deep neural network acoustic model; receiving audio data including one or more utterances of a speaker; extracting a plurality of speech recognition features from the one or more utterances of the speaker; creating a speaker identity vector for the speaker based on the speech recognition features extracted from the one or more utterances of the speaker; performing, by the processor, an automatic speech recognition using the speech recognition features extracted from the one or more utterances of the speaker and the speaker identity vector by executing the deep neural network acoustic model; and adapting the deep neural network acoustic model executing on a computer system the processor performing the automatic speech recognition using the speech recognition features extracted from the one or more utterances of the speaker and the speaker identity vector, wherein adapting the deep neural network acoustic model further comprises concatenating the speaker identity vector to each of the speech recognition features extracted from the one or more utterances of the speakers to form an input to the deep neural network acoustic model. 7. The computer program product of claim 6 , wherein the speaker identity vector encapsulates information about an identity of the speaker in a low-dimensional fixed-length representation. | 0.701587 |
9,130,651 | 1 | 30 | 1. An energy harvesting communication device configured with on chip signal booster apparatus; comprising: at least a communication apparatus; at least an antenna apparatus in association with an input and/or output device; at least a processor in communication with at least one of: said at least a communication apparatus; said at least an antenna apparatus; a charge platform in association with at least charging circuit; at least an interactive media in association with at least an interactive interface; an output device; and at least a sensor apparatus embedded in silicon substrate and etched and/or fused in nano-fiber and/or microfiber material, said at least a sensor apparatus in association with said at least a communication apparatus to provide at least one of an effective energy harvesting medium, communication clarity, communication medium, detection selectivity medium, and detection platform. | 1. An energy harvesting communication device configured with on chip signal booster apparatus; comprising: at least a communication apparatus; at least an antenna apparatus in association with an input and/or output device; at least a processor in communication with at least one of: said at least a communication apparatus; said at least an antenna apparatus; a charge platform in association with at least charging circuit; at least an interactive media in association with at least an interactive interface; an output device; and at least a sensor apparatus embedded in silicon substrate and etched and/or fused in nano-fiber and/or microfiber material, said at least a sensor apparatus in association with said at least a communication apparatus to provide at least one of an effective energy harvesting medium, communication clarity, communication medium, detection selectivity medium, and detection platform. 30. The energy harvesting communication device of claim 1 , wherein said detection platform further comprises at least a nanotechnology application; wherein the nanotechnology further comprises at least one of: an energy platform; an intra-chip multiple antenna network; a CMOS antenna configured with at least an opened end and at least a shorted end; CMOS multiple antennas on chip; sensor network; mobile network management application. | 0.876824 |
8,924,215 | 1 | 8 | 1. A method comprising: identifying, via a processor, a plurality of dialects within a speech utterance, for each dialect in the plurality of dialects, selecting a corresponding dialect grammar, to yield a plurality of dialect grammars; blending the plurality of dialect grammars, to yield a blended dialect grammar; and recognizing the speech utterance using the blended dialect grammar. | 1. A method comprising: identifying, via a processor, a plurality of dialects within a speech utterance, for each dialect in the plurality of dialects, selecting a corresponding dialect grammar, to yield a plurality of dialect grammars; blending the plurality of dialect grammars, to yield a blended dialect grammar; and recognizing the speech utterance using the blended dialect grammar. 8. The method of claim 1 , wherein the plurality of dialect grammars are domain specific. | 0.830153 |
8,825,613 | 11 | 14 | 11. A method comprising: receiving a first management pack at a database, the first management pack defining a structure of the first management pack and at least one second management pack; and storing the first management pack at the database in an instance space described by the first management pack. | 11. A method comprising: receiving a first management pack at a database, the first management pack defining a structure of the first management pack and at least one second management pack; and storing the first management pack at the database in an instance space described by the first management pack. 14. The method of claim 11 , further comprising: storing an instance of an entity that is defined by a management pack that is included in the at least one second management pack at the database in the instance space described by the first management pack. | 0.5 |
8,656,348 | 1 | 10 | 1. A computer implemented method of executing computations representative of a spreadsheet, the method comprising: receiving, by a processor, a request to load data representative of spreadsheet data; instantiating, by the processor, in response to the received load request, at least one instance of a data structure representative of each of at least one cell from the spreadsheet data, the data structure having been generated from information extracted from the spreadsheet data and transformed into a representation of the spreadsheet data, each of the at least one instance of the data structure representative of each of the at least one cell from the spreadsheet data having a value associated therewith, the value comprising one of a literal value or a computed value; receiving, by the processor, a request for a result representative of the result of a cell from the spreadsheet data; locating, by the processor, in response to the result request, the instance of the data structure representative of the cell from the spreadsheet data and the value associated therewith; and wherein, if the located value comprises a literal value, returning, by the processor, the located value in response to the result request; and further wherein, if the located value comprises a computed value, computing, by the processor, any values on which the located value necessarily depends, if necessary, prior to computing the located value based thereon and then returning, by the processor, the computed located value in response to the result request. | 1. A computer implemented method of executing computations representative of a spreadsheet, the method comprising: receiving, by a processor, a request to load data representative of spreadsheet data; instantiating, by the processor, in response to the received load request, at least one instance of a data structure representative of each of at least one cell from the spreadsheet data, the data structure having been generated from information extracted from the spreadsheet data and transformed into a representation of the spreadsheet data, each of the at least one instance of the data structure representative of each of the at least one cell from the spreadsheet data having a value associated therewith, the value comprising one of a literal value or a computed value; receiving, by the processor, a request for a result representative of the result of a cell from the spreadsheet data; locating, by the processor, in response to the result request, the instance of the data structure representative of the cell from the spreadsheet data and the value associated therewith; and wherein, if the located value comprises a literal value, returning, by the processor, the located value in response to the result request; and further wherein, if the located value comprises a computed value, computing, by the processor, any values on which the located value necessarily depends, if necessary, prior to computing the located value based thereon and then returning, by the processor, the computed located value in response to the result request. 10. The computer implemented method of claim 1 wherein the at least one cell from the spreadsheet data comprises a range of cells from the spreadsheet data. | 0.776504 |
8,463,715 | 24 | 29 | 24. The system of claim 1 , wherein to satisfy the job description, the resume includes, for each said at least one job requirement, either the required skill or experience-related phrase, or an alternative required skill or experience-related phrase, and wherein the term of experience for either the required skill or experience-related phrase, or the alternative required skill or experience-related phrase, is greater than or equal to the required term of experience. | 24. The system of claim 1 , wherein to satisfy the job description, the resume includes, for each said at least one job requirement, either the required skill or experience-related phrase, or an alternative required skill or experience-related phrase, and wherein the term of experience for either the required skill or experience-related phrase, or the alternative required skill or experience-related phrase, is greater than or equal to the required term of experience. 29. The system of claim 24 , wherein the required term of experience is rounded up to a unit of time. | 0.5 |
9,812,109 | 1 | 3 | 1. An apparatus for forming an audio template for determining semantic audio information, the apparatus comprising: a processor to: extract a plurality of audio features from audio, at least one of the plurality of audio features including at least one of a temporal feature, a spectral feature, a harmonic feature, or a rhythmic feature; determine a range for each of the plurality of audio features; and store a set of ranges of the plurality of audio features to compare against other audio features from subsequent audio to generate a tag for the set of ranges signifying semantic audio information for the subsequent audio, wherein the set of ranges includes more than one range and the tag is associated with an audio timbre range, a beat range, a loudness range and a spectral histogram range. | 1. An apparatus for forming an audio template for determining semantic audio information, the apparatus comprising: a processor to: extract a plurality of audio features from audio, at least one of the plurality of audio features including at least one of a temporal feature, a spectral feature, a harmonic feature, or a rhythmic feature; determine a range for each of the plurality of audio features; and store a set of ranges of the plurality of audio features to compare against other audio features from subsequent audio to generate a tag for the set of ranges signifying semantic audio information for the subsequent audio, wherein the set of ranges includes more than one range and the tag is associated with an audio timbre range, a beat range, a loudness range and a spectral histogram range. 3. The apparatus of claim 1 , wherein the harmonic feature includes at least one of a pitch, a tonality, a pitch class profile, harmonic changes, a main pitch class, an octave range of dominant pitch, a main tonal interval relation, or an overall pitch strength of at least some of the audio, the rhythmic feature includes at least one of a rhythmic structure, a beat period, a rhythmic fluctuation, or an average tempo for at least some of the audio, the spectral feature includes at least one of a spectral centroid, a spectral rolloff, a spectral flux, a spectral flatness measure, a spectral crest factor, Mel-frequency cepstral coefficients, Daubechies wavelet coefficients, a spectral dissonance, a spectral irregularity, or a spectral inharmonicity of at least some of the audio, and the temporal feature includes at least one of amplitude, power, or zero crossing of at least some of the audio. | 0.5 |
10,162,819 | 1 | 3 | 1. A computer-implemented method for translating text strings, the method comprising: receiving via a first namespace a source language text string from an application, wherein the first namespace is associated with a first subset of a set of target languages; determining that a translated text string that includes a translation in a first target language of the source language text string is not available for use by the application, wherein the first target language is included in the set of target languages but not included in the first subset; transmitting the source language text string to a translation service for translation; receiving the translated text string from the translation service; merging the translated text string into a second namespace, wherein the second namespace is associated with the set of target languages; and causing the translated text string to be available for use by the application via the second namespace. | 1. A computer-implemented method for translating text strings, the method comprising: receiving via a first namespace a source language text string from an application, wherein the first namespace is associated with a first subset of a set of target languages; determining that a translated text string that includes a translation in a first target language of the source language text string is not available for use by the application, wherein the first target language is included in the set of target languages but not included in the first subset; transmitting the source language text string to a translation service for translation; receiving the translated text string from the translation service; merging the translated text string into a second namespace, wherein the second namespace is associated with the set of target languages; and causing the translated text string to be available for use by the application via the second namespace. 3. The method of claim 1 , wherein determining that the translated text string is not available for use by the application comprises receiving the source language text string as part of a request to translate the source language text string into the first target language. | 0.5 |
8,607,311 | 8 | 9 | 8. A method of facilitating access to a resource, the method comprising: using a processor to perform acts comprising: abducing a first plurality of assertions from information that comprises an access request and a policy under which a guard controls access to the resource, a system that performs said abducing not having in possession said first plurality of assertions, said abducing being performed by acts comprising: receiving a first answer set and a second answer set, said first answer set comprising said first plurality of assertions, said second answer set comprising a second plurality of assertions, said first plurality of assertions and said second plurality of assertions each satisfying a condition that either said first plurality of assertions or said second plurality of assertions will, when presented to a guard of the resource, cause said guard to find that a query evaluates to true under a policy implemented by said guard; and determining that said first answer set is not subsumed by said second answer set; receiving, from a first principal, a template that specifies said first plurality of assertions and that further specifies a first token that satisfies a first one of said first plurality of assertions; determining from the template that a second one of said first plurality of assertions can be satisfied by a second token containing an assertion made by a second principal; retrieving or generating said second token; sending the guard of the resource said access request which includes a set of tokens which satisfy the template; and gaining access to the resource based on the request. | 8. A method of facilitating access to a resource, the method comprising: using a processor to perform acts comprising: abducing a first plurality of assertions from information that comprises an access request and a policy under which a guard controls access to the resource, a system that performs said abducing not having in possession said first plurality of assertions, said abducing being performed by acts comprising: receiving a first answer set and a second answer set, said first answer set comprising said first plurality of assertions, said second answer set comprising a second plurality of assertions, said first plurality of assertions and said second plurality of assertions each satisfying a condition that either said first plurality of assertions or said second plurality of assertions will, when presented to a guard of the resource, cause said guard to find that a query evaluates to true under a policy implemented by said guard; and determining that said first answer set is not subsumed by said second answer set; receiving, from a first principal, a template that specifies said first plurality of assertions and that further specifies a first token that satisfies a first one of said first plurality of assertions; determining from the template that a second one of said first plurality of assertions can be satisfied by a second token containing an assertion made by a second principal; retrieving or generating said second token; sending the guard of the resource said access request which includes a set of tokens which satisfy the template; and gaining access to the resource based on the request. 9. The method of claim 8 , wherein said assertion involves a variable, wherein said template specifies a constraint on said variable, and wherein said determining comprises determining a constant that, when substituted in place of said variable in said assertion, satisfies said constraint. | 0.5 |
8,051,096 | 6 | 8 | 6. A computer-implemented method, comprising: identifying a character string in an alphanumeric format having no token delineating breaks and comprising one or more tokens in the alphanumeric format from an internet-accessible article; and for each of the one or more tokens, parsing the identified character string into a first portion containing a first token and a second portion containing the remaining tokens; determining a first frequency with which the first token appears in the internet-accessible article, or a second frequency with which the first token appears at least once in a number of different internet-accessible articles; determining whether the determined first frequency with which the first token appears in the internet-accessible article exceeds a first threshold level, or whether the determined second frequency with which the first token appears at least once in the number of different internet-accessible articles exceeds a second threshold level; and storing the first token in a lexicon data storage based on the determination of whether the determined first frequency with which the first token appears in the internet-accessible article exceeds the first threshold level, or whether the determined second frequency with which the first token appears at least once in the number of different internet-accessible articles exceeds the second threshold level, wherein the lexicon data storage comprises an ontology associating at least one of a misspelling of the first token with a correct spelling, or an alternate spelling of the first token with a preferred spelling. | 6. A computer-implemented method, comprising: identifying a character string in an alphanumeric format having no token delineating breaks and comprising one or more tokens in the alphanumeric format from an internet-accessible article; and for each of the one or more tokens, parsing the identified character string into a first portion containing a first token and a second portion containing the remaining tokens; determining a first frequency with which the first token appears in the internet-accessible article, or a second frequency with which the first token appears at least once in a number of different internet-accessible articles; determining whether the determined first frequency with which the first token appears in the internet-accessible article exceeds a first threshold level, or whether the determined second frequency with which the first token appears at least once in the number of different internet-accessible articles exceeds a second threshold level; and storing the first token in a lexicon data storage based on the determination of whether the determined first frequency with which the first token appears in the internet-accessible article exceeds the first threshold level, or whether the determined second frequency with which the first token appears at least once in the number of different internet-accessible articles exceeds the second threshold level, wherein the lexicon data storage comprises an ontology associating at least one of a misspelling of the first token with a correct spelling, or an alternate spelling of the first token with a preferred spelling. 8. The computer-implemented method of claim 6 , wherein the first token comprises at least one of a misspelled word, a domain name, an abbreviation, or a proper name. | 0.580808 |
7,831,836 | 1 | 6 | 1. One or more computer-readable media usable to determine a password, the computer-readable media comprising instructions, executable by a processor, for: generating words, one after another, the words each having at least one character position, each word being generated by selecting characters, one after another, for each character position of the word from a character string for the respective character position, each character string: being stored in memory; comprising a plurality of permissible characters that may be used in the password, the order of the characters in the character string being individually selected for each character position of the word based on a frequency that each character occurs at the respective character position in words in a database, such that the characters in each character string are ordered from most frequent occurrence at the respective character position to least frequent occurrence at the respective character position and each character string begins with a permissible character most frequently used in the words in the database at the respective position and ends with a permissible character least frequently used in the words in the database at the respective position; and entering each generated word, one after another and based on an order in which the words are generated, until the password is determined. | 1. One or more computer-readable media usable to determine a password, the computer-readable media comprising instructions, executable by a processor, for: generating words, one after another, the words each having at least one character position, each word being generated by selecting characters, one after another, for each character position of the word from a character string for the respective character position, each character string: being stored in memory; comprising a plurality of permissible characters that may be used in the password, the order of the characters in the character string being individually selected for each character position of the word based on a frequency that each character occurs at the respective character position in words in a database, such that the characters in each character string are ordered from most frequent occurrence at the respective character position to least frequent occurrence at the respective character position and each character string begins with a permissible character most frequently used in the words in the database at the respective position and ends with a permissible character least frequently used in the words in the database at the respective position; and entering each generated word, one after another and based on an order in which the words are generated, until the password is determined. 6. The one or more computer-readable media of claim 1 , wherein the frequency that each of the characters occurs at each position is determined based on a grammatical rule. | 0.69395 |
8,392,444 | 2 | 4 | 2. A method according to claim 1 , wherein the user chooses a level of search by choosing the scope of the short-hand dictionaries to be searched. | 2. A method according to claim 1 , wherein the user chooses a level of search by choosing the scope of the short-hand dictionaries to be searched. 4. A method according to claim 2 , wherein a user chooses a level of the search by choosing a specific user, team, group, or category. | 0.5 |
8,041,701 | 1 | 10 | 1. A method for visually displaying search results comprising: receiving, by a processor from a first search engine, first search result data; determining, by the processor, search query information from said first search result data; transmitting said search query information to a second search engine; receiving, from said second search engine, second search result data identifying a plurality of webpages; determining network address information for a webpage of said plurality of webpages from the second search result data; retrieving, at a first location, said webpage using said network address information determined from the second search result data; creating, at said first location, a reduced size representation of said webpage as it would currently appear if presently displayed; and displaying, at said first location, said representation of said webpage from the second search result data and said first search result data. | 1. A method for visually displaying search results comprising: receiving, by a processor from a first search engine, first search result data; determining, by the processor, search query information from said first search result data; transmitting said search query information to a second search engine; receiving, from said second search engine, second search result data identifying a plurality of webpages; determining network address information for a webpage of said plurality of webpages from the second search result data; retrieving, at a first location, said webpage using said network address information determined from the second search result data; creating, at said first location, a reduced size representation of said webpage as it would currently appear if presently displayed; and displaying, at said first location, said representation of said webpage from the second search result data and said first search result data. 10. The method of claim 1 , wherein the determining network address information comprises: in response to a determination that a uniform resource locator for the webpage is a redirect link, displaying a root webpage as the reduced sized presentation of the webpage. | 0.578025 |
8,358,811 | 16 | 17 | 16. A method, comprising: receiving a subject name from a user; retrieving a first set of facial images from at least one named similarity group of facial images stored in the facial images database, wherein a name associated with said at least one similarity group substantially matches the subject name; determining a first facial recognition template for the first set; and retrieving a second set of facial images from one or more unnamed similarity groups in the facial images database, wherein the unnamed similarity groups have no associated name, and wherein facial recognition templates of the unnamed similarity groups substantially match the first facial recognition template. | 16. A method, comprising: receiving a subject name from a user; retrieving a first set of facial images from at least one named similarity group of facial images stored in the facial images database, wherein a name associated with said at least one similarity group substantially matches the subject name; determining a first facial recognition template for the first set; and retrieving a second set of facial images from one or more unnamed similarity groups in the facial images database, wherein the unnamed similarity groups have no associated name, and wherein facial recognition templates of the unnamed similarity groups substantially match the first facial recognition template. 17. The method of claim 16 comprising: searching one or more digital image collections wherein the searching includes automatic face recognition using at least one of said first or said second set of facial images. | 0.5 |
7,523,077 | 16 | 18 | 16. A computer system for managing a repository of knowledge entities, the computer system comprising: a knowledge repository tangibly embodied a computer readable medium and having stored therein knowledge entities described by a configuration template, the knowledge entities having a format such that they can be merged with a document template for display; and a knowledge management module tangibly embodied a computer readable medium and that merges at least one of the knowledge entities with the document template. | 16. A computer system for managing a repository of knowledge entities, the computer system comprising: a knowledge repository tangibly embodied a computer readable medium and having stored therein knowledge entities described by a configuration template, the knowledge entities having a format such that they can be merged with a document template for display; and a knowledge management module tangibly embodied a computer readable medium and that merges at least one of the knowledge entities with the document template. 18. The system of claim 16 , wherein the configuration template describes at least one connector that the knowledge management module uses in managing the knowledge entities. | 0.713816 |
7,650,286 | 135 | 168 | 135. A system for using a computer to identify a matching resume for a job description, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive the job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; store the job description; associate, for each said at least one job requirement, the required skill or experience-related phrase with at least one implying skill or experience-related phrase; store at least one searchable phrase for each said at least one job requirement, one of said at least one searchable phrase including the required skill or experience-related phrase, and said at least one searchable phrase including each said at least one implying skill or experience-related phrase; receive at least one resume; parse each said at least one resume to: locate at least one of said at least one searchable phrase in the resume; determine an experience range for each searchable phrase located in the resume by examining a use of each searchable phrase in the resume; and compute a term of experience for each searchable phrase located in the resume based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; store each said at least one resume; compute, for each said at least one resume, a term of experience for the required skill or experience-related phrase for each said at least one job requirement; and determine whether each said at least one resume is the matching resume that satisfies the job description. | 135. A system for using a computer to identify a matching resume for a job description, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive the job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; store the job description; associate, for each said at least one job requirement, the required skill or experience-related phrase with at least one implying skill or experience-related phrase; store at least one searchable phrase for each said at least one job requirement, one of said at least one searchable phrase including the required skill or experience-related phrase, and said at least one searchable phrase including each said at least one implying skill or experience-related phrase; receive at least one resume; parse each said at least one resume to: locate at least one of said at least one searchable phrase in the resume; determine an experience range for each searchable phrase located in the resume by examining a use of each searchable phrase in the resume; and compute a term of experience for each searchable phrase located in the resume based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; store each said at least one resume; compute, for each said at least one resume, a term of experience for the required skill or experience-related phrase for each said at least one job requirement; and determine whether each said at least one resume is the matching resume that satisfies the job description. 168. The system of claim 135 , wherein each said at least one job requirement further comprises a required time range for the required skill or experience-related phrase, and wherein the matching resume satisfies the job description when the experience range of the skill or experience-related phrase overlaps with the required time range. | 0.625828 |
9,473,465 | 1 | 3 | 1. A method comprising: parsing, by use of a processor, a secure message into lingual units, wherein each lingual unit is a phoneme; generating a validation nonce from the lingual units; generating at least one transform unit for each lingual unit by applying a lingual message transformation to each lingual unit as an encryption function; selecting one of the at least one transform unit for each lingual unit using a selection rule; generating an encrypted message from the selected transform units; parsing the encrypted message into transform units; generating a decrypted lingual unit for each transform unit by applying the lingual message transformation to each transform unit as a decryption function; regenerating at least one decrypted lingual unit from a selected transform unit with two or more corresponding lingual units with an alternate lingual unit if the validation nonce is not satisfied; in response to identifying a modification phrase in the communication data, generating a modification nonce from the communication data; selecting a transformation modification in response to the modification nonce and the lingual message transformation; and modifying one or more of the lingual message transformation and the selection rule in response to the transformation modification. | 1. A method comprising: parsing, by use of a processor, a secure message into lingual units, wherein each lingual unit is a phoneme; generating a validation nonce from the lingual units; generating at least one transform unit for each lingual unit by applying a lingual message transformation to each lingual unit as an encryption function; selecting one of the at least one transform unit for each lingual unit using a selection rule; generating an encrypted message from the selected transform units; parsing the encrypted message into transform units; generating a decrypted lingual unit for each transform unit by applying the lingual message transformation to each transform unit as a decryption function; regenerating at least one decrypted lingual unit from a selected transform unit with two or more corresponding lingual units with an alternate lingual unit if the validation nonce is not satisfied; in response to identifying a modification phrase in the communication data, generating a modification nonce from the communication data; selecting a transformation modification in response to the modification nonce and the lingual message transformation; and modifying one or more of the lingual message transformation and the selection rule in response to the transformation modification. 3. The method of claim 1 , the method further comprising modifying the lingual message transformation in response to communication data exchanged with a node. | 0.674897 |
8,190,628 | 12 | 19 | 12. A system comprising: one or more computers operable to perform operations including: identifying a plurality of phrase candidates from a plurality of text string entries in a corpus; for each phrase candidate of the plurality of phrase candidates: identifying a plurality of left contexts and a plurality of right contexts for the phrase candidate, each left context of the plurality of left contexts being a nearest unique feature to the left of the phrase candidate in each respective text string entry and each right context of the plurality of right contexts being a nearest unique feature to the right of the phrase candidate in each respective text string entry, and calculating both a left context vector including a respective score for each left context feature and a right context vector including a respective score for each right context feature of the phrase candidate; and determining a similarity between one or more pairs of phrase candidates of the plurality of phrase candidates using the respective left and right context vectors for each phrase candidate of each pair, wherein determining a similarity between a pair of phrase candidates includes: calculating a first similarity between the respective left context vectors of the pair of phrase candidates; calculating a second similarity between the respective right context vectors of the pair of phrase candidates; and calculating the similarity between the pair of phrase candidates using the first similarity and the second similarity. | 12. A system comprising: one or more computers operable to perform operations including: identifying a plurality of phrase candidates from a plurality of text string entries in a corpus; for each phrase candidate of the plurality of phrase candidates: identifying a plurality of left contexts and a plurality of right contexts for the phrase candidate, each left context of the plurality of left contexts being a nearest unique feature to the left of the phrase candidate in each respective text string entry and each right context of the plurality of right contexts being a nearest unique feature to the right of the phrase candidate in each respective text string entry, and calculating both a left context vector including a respective score for each left context feature and a right context vector including a respective score for each right context feature of the phrase candidate; and determining a similarity between one or more pairs of phrase candidates of the plurality of phrase candidates using the respective left and right context vectors for each phrase candidate of each pair, wherein determining a similarity between a pair of phrase candidates includes: calculating a first similarity between the respective left context vectors of the pair of phrase candidates; calculating a second similarity between the respective right context vectors of the pair of phrase candidates; and calculating the similarity between the pair of phrase candidates using the first similarity and the second similarity. 19. The system of claim 12 , further comprising: identifying good phrases including: identifying seed good phrases; and determining phrase candidates similar to seed good phrases as good phrases. | 0.648014 |
7,562,069 | 18 | 19 | 18. A machine-accessible medium that when accessed, results in a machine performing operations for resolving a query, comprising: maintaining, in electronic storage, a query ontology that includes one or more query categories and one or more queries associated with each of the one or more categories; receiving a query from a user, the received query including a first portion and a second portion that is different than the first portion; in response to receiving the query, accessing, from the electronic storage, one or more queries included within the query ontology; comparing the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a first group of multiple categories that are associated with a query that matches the first portion of the received query; comparing the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a second group of multiple categories that are associated with a query that matches the second portion of the received query, the second group of multiple categories being different than the first group of multiple categories; comparing the second group of multiple categories with the first group of multiple categories; based on the comparison of the second group of multiple categories with the first group of multiple categories, identifying a category that is included in the second group of multiple categories identified for the second portion of the received query and the first group of multiple categories identified for the first portion of the received query; performing a search process that uses the identified category in identifying search results responsive to the received query, the search process comprising: accessing, from the electronic storage, a subset of one or more query terms included within the query ontology and associated with the identified category; configuring the received query to include the accessed subset of one or more query terms associated with the identified category, the configured query being different than the received query; submitting the configured query to a search engine; receiving, from the search engine, search results corresponding to the configured query; and storing, using a processor in electronic storage, the received search results corresponding to the configured query. | 18. A machine-accessible medium that when accessed, results in a machine performing operations for resolving a query, comprising: maintaining, in electronic storage, a query ontology that includes one or more query categories and one or more queries associated with each of the one or more categories; receiving a query from a user, the received query including a first portion and a second portion that is different than the first portion; in response to receiving the query, accessing, from the electronic storage, one or more queries included within the query ontology; comparing the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a first group of multiple categories that are associated with a query that matches the first portion of the received query; comparing the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a second group of multiple categories that are associated with a query that matches the second portion of the received query, the second group of multiple categories being different than the first group of multiple categories; comparing the second group of multiple categories with the first group of multiple categories; based on the comparison of the second group of multiple categories with the first group of multiple categories, identifying a category that is included in the second group of multiple categories identified for the second portion of the received query and the first group of multiple categories identified for the first portion of the received query; performing a search process that uses the identified category in identifying search results responsive to the received query, the search process comprising: accessing, from the electronic storage, a subset of one or more query terms included within the query ontology and associated with the identified category; configuring the received query to include the accessed subset of one or more query terms associated with the identified category, the configured query being different than the received query; submitting the configured query to a search engine; receiving, from the search engine, search results corresponding to the configured query; and storing, using a processor in electronic storage, the received search results corresponding to the configured query. 19. The machine-accessible medium of claim 18 wherein configuring the received query to include the accessed subset of one or more query terms associated with the identified category comprises formatting the received query into a canonical form of the received query for the identified category. | 0.696502 |
8,732,208 | 1 | 18 | 1. A method comprising, by one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; receiving from the first user an unstructured text query comprising one or more n-grams; identifying one or more of the second nodes, each of the identified second nodes corresponding to one or more of the n-grams; identifying one or more of the edges, each of the identified edges being connected to at least one of the identified second nodes, each of the identified edges corresponding to one or more of the n-grams; and generating one or more structured queries that each comprise references to one or more of the identified second nodes and one or more of the identified edges. | 1. A method comprising, by one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; receiving from the first user an unstructured text query comprising one or more n-grams; identifying one or more of the second nodes, each of the identified second nodes corresponding to one or more of the n-grams; identifying one or more of the edges, each of the identified edges being connected to at least one of the identified second nodes, each of the identified edges corresponding to one or more of the n-grams; and generating one or more structured queries that each comprise references to one or more of the identified second nodes and one or more of the identified edges. 18. The method of claim 1 , further comprising sending one or more of the structured queries for presentation to the first user. | 0.780822 |
7,647,580 | 1 | 5 | 1. A computer-implemented system that facilitates null-support in programming languages, comprising: a computer processor for executing the following software components, at least one type associated with at least one programming language; and a type modifier to signal that the type is nullable, the type modifier enables a multi-element structure to be created in association with the type, the multi-element structure includes an original value, and a Boolean element for whether or not a variable is null, wherein the nullable type is associated with a nested type to construct a nested nullable type, and the nested nullable type is associated with a constraint for limiting operations of types, the constraint is associated with throwing an error in a static constructor of a nullable type <T> when T is nullable, and wherein the nested nullable type is associated with an arbitrary constraint for limiting operations of types; wherein the constraint is associated with performing a check in a constructor of a nullable type and propagating an underlying null, and inserting a unification code at points in a program where nested nullable values are constructed; wherein the type modifier creates a structure that combines a value of an underlying type with a Boolean null indicator, and wherein the nullable type is associated with an operator and is a nullable Boolean type that represents three values, true, false and null, such that the nullable Boolean type produces the three-valued type used for Boolean expressions in Structured Query Language (SQL). | 1. A computer-implemented system that facilitates null-support in programming languages, comprising: a computer processor for executing the following software components, at least one type associated with at least one programming language; and a type modifier to signal that the type is nullable, the type modifier enables a multi-element structure to be created in association with the type, the multi-element structure includes an original value, and a Boolean element for whether or not a variable is null, wherein the nullable type is associated with a nested type to construct a nested nullable type, and the nested nullable type is associated with a constraint for limiting operations of types, the constraint is associated with throwing an error in a static constructor of a nullable type <T> when T is nullable, and wherein the nested nullable type is associated with an arbitrary constraint for limiting operations of types; wherein the constraint is associated with performing a check in a constructor of a nullable type and propagating an underlying null, and inserting a unification code at points in a program where nested nullable values are constructed; wherein the type modifier creates a structure that combines a value of an underlying type with a Boolean null indicator, and wherein the nullable type is associated with an operator and is a nullable Boolean type that represents three values, true, false and null, such that the nullable Boolean type produces the three-valued type used for Boolean expressions in Structured Query Language (SQL). 5. The system of claim 1 , further comprising at least one instance of a nullable type having two public properties: HasValue, of type bool, and Value, of the nullable type's underlying type, wherein HasValue is true for a non-null instance and false for a null instance. | 0.5 |
8,826,125 | 1 | 4 | 1. A method for presenting articles to a user on a news reader system, the method comprising: creating a profile for the user; receiving an article from a news provider, wherein the article is stored on a non-transitory computer readable storage medium; analyzing, with a processor, characteristics associated with the article; designating with a processor, a primary article based on the characteristics associated with the article; comparing the characteristics of the article with a second set of characteristics associated with a second article that is currently designated as the primary article; determining whether the article is more optimal for presentation than the second article based on said comparison; designating the article as the primary article if it is determined that the article is more optimal for presentation than the second article; presenting the article to the user for review; receiving an input from the user to highlighting a portion of the article, wherein highlighting the portion of the article comprises selecting the portion of the article with a cursor or touch screen device; in response to highlighting the portion of the article, displaying a menu of selectable options; receiving a second input from the user associated with choosing one of the selectable options; associating the selected portion of the article with the profile created for the user; and in response to a request to view the user's profile, displaying the selected portion of the article along with other content associated with the user's interaction with the news reader system. | 1. A method for presenting articles to a user on a news reader system, the method comprising: creating a profile for the user; receiving an article from a news provider, wherein the article is stored on a non-transitory computer readable storage medium; analyzing, with a processor, characteristics associated with the article; designating with a processor, a primary article based on the characteristics associated with the article; comparing the characteristics of the article with a second set of characteristics associated with a second article that is currently designated as the primary article; determining whether the article is more optimal for presentation than the second article based on said comparison; designating the article as the primary article if it is determined that the article is more optimal for presentation than the second article; presenting the article to the user for review; receiving an input from the user to highlighting a portion of the article, wherein highlighting the portion of the article comprises selecting the portion of the article with a cursor or touch screen device; in response to highlighting the portion of the article, displaying a menu of selectable options; receiving a second input from the user associated with choosing one of the selectable options; associating the selected portion of the article with the profile created for the user; and in response to a request to view the user's profile, displaying the selected portion of the article along with other content associated with the user's interaction with the news reader system. 4. The method as recited in claim 1 , wherein analyzing the characteristics of the article includes determining whether the article includes multimedia items that support a description associated with the article. | 0.703343 |
6,044,347 | 10 | 11 | 10. The method of claim 1 wherein the processing and utilizing steps are implemented in a dialogue manager which serves as an interface between the user and an application running on the system and defining the set of frames, the method further including the steps of: converting the user input to a tree representation in the dialogue manager; and supplying the tree representation to an input filter which serves as an interface between the dialogue manager and the application, such that the input filter extracts information from the tree representation and places it in a format suitable for processing by the application. | 10. The method of claim 1 wherein the processing and utilizing steps are implemented in a dialogue manager which serves as an interface between the user and an application running on the system and defining the set of frames, the method further including the steps of: converting the user input to a tree representation in the dialogue manager; and supplying the tree representation to an input filter which serves as an interface between the dialogue manager and the application, such that the input filter extracts information from the tree representation and places it in a format suitable for processing by the application. 11. The method of claim 10 wherein the user input comprises a user request for information from the application, the method further including the steps of: executing the user request in the application to generate a response; passing the response through an output filter to place it in a format suitable for processing by the dialogue manager; clarifying the user request in the dialogue manager by directing at least one question to the user, if executing the user request in the application led to any ambiguity; and presenting the response to the user if executing the user request in the application did not lead to any ambiguity. | 0.5 |
7,707,220 | 1 | 5 | 1. A search method, comprising: A) causing a first information set to be generated, comprising a first plurality of items, wherein each item of the first plurality of items is associated with at least one characteristic; B) representing at least some of the first information set in a first presentation; C) receiving a first feedback based upon the first presentation from a user; D) applying an evolutionary algorithm to a plurality of characteristics associated with the first plurality of items to generate a first search query, wherein the evolutionary algorithm is based on the first feedback; E) causing the first search query to be executed to generate a second information set comprising a second plurality of items, wherein each item of the second plurality of items is associated with at least one characteristic; F) representing at least some of the second information set in a second presentation; G) in response to a user input, repeating step B and representing at least some of the first information set in the first presentation; H) receiving a second feedback based upon the second presentation from a user; I) applying an evolutionary algorithm to a plurality of characteristics associated with the second plurality of items to generate a second search query, wherein the evolutionary algorithm is based on the second feedback; J) causing the second search query to be executed to generate a third information set comprising a third plurality of items, wherein each item of the third plurality of items is associated with at least one characteristic; and K) representing at least some of the third information set in a third presentation; wherein at least one characteristic associated with each item is chosen from a group comprising: at least one descriptor made available by a search engine or web directory service; at least one tag; at least one keyword; at least one classification-oriented identifier; at least one categorization-oriented identifier; and at least one semantic web-oriented identifier; and wherein at least one characteristic associated with each item is not a word or phrase selected from text displayed as part of the item. | 1. A search method, comprising: A) causing a first information set to be generated, comprising a first plurality of items, wherein each item of the first plurality of items is associated with at least one characteristic; B) representing at least some of the first information set in a first presentation; C) receiving a first feedback based upon the first presentation from a user; D) applying an evolutionary algorithm to a plurality of characteristics associated with the first plurality of items to generate a first search query, wherein the evolutionary algorithm is based on the first feedback; E) causing the first search query to be executed to generate a second information set comprising a second plurality of items, wherein each item of the second plurality of items is associated with at least one characteristic; F) representing at least some of the second information set in a second presentation; G) in response to a user input, repeating step B and representing at least some of the first information set in the first presentation; H) receiving a second feedback based upon the second presentation from a user; I) applying an evolutionary algorithm to a plurality of characteristics associated with the second plurality of items to generate a second search query, wherein the evolutionary algorithm is based on the second feedback; J) causing the second search query to be executed to generate a third information set comprising a third plurality of items, wherein each item of the third plurality of items is associated with at least one characteristic; and K) representing at least some of the third information set in a third presentation; wherein at least one characteristic associated with each item is chosen from a group comprising: at least one descriptor made available by a search engine or web directory service; at least one tag; at least one keyword; at least one classification-oriented identifier; at least one categorization-oriented identifier; and at least one semantic web-oriented identifier; and wherein at least one characteristic associated with each item is not a word or phrase selected from text displayed as part of the item. 5. The method of claim 1 , wherein the first feedback comprises a rejection of at least one item of the first plurality of items. | 0.915354 |
9,239,830 | 1 | 6 | 1. A method for building a relationship hierarchy comprises: obtaining a plurality of relationships from training samples drawn from big data through open information extraction models; grouping the obtained relationships under generic relationships based on similarity; creating sub-groups of the grouped relationships; tagging the training sample with relationship tags to the occurrences of relationships in training samples; building relationship extraction models from the tagged training samples using one or more machine learning approaches; and providing new training samples from the big data; extracting new relationships using natural language processing based open information extraction models; reconciling the new relationships under at least one of the existing generic relationships or a new generic relationship; annotating training samples with the relationships extracted through the open information extraction models; create one or more new relationship extraction models; populating the relationship extraction models with new relationship extraction models that can successfully identify new relationships; and passing the text data through new relationship recognition models to identify new relationships from data using one or more machine Learning models; extract relationships from the big data using the relationship extraction models; building relationship recognition models adapted to identify different forms of generic relationships; resolving the relationships by grouping the similar relationships together and separating the relationships which are syntactically and semantically dissimilar; and reconciling the resolved relationships to build the relationship hierarchy, wherein the relationship hierarchy comprises groups and subgroups of relationships created based on generic relationship similarity based on a contextual aspect and a specialization aspect using a Language and Domain model. | 1. A method for building a relationship hierarchy comprises: obtaining a plurality of relationships from training samples drawn from big data through open information extraction models; grouping the obtained relationships under generic relationships based on similarity; creating sub-groups of the grouped relationships; tagging the training sample with relationship tags to the occurrences of relationships in training samples; building relationship extraction models from the tagged training samples using one or more machine learning approaches; and providing new training samples from the big data; extracting new relationships using natural language processing based open information extraction models; reconciling the new relationships under at least one of the existing generic relationships or a new generic relationship; annotating training samples with the relationships extracted through the open information extraction models; create one or more new relationship extraction models; populating the relationship extraction models with new relationship extraction models that can successfully identify new relationships; and passing the text data through new relationship recognition models to identify new relationships from data using one or more machine Learning models; extract relationships from the big data using the relationship extraction models; building relationship recognition models adapted to identify different forms of generic relationships; resolving the relationships by grouping the similar relationships together and separating the relationships which are syntactically and semantically dissimilar; and reconciling the resolved relationships to build the relationship hierarchy, wherein the relationship hierarchy comprises groups and subgroups of relationships created based on generic relationship similarity based on a contextual aspect and a specialization aspect using a Language and Domain model. 6. The method of claim 1 , wherein resolving the plurality of relationships comprises separating the relationships which are syntactically and semantically dissimilar, where the relationships are resolved by capturing specialization aspect of the relationships. | 0.509398 |
10,102,454 | 12 | 16 | 12. A computer program product comprising a computer readable storage medium for storing computer readable program code which, when executed, causes a computer: to utilize two or more classifiers to calculate, for an input image, probability scores for a plurality of classes based on visual information extracted from the input image and semantic relationships in a classification hierarchy, wherein each of the two or more classifiers is associated with a given one of two or more levels in the classification hierarchy with each level in the classification hierarchy comprising a subset of the plurality of classes; to classify the input image based on the calculated probability scores; to train the two or more classifiers to calculate probability scores for respective subset of the plurality of classes; and to perform label inference to refine classification probabilities in the two or more classifiers based on semantic relationships in the classification hierarchy; wherein training the two or more classifiers and performing label inference comprises at least one of: taking as input a graph structure having initial values for nodes corresponding to classification probabilities in the two or more classifier and outputting the graph structure with modified values for the nodes; utilizing a multi-task learning based loss function that jointly optimizes classifiers associated with each of the two or more levels in the classification hierarchy; and utilizing a random walk process that smooths classification probabilities over two or more classes in a same semantic path in the classification hierarchy. | 12. A computer program product comprising a computer readable storage medium for storing computer readable program code which, when executed, causes a computer: to utilize two or more classifiers to calculate, for an input image, probability scores for a plurality of classes based on visual information extracted from the input image and semantic relationships in a classification hierarchy, wherein each of the two or more classifiers is associated with a given one of two or more levels in the classification hierarchy with each level in the classification hierarchy comprising a subset of the plurality of classes; to classify the input image based on the calculated probability scores; to train the two or more classifiers to calculate probability scores for respective subset of the plurality of classes; and to perform label inference to refine classification probabilities in the two or more classifiers based on semantic relationships in the classification hierarchy; wherein training the two or more classifiers and performing label inference comprises at least one of: taking as input a graph structure having initial values for nodes corresponding to classification probabilities in the two or more classifier and outputting the graph structure with modified values for the nodes; utilizing a multi-task learning based loss function that jointly optimizes classifiers associated with each of the two or more levels in the classification hierarchy; and utilizing a random walk process that smooths classification probabilities over two or more classes in a same semantic path in the classification hierarchy. 16. The computer program product of claim 12 , wherein the classification hierarchy comprises a tree structure and performing label inference to refine the classification probabilities in the two or more classifiers comprises, for two or more leaf nodes having classification probabilities within a designated threshold from one another, adjusting the classification probabilities for the two or more leaf nodes based on classification probabilities for parent nodes in a higher level of the classification hierarchy relative to the two or more leaf nodes. | 0.58006 |
8,527,516 | 1 | 7 | 1. A computer-implemented method for identifying relationships between a plurality of digital text volumes in a corpus, the method comprising: comparing the plurality of digital text volumes in the corpus to produce volume similarity data describing similarities among pairs of digital text volumes; identifying a cluster of similar digital text volumes based on the volume similarity data; comparing pages of a pair of digital text volumes within the cluster to determine page similarity data indicating degrees of similarity between the compared pages; extracting signals from the volume similarity data and the page similarity data that describe a relationship between the pair of digital text volumes, the extracted signals including at least one of: a measure of linear page-to-page fit that models volume text uniformly distributed across pages of the pair of digital text volumes; and a measure of relative consecutive page correlation between pages of the pair of digital text volumes; classifying the relationship between the pair of digital text volumes based on the extracted signals; and storing classification data describing the relationship between the pair of digital text volumes. | 1. A computer-implemented method for identifying relationships between a plurality of digital text volumes in a corpus, the method comprising: comparing the plurality of digital text volumes in the corpus to produce volume similarity data describing similarities among pairs of digital text volumes; identifying a cluster of similar digital text volumes based on the volume similarity data; comparing pages of a pair of digital text volumes within the cluster to determine page similarity data indicating degrees of similarity between the compared pages; extracting signals from the volume similarity data and the page similarity data that describe a relationship between the pair of digital text volumes, the extracted signals including at least one of: a measure of linear page-to-page fit that models volume text uniformly distributed across pages of the pair of digital text volumes; and a measure of relative consecutive page correlation between pages of the pair of digital text volumes; classifying the relationship between the pair of digital text volumes based on the extracted signals; and storing classification data describing the relationship between the pair of digital text volumes. 7. The method of claim 1 , wherein the classifying the relationship between the pair of digital text volumes based on the extracted signals comprises: calculating a confidence level for each of a plurality of classes, the confidence level for a class indicating a likelihood of the relationship being described by that class; and assigning a class to the relationship between the pair of digital text volumes responsive to the calculated confidence level. | 0.736994 |
9,058,315 | 10 | 11 | 10. A computer system comprising: a processor; a memory; a user interface configured to receive input from a user; a tree generator configured to generate a parameter tree related to a current workflow, wherein the parameter tree includes a different node corresponding to each parameter included in a document of a plurality of documents associated with the current workflow, wherein each of the plurality of documents comprises one or more functions; a parameterization module configured to: modify a first value associated with a first node included in the parameter tree based on an input from the user interface through the user interface, wherein the first node corresponds to a first parameter included in a first document associated with the current workflow; wherein a second node included in the parameter tree corresponds to a second parameter included in a second document in the current workflow, and wherein the first node is associated with the second node; a workflow generator configured to generate a new workflow based on evaluating the second document by performing the one or more functions in the second document based on the first value associated with the first node to produce an evaluated second document in response to determining the second node is associated with the first node in the parameter tree. | 10. A computer system comprising: a processor; a memory; a user interface configured to receive input from a user; a tree generator configured to generate a parameter tree related to a current workflow, wherein the parameter tree includes a different node corresponding to each parameter included in a document of a plurality of documents associated with the current workflow, wherein each of the plurality of documents comprises one or more functions; a parameterization module configured to: modify a first value associated with a first node included in the parameter tree based on an input from the user interface through the user interface, wherein the first node corresponds to a first parameter included in a first document associated with the current workflow; wherein a second node included in the parameter tree corresponds to a second parameter included in a second document in the current workflow, and wherein the first node is associated with the second node; a workflow generator configured to generate a new workflow based on evaluating the second document by performing the one or more functions in the second document based on the first value associated with the first node to produce an evaluated second document in response to determining the second node is associated with the first node in the parameter tree. 11. The computer system of claim 10 , wherein the parameterization module is configured to modify a second value associated with the first parameter to equal the first value associated with the first node. | 0.712885 |
7,599,954 | 7 | 8 | 7. The method of claim 6 , further comprising displaying a filename pane containing a pathname of said user specified file. | 7. The method of claim 6 , further comprising displaying a filename pane containing a pathname of said user specified file. 8. The method of claim 7 , wherein all of said writing, said building, said receiving, said searching, said displaying at least one search result, said displaying a preview pane, and said displaying a filename pane are all executed from a singular customized File Open dialog box. | 0.5 |
9,483,453 | 16 | 17 | 16. A system for displaying clips of content and annotations comprising: an input device for receiving, within a current access session, a first annotation of active first content that is displayed within a displayed document, the document stored at a source location, wherein there exists a link to the active first content, the active first content is non-static, and the first annotation is displayed within the displayed document, wherein the first annotation is created in response to a first user input that annotates the active first content; the input device for receiving, within the current access session, a second annotation of second content that is displayed within the displayed document, wherein there exists a link to the second content, and the second annotation is displayed within the displayed document, wherein the second annotation is created in response to a second user input that annotates the second content; a processor for storing the first annotation together with a static image of the displayed active first content from the current access session; the processor for storing the link to the active first content, wherein the link to the active first content refers to the source location; the processor for storing the second annotation as displayed in the current access session together with an image of the displayed second content; the processor for storing the link to the second content, wherein the link to the second content refers to the source location; the processor for, responsive to a user request, combining the stored first annotation and the stored second annotation based on a criterion; the processor for rendering an image by retrieving a clip comprising the combination of the stored first annotation and static image of the active first content and the stored second annotation and the image of the second content; and a display displaying the rendered chip, wherein selection of said first annotation in said clip accesses the active first content via the stored link to the active first content. | 16. A system for displaying clips of content and annotations comprising: an input device for receiving, within a current access session, a first annotation of active first content that is displayed within a displayed document, the document stored at a source location, wherein there exists a link to the active first content, the active first content is non-static, and the first annotation is displayed within the displayed document, wherein the first annotation is created in response to a first user input that annotates the active first content; the input device for receiving, within the current access session, a second annotation of second content that is displayed within the displayed document, wherein there exists a link to the second content, and the second annotation is displayed within the displayed document, wherein the second annotation is created in response to a second user input that annotates the second content; a processor for storing the first annotation together with a static image of the displayed active first content from the current access session; the processor for storing the link to the active first content, wherein the link to the active first content refers to the source location; the processor for storing the second annotation as displayed in the current access session together with an image of the displayed second content; the processor for storing the link to the second content, wherein the link to the second content refers to the source location; the processor for, responsive to a user request, combining the stored first annotation and the stored second annotation based on a criterion; the processor for rendering an image by retrieving a clip comprising the combination of the stored first annotation and static image of the active first content and the stored second annotation and the image of the second content; and a display displaying the rendered chip, wherein selection of said first annotation in said clip accesses the active first content via the stored link to the active first content. 17. The system according to claim 16 , further comprising a storage storing said first annotation and an image of said active first content. | 0.716599 |
8,190,988 | 16 | 17 | 16. The computer-readable storage medium of claim 11 wherein the operation of renaming at least one named form field comprises: identifying one or more named form fields that are not unique across the selection of electronic form instances; renaming the identified non-unique named form fields resident in any of the selected electronic form instances to be unique across the selection of electronic form instances. | 16. The computer-readable storage medium of claim 11 wherein the operation of renaming at least one named form field comprises: identifying one or more named form fields that are not unique across the selection of electronic form instances; renaming the identified non-unique named form fields resident in any of the selected electronic form instances to be unique across the selection of electronic form instances. 17. The computer-readable storage medium of claim 16 wherein the operation of renaming one or more references to the named form field comprises: renaming all references to the identified non-unique named form fields in the at least one script in the at least one of the electronic form instances of the selection to match the renamed form fields. | 0.5 |
10,067,918 | 10 | 11 | 10. The system of claim 6 , wherein the plurality of computer instructions further cause the at least one computing device to at least designate the series of characters in the text block as the text unit in response to a rule. | 10. The system of claim 6 , wherein the plurality of computer instructions further cause the at least one computing device to at least designate the series of characters in the text block as the text unit in response to a rule. 11. The system of claim 10 , wherein the rule specifies designating the series of characters as the text unit in response to a presence of a specified character in the text block. | 0.5 |
9,299,010 | 17 | 18 | 17. The system of claim 16 , wherein the combining of the first class designation, the second class designation and the third class designation to generate an overall class designation comprises forming a weighted combination of the first class designation, the second class designation and the third class designation. | 17. The system of claim 16 , wherein the combining of the first class designation, the second class designation and the third class designation to generate an overall class designation comprises forming a weighted combination of the first class designation, the second class designation and the third class designation. 18. The system of claim 17 , wherein the forming a weighted combination of the first class designation, the second class designation and the third class designation comprises weighting the first class designation with a weight of 2, weighting the second class designation with a weight of 2, and weighting the third class designation with a weight of 1. | 0.5 |
8,127,336 | 1 | 10 | 1. A system for policy-based service management, comprising: a hardware device including a rules definition interface module configured to receive a plurality of rule definitions stored in a data storage, wherein a rule definition includes a condition containing a rule definition variable; a policy management interface module configured to allow a user to define a rule instance from a rule definition and to define a policy instance based on one or more defined rule instances, wherein the user defines the rule instance by associating the condition in the rule definition containing the rule definition variable with one or more values in a user-defined value set; and a policy decision interface module configured to evaluate the policy instance upon request, for access to a network or a network resource by a subscriber device, wherein the policy decision interface is configured to retrieve one or more rule instances associated with the policy instance and to substitute one or more values in the user-defined value set associated with each variable in the rule instance in real-time when the rule instance is being evaluated by the policy decision interface module. | 1. A system for policy-based service management, comprising: a hardware device including a rules definition interface module configured to receive a plurality of rule definitions stored in a data storage, wherein a rule definition includes a condition containing a rule definition variable; a policy management interface module configured to allow a user to define a rule instance from a rule definition and to define a policy instance based on one or more defined rule instances, wherein the user defines the rule instance by associating the condition in the rule definition containing the rule definition variable with one or more values in a user-defined value set; and a policy decision interface module configured to evaluate the policy instance upon request, for access to a network or a network resource by a subscriber device, wherein the policy decision interface is configured to retrieve one or more rule instances associated with the policy instance and to substitute one or more values in the user-defined value set associated with each variable in the rule instance in real-time when the rule instance is being evaluated by the policy decision interface module. 10. The system of claim 1 , wherein the policy management interface comprises: a graphical user interface including an inclusion rule definition portion and an exclusion rule definition portion. | 0.5 |
8,131,728 | 7 | 10 | 7. The computer program product of claim 6 , wherein generating an index of nodes each node corresponding to a clause in the markup language document, comprises: computer usable program code for reading small chunks of the markup language document into a rolling buffer; computer usable program code for expression matching on the small chunks to identify individual clauses; and, computer usable program code for adding a node to the index with both an identifier for the individual clause and a position in the markup language document of the individual clause responsive to identifying an individual clause in the rolling buffer. | 7. The computer program product of claim 6 , wherein generating an index of nodes each node corresponding to a clause in the markup language document, comprises: computer usable program code for reading small chunks of the markup language document into a rolling buffer; computer usable program code for expression matching on the small chunks to identify individual clauses; and, computer usable program code for adding a node to the index with both an identifier for the individual clause and a position in the markup language document of the individual clause responsive to identifying an individual clause in the rolling buffer. 10. The computer program product of claim 7 , further comprising computer usable program code for performing the reading, expression matching and adding concurrently in separate threads of execution for different portions of the markup language document. | 0.728632 |
9,336,256 | 1 | 5 | 1. A database network router apparatus for data tokenization, the apparatus comprising: one or more processors; and one or more memories operatively coupled to at least one of the one or more processors and having instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: receive a request directed to a tokenized database, wherein the tokenized database contains one or more tokenized data values and wherein the request does not include any tokenized data values; apply one or more rules to the request; rewrite the request based on at least one of the one or more rules, wherein the rewritten request is configured to cause one or more non-tokenized data values specified in the request to be tokenized by a software agent resident on the tokenized database when data is added to the tokenized database as a result of the request and wherein the rewritten request is configured to cause the tokenized database to return non-tokenized data values when data is received from the tokenized database as a result of the request; and transmit the rewritten request to the tokenized database. | 1. A database network router apparatus for data tokenization, the apparatus comprising: one or more processors; and one or more memories operatively coupled to at least one of the one or more processors and having instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: receive a request directed to a tokenized database, wherein the tokenized database contains one or more tokenized data values and wherein the request does not include any tokenized data values; apply one or more rules to the request; rewrite the request based on at least one of the one or more rules, wherein the rewritten request is configured to cause one or more non-tokenized data values specified in the request to be tokenized by a software agent resident on the tokenized database when data is added to the tokenized database as a result of the request and wherein the rewritten request is configured to cause the tokenized database to return non-tokenized data values when data is received from the tokenized database as a result of the request; and transmit the rewritten request to the tokenized database. 5. The database network router apparatus of claim 1 , wherein applying one or more rules and rewriting the request comprises: selecting a filter terms rule when the request includes one or more filter data values, the one or more filter data values limiting the request to a subset of records related to the one or more filter data values; and rewriting the request to insert a tokenize command into the request, the tokenize command signaling to a software agent resident on the tokenized database to tokenize the one or more filter data values prior to the execution of the request on the tokenized database. | 0.664466 |
7,480,783 | 1 | 5 | 1. A method of loading a sequence of unaligned words starting from a first unaligned word address in a memory, said unaligned words comprising a plurality of indexed portions crossing a plurality of word boundaries, the method comprising: loading a first aligned word by executing a load instruction, said first aligned word commencing at a first aligned word address rounded from said first unaligned word address; identifying an index representing the location of the first unaligned word address relative to the first aligned word address; loading a second aligned word commencing at a second aligned word address rounded from a second unaligned word address; combining indexed portions of the first and second aligned words using the identified index to construct a first unaligned word; loading at least one subsequent third aligned word commencing at a third aligned word address from a subsequent third unaligned word address plus a second offset; and combining indexed portions of the subsequent third aligned word and the second aligned word to construct a subsequent second unaligned word. | 1. A method of loading a sequence of unaligned words starting from a first unaligned word address in a memory, said unaligned words comprising a plurality of indexed portions crossing a plurality of word boundaries, the method comprising: loading a first aligned word by executing a load instruction, said first aligned word commencing at a first aligned word address rounded from said first unaligned word address; identifying an index representing the location of the first unaligned word address relative to the first aligned word address; loading a second aligned word commencing at a second aligned word address rounded from a second unaligned word address; combining indexed portions of the first and second aligned words using the identified index to construct a first unaligned word; loading at least one subsequent third aligned word commencing at a third aligned word address from a subsequent third unaligned word address plus a second offset; and combining indexed portions of the subsequent third aligned word and the second aligned word to construct a subsequent second unaligned word. 5. A method according to claim 1 , wherein the index is a multibit index. | 0.861217 |
8,676,853 | 14 | 24 | 14. A system for accessing software, comprising: a library of existing software profiles and associated existing software components, each existing software profile including a set of attributes associated with an existing software component, and each existing software profile created from a semantic analysis of the corresponding existing software component, the semantic analysis based at least in part on a software classification system, and wherein the set of attributes included in each of the existing software profiles is according to at least a first software taxonomy; at least one processor; a search engine executable on the at least one processor to: create a profile for desired software, the desired software profile defining a conceptualized software component and comprising a set of search criteria associated with the library of existing software profiles, wherein the search criteria include attributes according to a second software taxonomy different from the at least first software taxonomy; search the existing software profiles of said library to identify one or more existing software profiles similar to the desired software profile; and identify one or more existing software profiles as a result of said search, each of the one or more identified existing software profiles associated with a corresponding existing software component; and an interface to accept the desired software profile and to output one or more existing software components associated with the one or more identified existing software profiles. | 14. A system for accessing software, comprising: a library of existing software profiles and associated existing software components, each existing software profile including a set of attributes associated with an existing software component, and each existing software profile created from a semantic analysis of the corresponding existing software component, the semantic analysis based at least in part on a software classification system, and wherein the set of attributes included in each of the existing software profiles is according to at least a first software taxonomy; at least one processor; a search engine executable on the at least one processor to: create a profile for desired software, the desired software profile defining a conceptualized software component and comprising a set of search criteria associated with the library of existing software profiles, wherein the search criteria include attributes according to a second software taxonomy different from the at least first software taxonomy; search the existing software profiles of said library to identify one or more existing software profiles similar to the desired software profile; and identify one or more existing software profiles as a result of said search, each of the one or more identified existing software profiles associated with a corresponding existing software component; and an interface to accept the desired software profile and to output one or more existing software components associated with the one or more identified existing software profiles. 24. The system of claim 14 , wherein each of the desired and existing software profiles includes attributes corresponding to categories of a software taxonomy, wherein the categories are arranged in a hierarchical structure, wherein the categories of the desired software profile are according to the second software taxonomy, and wherein the categories of the existing software profiles are according to the at least first software taxonomy. | 0.501129 |
9,996,583 | 7 | 10 | 7. A computer-implemented method comprising: receiving an original recursive expression that defines tuples belonging to an output relation, wherein the original recursive expression has a recursive aggregation construct, the recursive aggregation construct having a range and a recursive term; receiving an original recursive expression that defines tuples belonging to an output relation, wherein the original recursive expression has a recursive aggregation construct, the recursive aggregation construct having a range and a recursive term; generating an initial delta expression from the original recursive expression; generating a final delta expression including repeatedly applying one or more differential rules to the initial delta expression, including applying an aggregates delta rule to generate a conjunction of: (i) an existential term having a subterm that is a conjunction of the range and a delta term that is the recursive term of the aggregation construct, and (ii) a gamma term having a subterm that is the aggregation construct; evaluating the original recursive expression on an initial condition to generate one or more tuples; computing an initial delta relation as a difference between the one or more tuples and the initial condition; and until the final delta expression generates no new tuples, performing operations comprising: evaluating the existential term to generate tuples related by the range and tuples in the delta relation, evaluating the aggregation construct using tuples generated by the existential term as the range of the aggregation construct, and updating the output relation including adding to the output relation any tuples newly generated by evaluating the final delta expression. | 7. A computer-implemented method comprising: receiving an original recursive expression that defines tuples belonging to an output relation, wherein the original recursive expression has a recursive aggregation construct, the recursive aggregation construct having a range and a recursive term; receiving an original recursive expression that defines tuples belonging to an output relation, wherein the original recursive expression has a recursive aggregation construct, the recursive aggregation construct having a range and a recursive term; generating an initial delta expression from the original recursive expression; generating a final delta expression including repeatedly applying one or more differential rules to the initial delta expression, including applying an aggregates delta rule to generate a conjunction of: (i) an existential term having a subterm that is a conjunction of the range and a delta term that is the recursive term of the aggregation construct, and (ii) a gamma term having a subterm that is the aggregation construct; evaluating the original recursive expression on an initial condition to generate one or more tuples; computing an initial delta relation as a difference between the one or more tuples and the initial condition; and until the final delta expression generates no new tuples, performing operations comprising: evaluating the existential term to generate tuples related by the range and tuples in the delta relation, evaluating the aggregation construct using tuples generated by the existential term as the range of the aggregation construct, and updating the output relation including adding to the output relation any tuples newly generated by evaluating the final delta expression. 10. The method of claim 7 , further comprising: applying an aggregates epsilon rule to the initial delta expression to generate an epsilon expression having a conjunction of: (i) an existential term having a subterm that is a conjunction of the range and an epsilon term having a subterm that is the recursive term of the aggregation construct, and (ii) a gamma term having a subterm that is the aggregation construct. | 0.5 |
7,898,394 | 1 | 6 | 1. A method of organizing information, the method comprising: providing for a knowledgebase; providing for a first set of tags configured to be applied to items in the knowledgebase; providing for a second set of tags configured to be applied to items in the knowledgebase; searching the knowledgebase based on at least one of the first set of tags and the second set of tags; and ranking result items in a search result favoring the result items tagged with terms for the first set of tags. | 1. A method of organizing information, the method comprising: providing for a knowledgebase; providing for a first set of tags configured to be applied to items in the knowledgebase; providing for a second set of tags configured to be applied to items in the knowledgebase; searching the knowledgebase based on at least one of the first set of tags and the second set of tags; and ranking result items in a search result favoring the result items tagged with terms for the first set of tags. 6. The method of claim 1 , further comprising: determining a status of an incoming item for the knowledgebase; and providing access only to the first set of users for tagging the incoming item in response to the status being associated with a certified status. | 0.5 |
9,235,626 | 1 | 2 | 1. A system comprising: at least one processor; and a memory that stores instructions that, when executed by the at least one processor, cause the system to perform operations of: obtaining a document that is responsive to a user query, determining an interest of the user based on stored data associated with the user, wherein the interest of the user is determined based on a search history associated with the user, and wherein the search history is limited to within a predetermined period of time from the user query, determining that a portion of the document relates to the interest of the user, generating a first snippet for the document based on the portion of the document that relates to the interest of the user, and providing the first snippet for the document as part of a result list. | 1. A system comprising: at least one processor; and a memory that stores instructions that, when executed by the at least one processor, cause the system to perform operations of: obtaining a document that is responsive to a user query, determining an interest of the user based on stored data associated with the user, wherein the interest of the user is determined based on a search history associated with the user, and wherein the search history is limited to within a predetermined period of time from the user query, determining that a portion of the document relates to the interest of the user, generating a first snippet for the document based on the portion of the document that relates to the interest of the user, and providing the first snippet for the document as part of a result list. 2. The system of claim 1 , the instructions causing the system to further perform the operations of: refining the generated first snippet for the document prior to providing the first snippet. | 0.724928 |
7,882,100 | 15 | 21 | 15. A system for optimization of a query requesting data from a database, the system comprising: a computer having a processor and memory; a search engine for generating a search space comprising only left deep nested loop join trees for returning data requested by the query and traversing the search space to select an optimal left deep nested loop join tree for execution of the query; a transform module for transforming the left deep nested loop join tree selected by the search engine and including one or more outer joins and/or one or more semi-joins into a semantically correct bushy tree structure; and a generator module for generating a query execution plan for returning data requested by the query based on the semantically correct bushy tree structure. | 15. A system for optimization of a query requesting data from a database, the system comprising: a computer having a processor and memory; a search engine for generating a search space comprising only left deep nested loop join trees for returning data requested by the query and traversing the search space to select an optimal left deep nested loop join tree for execution of the query; a transform module for transforming the left deep nested loop join tree selected by the search engine and including one or more outer joins and/or one or more semi-joins into a semantically correct bushy tree structure; and a generator module for generating a query execution plan for returning data requested by the query based on the semantically correct bushy tree structure. 21. The system of claim 15 , wherein the search engine generates subplans structured as left deep nested loop join subtrees for obtaining data requested by the query. | 0.632743 |
8,086,960 | 10 | 11 | 10. A method, comprising: receiving an input to a body of an electronic markup language document that is being displayed in a browser; and in response to said receiving: generating a comment based on or including the input; marking a body section of a data structure for the electronic document with a tag based on the input, wherein the body section includes content for the body of the electronic markup language document; storing the comment in a comment section of the data structure for the electronic document, wherein said storing comprises storing the input using another tag to identify the comment, wherein the comment section of the data structure is separate from the body section of the data structure; and displaying the body of the electronic markup language document and an action user interface element, wherein the action user interface element is useable to cause the browser to parse the tag and the another tag to determine where the input can be applied to the electronic markup language document. | 10. A method, comprising: receiving an input to a body of an electronic markup language document that is being displayed in a browser; and in response to said receiving: generating a comment based on or including the input; marking a body section of a data structure for the electronic document with a tag based on the input, wherein the body section includes content for the body of the electronic markup language document; storing the comment in a comment section of the data structure for the electronic document, wherein said storing comprises storing the input using another tag to identify the comment, wherein the comment section of the data structure is separate from the body section of the data structure; and displaying the body of the electronic markup language document and an action user interface element, wherein the action user interface element is useable to cause the browser to parse the tag and the another tag to determine where the input can be applied to the electronic markup language document. 11. The method of claim 10 , further comprising the browser parsing the tag and the another tag to determine how to modify the document using the input. | 0.58011 |
8,009,928 | 13 | 14 | 13. A system for detecting and recognizing text in an image, the system comprising: a text-detection module, the text-detection module configured to detect text regions in an image by filtering and segmenting the image and intersecting the filtered and segmented image with a mask created from a plurality of bounding boxes, each bounding box enclosing a connected component, each connected component including a plurality of pixels comprising the image and connected on the basis of a predetermined pixel intensity and predefined distance between the pixels to form an output image and to form at least one gray-level image chip; a chip-processing module, the chip-processing module configured to process the at least one gray-level image chip to form at least one binary chip; and an optical character-recognizer module, the optical character-recognizer module configured to: recognize the text in the at least one binary chip using an optical character-recognizer; separately and independently recognize the text in the output image using the optical character-recognizer; and logically combining the separately recognized text by taking the logical OR of the recognized text to form a single output producing detected text. | 13. A system for detecting and recognizing text in an image, the system comprising: a text-detection module, the text-detection module configured to detect text regions in an image by filtering and segmenting the image and intersecting the filtered and segmented image with a mask created from a plurality of bounding boxes, each bounding box enclosing a connected component, each connected component including a plurality of pixels comprising the image and connected on the basis of a predetermined pixel intensity and predefined distance between the pixels to form an output image and to form at least one gray-level image chip; a chip-processing module, the chip-processing module configured to process the at least one gray-level image chip to form at least one binary chip; and an optical character-recognizer module, the optical character-recognizer module configured to: recognize the text in the at least one binary chip using an optical character-recognizer; separately and independently recognize the text in the output image using the optical character-recognizer; and logically combining the separately recognized text by taking the logical OR of the recognized text to form a single output producing detected text. 14. The system of claim 13 , wherein the text-detection module comprises: a gray-level conversion module, the gray-level conversion module converting the image to a gray-level version of the image to form a gray-level image; a filtering and thresholding module, the filtering and thresholding module filtering and thresholding the gray-level image to emphasize bar-like and line-like regions which potentially correspond to the text, to form a first image; a line-removal module, the line-removal module removing long straight lines and rectangles from the first image to form a second image; a character-finding module, the character-finding module identifying potential text regions in the second image based on predefined character constraints to form a third image; a word-finding module, the word-finding module removing potential text regions from the third image which are not consistent with words to create a fourth image; and an output text-image-creation module, the output text-image-creation module creating the output image and the at least one gray-level image chip from the fourth image. | 0.5 |
7,516,442 | 1 | 16 | 1. A method for creating language-neutral and corresponding language-specific resource files for a component, the method comprising: obtaining a resource manifest file; retrieving a resource file by accessing the resource manifest file; creating a language-neutral file and a language-specific resource file for the retrieved resource file, the language-specific resource file having a plurality of language-specific resources, the language neutral file and the language-specific resource file being created by reading localizable resource information contained in the resource manifest file, the localizable resource information specifying locations of specific resources to be retrieved during runtime from the language-specific resource file, the locations of the specific resources being mapped to resource identifiers used by applications to identify the specific resources within the language-specific resource file, in the resource manifest file, the resource manifest file further specifying a type of resource to be retrieved, and indicating whether the resource is localizable; creating a checksum data; updating a field in the resource manifest file with the checksum data; and the language-neutral file and language-specific resource file being created by splitting localizable resources identified by the localizable resource information into neutral and localized files, and by creating a language-neutral image and a language-specific image of the retrieved resource file. | 1. A method for creating language-neutral and corresponding language-specific resource files for a component, the method comprising: obtaining a resource manifest file; retrieving a resource file by accessing the resource manifest file; creating a language-neutral file and a language-specific resource file for the retrieved resource file, the language-specific resource file having a plurality of language-specific resources, the language neutral file and the language-specific resource file being created by reading localizable resource information contained in the resource manifest file, the localizable resource information specifying locations of specific resources to be retrieved during runtime from the language-specific resource file, the locations of the specific resources being mapped to resource identifiers used by applications to identify the specific resources within the language-specific resource file, in the resource manifest file, the resource manifest file further specifying a type of resource to be retrieved, and indicating whether the resource is localizable; creating a checksum data; updating a field in the resource manifest file with the checksum data; and the language-neutral file and language-specific resource file being created by splitting localizable resources identified by the localizable resource information into neutral and localized files, and by creating a language-neutral image and a language-specific image of the retrieved resource file. 16. The method of claim 1 wherein the plurality of fields are in a schema that comprises an Extensible Markup Language (XML) based declarative file. | 0.886677 |
8,520,983 | 8 | 10 | 8. A non-transitory computer-readable storage medium encoded with executable computer program code for selectively recognizing text in an image, the computer program code comprising program code for: displaying the image on a touch sensitive display device; detecting an underline gesture associated with an area of the touch sensitive display device, the area of the touch sensitive display device associated with the underline gesture being vertical relative to an orientation of the image; identifying a text region in the image associated with the area of the touch sensitive display device, the text region comprising text displayed vertically relative to the orientation of the image; and recognizing the text in the text region using OCR technology. | 8. A non-transitory computer-readable storage medium encoded with executable computer program code for selectively recognizing text in an image, the computer program code comprising program code for: displaying the image on a touch sensitive display device; detecting an underline gesture associated with an area of the touch sensitive display device, the area of the touch sensitive display device associated with the underline gesture being vertical relative to an orientation of the image; identifying a text region in the image associated with the area of the touch sensitive display device, the text region comprising text displayed vertically relative to the orientation of the image; and recognizing the text in the text region using OCR technology. 10. The non-transitory computer-readable storage medium of claim 8 , wherein the computer program code further comprises program code for: cropping the image, the cropped image including the text region; wherein recognizing the text comprises: transmitting the cropped image to an OCR engine through a computer network; and receiving the text from the OCR engine through the computer network. | 0.666099 |
8,024,317 | 29 | 30 | 29. The non-transitory computer-readable storage medium of claim 23 wherein each entry on the context query bid database additionally includes a bid targeting context having targeting context criteria, wherein each entry of the plurality of entries in in the context query bid database is evaluated to determine if the user falls within the bid targeting context of the respective entry of the plurality of entries in the context query bid database. | 29. The non-transitory computer-readable storage medium of claim 23 wherein each entry on the context query bid database additionally includes a bid targeting context having targeting context criteria, wherein each entry of the plurality of entries in in the context query bid database is evaluated to determine if the user falls within the bid targeting context of the respective entry of the plurality of entries in the context query bid database. 30. The non-transitory computer-readable storage medium of claim 29 wherein for each entry of the plurality of entries in the context query bid database, profile data, spatial data, temporal data, social data and topical data available to the network relating to the user and the respective bid targeting context criteria in the respective entry are searched to determine if the user falls within the targeting context of the respective entry of the plurality of entries in the context query bid database. | 0.5 |
8,423,577 | 11 | 14 | 11. One or more non-transitory computer-readable media having computer-executable instructions embodied thereon for performing a method of performing an action in response to identifying information within a textual communication, the method including: providing a user interface that allows a user to generate a template that is associated with two or more types of information used to generate a calendar entry; storing the template in a data store configured for storing a plurality of templates; receiving the textual communication, wherein the textual communication is one of a text message and an email; identifying a plurality of descriptors, wherein a descriptor is a series of alphanumeric characters within a body of the textual communication; displaying the textual communication to a recipient with the plurality of descriptors displayed with an appearance that indicates the plurality of descriptors are selectable; receiving an indication that the recipient selected two or more descriptors; determining that the two or more descriptors correspond to the two or more types of information in the template; determining a time of travel between a default location and a physical location indicated by one of the two or more descriptors; generating directions from the default location to the physical location; generating a suggested calendar entry that includes the time of travel and the directions; and displaying, to the recipient, the suggested calendar entry based on the first selection and the second selection. | 11. One or more non-transitory computer-readable media having computer-executable instructions embodied thereon for performing a method of performing an action in response to identifying information within a textual communication, the method including: providing a user interface that allows a user to generate a template that is associated with two or more types of information used to generate a calendar entry; storing the template in a data store configured for storing a plurality of templates; receiving the textual communication, wherein the textual communication is one of a text message and an email; identifying a plurality of descriptors, wherein a descriptor is a series of alphanumeric characters within a body of the textual communication; displaying the textual communication to a recipient with the plurality of descriptors displayed with an appearance that indicates the plurality of descriptors are selectable; receiving an indication that the recipient selected two or more descriptors; determining that the two or more descriptors correspond to the two or more types of information in the template; determining a time of travel between a default location and a physical location indicated by one of the two or more descriptors; generating directions from the default location to the physical location; generating a suggested calendar entry that includes the time of travel and the directions; and displaying, to the recipient, the suggested calendar entry based on the first selection and the second selection. 14. The media of claim 11 , wherein the method further comprises displaying one or more alternate suggested actions to the recipient concurrently with the suggested calendar entry. | 0.689655 |
8,959,449 | 15 | 25 | 15. A non-transitory computer-readable medium comprising instructions stored thereon, which when executed by a computer, cause the computer to: use a first software module to access the web page content to retrieve address information for a second software module, the first software module to access hypertext markup language (HTML) web content including the address information and the HTML web content accessible to a web browser, wherein the second software module comprises a non-browser application; automatically identify a variable value signifying the address information associated with a hypertext element within a hypertext document for the web page; automatically extract the address information data; provide the extracted address information data as input data to the second software module; and request to display an overlaying icon corresponding to the second software module on a user interface, the second software module to access the address information. | 15. A non-transitory computer-readable medium comprising instructions stored thereon, which when executed by a computer, cause the computer to: use a first software module to access the web page content to retrieve address information for a second software module, the first software module to access hypertext markup language (HTML) web content including the address information and the HTML web content accessible to a web browser, wherein the second software module comprises a non-browser application; automatically identify a variable value signifying the address information associated with a hypertext element within a hypertext document for the web page; automatically extract the address information data; provide the extracted address information data as input data to the second software module; and request to display an overlaying icon corresponding to the second software module on a user interface, the second software module to access the address information. 25. The medium of claim 15 , wherein the computer is also to automatically locate the hypertext element in response to a request from the second software module to automatically identify the variable value. | 0.509524 |
6,167,398 | 7 | 9 | 7. A method of generating a language model, said method comprising: (i) providing a reference corpus; (ii) forming from said reference corpus a training portion and a development portion; (iii) generating initial values of respective weights corresponding to a plurality of analysis algorithms by processing the training portion in accordance with a predetermined algorithm; (iv) performing a comparison between the training portion and the development portion in accordance with a first of said analysis algorithms and producing an initial comparison result, said first analysis algorithm being arranged to generate and compare word-level n-gram frequency lists having n-grams from unigrams up to m-grams, where m is a predetermined integer, the word-level n-gram frequency list generated from the training portion constituting a language model; (v) performing information retrieval in accordance with steps (d) to (h) of the method of claim 1, using the above mentioned plurality of analysis algorithms, and using the training portion as the reference corpus; (vi) retrieving a document from the retained text store; (vii) modifying the training portion by combining it with the document retrieved from the retained text store; (viii) repeating step (iv) in respect of the modified training portion to produce a further comparison result; and (ix) modifying the weights in accordance with a weight modifying function of said initial and further comparison results. | 7. A method of generating a language model, said method comprising: (i) providing a reference corpus; (ii) forming from said reference corpus a training portion and a development portion; (iii) generating initial values of respective weights corresponding to a plurality of analysis algorithms by processing the training portion in accordance with a predetermined algorithm; (iv) performing a comparison between the training portion and the development portion in accordance with a first of said analysis algorithms and producing an initial comparison result, said first analysis algorithm being arranged to generate and compare word-level n-gram frequency lists having n-grams from unigrams up to m-grams, where m is a predetermined integer, the word-level n-gram frequency list generated from the training portion constituting a language model; (v) performing information retrieval in accordance with steps (d) to (h) of the method of claim 1, using the above mentioned plurality of analysis algorithms, and using the training portion as the reference corpus; (vi) retrieving a document from the retained text store; (vii) modifying the training portion by combining it with the document retrieved from the retained text store; (viii) repeating step (iv) in respect of the modified training portion to produce a further comparison result; and (ix) modifying the weights in accordance with a weight modifying function of said initial and further comparison results. 9. A method as in claim 7 wherein step (vi) comprises selecting the document for retrieval on the basis of the least degree of dissimilarity. | 0.804167 |
9,405,532 | 1 | 2 | 1. A multi-tenant data processing system, comprising: one or more business related data processing applications installed in the system and accessible by a plurality of tenants of the multi-tenant data processing system; a data storage element accessible by a plurality of tenants of the multitenant data processing system; a set of software development tools to enable a tenant to develop one or more of a new business related data processing application, an extension to one of the one or more business related data processing applications, a new user interface, an extension to an existing user interface, or content related to an application or user interface; a plurality of language segments in one or more languages stored in the data storage element; and a processor programmed with a set of instructions, wherein when executed by the processor the instructions cause the system to receive a request from a first tenant for a language segment in a specified language; determine if the request can be satisfied by a language segment contained in the data storage element; provide the language segment contained in the data storage element if the request can be satisfied; generate a request for translation services if the request cannot be satisfied by a language segment contained in the data storage element; transfer the request to a provider of the translation services; receive a response to the request from the provider of the translation services; process the received response to validate the contents of the response; provide the translated language segment to the first tenant; determine if the translated language segment is to be stored suitable in the data storage element based on a likelihood of interest for use of content expressed in the translated language for a similar purpose by other tenants of the plurality of tenants; store the translated language segment in the data storage element if the translated language segment meets a threshold for including in the data storage element; receive a request from a second tenant for a language segment in a specified language; and provide the translated language segment received in response to the request for translation services to the second tenant in response to the request from the second tenant. | 1. A multi-tenant data processing system, comprising: one or more business related data processing applications installed in the system and accessible by a plurality of tenants of the multi-tenant data processing system; a data storage element accessible by a plurality of tenants of the multitenant data processing system; a set of software development tools to enable a tenant to develop one or more of a new business related data processing application, an extension to one of the one or more business related data processing applications, a new user interface, an extension to an existing user interface, or content related to an application or user interface; a plurality of language segments in one or more languages stored in the data storage element; and a processor programmed with a set of instructions, wherein when executed by the processor the instructions cause the system to receive a request from a first tenant for a language segment in a specified language; determine if the request can be satisfied by a language segment contained in the data storage element; provide the language segment contained in the data storage element if the request can be satisfied; generate a request for translation services if the request cannot be satisfied by a language segment contained in the data storage element; transfer the request to a provider of the translation services; receive a response to the request from the provider of the translation services; process the received response to validate the contents of the response; provide the translated language segment to the first tenant; determine if the translated language segment is to be stored suitable in the data storage element based on a likelihood of interest for use of content expressed in the translated language for a similar purpose by other tenants of the plurality of tenants; store the translated language segment in the data storage element if the translated language segment meets a threshold for including in the data storage element; receive a request from a second tenant for a language segment in a specified language; and provide the translated language segment received in response to the request for translation services to the second tenant in response to the request from the second tenant. 2. The system of claim 1 , wherein the one or more business related data processing applications installed in the system include an Enterprise Resource Planning (ERP) or a Customer Relationship Management (CRM) application. | 0.630795 |
7,853,888 | 4 | 6 | 4. A non-transitory computer readable storage medium comprising executable instructions encoded thereon operable on a computerized device to perform processing comprising instructions for: generating a first thumbnail in response to selection of a paste destination in a first document, wherein the instructions for generating the first thumbnail include: instructions for generating a miniaturized view of a text input box and a text input box label, wherein the paste destination is positioned within the text input box, the paste destination comprising a location in the first document at which to insert document content selected from a second document, the first thumbnail comprising a miniaturized pictorial representation of (i) the paste destination in the first document and (ii) at least a portion of the first document surrounding the paste destination, the first document different than the second document; upon detecting selection of the document content from the second document, displaying the first thumbnail in conjunction with display of the second document; while the second document is currently displayed, inserting the selected document content into the paste destination in response to detecting selection of the first thumbnail; upon detecting selection of second document content from the second document, generating a second thumbnail, the second thumbnail comprising a pictorial representation of the second document content; while the first document is displayed, detecting selection of a paste location in the first document; upon receiving selection of a paste command, displaying the second thumbnail in conjunction with display of the first document; and upon detecting selection of the second thumbnail, inserting the second document content into to the paste location in the currently displayed first document. | 4. A non-transitory computer readable storage medium comprising executable instructions encoded thereon operable on a computerized device to perform processing comprising instructions for: generating a first thumbnail in response to selection of a paste destination in a first document, wherein the instructions for generating the first thumbnail include: instructions for generating a miniaturized view of a text input box and a text input box label, wherein the paste destination is positioned within the text input box, the paste destination comprising a location in the first document at which to insert document content selected from a second document, the first thumbnail comprising a miniaturized pictorial representation of (i) the paste destination in the first document and (ii) at least a portion of the first document surrounding the paste destination, the first document different than the second document; upon detecting selection of the document content from the second document, displaying the first thumbnail in conjunction with display of the second document; while the second document is currently displayed, inserting the selected document content into the paste destination in response to detecting selection of the first thumbnail; upon detecting selection of second document content from the second document, generating a second thumbnail, the second thumbnail comprising a pictorial representation of the second document content; while the first document is displayed, detecting selection of a paste location in the first document; upon receiving selection of a paste command, displaying the second thumbnail in conjunction with display of the first document; and upon detecting selection of the second thumbnail, inserting the second document content into to the paste location in the currently displayed first document. 6. The non-transitory computer readable storage medium of claim 4 , wherein the instructions for generating the first thumbnail include: instructions for generating a miniaturized view of a text input box and a text input box label currently placed in the first document, wherein the paste destination is positioned within the text input box; wherein the instructions for inserting the selected document content into the paste destination includes: instructions for inserting the selected document content into the text input box in the first document; and the computer-implemented method further comprises instructions for: upon detecting selection of second document content from the second document, generating a second thumbnail, the second thumbnail comprising a pictorial representation of the second document content; while the first document is displayed, detecting selection of a paste location in the first document; upon receiving selection of a paste command, displaying the second thumbnail in conjunction with display of the first document; and upon detecting selection of the second thumbnail, inserting the second document content into to the paste location in the currently displayed first document. | 0.5 |
8,312,157 | 12 | 13 | 12. A system for implicitly authenticating a user to access a controlled resource, the system comprising: a user access request receiver configured to receive a request, from a computer device, to access the controlled resource; a selection mechanism configured to select a user behavior model for the user, wherein the user behavior model is derived from historical context data of the user; a determination mechanism configured to determine recent contextual data of the user, wherein the recent contextual data are collected from one or more user devices without prompting the user to perform an action associated with authentication, and wherein the recent contextual data comprise a plurality of data streams which provide a basis for determining whether the user owns the computing device; a behavioral score grader configured to determine a user behavior score which indicates a likelihood that the user owns the computing device, wherein while determining the user behavior score the behavioral score grader is further configured to: observe a recent event that is associated with the user's computing device; calculate a quality measure for the recent event, and a weight associated with a type of the observation; determine that the observed recent event is consistent with the user behavior model; and adjust the user behavior score based on the quality measure and the weight; and an authentication information provision mechanism configured to provide the user behavior score to an access controller of the controlled resource, wherein the access controller is configured to facilitate access to the controlled resource for the user in response to the user behavior score exceeding a predetermined threshold value. | 12. A system for implicitly authenticating a user to access a controlled resource, the system comprising: a user access request receiver configured to receive a request, from a computer device, to access the controlled resource; a selection mechanism configured to select a user behavior model for the user, wherein the user behavior model is derived from historical context data of the user; a determination mechanism configured to determine recent contextual data of the user, wherein the recent contextual data are collected from one or more user devices without prompting the user to perform an action associated with authentication, and wherein the recent contextual data comprise a plurality of data streams which provide a basis for determining whether the user owns the computing device; a behavioral score grader configured to determine a user behavior score which indicates a likelihood that the user owns the computing device, wherein while determining the user behavior score the behavioral score grader is further configured to: observe a recent event that is associated with the user's computing device; calculate a quality measure for the recent event, and a weight associated with a type of the observation; determine that the observed recent event is consistent with the user behavior model; and adjust the user behavior score based on the quality measure and the weight; and an authentication information provision mechanism configured to provide the user behavior score to an access controller of the controlled resource, wherein the access controller is configured to facilitate access to the controlled resource for the user in response to the user behavior score exceeding a predetermined threshold value. 13. The system of claim 12 , further comprising: a contextual data collector configured to collect contextual data of the user periodically from the one or more user devices; and a user behavior modeler configured to update the user behavior model based on the collected contextual data of the user. | 0.735866 |
8,145,648 | 3 | 4 | 3. A computing device as recited in claim 2 further comprising: a metadata tagging sub-module for deriving the second plurality of keywords. | 3. A computing device as recited in claim 2 further comprising: a metadata tagging sub-module for deriving the second plurality of keywords. 4. A computing device as recited in claim 3 wherein the keyword list includes the first plurality of keywords and the second plurality of keywords. | 0.5 |
9,785,850 | 1 | 24 | 1. A method of communicating adjustments for relative positioning of a handheld electronic device with a camera, and a document, the method comprising: continuously receiving, at a processor of the handheld electronic device, a plurality of images of characters on the document; dynamically detecting edges of the characters while continuously receiving the images; thickening the edges of the characters; thresholding the edges of the characters; determining a contour of the characters; displaying, using a display of the handheld camera, the edges of the characters; determining an average font height of the characters using the edges of the characters; and determining relative positioning information about positioning of the handheld electronic device relative to the document. | 1. A method of communicating adjustments for relative positioning of a handheld electronic device with a camera, and a document, the method comprising: continuously receiving, at a processor of the handheld electronic device, a plurality of images of characters on the document; dynamically detecting edges of the characters while continuously receiving the images; thickening the edges of the characters; thresholding the edges of the characters; determining a contour of the characters; displaying, using a display of the handheld camera, the edges of the characters; determining an average font height of the characters using the edges of the characters; and determining relative positioning information about positioning of the handheld electronic device relative to the document. 24. The method of claim 1 , wherein approximating the contour points includes reducing the contour to a simple closed polygon. | 0.928328 |
8,484,557 | 1 | 7 | 1. A computer-implemented method of defining preflight rules for preflight profiles, the method comprising: defining a first parameter and a second parameter to be included in a preflight rule, the defining of the first parameter and the second parameter including defining a data type for each of the first parameter and the second parameter, the data type representing a format of the first or the second parameter; creating a control interface based on at least one of the defined data types representing the format of the first or second parameter; defining relationship information between the first parameter and the second parameter in the preflight rule, the relationship information placing constraints on parameter values for the first parameter and the second parameter in the preflight rule to maintain consistency between the first parameter and second parameter, the relationship information suitable for use by at least one handler to check for the consistency in the parameter values for the first parameter and the second parameter in the preflight rule; storing the relationship information to a relationship table that is accessible by the at least one handler to check for the consistency in the parameter values for the first parameter and the second parameter in the preflight rule; creating attribute information for the preflight rule, the attribute information comprising a summary of the first parameter and the second parameter; and storing the attribute information for the preflight rule in an attribute table uniquely associated with the preflight rule. | 1. A computer-implemented method of defining preflight rules for preflight profiles, the method comprising: defining a first parameter and a second parameter to be included in a preflight rule, the defining of the first parameter and the second parameter including defining a data type for each of the first parameter and the second parameter, the data type representing a format of the first or the second parameter; creating a control interface based on at least one of the defined data types representing the format of the first or second parameter; defining relationship information between the first parameter and the second parameter in the preflight rule, the relationship information placing constraints on parameter values for the first parameter and the second parameter in the preflight rule to maintain consistency between the first parameter and second parameter, the relationship information suitable for use by at least one handler to check for the consistency in the parameter values for the first parameter and the second parameter in the preflight rule; storing the relationship information to a relationship table that is accessible by the at least one handler to check for the consistency in the parameter values for the first parameter and the second parameter in the preflight rule; creating attribute information for the preflight rule, the attribute information comprising a summary of the first parameter and the second parameter; and storing the attribute information for the preflight rule in an attribute table uniquely associated with the preflight rule. 7. The computer-implemented method of claim 1 , further comprising: enabling a value associated with the first parameter or the second parameter to be modified when the value is inconsistent with the relationship information between the first parameter and the second parameter. | 0.5 |
8,471,871 | 1 | 5 | 1. A computerized method for rendering text on a client computing device by a server, the method comprising: sending the text from the server to the client computing device for rendering; receiving at the server initial text formatting information from the client computing device; generating revised text formatting information on the server; and sending the revised text formatting information from the server to the client computing device for re-rendering of the text in accordance with the revised text formatting information. | 1. A computerized method for rendering text on a client computing device by a server, the method comprising: sending the text from the server to the client computing device for rendering; receiving at the server initial text formatting information from the client computing device; generating revised text formatting information on the server; and sending the revised text formatting information from the server to the client computing device for re-rendering of the text in accordance with the revised text formatting information. 5. The method of claim 1 , wherein the initial text formatting information and revised text formatting information comprises text formatting information for characters, words, or symbols. | 0.5 |
9,747,925 | 1 | 16 | 1. A method of selectively visually representing speaker content generated in an audio conference, the method comprising: obtaining a profile for each of a plurality of audience members who participates in the audio conference through a respective communication device; monitoring, using a computer with a processor and memory, the speaker content spoken during the audio conference; classifying different words included in the speaker content to have different weights according to a parameter of the profile for each of the plurality of audience members; determining a relation of the speaker content to the profile for each of the plurality of audience members based on the classifying; and presenting, at a specific point in time, different visual representations of the speaker content to different ones of the plurality of audience members based on the determining, wherein the visual representations presented include a selective visual representation of the speaker content related to the parameter of the profile, such that the speaker content that is not related to the parameter of the profile is not visually represented. | 1. A method of selectively visually representing speaker content generated in an audio conference, the method comprising: obtaining a profile for each of a plurality of audience members who participates in the audio conference through a respective communication device; monitoring, using a computer with a processor and memory, the speaker content spoken during the audio conference; classifying different words included in the speaker content to have different weights according to a parameter of the profile for each of the plurality of audience members; determining a relation of the speaker content to the profile for each of the plurality of audience members based on the classifying; and presenting, at a specific point in time, different visual representations of the speaker content to different ones of the plurality of audience members based on the determining, wherein the visual representations presented include a selective visual representation of the speaker content related to the parameter of the profile, such that the speaker content that is not related to the parameter of the profile is not visually represented. 16. The method of claim 1 , further comprising: obtaining profile information of the communication device used by each of the plurality of audience members, wherein the visual representations of the speaker content are generated based on the profile information of the communications device. | 0.5 |
9,384,678 | 1 | 15 | 1. A computer-implemented method for generating vocabulary questions, the method comprising: obtaining, by a computer processor, a sentence from a database; determining, by the computer processor, whether a word of the obtained sentence, the word having multiple definitions, is used in the sentence consistently with one of the multiple definitions which has been selected as a target definition; responsive to a result of the determining being that the use of the word in the sentence is consistent with the one of the multiple definitions, providing, by the computer processor, the sentence for use to generate a question concerning the word of the sentence; and outputting, by the computer processor, the question. | 1. A computer-implemented method for generating vocabulary questions, the method comprising: obtaining, by a computer processor, a sentence from a database; determining, by the computer processor, whether a word of the obtained sentence, the word having multiple definitions, is used in the sentence consistently with one of the multiple definitions which has been selected as a target definition; responsive to a result of the determining being that the use of the word in the sentence is consistent with the one of the multiple definitions, providing, by the computer processor, the sentence for use to generate a question concerning the word of the sentence; and outputting, by the computer processor, the question. 15. The method of claim 1 , further comprising: automatically recognizing, and removing from a corpus of text that includes the sentence, boilerplate language. | 0.766862 |
10,108,767 | 11 | 12 | 11. The computer implemented method of claim 10 , determining whether the deadlock candidate is the real deadlock comprising: determining whether the electronic design exits the candidate state within a threshold limit. | 11. The computer implemented method of claim 10 , determining whether the deadlock candidate is the real deadlock comprising: determining whether the electronic design exits the candidate state within a threshold limit. 12. The computer implemented method of claim 11 , determining whether the deadlock candidate is the real deadlock comprising: identifying the deadlock candidate as the real deadlock when it is determined that the electronic design fails to exit the candidate state within the threshold limit; and resolving the real deadlock by modifying the electronic design. | 0.5 |
9,693,724 | 13 | 14 | 13. The computer-readable medium of claim 12 , wherein the one or more interactions includes at least one of: applications opened, inputs typed, gesture patterns used on a touch screen, body motions, eye movements, voice input, accelerometer sensor data, and gyroscopic sensor data. | 13. The computer-readable medium of claim 12 , wherein the one or more interactions includes at least one of: applications opened, inputs typed, gesture patterns used on a touch screen, body motions, eye movements, voice input, accelerometer sensor data, and gyroscopic sensor data. 14. The computer-readable medium of claim 13 , wherein learning the function mapping from the inputs to the brain health metric further comprises using at least one of: global positioning coordinate data, an outgoing phone call number and duration, an outgoing email address and length, an outgoing text message number and length, an incoming phone call number and duration, an incoming email address and length, and an incoming text message number and length. | 0.5 |
8,671,078 | 18 | 19 | 18. A computer-readable storage device storing computer-executable instructions which when executed by a computer perform a method for sharing business logic items, the method comprising: receiving an annotation associated with one or more business logic items in a first document, the annotation designating the one or more business logic items as a shared business logic item; generating an identifier for each of the one or more annotated shared business logic items; publishing the first document to an integrated server platform document library; populating an index component with the one or more annotated shared business logic items and associated identifiers, the index component being utilized to index and catalog shared business logic items, the index component using one or more of metadata, content and other information when indexing against one or more disparate information sources, the index component being further utilized to identify unique document parts; receiving a query input to search for related shared business logic items; querying the index component for related shared business logic items; providing a list of one or more search results of related shared business logic items; and maintaining references to unique business logic items, the references comprising at least a relative path of a parent document site collection and the identifier, the identifier being utilized to repair a reference that is no longer available, the identifier being separate from the relative path. | 18. A computer-readable storage device storing computer-executable instructions which when executed by a computer perform a method for sharing business logic items, the method comprising: receiving an annotation associated with one or more business logic items in a first document, the annotation designating the one or more business logic items as a shared business logic item; generating an identifier for each of the one or more annotated shared business logic items; publishing the first document to an integrated server platform document library; populating an index component with the one or more annotated shared business logic items and associated identifiers, the index component being utilized to index and catalog shared business logic items, the index component using one or more of metadata, content and other information when indexing against one or more disparate information sources, the index component being further utilized to identify unique document parts; receiving a query input to search for related shared business logic items; querying the index component for related shared business logic items; providing a list of one or more search results of related shared business logic items; and maintaining references to unique business logic items, the references comprising at least a relative path of a parent document site collection and the identifier, the identifier being utilized to repair a reference that is no longer available, the identifier being separate from the relative path. 19. The computer readable storage device of claim 18 , the method further comprising: receiving a selection of one or more of the one or more search results of related shared business logic items; reading the first document containing the one or more related shared business logic items from the integrated server platform document library; providing the one or more selected shared business logic items to the second document; maintaining shared business logic item relationship data and identifiers; receiving an indication that a shared business logic item has been modified in the first document; populating the index component with the modified shared business logic item; receiving an indication of a document connection refresh of the second document; querying the index component for modified business logic items; and updating the second document with any new modified shared business logic items. | 0.740847 |
9,495,559 | 1 | 15 | 1. A method for sharing notes associated with a document on a computer system, the method comprising: creating, by a first user, notes associated with a location within the document by linking the first user's notes to a portion of a table to contents of the document that reference the location within document, wherein the notes are associated with the document and stored on the system; receiving, at the system, a request from a second user to share the notes created by the first user, the second user's existing notes associated with the same document stored on the system; designating access rights to the second user to share the notes created by the first user, the access rights defined by the first user when creating the notes, the access rights specifying a time constraint on access to the first user's notes by the second user and permission for one or more access types given to the second user for accessing the first user's notes; inserting, by the system, the first user's notes into the second user's existing notes associated with the document in accordance with the access rights designated to the second user, wherein inserting includes accessing the table of contents for the document, identifying page locations within an instance of the document provided to the second user and referenced by the portion of the table of contents linked to the first user's notes, the instance of the document provided to the second user also comprising the second user's notes linked to portions of the same table of contents, and enabling display of the first user's notes at the identified page locations, within the instance of the document provided to the second user, that are referenced by the portion of the table of contents linked to the first user's notes; and notifying the second user of the availability of the shared notes, thereby allowing the second user to retrieve the shared notes. | 1. A method for sharing notes associated with a document on a computer system, the method comprising: creating, by a first user, notes associated with a location within the document by linking the first user's notes to a portion of a table to contents of the document that reference the location within document, wherein the notes are associated with the document and stored on the system; receiving, at the system, a request from a second user to share the notes created by the first user, the second user's existing notes associated with the same document stored on the system; designating access rights to the second user to share the notes created by the first user, the access rights defined by the first user when creating the notes, the access rights specifying a time constraint on access to the first user's notes by the second user and permission for one or more access types given to the second user for accessing the first user's notes; inserting, by the system, the first user's notes into the second user's existing notes associated with the document in accordance with the access rights designated to the second user, wherein inserting includes accessing the table of contents for the document, identifying page locations within an instance of the document provided to the second user and referenced by the portion of the table of contents linked to the first user's notes, the instance of the document provided to the second user also comprising the second user's notes linked to portions of the same table of contents, and enabling display of the first user's notes at the identified page locations, within the instance of the document provided to the second user, that are referenced by the portion of the table of contents linked to the first user's notes; and notifying the second user of the availability of the shared notes, thereby allowing the second user to retrieve the shared notes. 15. The method of claim 1 , wherein: the request from the second user to share the notes created by the first user comprises an indication to view the first user's notes along with the second user's existing notes independent of the document, the second user's existing notes linked to portions of the same table of contents of the document; inserting the first user's notes into the second user's existing notes associated with the document comprises organizing the first user's notes with respect to the second user's notes based on relative portions of the table of contents to which the first and second user's notes are linked; and enabling display, to the second user, of the first user's notes organized with respect to the second user's existing notes without providing the document. | 0.5 |
9,560,206 | 9 | 13 | 9. A method for providing real-time resources to participants in an audio conference session via a communication network, the method comprising: a conferencing system establishing an audio conference session between a plurality of computing devices via a communication network, each computing device generating a corresponding audio stream comprising a speech signal; and in real-time during the audio conference session, a server: receiving and processing the audio streams to determine the speech signals; extracting words from the speech signals; inputting the extracted words to a relevance algorithm; the relevance algorithm outputting a relevant keyword being discussed in the audio conference session based on a speaker identity with a corresponding role or category of one or more participants who spoke the extracted words, the relevant keyword determined by calculating and updating a relevance score during the audio conference session and, if the relevance score exceeds a threshold, outputting the relevant keyword, wherein the relevance score is based on a usage density associated with the one or more extracted words; identifying a plurality of resources related to the relevant keyword output from the relevance algorithm based on the speaker identity with the corresponding role or category of the one or more participants who spoke the extracted words; displaying the plurality of resources to one or more of the computing devices in a conference user interface associated with the audio conference session; and receiving a user selection of one or more of the plurality of resources to present, via the conference user interface to the one or more participants. | 9. A method for providing real-time resources to participants in an audio conference session via a communication network, the method comprising: a conferencing system establishing an audio conference session between a plurality of computing devices via a communication network, each computing device generating a corresponding audio stream comprising a speech signal; and in real-time during the audio conference session, a server: receiving and processing the audio streams to determine the speech signals; extracting words from the speech signals; inputting the extracted words to a relevance algorithm; the relevance algorithm outputting a relevant keyword being discussed in the audio conference session based on a speaker identity with a corresponding role or category of one or more participants who spoke the extracted words, the relevant keyword determined by calculating and updating a relevance score during the audio conference session and, if the relevance score exceeds a threshold, outputting the relevant keyword, wherein the relevance score is based on a usage density associated with the one or more extracted words; identifying a plurality of resources related to the relevant keyword output from the relevance algorithm based on the speaker identity with the corresponding role or category of the one or more participants who spoke the extracted words; displaying the plurality of resources to one or more of the computing devices in a conference user interface associated with the audio conference session; and receiving a user selection of one or more of the plurality of resources to present, via the conference user interface to the one or more participants. 13. The method of claim 9 , wherein the identifying the plurality of resources related to the relevant keyword comprises determining a URL associated with the corresponding resource, and the providing the plurality of resources to the computing device comprises providing the URL to a browser associated with the computing device. | 0.5 |
7,475,018 | 2 | 6 | 2. The method of claim 1 , wherein the step of developing an initial domain model comprises at least one of the steps of defining an organizational scope, defining a content scope, defining a process scope, and defining economic factors relating to the domain. | 2. The method of claim 1 , wherein the step of developing an initial domain model comprises at least one of the steps of defining an organizational scope, defining a content scope, defining a process scope, and defining economic factors relating to the domain. 6. The method of claim 2 , wherein the step of defining a process scope comprises the step of identifying a business process that can be improved by structuring contents of the unstructured domain. | 0.794792 |
7,499,956 | 10 | 12 | 10. A computer readable storage medium having program instructions for providing annotation processors, comprising: program instructions for identifying an annotation present in a file; program instructions for identifying factories available for processing annotations; program instructions for determining annotations supported by each of the available factories; program instructions for arranging each of the available factories in a determined order such that conflicts between factories having different versions of a processor supporting the annotation present are resolved through the determined order; and program instructions for assigning one of the available factories to process the annotation based on the annotation present in the file being supported by the one of the available factories. | 10. A computer readable storage medium having program instructions for providing annotation processors, comprising: program instructions for identifying an annotation present in a file; program instructions for identifying factories available for processing annotations; program instructions for determining annotations supported by each of the available factories; program instructions for arranging each of the available factories in a determined order such that conflicts between factories having different versions of a processor supporting the annotation present are resolved through the determined order; and program instructions for assigning one of the available factories to process the annotation based on the annotation present in the file being supported by the one of the available factories. 12. The computer readable storage medium of claim 10 , wherein the program instructions for assigning one of the available factories to process the annotation based on the annotation present in the file being supported by the one of the available factories includes, program instructions for matching the annotation present in the file with an annotation supported by one of the available factories. | 0.5 |
6,023,669 | 5 | 6 | 5. A natural language processing system for processing internal conceptual expressions of a computer not in a natural language so that they are converted to a message in a natural language from an author to a reader in accordance with the expression form of the message determined to be preferred by a person intended to receive the message, comprising: input means for inputting information expressed by a concept comprising an internal conceptual expression of a computer not in a natural language that is to be communicated to a person intended to receive a message embodying the concept; a knowledge base having the knowledge of natural languages, general knowledge, and the knowledge of specific domains; determination means for determining information to be added to a concept input from said input means by referring to the knowledge base in consideration of precedent concepts and for selecting a message embodying the concept with the added information, said determining means determining the expression form of the message preferred by the person intended to receive the message by using data in said knowledge base and by determining the information to be added to the input concept, wherein said determining means selects the expression form of the message from a plurality of possible expression forms embodying the concept and the information to be added to the concept in accordance with the determined, preferred expression form of the message; modulation means for modulating the concept input from said input means by adding the information determined by said determination means to the concept; and conversion means for converting the concept modulated by said modulation means into the message embodying the concept in a natural language. | 5. A natural language processing system for processing internal conceptual expressions of a computer not in a natural language so that they are converted to a message in a natural language from an author to a reader in accordance with the expression form of the message determined to be preferred by a person intended to receive the message, comprising: input means for inputting information expressed by a concept comprising an internal conceptual expression of a computer not in a natural language that is to be communicated to a person intended to receive a message embodying the concept; a knowledge base having the knowledge of natural languages, general knowledge, and the knowledge of specific domains; determination means for determining information to be added to a concept input from said input means by referring to the knowledge base in consideration of precedent concepts and for selecting a message embodying the concept with the added information, said determining means determining the expression form of the message preferred by the person intended to receive the message by using data in said knowledge base and by determining the information to be added to the input concept, wherein said determining means selects the expression form of the message from a plurality of possible expression forms embodying the concept and the information to be added to the concept in accordance with the determined, preferred expression form of the message; modulation means for modulating the concept input from said input means by adding the information determined by said determination means to the concept; and conversion means for converting the concept modulated by said modulation means into the message embodying the concept in a natural language. 6. A system according to claim 5, wherein said determination means determines a specific word and/or phrase corresponding to the input concept to be information to be added. | 0.529891 |
7,788,250 | 12 | 13 | 12. The system of claim 10 , the processor further to combine the supplier links and the parameter names in order to obtain universal resource locators for sending the user requests to the suppliers. | 12. The system of claim 10 , the processor further to combine the supplier links and the parameter names in order to obtain universal resource locators for sending the user requests to the suppliers. 13. The system of claim 12 , the processor further to: receive from the user a set of search terms indicating a set of values assigned to the set of parameters; retrieve from the database the new request type, the request type associated with the supplier links; send the set of values to the suppliers as indicated by the supplier links; receive a set of results from the suppliers in response; and send the set of results to the user. | 0.5 |
7,680,668 | 14 | 24 | 14. A computer-usable storage medium having computer-readable program code embodied therein for causing a computer system to perform a method for generating a language-independent regression test script, said method comprising: receiving a language-specific regression test script for an application, said language-specific regression test script comprising at least one object and configured for use by an automated testing tool operable to interact with and execute the application according to said language-specific-regression test script; identifying a translatable string of said object, wherein said translatable string is represented in a first language; and replacing said translatable string with a language-independent variable associated with a plurality of strings in a corresponding plurality of languages. | 14. A computer-usable storage medium having computer-readable program code embodied therein for causing a computer system to perform a method for generating a language-independent regression test script, said method comprising: receiving a language-specific regression test script for an application, said language-specific regression test script comprising at least one object and configured for use by an automated testing tool operable to interact with and execute the application according to said language-specific-regression test script; identifying a translatable string of said object, wherein said translatable string is represented in a first language; and replacing said translatable string with a language-independent variable associated with a plurality of strings in a corresponding plurality of languages. 24. The computer-usable storage medium of claim 14 , wherein the method further comprises generating, by the computer system, said language-independent regression test script, said language-independent regression test script including said language-independent variable and executable by said automated testing tool. | 0.5 |
9,336,256 | 1 | 6 | 1. A database network router apparatus for data tokenization, the apparatus comprising: one or more processors; and one or more memories operatively coupled to at least one of the one or more processors and having instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: receive a request directed to a tokenized database, wherein the tokenized database contains one or more tokenized data values and wherein the request does not include any tokenized data values; apply one or more rules to the request; rewrite the request based on at least one of the one or more rules, wherein the rewritten request is configured to cause one or more non-tokenized data values specified in the request to be tokenized by a software agent resident on the tokenized database when data is added to the tokenized database as a result of the request and wherein the rewritten request is configured to cause the tokenized database to return non-tokenized data values when data is received from the tokenized database as a result of the request; and transmit the rewritten request to the tokenized database. | 1. A database network router apparatus for data tokenization, the apparatus comprising: one or more processors; and one or more memories operatively coupled to at least one of the one or more processors and having instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: receive a request directed to a tokenized database, wherein the tokenized database contains one or more tokenized data values and wherein the request does not include any tokenized data values; apply one or more rules to the request; rewrite the request based on at least one of the one or more rules, wherein the rewritten request is configured to cause one or more non-tokenized data values specified in the request to be tokenized by a software agent resident on the tokenized database when data is added to the tokenized database as a result of the request and wherein the rewritten request is configured to cause the tokenized database to return non-tokenized data values when data is received from the tokenized database as a result of the request; and transmit the rewritten request to the tokenized database. 6. The database network router apparatus of claim 1 , wherein applying the one or more rules and rewriting the request comprises: selecting an incomplete request rule when the request is determined to be incomplete; transmitting a request for missing data to the tokenized database, wherein the missing data is the incomplete portion of the request; receiving the missing data from the tokenized database; and rewriting the request to include missing data. | 0.749175 |
9,495,618 | 1 | 4 | 1. A method for object detection in remotely-sensed images, the method comprising: identifying a first domain within a remotely-sensed image, wherein the first domain comprises textural features and spectral features; training a first classifier to detect a first object within the image based on a textural relationship between the textural features within the first domain; training a second classifier to detect the first object based on: the textural relationships within the first domain; and a spectral relationship between the spectral features within the first domain; learning a classifier relationship between the trained first classifier and the trained second classifier; training an object detector to detect at least one object based on the learned classifier relationship in the first domain; detecting the at least one object within a second domain using the trained object detector, wherein the second domain comprises textural and spectral features; comparing the detection of the at least one object in the first domain to the detection of the at least one object detected in the second domain; modifying the object detector based on the comparison between the detection of the at least one object in the first domain and the detection of the at least one object in the second domain; and detecting one or more objects in an additional domain with the modified optimal fast object detector. | 1. A method for object detection in remotely-sensed images, the method comprising: identifying a first domain within a remotely-sensed image, wherein the first domain comprises textural features and spectral features; training a first classifier to detect a first object within the image based on a textural relationship between the textural features within the first domain; training a second classifier to detect the first object based on: the textural relationships within the first domain; and a spectral relationship between the spectral features within the first domain; learning a classifier relationship between the trained first classifier and the trained second classifier; training an object detector to detect at least one object based on the learned classifier relationship in the first domain; detecting the at least one object within a second domain using the trained object detector, wherein the second domain comprises textural and spectral features; comparing the detection of the at least one object in the first domain to the detection of the at least one object detected in the second domain; modifying the object detector based on the comparison between the detection of the at least one object in the first domain and the detection of the at least one object in the second domain; and detecting one or more objects in an additional domain with the modified optimal fast object detector. 4. The method of claim 1 , wherein the first domain comprises a first spectral dataset and the second domain comprises a second spectral dataset, wherein the first spectral dataset is different from the second spectral dataset. | 0.796959 |
9,244,979 | 1 | 6 | 1. A method comprising: storing summary data that (a) specifies a number of each element of a plurality of elements of an XML document that is part of XML data and (b) indicates a hierarchical relationship among the plurality of elements; identifying, in a particular query that targets a portion of the XML data, a plurality of predicates that comprises a first subset and a second subset that is different than the first subset; analyzing the summary data based on the first subset of the plurality of predicates; determining that at least a first predicate in the first subset of the plurality of predicates is correlated with a second predicate in the second subset of the plurality of predicates; in response to determining that the first predicate is correlated with the second predicate, generating a single selectivity value based on the first subset of the plurality of predicates, one or more predicates that do not belong to the first subset of the plurality of predicates, and the summary data; associating the single selectivity value with the first subset of the plurality predicates; and estimating, based on the single selectivity value, a cost of executing the particular query; wherein the method is performed by one or more computing devices. | 1. A method comprising: storing summary data that (a) specifies a number of each element of a plurality of elements of an XML document that is part of XML data and (b) indicates a hierarchical relationship among the plurality of elements; identifying, in a particular query that targets a portion of the XML data, a plurality of predicates that comprises a first subset and a second subset that is different than the first subset; analyzing the summary data based on the first subset of the plurality of predicates; determining that at least a first predicate in the first subset of the plurality of predicates is correlated with a second predicate in the second subset of the plurality of predicates; in response to determining that the first predicate is correlated with the second predicate, generating a single selectivity value based on the first subset of the plurality of predicates, one or more predicates that do not belong to the first subset of the plurality of predicates, and the summary data; associating the single selectivity value with the first subset of the plurality predicates; and estimating, based on the single selectivity value, a cost of executing the particular query; wherein the method is performed by one or more computing devices. 6. The method of claim 1 , wherein the first subset of the plurality of predicates corresponds to a column of a table. | 0.782288 |
7,499,909 | 5 | 18 | 5. The method of claim 2 , wherein: the particular representation of the XML datatype indicates that the first data is stored by the database server in second one or more relational tables as Large Object (LOB) storage; and the index information includes an XML path index for the first data, wherein the XML path index stores one or more XML paths to elements of the first data in association with one or more corresponding LOB locators that point to fragments of the LOB storage where the elements are stored. | 5. The method of claim 2 , wherein: the particular representation of the XML datatype indicates that the first data is stored by the database server in second one or more relational tables as Large Object (LOB) storage; and the index information includes an XML path index for the first data, wherein the XML path index stores one or more XML paths to elements of the first data in association with one or more corresponding LOB locators that point to fragments of the LOB storage where the elements are stored. 18. A machine-readable volatile or non-volatile medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 5 . | 0.5 |
8,015,176 | 14 | 16 | 14. The system of claim 13 , wherein said means for automatically rewriting includes said means for performing said expanded rewrite algorithm, and wherein said means for performing said expanded rewrite algorithm further includes: means for performing a loop for each context reference X of one or more context references included in a pattern of said cleansing rule (C) on a relational table R, said means for performing said loop including: means for setting a correlation condition cr to a list of one or more conjuncts, said one or more conjuncts comprising at least one of: one or more explicit conjuncts included in a condition of said cleansing rule C and referring to said context reference X and one or more implied conjuncts, each implied conjunct being on a cluster key of said relational table R or a sequence key of said relational table R, wherein said correlation condition cr is a correlation condition between said context reference X and T, said T being a target reference included in said pattern, means for retaining in said one or more conjuncts of said correlation condition cr only position-preserving conjuncts, if said context reference X is a position-based context reference, means for binding s to said target reference T, wherein said s is a query condition on said relational table R and is included in said user query (Q), means for running a transitivity analysis between said correlation condition cr and said query condition s, means for determining d, said d being a set including any conjunct of a condition generated through said transitivity analysis that refers only to said context reference X, and means for adding set d to a context condition cc if set d is not empty, and otherwise for setting said context condition cc to an empty set and breaking out of said loop, wherein said context condition cc defines a context set for context reference X; and means for generating, if said context condition cc is not said empty set, an expanded rewrite Q e as said rewritten query, and otherwise for setting said expanded rewrite Q e to a null value. | 14. The system of claim 13 , wherein said means for automatically rewriting includes said means for performing said expanded rewrite algorithm, and wherein said means for performing said expanded rewrite algorithm further includes: means for performing a loop for each context reference X of one or more context references included in a pattern of said cleansing rule (C) on a relational table R, said means for performing said loop including: means for setting a correlation condition cr to a list of one or more conjuncts, said one or more conjuncts comprising at least one of: one or more explicit conjuncts included in a condition of said cleansing rule C and referring to said context reference X and one or more implied conjuncts, each implied conjunct being on a cluster key of said relational table R or a sequence key of said relational table R, wherein said correlation condition cr is a correlation condition between said context reference X and T, said T being a target reference included in said pattern, means for retaining in said one or more conjuncts of said correlation condition cr only position-preserving conjuncts, if said context reference X is a position-based context reference, means for binding s to said target reference T, wherein said s is a query condition on said relational table R and is included in said user query (Q), means for running a transitivity analysis between said correlation condition cr and said query condition s, means for determining d, said d being a set including any conjunct of a condition generated through said transitivity analysis that refers only to said context reference X, and means for adding set d to a context condition cc if set d is not empty, and otherwise for setting said context condition cc to an empty set and breaking out of said loop, wherein said context condition cc defines a context set for context reference X; and means for generating, if said context condition cc is not said empty set, an expanded rewrite Q e as said rewritten query, and otherwise for setting said expanded rewrite Q e to a null value. 16. The system of claim 14 , wherein said user query is of a form σ s R K1 σ S1 D 1 . . . Kn σ Sn D n , wherein said relational table R joins each table D i on column K i by n:1 joins, wherein said any conjunct generated through said transitivity analysis is P i on tables D′ i , wherein i=1, . . . , m and m<=n, and wherein said means for performing said expanded rewrite algorithm further includes: means for ordering said D′ i in ascending selectivity order of S′ i for i=1, . . . , m; means for performing a loop utilizing a counter incremented over a series of m+1 values, said means for performing said loop utilizing said counter including: if said counter is equal to an initial value, means for generating a first SQL statement that defers all of said joins after a cleansing of said sequence-based data, said cleansing including utilizing said cleansing rule, otherwise means for generating an additional SQL statement that joins said relational table R with said tables D′ 1 to D′ i in an order specified by said ordering, means for converting each join condition associated with said n:1 joins to a local conjunct on said relational table R of the form R.K i in (select K i from D i where S i ), means for performing steps of said expanded rewrite algorithm of claim 7 , means for generating a new SQL statement if all “in” conjuncts are derived on said context reference, said means for generating said new SQL statement including means for utilizing said performing said steps of said expanded rewrite algorithm of claim 7 , and means for converting said “in” conjuncts to joins if all of said “in” conjuncts are derived on said context reference; means for compiling a set of up to m+1 SQL statements comprising said first SQL statement and said additional SQL statements generated by said loop utilizing said counter, said means for compiling including means for utilizing an optimizer of said DBMS; means for determining, by said DBMS, estimates of costs of computing resources required for an execution of said SQL statements included in said set of up to m+1 SQL statements; and means for selecting, as said rewritten query and subsequent to said determining, an optimal SQL statement from said set of up to m+1 SQL statements, said optimal SQL statement being associated with a least estimate of said determined estimates. | 0.5 |
7,831,529 | 9 | 12 | 9. The system of claim 1 , wherein the language component comprises policy controls to influence at least one of basic and decision-theoretic policies for at least one of routing, alerting, and communications within the system. | 9. The system of claim 1 , wherein the language component comprises policy controls to influence at least one of basic and decision-theoretic policies for at least one of routing, alerting, and communications within the system. 12. The system of claim 9 , wherein the policy controls specify curves that can be reasoned about in a decision-theoretic manner by the system. | 0.661137 |
7,865,955 | 14 | 16 | 14. The apparatus according to claim 1 , wherein the signature frequency table includes a field denoting an observation period of each entry. | 14. The apparatus according to claim 1 , wherein the signature frequency table includes a field denoting an observation period of each entry. 16. The apparatus according to claim 14 , wherein if the signature candidate extractor is required to generate a new entry when the entries of the signature frequency table are exhausted, the signature candidate extractor replaces an entry having a smallest signature generation frequency among entries not updated for about the longest time with a new entry. | 0.681172 |
8,019,710 | 29 | 36 | 29. A system for guiding the progressive development and documentation of user thinking and knowledge about an inquiry based project according to exemplary approaches used by experts, comprising: processor executable instructions embodied on a computer readable media, memory, or processor readable device, or a combination thereof, said instructions comprising: instructions to receive user specification of an initial stage of understanding regarding an arbitrary problem or inquiry based project according to at least one of a plurality of entry or starting points; instructions for accomplishing at least one of an interactive workspace or a user suggestion or both, to facilitate the further development of the understanding regarding an arbitrary problem or inquiry project towards a completion stage; instructions to display or output, or both, an integrated archetype based model of user understanding regarding the arbitrary problem or inquiry based project. | 29. A system for guiding the progressive development and documentation of user thinking and knowledge about an inquiry based project according to exemplary approaches used by experts, comprising: processor executable instructions embodied on a computer readable media, memory, or processor readable device, or a combination thereof, said instructions comprising: instructions to receive user specification of an initial stage of understanding regarding an arbitrary problem or inquiry based project according to at least one of a plurality of entry or starting points; instructions for accomplishing at least one of an interactive workspace or a user suggestion or both, to facilitate the further development of the understanding regarding an arbitrary problem or inquiry project towards a completion stage; instructions to display or output, or both, an integrated archetype based model of user understanding regarding the arbitrary problem or inquiry based project. 36. The system of claim 29 further comprising at least one representation comprising at least one of three dimensional representation, three dimensional rotatable representation, three dimensional representation that can be zoomed, three dimensional-like representation, three dimensional combined with two dimensional representation, outline representation, tree-type representation, linkage representation, two dimensional representation, or matrix representation, or a combination thereof. | 0.73746 |
8,577,901 | 15 | 17 | 15. A non-transitory computer-readable memory device, comprising: one or more instructions, which, when executed by one or more processors, cause the one or more processors to: determine, at a first time, a first position of a document with respect to a first set of documents in a first list of search results, the first position being based on a first score of the document with respect to one or more scores associated with the first set of documents in the first list of search results; determine, at a second time, a second position of the document with respect to a second set of documents in a second list of search results, the second position being based on a second score of the document with respect to one or more scores associated with the second set of documents in the second list of search results; determine an amount or rate of change between the first position and the second position; generate a third score for the document based on the determined amount or rate of change between the first position and the second position; and rank the document against at least one other document based on the third score. | 15. A non-transitory computer-readable memory device, comprising: one or more instructions, which, when executed by one or more processors, cause the one or more processors to: determine, at a first time, a first position of a document with respect to a first set of documents in a first list of search results, the first position being based on a first score of the document with respect to one or more scores associated with the first set of documents in the first list of search results; determine, at a second time, a second position of the document with respect to a second set of documents in a second list of search results, the second position being based on a second score of the document with respect to one or more scores associated with the second set of documents in the second list of search results; determine an amount or rate of change between the first position and the second position; generate a third score for the document based on the determined amount or rate of change between the first position and the second position; and rank the document against at least one other document based on the third score. 17. The computer-readable memory device of claim 15 , where the one or more instructions to determine the amount or rate of change further cause the one or more processors to: determine a rate at which the document moves between the first position and the second position, and where the one or more instructions to generate the third score for the document further cause the one or more processors to: generate the third score based on the determined rate. | 0.532787 |
7,555,471 | 13 | 18 | 13. A computer program product having a computer-readable medium having computer program instructions embodied therein for presenting facts, the computer program instructions comprising: an object access module adapted to establish a set of objects in response to a search query received from a user, each object having a set of facts stored in a computer memory containing information about an entity associated with the object, each fact having an attribute indicating a property of the entity and a corresponding value describing the indicated property; an interface module adapted to provide a user interface for allowing the user to identify one or more facts of the objects in the set to present and for allowing the user to manipulate a representation of the identified facts; and a presentation module for presenting via the user interface the representation of the identified facts of the objects in the set, the representation describing the attributes and corresponding values of the identified facts. | 13. A computer program product having a computer-readable medium having computer program instructions embodied therein for presenting facts, the computer program instructions comprising: an object access module adapted to establish a set of objects in response to a search query received from a user, each object having a set of facts stored in a computer memory containing information about an entity associated with the object, each fact having an attribute indicating a property of the entity and a corresponding value describing the indicated property; an interface module adapted to provide a user interface for allowing the user to identify one or more facts of the objects in the set to present and for allowing the user to manipulate a representation of the identified facts; and a presentation module for presenting via the user interface the representation of the identified facts of the objects in the set, the representation describing the attributes and corresponding values of the identified facts. 18. The computer program product of claim 13 , wherein the presentation module comprises: a tabular presentation module adapted to generate a table describing the identified facts of the objects in the set. | 0.679128 |
8,543,646 | 8 | 14 | 8. A real-time communication method for resource content, the method comprising: receiving from a subscriber device, by a resource content publishing device, identification information of the subscriber device and an event topic, wherein the identification information comprises path information defining a topic path for receiving a notification event related to the selected event topic and the event topic selected by the subscriber device is a complex event topic set constituted by at least two separate event topics; adding the identification information of the subscriber device and the selected event topic to an event topic subscription search table; determining, by the resource content publishing device, if new resource content is available, whether an event topic of the new resource content belongs to the complex event topic set; creating, by the resource content publishing device, if it is determined that the event topic of the new resource content belongs to the complex event topic set, a complex event by applying a predefined rule describing a relation between the separate events related to the complex event topic set onto the new resource content, so as to send the complex event to the subscriber device after obtaining the identification information of the subscriber device; obtaining by the resource content publishing device, the identification information of a subscriber device subscribing to an event topic related to new resource content, where the identification information is obtained from the event topic subscription search table, if new resource content is available; and sending, by the resource content publishing device, a notification event comprising the new resource content to the subscriber device according to the identification information of the subscriber device. | 8. A real-time communication method for resource content, the method comprising: receiving from a subscriber device, by a resource content publishing device, identification information of the subscriber device and an event topic, wherein the identification information comprises path information defining a topic path for receiving a notification event related to the selected event topic and the event topic selected by the subscriber device is a complex event topic set constituted by at least two separate event topics; adding the identification information of the subscriber device and the selected event topic to an event topic subscription search table; determining, by the resource content publishing device, if new resource content is available, whether an event topic of the new resource content belongs to the complex event topic set; creating, by the resource content publishing device, if it is determined that the event topic of the new resource content belongs to the complex event topic set, a complex event by applying a predefined rule describing a relation between the separate events related to the complex event topic set onto the new resource content, so as to send the complex event to the subscriber device after obtaining the identification information of the subscriber device; obtaining by the resource content publishing device, the identification information of a subscriber device subscribing to an event topic related to new resource content, where the identification information is obtained from the event topic subscription search table, if new resource content is available; and sending, by the resource content publishing device, a notification event comprising the new resource content to the subscriber device according to the identification information of the subscriber device. 14. The real-time communication method for resource content according to claim 8 , further comprising: generating for a predetermined event topic, by the resource content publishing device, event change history information related to the predetermined event topic; and sending, by the resource content publishing device, a link to the event change history information to a subscriber device subscribing to the predetermined event topic, in order for the subscriber device to obtain the event change history information via the link. | 0.641026 |
9,659,094 | 1 | 9 | 1. A method for storing fingerprints for multimedia streams, the method comprising the following operations performed with one or more processors: identifying a multimedia stream associated with a link, the multimedia stream comprising content and metadata that describes content; removing the metadata from the stream and encoding the content using a compression algorithm to generate a fingerprint for the multimedia stream, the fingerprint comprising a set of unique bits; comparing the generated fingerprint to at least one fingerprint stored in a fingerprint database; determining, based on the comparison, whether the generated fingerprint matches at least one fingerprint stored in the fingerprint database; storing the generated fingerprint in the fingerprint database when it is determined that there is not a match to the generated fingerprint; creating a canonical resource locator for the identified multimedia stream by resolving the link and at least one other link into a simplified format; and associating the canonical resource locator with the generated fingerprint. | 1. A method for storing fingerprints for multimedia streams, the method comprising the following operations performed with one or more processors: identifying a multimedia stream associated with a link, the multimedia stream comprising content and metadata that describes content; removing the metadata from the stream and encoding the content using a compression algorithm to generate a fingerprint for the multimedia stream, the fingerprint comprising a set of unique bits; comparing the generated fingerprint to at least one fingerprint stored in a fingerprint database; determining, based on the comparison, whether the generated fingerprint matches at least one fingerprint stored in the fingerprint database; storing the generated fingerprint in the fingerprint database when it is determined that there is not a match to the generated fingerprint; creating a canonical resource locator for the identified multimedia stream by resolving the link and at least one other link into a simplified format; and associating the canonical resource locator with the generated fingerprint. 9. The method of claim 1 , further comprising: comparing the canonical resource locator to at least one stored canonical resource locator; determining, based on the comparison, whether the canonical resource locator matches at least one stored canonical resource locator; and storing the canonical resource locator in the fingerprint database when it is determined that there is not a match to the stored canonical resource locator. | 0.5 |
10,090,002 | 2 | 3 | 2. The method of claim 1 , wherein, for each user in the set of users, the at least one attribute comprises at least one personality trait of the user. | 2. The method of claim 1 , wherein, for each user in the set of users, the at least one attribute comprises at least one personality trait of the user. 3. The method of claim 2 , wherein retrieving the user model for each user in the set of users comprises: determining the at least one personality trait associated with the user, and wherein the at least one personality trait of the user is identified based on at least one of information specified in a stored profile of the user or indicators in natural language of one or more communications, in the plurality of communications, associated with the user as identified by natural language processing performed on the one or more communications. | 0.53413 |
8,655,643 | 1 | 6 | 1. A computer-based method for adaptive transliteration between a first and a second character set, comprising: receiving a set of input tokens in a first character set, entered into an input element of a user interface; transliterating, in a processor, a subset of said set of input tokens substantially in real-time as said input tokens are received in said input portion of a user interface by comparing said subset of the input tokens against a database of known tokens in a second character set; determining a set of output tokens in said second character set; and providing a machine-readable output representative of said output tokens substantially in real-time responsive to receiving said input and upon processing and determining said output tokens. | 1. A computer-based method for adaptive transliteration between a first and a second character set, comprising: receiving a set of input tokens in a first character set, entered into an input element of a user interface; transliterating, in a processor, a subset of said set of input tokens substantially in real-time as said input tokens are received in said input portion of a user interface by comparing said subset of the input tokens against a database of known tokens in a second character set; determining a set of output tokens in said second character set; and providing a machine-readable output representative of said output tokens substantially in real-time responsive to receiving said input and upon processing and determining said output tokens. 6. The method of claim 1 , said providing an output comprising providing an output to an output element of said user interface. | 0.669271 |
9,031,861 | 1 | 7 | 1. A method comprising: identifying a corpus of campaigns, each campaign including constraints, delivery goals and selection criteria for the delivery of one or more associated content items; determining, by one or more processors, a candidate campaign from the corpus of campaigns including evaluating constraints associated with delivery of the one or more content items for a first campaign and determining that the constraints include a budget constraint that is sufficient so as to enable the first campaign to be included in an experiment while still enabling the first campaign to meet its respective delivery goals; identifying a content item to be presented to users in response to requests for content, the content item including a link to a resource and being part of the first campaign associated with a content item sponsor, the campaign being associated with a geographic region; determining a division of the geographic region including identifying a plurality of different geographic locations in the geographic region wherein each geographic location is sufficiently small so as to not consume more than a predetermined percentage of the impressions of the content item for the first campaign; selecting one or more of the plurality of different geographic locations to be experimental geographic locations; selecting one or more of the plurality of different geographic locations to be control geographic locations; pausing presentation of the content item in the one or more experimental geographic locations for a time period, while continuing presentation of the content item in the one or more control geographic locations; and measuring content item effectiveness of the content item including comparing conversions associated with the resource during the time period for the one or more experimental geographic locations and conversions associated with the resource during the time period for the one or more control geographic locations. | 1. A method comprising: identifying a corpus of campaigns, each campaign including constraints, delivery goals and selection criteria for the delivery of one or more associated content items; determining, by one or more processors, a candidate campaign from the corpus of campaigns including evaluating constraints associated with delivery of the one or more content items for a first campaign and determining that the constraints include a budget constraint that is sufficient so as to enable the first campaign to be included in an experiment while still enabling the first campaign to meet its respective delivery goals; identifying a content item to be presented to users in response to requests for content, the content item including a link to a resource and being part of the first campaign associated with a content item sponsor, the campaign being associated with a geographic region; determining a division of the geographic region including identifying a plurality of different geographic locations in the geographic region wherein each geographic location is sufficiently small so as to not consume more than a predetermined percentage of the impressions of the content item for the first campaign; selecting one or more of the plurality of different geographic locations to be experimental geographic locations; selecting one or more of the plurality of different geographic locations to be control geographic locations; pausing presentation of the content item in the one or more experimental geographic locations for a time period, while continuing presentation of the content item in the one or more control geographic locations; and measuring content item effectiveness of the content item including comparing conversions associated with the resource during the time period for the one or more experimental geographic locations and conversions associated with the resource during the time period for the one or more control geographic locations. 7. The method of claim 1 where the one or more experimental geographic locations are selected based at least in part on being substantially representative of the geographic region. | 0.701987 |
8,370,438 | 11 | 12 | 11. A non-transitory recording medium on which is recorded a program executed by a server for storing message information of messages of a user in a storage area and for allowing viewing of the messages in response to instructions of another user, the program causing the server to execute: receiving the messages of the user from a first game device via a network, the messages including only a plurality of predetermined useable items that are stored in a message preparation list and being restricted from including other items different than the plurality of predetermined useable items for limiting content of the messages, each of the messages including multiple ones of the plurality of predetermined usable items that are each independently selected by the user for enabling the content of the messages to be user-defined, each of the plurality of predetermined usable items of the messages being received in a first language; converting each of the plurality of predetermined usable items into a second language different than the first language:, receiving the instructions of the another user for viewing the messages; detecting a handle name of the another user in the instructions in response to receiving the instructions; confirming whether the handle name of the another user is stored in a friend list of the user, the friend list storing handle names of users who are allowed to view the messages; and transmitting one of the messages of the user to a second game device of the another user via the network when each of the instructions is received and it is confirmed that the handle name of the another user is stored in the friend list, the one of the messages of the user that is transmitted to the another user including the plurality of predetermined usable items that are converted into the second language, wherein the plurality of predetermined usable items include a plurality of words. | 11. A non-transitory recording medium on which is recorded a program executed by a server for storing message information of messages of a user in a storage area and for allowing viewing of the messages in response to instructions of another user, the program causing the server to execute: receiving the messages of the user from a first game device via a network, the messages including only a plurality of predetermined useable items that are stored in a message preparation list and being restricted from including other items different than the plurality of predetermined useable items for limiting content of the messages, each of the messages including multiple ones of the plurality of predetermined usable items that are each independently selected by the user for enabling the content of the messages to be user-defined, each of the plurality of predetermined usable items of the messages being received in a first language; converting each of the plurality of predetermined usable items into a second language different than the first language:, receiving the instructions of the another user for viewing the messages; detecting a handle name of the another user in the instructions in response to receiving the instructions; confirming whether the handle name of the another user is stored in a friend list of the user, the friend list storing handle names of users who are allowed to view the messages; and transmitting one of the messages of the user to a second game device of the another user via the network when each of the instructions is received and it is confirmed that the handle name of the another user is stored in the friend list, the one of the messages of the user that is transmitted to the another user including the plurality of predetermined usable items that are converted into the second language, wherein the plurality of predetermined usable items include a plurality of words. 12. The medium as set forth in claim 11 , wherein the plurality of predetermined useable items of the message preparation list is divided into a plurality of subsets. | 0.755882 |
7,593,843 | 8 | 10 | 8. The method of claim 1 , wherein calculating a score for each transfer mapping in the set of transfer mappings that describe a select node of the input semantic structure comprises: computing separate scores for a plurality of models; and combining the separate scores to determine the score for each transfer mapping that describe a select node of the input semantic structure. | 8. The method of claim 1 , wherein calculating a score for each transfer mapping in the set of transfer mappings that describe a select node of the input semantic structure comprises: computing separate scores for a plurality of models; and combining the separate scores to determine the score for each transfer mapping that describe a select node of the input semantic structure. 10. The method of claim 8 wherein the plurality of models comprises a fertility model that provides a probability of node deletion in a transfer mapping. | 0.846386 |
8,201,142 | 1 | 10 | 1. A method for creating a graph that defines a parallel processing job, comprising: reading code for building said graph, said code includes syntax for replication, pointwise connect, cross connect and merge, said pointwise connect connects point to point outputs from a first sub-graph to inputs of a second sub-graph, said pointwise connect further includes connecting a first output of said first sub-graph only to a first input of said second sub-graph, and connecting a second output of said first sub-graph only to a second input of said second sub-graph; building said graph based on said code, building said graph including creating a data structure storing a set of identifications of vertices corresponding to a set of program units to be executed, a set of identifications of edges corresponding to flow of data between the set of program units, a set of identifications of inputs and a set of identifications of outputs; populating one or more vertices into a vertex queue; determining at least one vertex in the vertex queue that are ready to be executed based on inputs associated with the at least one vertex; and creating an execution record associated with the at least one vertex, the execution record associated with the at least one vertex including a ready state associated with the at least one vertex. | 1. A method for creating a graph that defines a parallel processing job, comprising: reading code for building said graph, said code includes syntax for replication, pointwise connect, cross connect and merge, said pointwise connect connects point to point outputs from a first sub-graph to inputs of a second sub-graph, said pointwise connect further includes connecting a first output of said first sub-graph only to a first input of said second sub-graph, and connecting a second output of said first sub-graph only to a second input of said second sub-graph; building said graph based on said code, building said graph including creating a data structure storing a set of identifications of vertices corresponding to a set of program units to be executed, a set of identifications of edges corresponding to flow of data between the set of program units, a set of identifications of inputs and a set of identifications of outputs; populating one or more vertices into a vertex queue; determining at least one vertex in the vertex queue that are ready to be executed based on inputs associated with the at least one vertex; and creating an execution record associated with the at least one vertex, the execution record associated with the at least one vertex including a ready state associated with the at least one vertex. 10. A method according to claim 1 , further comprising: assigning execution of program units to different nodes of a distributed parallel processing engine based on said graph so that said program units execute in parallel, each of said program units correspond to a vertex of said graph. | 0.704312 |
10,061,818 | 8 | 9 | 8. A computer system for keyword searching, the computer system comprising: one or more computer processors; one or more computer readable storage media; and program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to collect user information associated with a keyword search, wherein the user information comprises object search information, holding time information, and selecting time information, wherein the selecting time information comprises information associated with a section of a document highlighted by a user when viewing the document; program instructions to store the collected user information associated with the keyword search in a memory; program instructions to receive an indication of a search of content for at least one keyword; program instructions to determine whether the at least one keyword is associated with the collected user information associated with the keyword search in the memory; and program instructions to, responsive to determining that the at least one keyword is associated with the collected user information associated with the keyword search in the memory, calculate a rank for the at least one keyword. | 8. A computer system for keyword searching, the computer system comprising: one or more computer processors; one or more computer readable storage media; and program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to collect user information associated with a keyword search, wherein the user information comprises object search information, holding time information, and selecting time information, wherein the selecting time information comprises information associated with a section of a document highlighted by a user when viewing the document; program instructions to store the collected user information associated with the keyword search in a memory; program instructions to receive an indication of a search of content for at least one keyword; program instructions to determine whether the at least one keyword is associated with the collected user information associated with the keyword search in the memory; and program instructions to, responsive to determining that the at least one keyword is associated with the collected user information associated with the keyword search in the memory, calculate a rank for the at least one keyword. 9. The computer system of claim 8 , further comprising: program instructions to, responsive to determining that the at least one keyword is not associated with the collected user information associated with the keyword search in the memory, search a hard disk for information associated with the at least one keyword. | 0.556022 |
8,793,253 | 3 | 5 | 3. The method of claim 1 , further comprising calculating similarity coefficients, based on one or more similarity measures, between some of partitions, assigned with the order l, using said at least one ordered data array. | 3. The method of claim 1 , further comprising calculating similarity coefficients, based on one or more similarity measures, between some of partitions, assigned with the order l, using said at least one ordered data array. 5. The method of claim 3 , wherein the similarity coefficients are used to assign or calculate scores for said partitions, from said set of partitions assigned with the order l, or the ontological subjects from said set of ontological subjects assigned with the order k. | 0.5 |
9,563,399 | 10 | 11 | 10. The method of claim 1 , wherein the plurality of node types includes a variable count node type and the examining includes examining the pattern for the variable count node type, and wherein examining the pattern for the variable count node type includes determining whether a portion of the pattern indicates matching for the element a variable number of times. | 10. The method of claim 1 , wherein the plurality of node types includes a variable count node type and the examining includes examining the pattern for the variable count node type, and wherein examining the pattern for the variable count node type includes determining whether a portion of the pattern indicates matching for the element a variable number of times. 11. The method of claim 10 , wherein the variable number of times is at least one of a finite number of times or an infinite number of times. | 0.5 |
8,464,234 | 26 | 31 | 26. A non-transitory computer readable storage medium having code stored thereon that, when executed by one or more processors, causes the one or more processors to perform operations comprising: scanning one or more header files on a computing device into a tokenized form and scanning the tokenized form for one or more symbols and creating one or more preprocessor symbol tables based upon the one or more symbols; parsing the tokenized form on the computing device into one or more abstract syntax trees; creating one or more pre-parsed headers for the one or more header files, by: serializing in a modular form, the one or more abstract syntax trees to a storage device; serializing in a modular form the tokenized form to the storage device; and serializing in a modular form the one or more preprocessor symbol tables to the storage device; locating the one or more pre-parsed headers from the storage device based upon directives in one or more source files; deserializing the one or more abstract syntax trees from the pre-parsed headers on the computing device; and compiling the one or more source files using the one or more abstract syntax trees on the computing device. | 26. A non-transitory computer readable storage medium having code stored thereon that, when executed by one or more processors, causes the one or more processors to perform operations comprising: scanning one or more header files on a computing device into a tokenized form and scanning the tokenized form for one or more symbols and creating one or more preprocessor symbol tables based upon the one or more symbols; parsing the tokenized form on the computing device into one or more abstract syntax trees; creating one or more pre-parsed headers for the one or more header files, by: serializing in a modular form, the one or more abstract syntax trees to a storage device; serializing in a modular form the tokenized form to the storage device; and serializing in a modular form the one or more preprocessor symbol tables to the storage device; locating the one or more pre-parsed headers from the storage device based upon directives in one or more source files; deserializing the one or more abstract syntax trees from the pre-parsed headers on the computing device; and compiling the one or more source files using the one or more abstract syntax trees on the computing device. 31. The non-transitory computer readable storage medium of claim 26 , wherein the operations further comprise: detecting a change in the one or more header files on the computing device; generating one or more new abstract syntax trees on the computing device for each of the one or more header files that has changed; and creating one or more new pre-parsed headers for each of the one or more header files that have changed, by serializing in a modular form, the one or more new abstract syntax trees to a storage device. | 0.63169 |
9,703,768 | 12 | 13 | 12. The method of claim 9 wherein the received query includes a select clause comprising the list of metadata keys. | 12. The method of claim 9 wherein the received query includes a select clause comprising the list of metadata keys. 13. The method of claim 12 wherein the received query includes a where clause comprising the predicates. | 0.5 |
8,977,536 | 1 | 26 | 1. A method comprising: executing instructions stored in memory via a processor of a language engine for: training the language engine to train for statistical machine translation; training the language engine when to use statistical machine translation by applying a machine learning method to a bilingual text that has been annotated with the output of a non-statistical translation component along with information identifying the type of the translation component; translating information from a first language to a second language using at least two translation components, wherein at least one translation component is a non-statistical translation component, each of the at least two translation components capable of translating equivalent phrases, each of the at least two translation components being selected based upon evaluation of an annotated training corpus, the annotated training corpus comprising substrings in the first language that have been annotated to associate the substrings with one or more translation components that are to be utilized to translate the substrings; and automatically selecting a preferred component from the at least two translation components, the preferred component providing a translation having a highest probability of being correct. | 1. A method comprising: executing instructions stored in memory via a processor of a language engine for: training the language engine to train for statistical machine translation; training the language engine when to use statistical machine translation by applying a machine learning method to a bilingual text that has been annotated with the output of a non-statistical translation component along with information identifying the type of the translation component; translating information from a first language to a second language using at least two translation components, wherein at least one translation component is a non-statistical translation component, each of the at least two translation components capable of translating equivalent phrases, each of the at least two translation components being selected based upon evaluation of an annotated training corpus, the annotated training corpus comprising substrings in the first language that have been annotated to associate the substrings with one or more translation components that are to be utilized to translate the substrings; and automatically selecting a preferred component from the at least two translation components, the preferred component providing a translation having a highest probability of being correct. 26. The method as in claim 1 , further comprising generating an annotated training corpus by: applying a plurality of translation components to substrings in a first language to translate the substrings into a second language; and annotating strings in a first language for each translation component that accurately translates the substring into a second language. | 0.5 |
9,910,849 | 1 | 2 | 1. A method of providing multilingual support, the method comprising: receiving, with a multilingual support system operating on a hardware computer system, a user-entered communication in a first language entered by a first user; determining that the user entered communication is in the first language and not in a predetermined standard language of the multilingual support system based on a first user profile that specifies the first language as a preferred language associated with the first user, wherein the predetermined standard language is a language used by the multilingual support system to store user-entered communications received in any one of a plurality of different languages; in response to the determination that user entered communication is in the first language and not in the predetermined standard language, causing execution of a first machine translation of the user-entered communication from the first language into the predetermined standard language of the multilingual support system; storing, in association with the user-entered communication in the first language, the first translation of the user-entered communication in the predetermined standard language; receiving, after the first machine translation, by the multilingual support system, a request to access the user-entered communication from a second user; determining, by the multilingual support system, that the request is a request to access the user-entered communication in a second language based on a second user profile associated with the second user; determining, by the multilingual support system, whether the second language is the same language as the first language or the predetermined standard language; in response to a determination that the second language is not the same language as the first language or the predetermined standard language, accessing a second machine translation of the user-entered communication in which the user-entered communication is translated from the first language into the second language; storing the translated user-entered communication in the second language in association with the user-entered communication in the first language and in the predetermined standard language; and providing the translated user-entered communication in the second language to the second user to at least partially satisfy the request. | 1. A method of providing multilingual support, the method comprising: receiving, with a multilingual support system operating on a hardware computer system, a user-entered communication in a first language entered by a first user; determining that the user entered communication is in the first language and not in a predetermined standard language of the multilingual support system based on a first user profile that specifies the first language as a preferred language associated with the first user, wherein the predetermined standard language is a language used by the multilingual support system to store user-entered communications received in any one of a plurality of different languages; in response to the determination that user entered communication is in the first language and not in the predetermined standard language, causing execution of a first machine translation of the user-entered communication from the first language into the predetermined standard language of the multilingual support system; storing, in association with the user-entered communication in the first language, the first translation of the user-entered communication in the predetermined standard language; receiving, after the first machine translation, by the multilingual support system, a request to access the user-entered communication from a second user; determining, by the multilingual support system, that the request is a request to access the user-entered communication in a second language based on a second user profile associated with the second user; determining, by the multilingual support system, whether the second language is the same language as the first language or the predetermined standard language; in response to a determination that the second language is not the same language as the first language or the predetermined standard language, accessing a second machine translation of the user-entered communication in which the user-entered communication is translated from the first language into the second language; storing the translated user-entered communication in the second language in association with the user-entered communication in the first language and in the predetermined standard language; and providing the translated user-entered communication in the second language to the second user to at least partially satisfy the request. 2. The method of claim 1 , wherein accessing the second machine translation comprises executing the second machine translation by accessing one of a plurality of translation sub-modules corresponding to different language input-and-output pairs, the accessed one of the plurality of sub-modules being a sub-module having the first language as an input and the second language as an output. | 0.561937 |
8,386,435 | 15 | 16 | 15. The method of claim 3 , wherein the metadata file includes values identifying a token value range index for selecting the compacted file. | 15. The method of claim 3 , wherein the metadata file includes values identifying a token value range index for selecting the compacted file. 16. The method of claim 15 , wherein the range index includes the minimum and maximum token values of the tokens that are stored in the associated compacted file. | 0.5 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.