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7,793,233 | 3 | 5 | 3. The method of claim 2 , further comprising displaying Icon options for the selected note flag. | 3. The method of claim 2 , further comprising displaying Icon options for the selected note flag. 5. The method of claim 3 , further comprising receiving a selection of an icon option. | 0.5 |
9,643,722 | 1 | 3 | 1. A system comprising; a. a security system; and b. a aerial drone device configured for acquiring content and communicating with the security system including receiving trigger location information from the security system, wherein the aerial drone device is configured to acquire an image of an object based on a database of template targets, including scanning an area and comparing the object in the area with the database of template targets to determine whether to acquire the image of the object, wherein the aerial drone device is configured to determine when to patrol an area by analyzing social networking information and detecting one or more keywords within the social networking information, wherein the one or more keywords are related to a location of the aerial drone device, wherein the aerial drone device includes one or more lights to indicate different situations based on the content acquired by the aerial drone device, wherein the aerial drone device comprises a nested aerial drone device including a first separable aerial drone device and a second separable aerial drone device, wherein each separable aerial drone device is configured to acquire separate information by traveling in different directions. | 1. A system comprising; a. a security system; and b. a aerial drone device configured for acquiring content and communicating with the security system including receiving trigger location information from the security system, wherein the aerial drone device is configured to acquire an image of an object based on a database of template targets, including scanning an area and comparing the object in the area with the database of template targets to determine whether to acquire the image of the object, wherein the aerial drone device is configured to determine when to patrol an area by analyzing social networking information and detecting one or more keywords within the social networking information, wherein the one or more keywords are related to a location of the aerial drone device, wherein the aerial drone device includes one or more lights to indicate different situations based on the content acquired by the aerial drone device, wherein the aerial drone device comprises a nested aerial drone device including a first separable aerial drone device and a second separable aerial drone device, wherein each separable aerial drone device is configured to acquire separate information by traveling in different directions. 3. The system of claim 1 wherein the security system is configured to detect a breach and send a signal to the aerial drone device, wherein when the breach is detected, the aerial drone device is configured to move to a location of the breach based on the trigger location information, further wherein the aerial drone device records video and takes pictures at the location of the breach. | 0.5 |
9,569,527 | 14 | 15 | 14. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: identifying a plurality of documents having one or more questions and, for each question, a corresponding answer; generating a plurality of question-answer pairs from the questions and respective corresponding answers occurring in the plurality of documents; training a statistical machine translation model using the plurality of question-answer pairs, including using each question of each question-answer pair as a source language input and a corresponding answer of the question-answer pair as a target language input, wherein each question and each corresponding answer are in the same natural language; translating, using the statistical machine translation model trained on the plurality of question-answer pairs, a phrase into one or more corresponding translated phrases; and determining one or more synonym pairs by comparing the phrase with the one or more corresponding translated phrases. | 14. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: identifying a plurality of documents having one or more questions and, for each question, a corresponding answer; generating a plurality of question-answer pairs from the questions and respective corresponding answers occurring in the plurality of documents; training a statistical machine translation model using the plurality of question-answer pairs, including using each question of each question-answer pair as a source language input and a corresponding answer of the question-answer pair as a target language input, wherein each question and each corresponding answer are in the same natural language; translating, using the statistical machine translation model trained on the plurality of question-answer pairs, a phrase into one or more corresponding translated phrases; and determining one or more synonym pairs by comparing the phrase with the one or more corresponding translated phrases. 15. The system of claim 14 , wherein determining one or more synonym pairs comprises: computing a translation likelihood for a phrase and a corresponding translated phrase; generating a synonym pair from a term in the phrase and a corresponding translated term in the corresponding translated phrase; assigning a score to the synonym pair, wherein the score is derived from the translation likelihood of the phrase and the corresponding translated phrase; and determining that the term and the corresponding translated term are synonyms using the assigned score of the synonym pair. | 0.5 |
7,596,578 | 15 | 18 | 15. The method in accordance with claim 14 , wherein the at least one expert is presented simultaneously as an expert in at least the first forum and the second forum. | 15. The method in accordance with claim 14 , wherein the at least one expert is presented simultaneously as an expert in at least the first forum and the second forum. 18. The method in accordance with claim 15 , wherein the at least one expert is one of an employee or a contractor of the third party sponsor. | 0.771704 |
9,612,032 | 8 | 11 | 8. A method for using a wall-mounted device for sensing and control for one or more systems in a home environment, said method comprising: detecting a user rotation of an outer ring that laterally surrounds a body of said device to form a circular lateral periphery of said device, said body having a circular cross-section, a wall-facing rear surface, and a user-facing front surface, said outer ring being user-rotatable around said body for enabling said user rotation, said device having a user-facing circular display component, said user-facing circular display component and said outer ring forming a user input component, wherein at least one environmental sensing component is disposed within said body of said device, wherein said device includes a communication component configured for providing wired or wireless sensing and/or control-related communications with said one or more systems in the home environment, wherein said device includes a processor in operative communication with said at least one environmental sensing component, said communication component, and said user input component; highlighting, based on said user rotation of said outer ring, respective ones of a circular arrangement of display elements appearing near a periphery of said user-facing circular display component; detecting an inward pressing of said outer ring, said outer ring being inwardly pressable for enabling said inward pressing; identifying as a user selection one of said display elements that is highlighted when said inward pressing of said outer ring is detected, wherein plural respective user selections of different ones of said display elements are identified responsive to repeated user rotations and/or inward pressings of said outer ring; and permitting user access to the control of one or more sensing or control functions of said device if said plural respective user selections corresponds to a password or combination. | 8. A method for using a wall-mounted device for sensing and control for one or more systems in a home environment, said method comprising: detecting a user rotation of an outer ring that laterally surrounds a body of said device to form a circular lateral periphery of said device, said body having a circular cross-section, a wall-facing rear surface, and a user-facing front surface, said outer ring being user-rotatable around said body for enabling said user rotation, said device having a user-facing circular display component, said user-facing circular display component and said outer ring forming a user input component, wherein at least one environmental sensing component is disposed within said body of said device, wherein said device includes a communication component configured for providing wired or wireless sensing and/or control-related communications with said one or more systems in the home environment, wherein said device includes a processor in operative communication with said at least one environmental sensing component, said communication component, and said user input component; highlighting, based on said user rotation of said outer ring, respective ones of a circular arrangement of display elements appearing near a periphery of said user-facing circular display component; detecting an inward pressing of said outer ring, said outer ring being inwardly pressable for enabling said inward pressing; identifying as a user selection one of said display elements that is highlighted when said inward pressing of said outer ring is detected, wherein plural respective user selections of different ones of said display elements are identified responsive to repeated user rotations and/or inward pressings of said outer ring; and permitting user access to the control of one or more sensing or control functions of said device if said plural respective user selections corresponds to a password or combination. 11. The method of claim 8 , wherein said user-facing front surface is configured such that said at least one environmental sensing component is substantially visually concealed from user view while being substantially exposed to said environmental condition being sensed. | 0.5 |
8,990,102 | 1 | 17 | 1. A method comprising: accessing at least one database on one or more processor readable media, by one or more processors, the at least one database comprising: electronic user information including at least one from a group consisting of a trait, a brand-specific preference, and a person-specific identifier of each of a plurality of persons; and electronic advertiser information comprising information associated with at least one branded product and/or service associated with at least one respective advertiser of a plurality of advertisers; receiving, via one or more communication devices that are operatively connected to the one or more processors, first electronic information from a first user computing device associated with a first user, wherein the first electronic information includes at least some user information associated with the first user and information representing at least a trait, a preference, and/or a person-specific identifier; defining, by the one or more processors and in accordance with the first electronic information, a first group of at least two respective persons of the plurality of persons, wherein the first group is custom to the first user; determining, by the one or more processors and in accordance with at least a relationship of at least some user information associated with the first user and the electronic advertiser information, a relevance of the first user to at least two advertisers of the plurality of advertisers; processing, by the one or more processors, to identify one respective person of the first group in accordance with information representing a previously received selection of the one respective person by the first user; selecting, by the one or more processors, one of the at least two advertisers based at least on a relevance of the one respective person of the first group to at least some of the user information representing at least one person's preference of a brand associated with the one of the at least two advertisers; generating, by the one or more processors, advertising information that includes the brand associated with the one of the at least two advertisers, and a person-specific identifier associated with the one respective person of the first group; and transmitting, via the one or more communication devices, by the one or more processors, at least some of the advertising information to the first user computing device. | 1. A method comprising: accessing at least one database on one or more processor readable media, by one or more processors, the at least one database comprising: electronic user information including at least one from a group consisting of a trait, a brand-specific preference, and a person-specific identifier of each of a plurality of persons; and electronic advertiser information comprising information associated with at least one branded product and/or service associated with at least one respective advertiser of a plurality of advertisers; receiving, via one or more communication devices that are operatively connected to the one or more processors, first electronic information from a first user computing device associated with a first user, wherein the first electronic information includes at least some user information associated with the first user and information representing at least a trait, a preference, and/or a person-specific identifier; defining, by the one or more processors and in accordance with the first electronic information, a first group of at least two respective persons of the plurality of persons, wherein the first group is custom to the first user; determining, by the one or more processors and in accordance with at least a relationship of at least some user information associated with the first user and the electronic advertiser information, a relevance of the first user to at least two advertisers of the plurality of advertisers; processing, by the one or more processors, to identify one respective person of the first group in accordance with information representing a previously received selection of the one respective person by the first user; selecting, by the one or more processors, one of the at least two advertisers based at least on a relevance of the one respective person of the first group to at least some of the user information representing at least one person's preference of a brand associated with the one of the at least two advertisers; generating, by the one or more processors, advertising information that includes the brand associated with the one of the at least two advertisers, and a person-specific identifier associated with the one respective person of the first group; and transmitting, via the one or more communication devices, by the one or more processors, at least some of the advertising information to the first user computing device. 17. The method of claim 1 , further comprising receiving, by the one or more processors from the first user computing device, a selection of the respective person of the at least two respective persons, and further wherein the determining the one respective person is in accordance with the selection. | 0.800662 |
9,230,220 | 1 | 7 | 1. A system configured to generate a situation-dependent library, comprising: at least one processor and at least one memory, the at least one processor and the at least one memory cooperating to function as: a machine learning trainer configured to receive samples comprising temporal windows of token instances to which a user was exposed and situation identifiers corresponding to situations the user was in while being exposed to the temporal windows; wherein the token instances have overlapping instantiation periods and are spread over a period of time that spans at least a day, and the situation identifiers comprise situation identifiers for first and second situations; the machine learning trainer is further configured to receive target values corresponding to the temporal windows of token instances; the target values represent affective responses of the user to the token instances from the temporal windows of token instances; the machine learning trainer is further configured to train first and second situation-dependent machine learning-based user response models based on respective first and second datasets; wherein the first and second datasets are obtained from partitioning the samples according to the situations the user was in when exposed to the temporal windows of token instances corresponding to the samples; and wherein the first dataset comprises samples comprising situation identifiers for the first situation and corresponding target values, and the second dataset comprises samples comprising situation identifiers for the second situation and corresponding target values; and a model analyzer configured to generate, based on the first and second situation-dependent machine learning-based user response models, the situation-dependent library which describes a first set of expected affective responses of the user to certain tokens while being in the first situation, and a second set of expected affective responses of the user to the certain tokens while being in the second situation; wherein the first set is not identical to the second set, and wherein at least some of the token instances from the temporal windows of token instances are instantiations of the certain tokens. | 1. A system configured to generate a situation-dependent library, comprising: at least one processor and at least one memory, the at least one processor and the at least one memory cooperating to function as: a machine learning trainer configured to receive samples comprising temporal windows of token instances to which a user was exposed and situation identifiers corresponding to situations the user was in while being exposed to the temporal windows; wherein the token instances have overlapping instantiation periods and are spread over a period of time that spans at least a day, and the situation identifiers comprise situation identifiers for first and second situations; the machine learning trainer is further configured to receive target values corresponding to the temporal windows of token instances; the target values represent affective responses of the user to the token instances from the temporal windows of token instances; the machine learning trainer is further configured to train first and second situation-dependent machine learning-based user response models based on respective first and second datasets; wherein the first and second datasets are obtained from partitioning the samples according to the situations the user was in when exposed to the temporal windows of token instances corresponding to the samples; and wherein the first dataset comprises samples comprising situation identifiers for the first situation and corresponding target values, and the second dataset comprises samples comprising situation identifiers for the second situation and corresponding target values; and a model analyzer configured to generate, based on the first and second situation-dependent machine learning-based user response models, the situation-dependent library which describes a first set of expected affective responses of the user to certain tokens while being in the first situation, and a second set of expected affective responses of the user to the certain tokens while being in the second situation; wherein the first set is not identical to the second set, and wherein at least some of the token instances from the temporal windows of token instances are instantiations of the certain tokens. 7. The system of claim 1 , wherein the machine learning trainer is further configured to train a maximum entropy model classifier, and the situation-dependent library comprises feature function weighting parameters. | 0.812718 |
8,219,599 | 25 | 26 | 25. A computer-implemented method for providing access to a knowledge base, comprising: receiving a natural language question as input; transmitting the natural language question to the knowledge base for translation to an internal query that represents an interpretation of the natural language question and has an internal format compatible with structured data of the knowledge base, the structured data representing first knowledge; and presenting a definitive natural language answer responsive to the natural language question received from the knowledge base and including second knowledge derived from the first knowledge in response to the internal query, the second knowledge not having been stored in the knowledge base prior to transmission of the natural language question to the knowledge base. | 25. A computer-implemented method for providing access to a knowledge base, comprising: receiving a natural language question as input; transmitting the natural language question to the knowledge base for translation to an internal query that represents an interpretation of the natural language question and has an internal format compatible with structured data of the knowledge base, the structured data representing first knowledge; and presenting a definitive natural language answer responsive to the natural language question received from the knowledge base and including second knowledge derived from the first knowledge in response to the internal query, the second knowledge not having been stored in the knowledge base prior to transmission of the natural language question to the knowledge base. 26. The method of claim 25 further comprising presenting a detailed presentation for the definitive natural language answer that includes additional information relating to one or more objects represented in the natural language answer. | 0.5 |
8,977,620 | 1 | 7 | 1. A computer-implemented method of classifying documents including executing instructions stored on a computer-readable medium, said method comprising: receiving a plurality of documents from at least one user, wherein each document includes at least one of unplanned information relating to a customer support issue and an indication of a sentiment; identifying at least one customer support issue or sentiment contained within each document by parsing the plurality of documents; classifying, using a classifier, at least a portion of the plurality of documents that satisfy a confidence threshold into one of a plurality of classes, each class associated with the identified at least one customer support issue or sentiment; clustering a remainder of the plurality of documents that do not satisfy the confidence threshold for the identified at least one customer support issue or sentiment into a plurality of clustered groups using a clustering engine, the clustering engine applying a word analysis; and outputting a frequency of each identified customer support issue or sentiment in each of the classes and clustered groups, the frequency based on said classifying or said clustering. | 1. A computer-implemented method of classifying documents including executing instructions stored on a computer-readable medium, said method comprising: receiving a plurality of documents from at least one user, wherein each document includes at least one of unplanned information relating to a customer support issue and an indication of a sentiment; identifying at least one customer support issue or sentiment contained within each document by parsing the plurality of documents; classifying, using a classifier, at least a portion of the plurality of documents that satisfy a confidence threshold into one of a plurality of classes, each class associated with the identified at least one customer support issue or sentiment; clustering a remainder of the plurality of documents that do not satisfy the confidence threshold for the identified at least one customer support issue or sentiment into a plurality of clustered groups using a clustering engine, the clustering engine applying a word analysis; and outputting a frequency of each identified customer support issue or sentiment in each of the classes and clustered groups, the frequency based on said classifying or said clustering. 7. A method in accordance with claim 1 , further comprising receiving by the clustering engine all documents that do not meet the confidence threshold. | 0.791436 |
9,465,996 | 1 | 3 | 1. A method for recording a media content event at a media device, the method comprising: receiving by the media device, the media content event in a broadcasted media content stream; recording the media content event by the media device; monitoring real time provided by a system clock of the media device; comparing the monitored real time with a closing credits monitor time; in response to detecting the monitored real time reaches the closing credits monitor time, grabbing a series of subsequently received image frames from the media content event that is being recorded after the monitored real time reaches the closing credits monitor time, wherein the closing credits monitor real time is a predefined duration before recording end time of the media content event; wherein for each of the grabbed subsequently received image frames, the method further comprising: analyzing by the media device, the image frame to identify text presented in the analyzed image frame; identifying by the media device, at least one attribute pertaining to the identified text; comparing by the media device, the at least one attribute with a corresponding predefined closing credits attribute, wherein the corresponding predefined closing credits attribute is stored in a memory medium; and determining that the identified text corresponds to closing credits of the media content event in response to the at least one attribute matches the corresponding predefined closing credits attribute; and initiating an end of the recording of the media content event in response to determining that the identified text corresponds to the closing credits of the media content event. | 1. A method for recording a media content event at a media device, the method comprising: receiving by the media device, the media content event in a broadcasted media content stream; recording the media content event by the media device; monitoring real time provided by a system clock of the media device; comparing the monitored real time with a closing credits monitor time; in response to detecting the monitored real time reaches the closing credits monitor time, grabbing a series of subsequently received image frames from the media content event that is being recorded after the monitored real time reaches the closing credits monitor time, wherein the closing credits monitor real time is a predefined duration before recording end time of the media content event; wherein for each of the grabbed subsequently received image frames, the method further comprising: analyzing by the media device, the image frame to identify text presented in the analyzed image frame; identifying by the media device, at least one attribute pertaining to the identified text; comparing by the media device, the at least one attribute with a corresponding predefined closing credits attribute, wherein the corresponding predefined closing credits attribute is stored in a memory medium; and determining that the identified text corresponds to closing credits of the media content event in response to the at least one attribute matches the corresponding predefined closing credits attribute; and initiating an end of the recording of the media content event in response to determining that the identified text corresponds to the closing credits of the media content event. 3. The method of claim 1 , wherein the corresponding predefined closing credits attribute is stored in the memory medium of the media device. | 0.938802 |
7,522,967 | 1 | 8 | 1. An audio processing method, comprising: identifying audio summaries of respective audio pieces, wherein each of the audio summaries comprises digital content summarizing at least a portion of the respective audio piece, and the identifying comprises for each of the audio pieces selecting constituent segments of the audio piece as its respective ones of the audio summaries and ranking its audio summaries into different levels of a respective audio summary hierarchy; determining transition audio segments each comprising a form of audio content that is different from the audio summaries and distinguishes the transition audio segment from the audio summaries; concatenating the transition audio segments and ones of the audio summaries ranked at a selected level of the audio summary hierarchies into a sequence in which at least one of the transition audio segments is between successive ones of the audio summaries; and rendering the sequence. | 1. An audio processing method, comprising: identifying audio summaries of respective audio pieces, wherein each of the audio summaries comprises digital content summarizing at least a portion of the respective audio piece, and the identifying comprises for each of the audio pieces selecting constituent segments of the audio piece as its respective ones of the audio summaries and ranking its audio summaries into different levels of a respective audio summary hierarchy; determining transition audio segments each comprising a form of audio content that is different from the audio summaries and distinguishes the transition audio segment from the audio summaries; concatenating the transition audio segments and ones of the audio summaries ranked at a selected level of the audio summary hierarchies into a sequence in which at least one of the transition audio segments is between successive ones of the audio summaries; and rendering the sequence. 8. The method of claim 1 , wherein at least one audio summary is linked to an associated audio piece by a browsable link. | 0.87155 |
9,529,343 | 17 | 18 | 17. A laser machine tool implemented method for examination of a processing operation to establish a proposal for improving at least one quality feature of a subsequent laser cutting operation in which an operator predetermines a quality feature for a dialogue system, the method comprising: establishing, by the dialogue system, at least one proposal for improving the quality feature using stored expert knowledge; and reading, by the dialogue system, data provided by a sensor system of the laser machine tool and image data of at least one laser cut edge of a processed metal sheet together with associated metal sheet material and processing data in order to establish the proposal. | 17. A laser machine tool implemented method for examination of a processing operation to establish a proposal for improving at least one quality feature of a subsequent laser cutting operation in which an operator predetermines a quality feature for a dialogue system, the method comprising: establishing, by the dialogue system, at least one proposal for improving the quality feature using stored expert knowledge; and reading, by the dialogue system, data provided by a sensor system of the laser machine tool and image data of at least one laser cut edge of a processed metal sheet together with associated metal sheet material and processing data in order to establish the proposal. 18. The method according to claim 17 , further comprising transmitting the data provided by the laser machine tool sensor system, the image data of at least one laser cut edge and the associated metal sheet material and processing data to the dialogue system using a telepresence portal. | 0.574184 |
7,587,412 | 12 | 22 | 12. A computer-implemented method for operation of a mixed media reality brokerage network, the method comprising: identifying electronic data from a customer; associating and optimizing the identified electronic data with a hot spot; securing a hot spot license; transferring a revenue model and content to a service bureau; interacting with users via service bureau; and collecting and distributing revenue generated by the interacting. | 12. A computer-implemented method for operation of a mixed media reality brokerage network, the method comprising: identifying electronic data from a customer; associating and optimizing the identified electronic data with a hot spot; securing a hot spot license; transferring a revenue model and content to a service bureau; interacting with users via service bureau; and collecting and distributing revenue generated by the interacting. 22. The method of claim 12 , wherein interacting with the users further comprises collecting information about whether a transaction was completed and the terms of the transaction. | 0.74212 |
9,015,182 | 1 | 5 | 1. A method for selecting at least one product record for embedding into a document and display with the document in a user interface, the method comprising: analyzing, with a computing device, at least a portion of the document, the analysis including at least a frequency of words in the document; constructing, with a computing device, a keyword query search string based on the analysis of the document, the keyword query search string at least partially based on words of the document having the highest frequencies; applying, with a computing device, the keyword query search string to a products database, the products database including a plurality of product records which include information regarding products, to identify at least one product record in the products database that satisfies the keyword query search string; selecting, with a computing device, at least one of the identified product records for embedding into the document and display in the user interface, and embedding, with a computing device, at least one of the selected product records into the document for display in the user interface, wherein the document is not stored within the products database. | 1. A method for selecting at least one product record for embedding into a document and display with the document in a user interface, the method comprising: analyzing, with a computing device, at least a portion of the document, the analysis including at least a frequency of words in the document; constructing, with a computing device, a keyword query search string based on the analysis of the document, the keyword query search string at least partially based on words of the document having the highest frequencies; applying, with a computing device, the keyword query search string to a products database, the products database including a plurality of product records which include information regarding products, to identify at least one product record in the products database that satisfies the keyword query search string; selecting, with a computing device, at least one of the identified product records for embedding into the document and display in the user interface, and embedding, with a computing device, at least one of the selected product records into the document for display in the user interface, wherein the document is not stored within the products database. 5. The method of claim 1 , wherein the user interface is a web page graphically rendered by a browser. | 0.677215 |
9,530,069 | 8 | 11 | 8. A computing system, comprising: a processor; and a memory including instructions that, when executed by the processor, cause the computing system to: receive an input image that includes at least one image variation; filter and segmenting the input image; select regions within the filtered and segmented input image having connected components; create a mask corresponding to the regions of connected components, the mask including bounding boxes that at least partially enclose corresponding regions of the connected components; intersect the filtered and segmented input image with the mask to produce a first output image; separately process the filtered and segmented input image corresponding to the mask to create a binary output image; separately recognize text in the first output image and in the binary output image using an optical character recognizer; and combine the separately recognized text from the first output image and from the binary output image to produce a single output. | 8. A computing system, comprising: a processor; and a memory including instructions that, when executed by the processor, cause the computing system to: receive an input image that includes at least one image variation; filter and segmenting the input image; select regions within the filtered and segmented input image having connected components; create a mask corresponding to the regions of connected components, the mask including bounding boxes that at least partially enclose corresponding regions of the connected components; intersect the filtered and segmented input image with the mask to produce a first output image; separately process the filtered and segmented input image corresponding to the mask to create a binary output image; separately recognize text in the first output image and in the binary output image using an optical character recognizer; and combine the separately recognized text from the first output image and from the binary output image to produce a single output. 11. The computing system of claim 8 , wherein the at least one image variation includes at least one of noise, blur, or a lighting variation. | 0.874555 |
9,323,838 | 1 | 2 | 1. A method comprising: extracting description information of multiple products; clustering the description information of the multiple products belonging to a particular model into a first text; processing the first text by segmenting the first text to one of remove from the first text one or more terms whose term frequencies are higher than a first set threshold, and remove from the first text one or more terms whose term frequencies are lower than a second set threshold; clustering, after processing the first text, first texts of products belonging to different models into a second text; applying a subject analysis to the second text to obtain one or more subjects; defining one or more names for the one or more subjects respectively; assigning a respective name of a respective subject correlated to description information of a respective product as an identifier of the respective product; and labeling the respective product by using the identifier, wherein the applying the subject analysis to the second text to obtain one or more subjects comprises: setting a number of subjects in one or more subject models; applying the subject analysis to the second text by using a text analysis method based on the one or more subject models; obtaining a number of subsets corresponding to the number of subjects from a set of terms in the second text, the number of subsets being equal to the number of subjects, a respective subset corresponding to a respective subject; and according to the respective subset that one or more terms in the description information of the products locate, correlating the description information of the products to the respective subject corresponding to the respective subset. | 1. A method comprising: extracting description information of multiple products; clustering the description information of the multiple products belonging to a particular model into a first text; processing the first text by segmenting the first text to one of remove from the first text one or more terms whose term frequencies are higher than a first set threshold, and remove from the first text one or more terms whose term frequencies are lower than a second set threshold; clustering, after processing the first text, first texts of products belonging to different models into a second text; applying a subject analysis to the second text to obtain one or more subjects; defining one or more names for the one or more subjects respectively; assigning a respective name of a respective subject correlated to description information of a respective product as an identifier of the respective product; and labeling the respective product by using the identifier, wherein the applying the subject analysis to the second text to obtain one or more subjects comprises: setting a number of subjects in one or more subject models; applying the subject analysis to the second text by using a text analysis method based on the one or more subject models; obtaining a number of subsets corresponding to the number of subjects from a set of terms in the second text, the number of subsets being equal to the number of subjects, a respective subset corresponding to a respective subject; and according to the respective subset that one or more terms in the description information of the products locate, correlating the description information of the products to the respective subject corresponding to the respective subset. 2. The method as recited in claim 1 , further comprising: prior to the extracting the description information of the multiple products, categorizing the multiple products, wherein the extracting the description information of the multiple products comprises extracting description information of multiple products under a particular category, and the second text includes the description information of the multiple products under the particular category. | 0.610445 |
8,225,343 | 11 | 12 | 11. The method of claim 10 , wherein total variance rankings are calculated at different time intervals within the gesture. | 11. The method of claim 10 , wherein total variance rankings are calculated at different time intervals within the gesture. 12. The method of claim 11 , wherein weights may be different at different intervals of time within the gesture. | 0.5 |
9,864,743 | 17 | 18 | 17. The method of claim 16 , further comprising: determining a relative ranking of each top word with respect to other top words that correspond to a same topic in which the relative ranking is based on a determined relevance of the respective top word with respect to its corresponding topic; and assigning a scalar to each of the top words according to the relative rank of the respective top word and according to the relationship of the respective top word with respect to the vocabulary of emotion synonym sets. | 17. The method of claim 16 , further comprising: determining a relative ranking of each top word with respect to other top words that correspond to a same topic in which the relative ranking is based on a determined relevance of the respective top word with respect to its corresponding topic; and assigning a scalar to each of the top words according to the relative rank of the respective top word and according to the relationship of the respective top word with respect to the vocabulary of emotion synonym sets. 18. The method of claim 17 , wherein determining the emotion weights includes determining one or more emotion weights by topic based on a sum of the scalars assigned to the top words of the respective topic. | 0.5 |
7,904,462 | 12 | 18 | 12. An article of manufacture comprising a computer readable storage medium having program instructions stored thereon that, in response to execution by a computer system, cause the computer system to perform operations including: receiving a first product description associated with a first product; receiving a second product description associated with a second product; selecting a rule set that defines a comparison between at least one token within a first set of attribute fields of the first product description and at least one token within a second set of attribute fields of a second product description, wherein the first set of attribute fields is different from the second set of attribute fields; evaluating the rule set in a first direction from the first set of attribute fields to the second set of attribute fields; evaluating the rule set in a second direction from the second set of attribute fields to the first set of attribute fields; and determining whether the first product is a duplicate of the second product in response to both evaluation operations. | 12. An article of manufacture comprising a computer readable storage medium having program instructions stored thereon that, in response to execution by a computer system, cause the computer system to perform operations including: receiving a first product description associated with a first product; receiving a second product description associated with a second product; selecting a rule set that defines a comparison between at least one token within a first set of attribute fields of the first product description and at least one token within a second set of attribute fields of a second product description, wherein the first set of attribute fields is different from the second set of attribute fields; evaluating the rule set in a first direction from the first set of attribute fields to the second set of attribute fields; evaluating the rule set in a second direction from the second set of attribute fields to the first set of attribute fields; and determining whether the first product is a duplicate of the second product in response to both evaluation operations. 18. The article of manufacture of claim 12 , wherein the program instructions, in response to execution by the computer system, further cause the computer system to execute a Jaccard algorithm that compares the at least one token within the first set of attribute fields with the at least one token within the second set of attribute fields. | 0.62362 |
9,672,815 | 25 | 26 | 25. The method of claim 24 , wherein step (a.2) comprises creating a set of Gaussian mixture models. | 25. The method of claim 24 , wherein step (a.2) comprises creating a set of Gaussian mixture models. 26. The method of claim 25 , wherein step (a.2) comprises creating the acoustic model selected from the group consisting of: context-independent model, context-dependent model, and triphone model. | 0.5 |
10,002,187 | 13 | 18 | 13. A computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a method comprising: generating a user interface that displays analysis results identified from within one or more social media data sources, the user interface comprising: (a) a first interface portion of the user interface comprising a list of one or more analysis results identified from within one or more social media data sources, an individual analysis result from among the one or more analysis results being selectable to display a set of terms associated with a selected individual analysis result in a second interface portion, (b) the second interface portion of the user interface comprising the set of terms, a first interface control, and a second interface control, the set of terms associated with the selected individual analysis result, the first interface control constraining a search to include themes that correspond to the selected individual analysis result, the second interface control constraining the search to exclude the themes that correspond to the selected individual analysis result, and (c) a third interface portion of the user interface comprising a set of one or more semantic filters selected according to the second interface portion; receiving a search criteria to perform a search of content from the one or more social media data sources; performing the search of the content from the one or more social media data sources to generate the list of the one or more analysis results, a volatility index corresponding to a level of commonality between two or more themes being generated for the one or more analysis results, the volatility index usable to automatically control creation of a new topic based at least in part upon a threshold value established for the volatility index, the level of commonality between the two or more themes is calculated by computing centroids for the two or more themes and determining distances between the centroids; displaying the list of one or more analysis results identified from within one or more social media data sources pertaining to the search criteria in the first interface portion of the user interface; receiving a selection of the first or second interface control in the second interface portion of the user interface corresponding to an application of a semantic filter, the semantic filter constraining the search of the content from the one or more social media data sources by: (a) adding the semantic filter to definition parameters for a new topic if the first interface control is selected; (b) adding the semantic filter to the set of one or more semantic filters in the third interface portion of the user interface if the second interface control is selected; and (c) performing a modified search of the content with application of the semantic filter, the modified search updating the list of one or more analysis results identified from within one or more social media data sources in the first interface portion of the user interface to either remove or add results in the first interface portion that pertain to the semantic filter; and creating the new topic based at least in part on the definition parameters, wherein the new topic corresponds to the search criteria and the semantic filter. | 13. A computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a method comprising: generating a user interface that displays analysis results identified from within one or more social media data sources, the user interface comprising: (a) a first interface portion of the user interface comprising a list of one or more analysis results identified from within one or more social media data sources, an individual analysis result from among the one or more analysis results being selectable to display a set of terms associated with a selected individual analysis result in a second interface portion, (b) the second interface portion of the user interface comprising the set of terms, a first interface control, and a second interface control, the set of terms associated with the selected individual analysis result, the first interface control constraining a search to include themes that correspond to the selected individual analysis result, the second interface control constraining the search to exclude the themes that correspond to the selected individual analysis result, and (c) a third interface portion of the user interface comprising a set of one or more semantic filters selected according to the second interface portion; receiving a search criteria to perform a search of content from the one or more social media data sources; performing the search of the content from the one or more social media data sources to generate the list of the one or more analysis results, a volatility index corresponding to a level of commonality between two or more themes being generated for the one or more analysis results, the volatility index usable to automatically control creation of a new topic based at least in part upon a threshold value established for the volatility index, the level of commonality between the two or more themes is calculated by computing centroids for the two or more themes and determining distances between the centroids; displaying the list of one or more analysis results identified from within one or more social media data sources pertaining to the search criteria in the first interface portion of the user interface; receiving a selection of the first or second interface control in the second interface portion of the user interface corresponding to an application of a semantic filter, the semantic filter constraining the search of the content from the one or more social media data sources by: (a) adding the semantic filter to definition parameters for a new topic if the first interface control is selected; (b) adding the semantic filter to the set of one or more semantic filters in the third interface portion of the user interface if the second interface control is selected; and (c) performing a modified search of the content with application of the semantic filter, the modified search updating the list of one or more analysis results identified from within one or more social media data sources in the first interface portion of the user interface to either remove or add results in the first interface portion that pertain to the semantic filter; and creating the new topic based at least in part on the definition parameters, wherein the new topic corresponds to the search criteria and the semantic filter. 18. The computer readable medium of claim 13 , wherein the new topic is stored as a vector value corresponding to the search criteria and the semantic filter. | 0.512346 |
8,689,117 | 4 | 5 | 4. The method of claim 1 , wherein: the particular content in the markup language document that is indicated by the comment tag includes conditional content that is conditionally displayed in a webpage represented by the markup language document depending on the value of the variable, where the conditional content is displayed if the variable holds the first value. | 4. The method of claim 1 , wherein: the particular content in the markup language document that is indicated by the comment tag includes conditional content that is conditionally displayed in a webpage represented by the markup language document depending on the value of the variable, where the conditional content is displayed if the variable holds the first value. 5. The method of claim 4 , wherein if the JavaScript code is not executed by the client computing device, then the conditional content is not displayed in the webpage as a result of the JavaScript code not being executed by the client computing device. | 0.5 |
9,208,515 | 8 | 10 | 8. The system of claim 7 , wherein the processor is to receive layout information associated with the plurality of element variants. | 8. The system of claim 7 , wherein the processor is to receive layout information associated with the plurality of element variants. 10. The system of claim 8 , wherein the layout information includes presentation information associated with the plurality of element variants. | 0.5 |
8,478,841 | 10 | 11 | 10. The computer implemented method of claim 9 , comprising: identifying a plurality of user channels, each associated with one of the plurality of users; and providing at least one of the plurality of user channels to the subscriber. | 10. The computer implemented method of claim 9 , comprising: identifying a plurality of user channels, each associated with one of the plurality of users; and providing at least one of the plurality of user channels to the subscriber. 11. The computer implemented method of claim 10 , comprising: receiving a request to link the subscriber with a user associated with at least one of the user channels. | 0.5 |
8,133,121 | 1 | 8 | 1. A process operable on one or more computers for arranging a plurality of game tables, said tables including changing information, comprising: displaying an active table; displaying a stacking component that provides at least a subset of said changing information about each of said plurality of game tables; updating said changing information on said tables; and updating said subset on said stacking component as said changing information changes; wherein said stacking component includes a grid for organizing and displaying information pertaining to said plurality of game tables; and further wherein said stacking component is configured such that selecting a row corresponding to one of said tables displays said table. | 1. A process operable on one or more computers for arranging a plurality of game tables, said tables including changing information, comprising: displaying an active table; displaying a stacking component that provides at least a subset of said changing information about each of said plurality of game tables; updating said changing information on said tables; and updating said subset on said stacking component as said changing information changes; wherein said stacking component includes a grid for organizing and displaying information pertaining to said plurality of game tables; and further wherein said stacking component is configured such that selecting a row corresponding to one of said tables displays said table. 8. A process according to claim 1 , further comprising displaying a timer in said stacking component, said timer including a table number and time to act for a corresponding table. | 0.647059 |
6,067,555 | 11 | 12 | 11. A document processor comprising: image information input means for inputting an electronic document described by a page description language, the page description language describing a black-and-white image having characters described by character code information and a highlight for the characters described by graphic code information; page layout determining means for determining a page layout of the electronic document input by said image information input means; graphic form detecting means for detecting the position of a highlighting graphic form described by said graphic code information in the page; character string designating means for designating a string of the character code information contained in said highlighting graphic form on the basis of both the result of the determination made by said page layout determining means and said position of the highlighting graphic form detected by said graphic form detecting means; color determining means for selecting a color different from black as a color to which the string of character code information designated by said character string designating means is to be colored; and means for converting the color of the string of character code information designated by said character string designating means into the color determined by said color determining means by inserting color code words into the electronic document. | 11. A document processor comprising: image information input means for inputting an electronic document described by a page description language, the page description language describing a black-and-white image having characters described by character code information and a highlight for the characters described by graphic code information; page layout determining means for determining a page layout of the electronic document input by said image information input means; graphic form detecting means for detecting the position of a highlighting graphic form described by said graphic code information in the page; character string designating means for designating a string of the character code information contained in said highlighting graphic form on the basis of both the result of the determination made by said page layout determining means and said position of the highlighting graphic form detected by said graphic form detecting means; color determining means for selecting a color different from black as a color to which the string of character code information designated by said character string designating means is to be colored; and means for converting the color of the string of character code information designated by said character string designating means into the color determined by said color determining means by inserting color code words into the electronic document. 12. A document processor according to claim 11, wherein said means for converting does not receive the character code information input by said image information input means that is not designated by said character string designating means. | 0.5 |
9,842,105 | 1 | 4 | 1. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to: receive a plurality of words; map each of the plurality of words; associate the mapped words to provide a plurality of phrases, each of the plurality of phrases having a representation of a first type; encode each of the plurality of phrases to provide a respective plurality of encoded phrases, each of the plurality of encoded phrases having a representation of a second type different than the first type; determine a value of each of the plurality of encoded phrases; and identify one or more phrases of the plurality of encoded phrases having a value exceeding a threshold. | 1. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to: receive a plurality of words; map each of the plurality of words; associate the mapped words to provide a plurality of phrases, each of the plurality of phrases having a representation of a first type; encode each of the plurality of phrases to provide a respective plurality of encoded phrases, each of the plurality of encoded phrases having a representation of a second type different than the first type; determine a value of each of the plurality of encoded phrases; and identify one or more phrases of the plurality of encoded phrases having a value exceeding a threshold. 4. The non-transitory computer-readable storage medium of claim 1 , wherein encoding each of the plurality of phrases to provide a respective plurality of encoded phrases comprises: for each phrase: adjusting a dimensionality of the phrase; and reconstructing the phrase to provide an encoded phrase. | 0.628713 |
8,046,736 | 1 | 2 | 1. A non-transitory computer-readable medium holding executable instructions for performing a method for generating executable code based on a user selection, the medium comprising: instructions for receiving the user selection via a graphical user interface (GUI), where the user selection is related to a processing choice used to generate a result on behalf of the user; instructions for generating dynamically typed programming language code using information about a state of the GUI, where the state of the GUI is related to the user selection or the processing choice; and instructions for storing the generated dynamically typed programming language code, where the stored generated dynamically typed programming language code reproduces the result by applying the user selection or the processing choice to information when the generated dynamically typed programming language code is executed. | 1. A non-transitory computer-readable medium holding executable instructions for performing a method for generating executable code based on a user selection, the medium comprising: instructions for receiving the user selection via a graphical user interface (GUI), where the user selection is related to a processing choice used to generate a result on behalf of the user; instructions for generating dynamically typed programming language code using information about a state of the GUI, where the state of the GUI is related to the user selection or the processing choice; and instructions for storing the generated dynamically typed programming language code, where the stored generated dynamically typed programming language code reproduces the result by applying the user selection or the processing choice to information when the generated dynamically typed programming language code is executed. 2. The computer-readable medium of claim 1 , wherein the information is data. | 0.8075 |
8,094,948 | 5 | 6 | 5. The method for classifying digital images of claim 1 , further comprising: determining an associated classification for each of the digital images based on the probability that a block vocabulary and a word vocabulary apply. | 5. The method for classifying digital images of claim 1 , further comprising: determining an associated classification for each of the digital images based on the probability that a block vocabulary and a word vocabulary apply. 6. The method for classifying digital images of claim 5 , further comprising: retrieving digital images searched by a query tag based on the word vocabulary. | 0.5 |
8,694,972 | 8 | 13 | 8. A system comprising: a storage device for storing: a class definition in a single language computing environment, wherein: the single language computing environment has a native object system, the class definition is used to instantiate a plurality of objects from a plurality of classes, the plurality of object are accessible in the single language computing environment, the plurality of classes are defined in a plurality of different types of foreign object systems, the foreign object systems comprise a first foreign object system, and the first foreign object system is hosted in a virtual machine; a processor for executing instructions for: implementing a mapping facility in the single language computing environment, bidirectionally mapping foreign metadata to single language computing environment metadata, wherein: the foreign metadata is associated with foreign objects created with the plurality of different types of foreign object systems, the single language computing environment metadata is created in a form supported by the single language computing environment, and the single language computing environment metadata is usable by the plurality of objects instantiated from the class definition, examining the first foreign class metadata, wherein the first foreign class metadata: is metadata for a first foreign class, is created in the first foreign object system, and describes how to access an instance of the foreign object system, creating new first foreign class metadata, the new first foreign class metadata: corresponding to the first foreign class metadata, and created in a form supported by the single language computing environment, and instantiating a first object instance, the first object instance: instantiated using the class definition, and referencing the new first foreign class metadata and the instance of the foreign class. | 8. A system comprising: a storage device for storing: a class definition in a single language computing environment, wherein: the single language computing environment has a native object system, the class definition is used to instantiate a plurality of objects from a plurality of classes, the plurality of object are accessible in the single language computing environment, the plurality of classes are defined in a plurality of different types of foreign object systems, the foreign object systems comprise a first foreign object system, and the first foreign object system is hosted in a virtual machine; a processor for executing instructions for: implementing a mapping facility in the single language computing environment, bidirectionally mapping foreign metadata to single language computing environment metadata, wherein: the foreign metadata is associated with foreign objects created with the plurality of different types of foreign object systems, the single language computing environment metadata is created in a form supported by the single language computing environment, and the single language computing environment metadata is usable by the plurality of objects instantiated from the class definition, examining the first foreign class metadata, wherein the first foreign class metadata: is metadata for a first foreign class, is created in the first foreign object system, and describes how to access an instance of the foreign object system, creating new first foreign class metadata, the new first foreign class metadata: corresponding to the first foreign class metadata, and created in a form supported by the single language computing environment, and instantiating a first object instance, the first object instance: instantiated using the class definition, and referencing the new first foreign class metadata and the instance of the foreign class. 13. The system of claim 8 , further comprising: a plurality of virtual machines loaded in the single language computing environment, each virtual machine hosting a different foreign object system. | 0.890869 |
9,195,735 | 8 | 9 | 8. An information extracting client configured to be capable of performing communication with an information extracting server having a local hot word storing unit in which a local hot word as a keyword within a local area indicating a range of a specific topic within a specific time interval, comprising: an input unit configured to accept a user text created by a user; a user keyword extracting unit configured to extract a user keyword included in the user text and a time of creation by the user of the user text; an identifying unit configured so as to specify the information of interest corresponding to the local hot word as the information of interest corresponding to the user text when the user keyword and the local hot word stored in the local hot word storing unit of the information extracting server match and the time of creation by the user is included in the time interval of the local hot word; and an annotating unit configured to annotate the user text with the information of interest. | 8. An information extracting client configured to be capable of performing communication with an information extracting server having a local hot word storing unit in which a local hot word as a keyword within a local area indicating a range of a specific topic within a specific time interval, comprising: an input unit configured to accept a user text created by a user; a user keyword extracting unit configured to extract a user keyword included in the user text and a time of creation by the user of the user text; an identifying unit configured so as to specify the information of interest corresponding to the local hot word as the information of interest corresponding to the user text when the user keyword and the local hot word stored in the local hot word storing unit of the information extracting server match and the time of creation by the user is included in the time interval of the local hot word; and an annotating unit configured to annotate the user text with the information of interest. 9. The information extracting client according to claim 8 , further comprising: a previous-next identifying unit configured to specify the information of interest of the previous and next user text created previously and next to the time of creation by the user of the original user text that is to be annotated with the information of interest; and a determining unit configured to determine whether or not the information of interest of the original user text and the previous and next information of interest belong to the same category, wherein the annotating unit annotates the original user text with the information of interest when the information of interest of the original user text and the previous and next information of interest are determined to belong to the same category. | 0.5 |
9,009,131 | 1 | 5 | 1. In a computer network system an improved method running on a server of said network system for performing document searches comprising the steps of: (a) initiating a search in response to a user's query from an input device, said query including a multiplicity of key words, with the words being searched one at a time through a word-indexed database; (b) eliminating duplicate documents from the results received from said search and sending these results to a smaller more relevant database; (c) initiating a secondary search of every document in said smaller more relevant database associated with the first of the multiplicity of key words, by means of searching the remaining key words through each document and noting in which document each key word appears, without regard to frequency of appearance; resulting in all combinations of key words in any document being identified and each document assigned a number indicating the number of key word appearances; (d) calculating a document relevancy factor as the percentage of key words appearing in each document as the number of key words found in the document disregarding word appearance frequency, divided by the number of key words employed in the search, times one hundred; (e) calculating a ranking number for each document that is the resultant of the total cumulative word count for all key words in the document multiplied by the document's relevancy factor, with higher numbers taking precedence over lower numbers; (f) repeating steps (a) through (e) above for the remaining words of said query; and, (g) sending the results back to the user. | 1. In a computer network system an improved method running on a server of said network system for performing document searches comprising the steps of: (a) initiating a search in response to a user's query from an input device, said query including a multiplicity of key words, with the words being searched one at a time through a word-indexed database; (b) eliminating duplicate documents from the results received from said search and sending these results to a smaller more relevant database; (c) initiating a secondary search of every document in said smaller more relevant database associated with the first of the multiplicity of key words, by means of searching the remaining key words through each document and noting in which document each key word appears, without regard to frequency of appearance; resulting in all combinations of key words in any document being identified and each document assigned a number indicating the number of key word appearances; (d) calculating a document relevancy factor as the percentage of key words appearing in each document as the number of key words found in the document disregarding word appearance frequency, divided by the number of key words employed in the search, times one hundred; (e) calculating a ranking number for each document that is the resultant of the total cumulative word count for all key words in the document multiplied by the document's relevancy factor, with higher numbers taking precedence over lower numbers; (f) repeating steps (a) through (e) above for the remaining words of said query; and, (g) sending the results back to the user. 5. The method of claim 1 in response to pre-programming the step of setting a document relevancy factor below which documents will be excluded from further processing. | 0.788071 |
8,515,894 | 8 | 10 | 8. A system to determine a probability that an email message is spam, the system comprising: one or more processors; machine-readable storage medium including instructions that are executable by the one or more processors; wherein the instructions include instructions to receive an email message; instructions to identify one or more words and/or phrases of the email message that are likely being obfuscated; and instructions to identify one or more obfuscation techniques that are being used to obfuscate the one or more words and/or phrases that are identified as likely being obfuscated; and instructions to determine a probability that the email message is spam in dependence on at least both of the following which particular one or more words and/or phrases are identified as likely being obfuscated, wherein identifying some particular words and/or phrases as likely being obfuscated increases the probability that the email message is spam more than identifying other particular words and/or phrases as likely being obfuscated, and which particular one or more obfuscation techniques are being used to obfuscate the one or more words and/or phrases that are identified as likely being obfuscated, wherein detecting use of some obfuscation techniques increases the probability that the email message is spam more than detecting use of other obfuscation techniques. | 8. A system to determine a probability that an email message is spam, the system comprising: one or more processors; machine-readable storage medium including instructions that are executable by the one or more processors; wherein the instructions include instructions to receive an email message; instructions to identify one or more words and/or phrases of the email message that are likely being obfuscated; and instructions to identify one or more obfuscation techniques that are being used to obfuscate the one or more words and/or phrases that are identified as likely being obfuscated; and instructions to determine a probability that the email message is spam in dependence on at least both of the following which particular one or more words and/or phrases are identified as likely being obfuscated, wherein identifying some particular words and/or phrases as likely being obfuscated increases the probability that the email message is spam more than identifying other particular words and/or phrases as likely being obfuscated, and which particular one or more obfuscation techniques are being used to obfuscate the one or more words and/or phrases that are identified as likely being obfuscated, wherein detecting use of some obfuscation techniques increases the probability that the email message is spam more than detecting use of other obfuscation techniques. 10. The system of claim 8 , wherein the instructions also include: instructions to deobfuscate each word or phrase of the text that is identified as likely being obfuscated, to produce deobfuscated text; and instructions to compare the deobfuscated text to text of one or more other messages known to be spam; wherein the instructions to determine a probability that the email message is spam also include instructions to determine the probability that the email message is spam also in dependence on results of the comparison of the deobfuscated text to text of one or more other messages known to be spam. | 0.570113 |
7,716,050 | 1 | 18 | 1. A computer-implemented method in which a computer system initiates execution of software instructions stored in memory, the computer-implemented method comprising: accepting text spellings of training words in a plurality of sets of training words, each set corresponding to a different one of a plurality of languages; for each of the sets of training words in the plurality, receiving pronunciations for the training words in the set, the pronunciations being characteristic of native speakers of the language of the set, the pronunciations also being in terms of subword units at least some of which are common to two or more of the languages; and training a single pronunciation estimator using data comprising the text spellings and the pronunciations of the training words; and calculating a single acoustic subword model for each subword unit, based on the pronunciations in the plurality of sets of training words, by mixing distributions of acoustic parameters representing the sounds of the subword unit in multiple languages when a subword unit is common to two or more languages. | 1. A computer-implemented method in which a computer system initiates execution of software instructions stored in memory, the computer-implemented method comprising: accepting text spellings of training words in a plurality of sets of training words, each set corresponding to a different one of a plurality of languages; for each of the sets of training words in the plurality, receiving pronunciations for the training words in the set, the pronunciations being characteristic of native speakers of the language of the set, the pronunciations also being in terms of subword units at least some of which are common to two or more of the languages; and training a single pronunciation estimator using data comprising the text spellings and the pronunciations of the training words; and calculating a single acoustic subword model for each subword unit, based on the pronunciations in the plurality of sets of training words, by mixing distributions of acoustic parameters representing the sounds of the subword unit in multiple languages when a subword unit is common to two or more languages. 18. The computer-implemented method of claim 1 , wherein mixing distributions of acoustic parameters from multiple languages comprises mixing Gaussian probability distributions of acoustic parameters from multiple languages. | 0.773279 |
8,694,887 | 3 | 4 | 3. The method of claim 2 , wherein the first and second subsets of the plurality of elements individually comprise contextual shortcuts further comprising text elements. | 3. The method of claim 2 , wherein the first and second subsets of the plurality of elements individually comprise contextual shortcuts further comprising text elements. 4. The method of claim 3 , further comprising receiving at the computing platform the selection by the user, wherein the computing platform comprises a server computing platform, and wherein the highlighting the second subset of the plurality of elements comprises highlighting the second subset of the plurality of elements at the server computing platform. | 0.5 |
9,710,944 | 1 | 2 | 1. A method for generating a low-resolution version of an electronic document at a content distribution system, the method comprising: from a content publishing application, receiving (i) a high-resolution version of the electronic document that comprises a plurality of high-resolution images and (ii) a markup language file associated with the high-resolution version of the electronic document, the markup language file comprising a plurality of annotations that each specify a resolution for a low-resolution version of a respective high-resolution image, the specified resolution identifying a maximum pixel width and pixel height resolution at which the respective image will be displayed on client devices having a particular resolution, wherein the low-resolution version of the electronic document is not received by the content distribution system from the content publishing application; creating, at the content distribution system, the low-resolution version of each respective high-resolution image of the plurality of high-resolution images based on the respective annotation of the plurality of annotations; generating, at the content distribution system, the low-resolution version of the electronic document using the created low-resolution image; and storing (i) the high-resolution version of the electronic document with the high-resolution image for distribution to a first plurality of client devices and (ii) the low-resolution version of the electronic document with the low-resolution image for distribution to a second plurality of client devices having the particular resolution. | 1. A method for generating a low-resolution version of an electronic document at a content distribution system, the method comprising: from a content publishing application, receiving (i) a high-resolution version of the electronic document that comprises a plurality of high-resolution images and (ii) a markup language file associated with the high-resolution version of the electronic document, the markup language file comprising a plurality of annotations that each specify a resolution for a low-resolution version of a respective high-resolution image, the specified resolution identifying a maximum pixel width and pixel height resolution at which the respective image will be displayed on client devices having a particular resolution, wherein the low-resolution version of the electronic document is not received by the content distribution system from the content publishing application; creating, at the content distribution system, the low-resolution version of each respective high-resolution image of the plurality of high-resolution images based on the respective annotation of the plurality of annotations; generating, at the content distribution system, the low-resolution version of the electronic document using the created low-resolution image; and storing (i) the high-resolution version of the electronic document with the high-resolution image for distribution to a first plurality of client devices and (ii) the low-resolution version of the electronic document with the low-resolution image for distribution to a second plurality of client devices having the particular resolution. 2. The method of claim 1 , wherein the high-resolution version of the electronic document is received from a device that is utilized to author the document. | 0.912063 |
7,590,606 | 1 | 15 | 1. A system for analyzing a mishap that has occurred, the system comprising: a reconfigurable ontology associated with a selected mishap, including a list of at least first and second ontology classes related to the selected mishap, at least one definition or property for each of the at least two ontology classes, a value range associated with each of the at least two ontology classes, and at least one relationship or link between the at least two ontology classes, wherein at least one of the at least first and second ontology classes includes information on at least one of the following: a collection of one or more persons assembled to investigate the mishap; a project with which the mishap is associated; a process or procedure associated with the mishap; at least one person involved in or responsible one or more events leading directly to the mishap; at least one location or site associated with the mishap; a characterization of the mishap; a record associated with the mishap; a document associated with the mishap; physical evidence associated with the mishap; a value of a parameter that is part of a description associated with the mishap; a characterization or classification of a sub-system associated with the mishap; an interview of at least one person associated with the mishap; a description of at least one operation associated with the mishap; at least one inspection associated with the mishap; at least one design record of at least one component associated with the mishap; an analysis of at least one aspect of the mishap; and at least one result of an investigation of the mishap; a semantic network that receives, indexes, stores and integrates, for retrieval, the at least two ontology classes, the definition and the value ranges of the at least two ontology classes and the at least one link between the at least two ontology classes; a network browser interface, having a display screen, that implements a procedure for retrieving and viewing each of the at least two ontology classes in the semantic network, wherein the browser interface (i) displays at least one screen having at least a first group and a second group of possible conclusions concerning a contributing factor to the mishap, where no possible conclusion in the first group also belongs to the second group and (ii) displays at least one conclusion in the first group or in the second group that is characterized as at least one of the following: not a credible conclusion; an unlikely conclusion; a credible conclusion; conclusion needs analysis; conclusion needs supporting data; conclusion proposed to be closed; and an un-reviewed conclusion; and a rule-based inference engine, including a collection of at least two rules, associated with one or more of the at least two ontology classes and applied to support the at least one conclusion displayed in the browser interface. | 1. A system for analyzing a mishap that has occurred, the system comprising: a reconfigurable ontology associated with a selected mishap, including a list of at least first and second ontology classes related to the selected mishap, at least one definition or property for each of the at least two ontology classes, a value range associated with each of the at least two ontology classes, and at least one relationship or link between the at least two ontology classes, wherein at least one of the at least first and second ontology classes includes information on at least one of the following: a collection of one or more persons assembled to investigate the mishap; a project with which the mishap is associated; a process or procedure associated with the mishap; at least one person involved in or responsible one or more events leading directly to the mishap; at least one location or site associated with the mishap; a characterization of the mishap; a record associated with the mishap; a document associated with the mishap; physical evidence associated with the mishap; a value of a parameter that is part of a description associated with the mishap; a characterization or classification of a sub-system associated with the mishap; an interview of at least one person associated with the mishap; a description of at least one operation associated with the mishap; at least one inspection associated with the mishap; at least one design record of at least one component associated with the mishap; an analysis of at least one aspect of the mishap; and at least one result of an investigation of the mishap; a semantic network that receives, indexes, stores and integrates, for retrieval, the at least two ontology classes, the definition and the value ranges of the at least two ontology classes and the at least one link between the at least two ontology classes; a network browser interface, having a display screen, that implements a procedure for retrieving and viewing each of the at least two ontology classes in the semantic network, wherein the browser interface (i) displays at least one screen having at least a first group and a second group of possible conclusions concerning a contributing factor to the mishap, where no possible conclusion in the first group also belongs to the second group and (ii) displays at least one conclusion in the first group or in the second group that is characterized as at least one of the following: not a credible conclusion; an unlikely conclusion; a credible conclusion; conclusion needs analysis; conclusion needs supporting data; conclusion proposed to be closed; and an un-reviewed conclusion; and a rule-based inference engine, including a collection of at least two rules, associated with one or more of the at least two ontology classes and applied to support the at least one conclusion displayed in the browser interface. 15. The system of claim 1 , wherein said information on said sub-system of said mishap includes information on at least one of the following: at least one design for a project associated with said mishap; at least one design record for the project; at least one analysis of at least one design for the project; at least one preceding record of a preceding mishap; at least one risk assessment for the project; at least one test and verification record for the project; and at least one integration record for the project. | 0.663437 |
7,546,581 | 9 | 11 | 9. A computer-readable medium, storing instructions that, when executed by a processor, cause the processor to emulate a sequence of actions performed by a user when interacting with a computer aided design (CAD) application, by performing the steps of: parsing a first instruction including a context prefix and a context block expression, wherein the context prefix specifies one or more contexts and the context block expression specifies one or more operations to perform with respect to one or more graphics components; parsing a first context of the context prefix into a first user input mode and a first operational state associated with the first user input mode; parsing a second context of the context prefix into a second user input mode and a second operational state associated with the second user input mode; setting the CAD application to operate using the first user input mode and the first operational state; executing the one or more operations specified by the context block expression using the first user input mode and the first operational state; setting the CAD application to operate using the second user input mode and the second operational state; and executing the one or more operations specified by the context block expression using the second user input mode and the second operational state. | 9. A computer-readable medium, storing instructions that, when executed by a processor, cause the processor to emulate a sequence of actions performed by a user when interacting with a computer aided design (CAD) application, by performing the steps of: parsing a first instruction including a context prefix and a context block expression, wherein the context prefix specifies one or more contexts and the context block expression specifies one or more operations to perform with respect to one or more graphics components; parsing a first context of the context prefix into a first user input mode and a first operational state associated with the first user input mode; parsing a second context of the context prefix into a second user input mode and a second operational state associated with the second user input mode; setting the CAD application to operate using the first user input mode and the first operational state; executing the one or more operations specified by the context block expression using the first user input mode and the first operational state; setting the CAD application to operate using the second user input mode and the second operational state; and executing the one or more operations specified by the context block expression using the second user input mode and the second operational state. 11. The computer-readable medium of claim 9 , wherein a first input mode type associated with the first user input mode is a dimensional coordinate system user input mode type, an animate user input mode type, a center point user input mode type, or a frame time user input mode type, wherein a second input mode type associated with the second user input mode is a dimensional coordinate system user input mode type, an animate user input mode type, a center point user input mode type, or a frame time user input mode type, and wherein the first input mode type is different from the second input mode type. | 0.5 |
7,693,842 | 13 | 14 | 13. A machine implemented method for effectuating in situ search for active note taking, comprising: receiving and recognizing a gesture from an input device identifying at least one inked text; generating an embeddable graphical object and associating the embeddable graphical object with the at least one handwritten script, the embeddable graphical object being associated with recognized query text and/or a number of results returned in response to the recognized query text and additional embeddable graphical objects, the additional embeddable graphical objects being associated with disparate functions; employing a tracking menu comprising: a scroll ring that receives pseudo-circular motion from the input device and translates the motion into vertical or horizontal scrolling in a focus application of a system manager window; a capture tool that allows a user to circumscribe an area of a display; a close box that dismisses the tracking menu; and a move handle for dragging the tracking menu to a new position, the tracking menu providing cross application functionality between disparate applications; digitizing and analyzing the at least one handwritten script; initiating a search with the digitized and analyzed at least one handwritten script to return results; coupling the results with the embeddable graphical object; and inserting the embeddable graphical object in close proximity to the at least one handwritten script. | 13. A machine implemented method for effectuating in situ search for active note taking, comprising: receiving and recognizing a gesture from an input device identifying at least one inked text; generating an embeddable graphical object and associating the embeddable graphical object with the at least one handwritten script, the embeddable graphical object being associated with recognized query text and/or a number of results returned in response to the recognized query text and additional embeddable graphical objects, the additional embeddable graphical objects being associated with disparate functions; employing a tracking menu comprising: a scroll ring that receives pseudo-circular motion from the input device and translates the motion into vertical or horizontal scrolling in a focus application of a system manager window; a capture tool that allows a user to circumscribe an area of a display; a close box that dismisses the tracking menu; and a move handle for dragging the tracking menu to a new position, the tracking menu providing cross application functionality between disparate applications; digitizing and analyzing the at least one handwritten script; initiating a search with the digitized and analyzed at least one handwritten script to return results; coupling the results with the embeddable graphical object; and inserting the embeddable graphical object in close proximity to the at least one handwritten script. 14. The method of claim 13 , further comprising displaying a directional stroke labeled with a short textual description that indicates a permissible gesture. | 0.570652 |
8,185,396 | 19 | 21 | 19. A computing device comprising: a processor; and memory interconnected with said processor storing instructions for facilitating text-to-speech conversion of a domain name having a top level domain and at least one other level domain that, when executed by said processor, cause said device to: determine a pronunciation of said top level domain based at least in part upon whether said top level domain is one of a predetermined set of top level domains; and for each of said at least one other level domain: search for one or more recognized words within said other level domain; and further determine a pronunciation of said other level domain based at least in part on an outcome of said search, wherein said set represents top level domains that are pronounced as a whole and wherein said determining said pronunciation of said top level domain comprises, if said top level domain is not one of said predetermined set of top level domains, generating a phonetic representation of each character in said top level domain pronounced individually or generating a tokenized representation of each individual character of said top level domain suitable for interpretation by a text-to-speech engine. | 19. A computing device comprising: a processor; and memory interconnected with said processor storing instructions for facilitating text-to-speech conversion of a domain name having a top level domain and at least one other level domain that, when executed by said processor, cause said device to: determine a pronunciation of said top level domain based at least in part upon whether said top level domain is one of a predetermined set of top level domains; and for each of said at least one other level domain: search for one or more recognized words within said other level domain; and further determine a pronunciation of said other level domain based at least in part on an outcome of said search, wherein said set represents top level domains that are pronounced as a whole and wherein said determining said pronunciation of said top level domain comprises, if said top level domain is not one of said predetermined set of top level domains, generating a phonetic representation of each character in said top level domain pronounced individually or generating a tokenized representation of each individual character of said top level domain suitable for interpretation by a text-to-speech engine. 21. The computing device of claim 19 wherein said determining said pronunciation for said top level domain is further based upon whether said top level domain has at least a threshold number of characters. | 0.772222 |
8,234,693 | 1 | 5 | 1. A method for providing secure document management, comprising: receiving a document from a user having an associated security access profile; generating a security label to be stored as an attribute of the document, the security label comprising: a clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of the plurality of clearance components determined based on the security access profile associated with the user; and a secondary security component selected from an authorized subset of a plurality of secondary security components, the authorized subset of the plurality of secondary security components determined based on the clearance component of the security label and the security access profile associated with the user; storing the document in a document repository storing a plurality of documents each having an associated security label; determining whether a third-party user is authorized access the document based on a comparison of a security access profile of the third-party user and the security label associated with the document; allowing, when a determination that the third-party user is authorized to access the document based on the comparison of the security access profile of the third-party user and the security label associated with the document, the third-party user to access the document: receiving an edited version of the document from the third-party user, the edited version of the document having an associated updated security label, the updated security label comprising: an updated clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of a plurality of clearance components determined based on the security access profile associated with the third-party user; and one or more updated secondary security components selected from a subset of a plurality of secondary security components, the subset of a plurality of secondary security components determined based on the updated clearance component of the updated security label and the security access profile associated with the third-party user; and storing the edited version of the document in the document repository storing the plurality of documents each having an associated security label. | 1. A method for providing secure document management, comprising: receiving a document from a user having an associated security access profile; generating a security label to be stored as an attribute of the document, the security label comprising: a clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of the plurality of clearance components determined based on the security access profile associated with the user; and a secondary security component selected from an authorized subset of a plurality of secondary security components, the authorized subset of the plurality of secondary security components determined based on the clearance component of the security label and the security access profile associated with the user; storing the document in a document repository storing a plurality of documents each having an associated security label; determining whether a third-party user is authorized access the document based on a comparison of a security access profile of the third-party user and the security label associated with the document; allowing, when a determination that the third-party user is authorized to access the document based on the comparison of the security access profile of the third-party user and the security label associated with the document, the third-party user to access the document: receiving an edited version of the document from the third-party user, the edited version of the document having an associated updated security label, the updated security label comprising: an updated clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of a plurality of clearance components determined based on the security access profile associated with the third-party user; and one or more updated secondary security components selected from a subset of a plurality of secondary security components, the subset of a plurality of secondary security components determined based on the updated clearance component of the updated security label and the security access profile associated with the third-party user; and storing the edited version of the document in the document repository storing the plurality of documents each having an associated security label. 5. The method of claim 1 , wherein the security label comprises an W1classified component, the unclassified component being independent of the security access profile of the user, the clearance component of the security label, and the one or more secondary security components of the security label. | 0.859756 |
9,811,513 | 16 | 17 | 16. The system of claim 12 , wherein retrieving, from the at least one configuration file, information identifying the first annotation structure comprises: determining that the first and second types of the first and second data objects are different types; and retrieving the plurality of annotation structures associated with data objects of the first and second types. | 16. The system of claim 12 , wherein retrieving, from the at least one configuration file, information identifying the first annotation structure comprises: determining that the first and second types of the first and second data objects are different types; and retrieving the plurality of annotation structures associated with data objects of the first and second types. 17. The system of claim 16 , wherein retrieving the plurality of annotation structures comprises: determining that a respective number of the first and second data objects received in the request is within a specified range associated with the first and second data types in the corresponding annotation structure, respectively; and if so, retrieving an identification of the plurality of annotation structures associated with data objects of the first and second types. | 0.5 |
9,300,682 | 1 | 4 | 1. A method for use in analyzing executable content within at least one network of an enterprise, the method comprising: receiving multiple instances of executable content at a central analysis server over at least one network of an enterprise via at least one of a plurality of collection agents disposed within the at least one network, the at least one of the plurality of collection agents remote from and in operative communication with the central analysis server; extracting, by a hardware processor of the central analysis server, one or more characteristics from each instance of the received executable content; identifying, by the hardware processor, associations among the extracted characteristics; determining, based on the associations among the extracted characteristics, that a first portion of executable content is associated with a non-trusted entity; obtaining a hash value of the first portion of executable content and storing the hash value and the associated extracted characteristics to create a non-trusted entity profile; storing the extracted characteristics, identified associations, and hash value in a database of the central analysis server, the database accessible by the plurality of collection agents such that each of the plurality of collection agents is operable to identify at least another portion of executable content associated with the non-trusted entity based on the hash value that has been recognized and presented in the database; and receiving, by the central analysis server, an indication of notice from one of the plurality of collection agents indicative of a detection of the at least another portion of executable content associated with the non-trusted entity at the one of the plurality of collection agents, the indication comprising the hash value, location information but not a copy of the at least another portion of executable content to limit use of enterprise infrastructure resources and so as to update the non-trusted entity profile. | 1. A method for use in analyzing executable content within at least one network of an enterprise, the method comprising: receiving multiple instances of executable content at a central analysis server over at least one network of an enterprise via at least one of a plurality of collection agents disposed within the at least one network, the at least one of the plurality of collection agents remote from and in operative communication with the central analysis server; extracting, by a hardware processor of the central analysis server, one or more characteristics from each instance of the received executable content; identifying, by the hardware processor, associations among the extracted characteristics; determining, based on the associations among the extracted characteristics, that a first portion of executable content is associated with a non-trusted entity; obtaining a hash value of the first portion of executable content and storing the hash value and the associated extracted characteristics to create a non-trusted entity profile; storing the extracted characteristics, identified associations, and hash value in a database of the central analysis server, the database accessible by the plurality of collection agents such that each of the plurality of collection agents is operable to identify at least another portion of executable content associated with the non-trusted entity based on the hash value that has been recognized and presented in the database; and receiving, by the central analysis server, an indication of notice from one of the plurality of collection agents indicative of a detection of the at least another portion of executable content associated with the non-trusted entity at the one of the plurality of collection agents, the indication comprising the hash value, location information but not a copy of the at least another portion of executable content to limit use of enterprise infrastructure resources and so as to update the non-trusted entity profile. 4. The method of claim 1 , further comprising: updating the non-trusted entity profile based on at least one of the identified associations, wherein the non-trusted entity profile identifies at least one entity associated with the executable content linked to the at least one association, the at least one entity including the non-trusted entity. | 0.629274 |
8,090,713 | 1 | 16 | 1. A computer-implemented method, comprising: receiving, at a server device and from a client device, a search query entered on the client device by a user; determining, using the server device, that the user belongs to at least a first population group; determining, using the server device, that at least a first article is responsive to the search query; determining, using the server device, an interest value reflecting an interest of the first population group in the first article, the interest value based on at least one selection of the first article made when the first article was previously presented to at least one member of the first population group in response to an earlier search query identical to the search query; determining, using the server device, a first ranking score for the first article, the first ranking score based at least in part on the interest value; and outputting a search result from the server device to the client device in response to the search query, the first article ranked in the search result according to the first ranking score. | 1. A computer-implemented method, comprising: receiving, at a server device and from a client device, a search query entered on the client device by a user; determining, using the server device, that the user belongs to at least a first population group; determining, using the server device, that at least a first article is responsive to the search query; determining, using the server device, an interest value reflecting an interest of the first population group in the first article, the interest value based on at least one selection of the first article made when the first article was previously presented to at least one member of the first population group in response to an earlier search query identical to the search query; determining, using the server device, a first ranking score for the first article, the first ranking score based at least in part on the interest value; and outputting a search result from the server device to the client device in response to the search query, the first article ranked in the search result according to the first ranking score. 16. The method of claim 1 , wherein the interest value comprises a number of members of the first population group that input the search query. | 0.870939 |
8,396,815 | 11 | 16 | 11. A system for process automation, comprising: a processor comprising: a screen scraper module; a monitoring agent for monitoring one or more workstations including monitoring screen contents and user actions at the workstations by executing the screen scraper module to obtain a dynamically updated current set of character and graphical information from screens of the workstations that includes user-entered data and retrieved screen data; a current set module for analyzing the current set to identify monitored functional events; a focal state provider for defining multiple focal states as sequences of functional events and a facilitating script provider providing one or more facilitating scripts associated with respective ones of the focal states, wherein the current set comprises time intervals associated with the user actions, respectively and the sequences of functional events of at least a portion of the focal states include the time intervals and wherein the facilitating scripts each provide one or more automatic actions; a matching module for matching a sequence of monitored functional events to the sequence of functional events of one of the focal states; and an applying module for applying the one or more automatic actions of the facilitating script associated with the one focal state. | 11. A system for process automation, comprising: a processor comprising: a screen scraper module; a monitoring agent for monitoring one or more workstations including monitoring screen contents and user actions at the workstations by executing the screen scraper module to obtain a dynamically updated current set of character and graphical information from screens of the workstations that includes user-entered data and retrieved screen data; a current set module for analyzing the current set to identify monitored functional events; a focal state provider for defining multiple focal states as sequences of functional events and a facilitating script provider providing one or more facilitating scripts associated with respective ones of the focal states, wherein the current set comprises time intervals associated with the user actions, respectively and the sequences of functional events of at least a portion of the focal states include the time intervals and wherein the facilitating scripts each provide one or more automatic actions; a matching module for matching a sequence of monitored functional events to the sequence of functional events of one of the focal states; and an applying module for applying the one or more automatic actions of the facilitating script associated with the one focal state. 16. The system as claimed in claim 11 , wherein the focal state provider: analyses monitored screen contents and user actions to determine repeated functional events; and automatically defines a focal state as a sequence of the monitored functional events. | 0.628986 |
9,122,950 | 18 | 30 | 18. An auto-segmentation apparatus comprising: a processor configured to: perform atlas-based auto-segmentation on a plurality of points in a subject image using atlas images to generate first data representative of at least one structure in the subject image, wherein the processor is further configured to perform the atlas-based auto-segmentation by registering the subject image with a plurality of the atlas images to map point of the subject images to points of the atlas images, apply a plurality of points in the subject image to a trained classifier to generate second data representative of the a least one structure in the subject image, combine the first data with the second data to generate third data representative of the at least one structure in the subject image, and determine based on the data structure classification associated with the subject image. | 18. An auto-segmentation apparatus comprising: a processor configured to: perform atlas-based auto-segmentation on a plurality of points in a subject image using atlas images to generate first data representative of at least one structure in the subject image, wherein the processor is further configured to perform the atlas-based auto-segmentation by registering the subject image with a plurality of the atlas images to map point of the subject images to points of the atlas images, apply a plurality of points in the subject image to a trained classifier to generate second data representative of the a least one structure in the subject image, combine the first data with the second data to generate third data representative of the at least one structure in the subject image, and determine based on the data structure classification associated with the subject image. 30. The apparatus of claim 18 , wherein each atlas image comprises a plurality of points, each atlas image point being associated with a label indicative of whether the associated atlas image point is classified as the at least one structure, wherein registering the subject image with a plurality of the atlas images associates the registered subject image points with the labels that are associated with the atlas image points that were mapped to the registered subject image points, and wherein the processor is further configured to generate the first data by combining the labels associated with the registered subject image points according to a lab& fusion technique. | 0.517192 |
8,417,695 | 11 | 15 | 11. An apparatus comprising: a memory; and one or more processors configured to: use structural parsing to extract information from user input comprising a URL or domain name, the information comprising one or more of a protocol, a location, and a subdirectory, wherein structural parsing comprises; determining whether the domain name can be mapped to one or more concepts in the concept association map by switching term positions or changing numbers; when the domain name can be mapped and if the mapped concepts have high score, identifying the concepts as seed concepts for further querying the concept association map; when the mapped concepts do not have a high enough score, or the domain name cannot be mapped, then determining whether the input domain name can be mapped to a concept in the concept association map by typographical error correction, the correction comprising one or more of insertion, deletion, and switching or replacement of 1 or 2 characters; and when the input domain name cannot be mapped by typographical error correction, or if concepts mapped as a result of typographical error correction do not have a high score, determining how to break the domain name into URL tokens by inserting separators at correction positions and correcting the tokens; use semantic parsing of the information to identify a first one or more concepts represented by one or more tokens within the extracted information; query a concept association map to retrieve a second one or more concepts related to the first one or more concepts, each of the concepts representing a unit of thought, expressed by a term, letter, or symbol, the concept association map comprising a representation of concepts, concept metadata, and relationships between the concepts; rank the first one or more concepts and the second one or more concepts to create ranked concepts; and store the ranked concepts for displaying to one or more users of the computer platform. | 11. An apparatus comprising: a memory; and one or more processors configured to: use structural parsing to extract information from user input comprising a URL or domain name, the information comprising one or more of a protocol, a location, and a subdirectory, wherein structural parsing comprises; determining whether the domain name can be mapped to one or more concepts in the concept association map by switching term positions or changing numbers; when the domain name can be mapped and if the mapped concepts have high score, identifying the concepts as seed concepts for further querying the concept association map; when the mapped concepts do not have a high enough score, or the domain name cannot be mapped, then determining whether the input domain name can be mapped to a concept in the concept association map by typographical error correction, the correction comprising one or more of insertion, deletion, and switching or replacement of 1 or 2 characters; and when the input domain name cannot be mapped by typographical error correction, or if concepts mapped as a result of typographical error correction do not have a high score, determining how to break the domain name into URL tokens by inserting separators at correction positions and correcting the tokens; use semantic parsing of the information to identify a first one or more concepts represented by one or more tokens within the extracted information; query a concept association map to retrieve a second one or more concepts related to the first one or more concepts, each of the concepts representing a unit of thought, expressed by a term, letter, or symbol, the concept association map comprising a representation of concepts, concept metadata, and relationships between the concepts; rank the first one or more concepts and the second one or more concepts to create ranked concepts; and store the ranked concepts for displaying to one or more users of the computer platform. 15. The apparatus of claim 11 wherein the one or more processors are further configured to break the URL into URL tokens by: associating a penalty with breaking a domain name into several tokens; and associating a score used to rank, prune and expand URL splitting paths. | 0.5 |
8,788,271 | 9 | 16 | 9. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving information specifying a first user interface at a client computer system, the first user interface enabling interaction with an existing application executed on an application server and being a standalone interface that is separate from the existing application; constructing one or more semantic operations by processing the information specifying the first user interface on the client computer system, each of the one or more semantic operations including sub-operations that are executable using user interface elements of the first user interface, the sub-operations comprising identifying a user interface element, selecting the user interface element, and inputting data using the user interface element; registering one or more voice commands to enable voice control of the first user interface and for initiating execution of the one or more semantic operations, each voice command corresponding to one of the semantic operations, the application executed on the application server remaining unmodified in view of the constructing one or more semantic operations and the registering one or more voice commands; displaying the first user interface at the client computer system upon registering the one or more voice commands; and performing one of the semantic operations in response to a first voice command, the first voice command not explicitly referencing the user interface element, wherein performing one of the semantic operations includes automatic execution of each of the sub-operations in response to the first voice command. | 9. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving information specifying a first user interface at a client computer system, the first user interface enabling interaction with an existing application executed on an application server and being a standalone interface that is separate from the existing application; constructing one or more semantic operations by processing the information specifying the first user interface on the client computer system, each of the one or more semantic operations including sub-operations that are executable using user interface elements of the first user interface, the sub-operations comprising identifying a user interface element, selecting the user interface element, and inputting data using the user interface element; registering one or more voice commands to enable voice control of the first user interface and for initiating execution of the one or more semantic operations, each voice command corresponding to one of the semantic operations, the application executed on the application server remaining unmodified in view of the constructing one or more semantic operations and the registering one or more voice commands; displaying the first user interface at the client computer system upon registering the one or more voice commands; and performing one of the semantic operations in response to a first voice command, the first voice command not explicitly referencing the user interface element, wherein performing one of the semantic operations includes automatic execution of each of the sub-operations in response to the first voice command. 16. The computer storage medium of claim 9 , wherein the first user interface is at least one from a group including a hypertext markup language (HTML) document presented in a web browser, a standalone application, and a user interface for a web services application. | 0.795559 |
9,836,646 | 20 | 21 | 20. Method according to claim 19 , further comprising the step of applying a decision model method on the updated graph. | 20. Method according to claim 19 , further comprising the step of applying a decision model method on the updated graph. 21. A method according to claim 20 , wherein the decision model method comprises a rule which favours character candidates which have the first likelihood parameter and the second likelihood parameters fulfilling a third predetermined criterion. | 0.5 |
9,607,102 | 9 | 12 | 9. A system, comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the system to perform: receiving, by a computing device comprising a natural language understanding automatic speech recognition computing engine device, a first natural language input comprising one or more words; activating, by the natural language understanding automatic speech recognition computing engine device, a first task based on the first natural language input, wherein the first task is associated with one or more first task agents configured for retrieving information associated with the first task; prompting, by the natural language understanding automatic speech recognition computing engine device and via a first of the one or more first task agents, for a subsequent natural language input based on a first transcription of the first natural language input and based on a first intent associated with the first task; receiving, by the natural language understanding automatic speech recognition computing engine device and while the first task is activated, a second natural language input comprising one or more words; responsive to determining, by the natural language understanding automatic speech recognition computing engine device, that a task activation switching parameter associated with the first task is not a false value and that a second intent associated with the second natural language input is different from the first intent associated with the first task, determining, by the natural language understanding automatic speech recognition computing engine device: one or more candidate second tasks that are capable of being activated based on one or more task switching rules that identify one or more tasks that are allowed to interrupt the activated first task, wherein an interrupted task is arranged in a task stack memory component of the computing device; and one or more candidate third tasks that are incapable of being activated based on the one or more task switching rules; activating, by the natural language understanding automatic speech recognition computing engine device, one of the one or more candidate second tasks, wherein the activated candidate second task is associated with one or more second task agents configured for retrieving information associated with the activated candidate second task; responsive to satisfying the one or more second task agents with the first natural language input, the second natural language input, or an additional natural language input, performing, by the computing device, an action associated with the activated second candidate task; determining, by the natural language understanding automatic speech recognition computing engine device, whether the second natural language input satisfies the one or more first task agents associated with the first task; performing, by the computing device, an action associated with the first task responsive to the second natural language input satisfying the one or more first task agents; and prompting, by the natural language understanding automatic speech recognition computing engine device and via one of the one or more first task agents, for a second subsequent natural language input based on the first transcription of the first natural language input responsive to the second natural language input not satisfying the one or more first task agents. | 9. A system, comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the system to perform: receiving, by a computing device comprising a natural language understanding automatic speech recognition computing engine device, a first natural language input comprising one or more words; activating, by the natural language understanding automatic speech recognition computing engine device, a first task based on the first natural language input, wherein the first task is associated with one or more first task agents configured for retrieving information associated with the first task; prompting, by the natural language understanding automatic speech recognition computing engine device and via a first of the one or more first task agents, for a subsequent natural language input based on a first transcription of the first natural language input and based on a first intent associated with the first task; receiving, by the natural language understanding automatic speech recognition computing engine device and while the first task is activated, a second natural language input comprising one or more words; responsive to determining, by the natural language understanding automatic speech recognition computing engine device, that a task activation switching parameter associated with the first task is not a false value and that a second intent associated with the second natural language input is different from the first intent associated with the first task, determining, by the natural language understanding automatic speech recognition computing engine device: one or more candidate second tasks that are capable of being activated based on one or more task switching rules that identify one or more tasks that are allowed to interrupt the activated first task, wherein an interrupted task is arranged in a task stack memory component of the computing device; and one or more candidate third tasks that are incapable of being activated based on the one or more task switching rules; activating, by the natural language understanding automatic speech recognition computing engine device, one of the one or more candidate second tasks, wherein the activated candidate second task is associated with one or more second task agents configured for retrieving information associated with the activated candidate second task; responsive to satisfying the one or more second task agents with the first natural language input, the second natural language input, or an additional natural language input, performing, by the computing device, an action associated with the activated second candidate task; determining, by the natural language understanding automatic speech recognition computing engine device, whether the second natural language input satisfies the one or more first task agents associated with the first task; performing, by the computing device, an action associated with the first task responsive to the second natural language input satisfying the one or more first task agents; and prompting, by the natural language understanding automatic speech recognition computing engine device and via one of the one or more first task agents, for a second subsequent natural language input based on the first transcription of the first natural language input responsive to the second natural language input not satisfying the one or more first task agents. 12. The system of claim 9 , wherein the instructions further cause the system to perform: determining a confidence score for each of the one or more candidate second tasks and for each of the one or more third candidate tasks via a statistical-based task switching model; and responsive to identifying a scored candidate third task associated with a high score compared to the scored one or more second candidate tasks, modifying at least one of the one or more task switching rules, wherein the modification is based on the scored candidate third task associated with the high score. | 0.715953 |
7,849,148 | 1 | 63 | 1. In a computer system, a computer-implemented method comprising: displaying at least one window in connection with a website; displaying, utilizing the at least one window, a stock-related field; receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; after the user types each character in the received text, dynamically determining whether the characters typed so far match any of n text strings in one of a plurality of n-tuples including n>1 text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; if it is determined that the characters typed so far match any of the n text strings in the one of the plurality of n-tuples, indicating to the user that a match has been found, utilizing the at least one window; displaying, utilizing the at least one window, a first set of representations of a first set of hyperlinks; receiving first input from the user indicating a selection of one of the first set of hyperlink representations; in response to receiving the first input, displaying a second set of representations of a second set of hyperlinks, utilizing the at least one window; receiving second input from the user indicating a selection of one of the second set of hyperlink representations; and in response to receiving the second input, navigating to a destination specified by the selected one of the second set of hyperlink representations. | 1. In a computer system, a computer-implemented method comprising: displaying at least one window in connection with a website; displaying, utilizing the at least one window, a stock-related field; receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; after the user types each character in the received text, dynamically determining whether the characters typed so far match any of n text strings in one of a plurality of n-tuples including n>1 text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; if it is determined that the characters typed so far match any of the n text strings in the one of the plurality of n-tuples, indicating to the user that a match has been found, utilizing the at least one window; displaying, utilizing the at least one window, a first set of representations of a first set of hyperlinks; receiving first input from the user indicating a selection of one of the first set of hyperlink representations; in response to receiving the first input, displaying a second set of representations of a second set of hyperlinks, utilizing the at least one window; receiving second input from the user indicating a selection of one of the second set of hyperlink representations; and in response to receiving the second input, navigating to a destination specified by the selected one of the second set of hyperlink representations. 63. The method of claim 1 , wherein the receiving the second input from the user comprises receiving input from the user indicating a mouse click on the selected one of the second set of hyperlink representations. | 0.740876 |
6,105,044 | 1 | 2 | 1. A method of producing a digital form of a portion of a hierarchical digital document, the digital document having descriptive markup defining a plurality of hierarchical elements, wherein each element has a type name, and has at least one of an ancestor element, a child element, a left sibling element, a right sibling element and unformatted text content, the method using a representation of the digital document, including, for each element, an indication of any ancestor element, child element, and left and right sibling element, the method comprising: sending a request for a portion of the digital document using an indication of a starting point within the digital document; receiving only the requested portion of the digital document including selected elements containing the indicated starting point; and generating a digital form of the received portion of the digital document by applying properties corresponding to the received selected elements to the text content of said elements. | 1. A method of producing a digital form of a portion of a hierarchical digital document, the digital document having descriptive markup defining a plurality of hierarchical elements, wherein each element has a type name, and has at least one of an ancestor element, a child element, a left sibling element, a right sibling element and unformatted text content, the method using a representation of the digital document, including, for each element, an indication of any ancestor element, child element, and left and right sibling element, the method comprising: sending a request for a portion of the digital document using an indication of a starting point within the digital document; receiving only the requested portion of the digital document including selected elements containing the indicated starting point; and generating a digital form of the received portion of the digital document by applying properties corresponding to the received selected elements to the text content of said elements. 2. The method of claim 1, wherein receiving only the requested portion includes receiving a starting point element, the starting point element having been selected according to the indicated starting point; and wherein the step of generating a digital form includes: providing a plurality of property specifications for type names utilized for elements in the digital document; receiving an identity of any ancestor elements of the starting point element; and applying a property specification corresponding to the type name of ancestor elements identified for each selected element to the text content of each selected element to produce the digital form. | 0.5 |
8,280,700 | 1 | 6 | 1. A configuration method for a room, the method comprising: selecting from a client device a consumer application from a plurality of consumer applications accessible from the client device, wherein each of the plurality of consumer applications is pre-configured to include a plurality of room components associated therewith; storing in a memory module data defining a plurality of attributes for the plurality of components associated with the selected consumer application, wherein the data are organized in a frame/slot hierarchy such that attributes of the plurality of attributes are represented as slots of a plurality of frames; and selecting a user-specified attribute from available attributes for at least one of the plurality of the room components wherein selection of invalid attributes is prevented, comprising performing in a processor-based system an attribute-based inference operation that identifies among the plurality of room components within the frame/slot hierarchy the available attributes and the invalid attributes for the at least one of the plurality of room components, wherein the selecting the consumer application imposes constraints that determine, at least in part, the available attributes within the frame/slot hierarchy. | 1. A configuration method for a room, the method comprising: selecting from a client device a consumer application from a plurality of consumer applications accessible from the client device, wherein each of the plurality of consumer applications is pre-configured to include a plurality of room components associated therewith; storing in a memory module data defining a plurality of attributes for the plurality of components associated with the selected consumer application, wherein the data are organized in a frame/slot hierarchy such that attributes of the plurality of attributes are represented as slots of a plurality of frames; and selecting a user-specified attribute from available attributes for at least one of the plurality of the room components wherein selection of invalid attributes is prevented, comprising performing in a processor-based system an attribute-based inference operation that identifies among the plurality of room components within the frame/slot hierarchy the available attributes and the invalid attributes for the at least one of the plurality of room components, wherein the selecting the consumer application imposes constraints that determine, at least in part, the available attributes within the frame/slot hierarchy. 6. The method of claim 1 wherein the plurality of attributes comprises attributes selected from the group consisting of colors, materials, textures, patterns, finishes, prices, sizes, shapes, styles, brands, types, locations, and spatial orientations. | 0.78021 |
8,776,009 | 1 | 3 | 1. A method for modeling interactive sequential applications for smart mobile devices, comprising the steps of: a) generating in a central processing unit (CPU) a static model describing all goals of target applications using their screens, Screen Input Elements (SIEs), transitions between screens, sub-goals and the links between them; b) building in said CPU a dynamic model based on said static model by tracking the use of the application screens over an actual device while using an inheritance mechanism whereby model entities having a parent-child relationship are reusable in different models; c) creating instances of said static and dynamic models specifically generated for a variety of devices; d) storing said static and dynamic models with their instances into a passive Task Model database, being in data communication with said CPU; e) downloading relevant passive Task Models to user's device according its type and the application supported by said user's device; f) tracking in real-time user's actions during user-system interactions and generating a unique identifier for each application's screen that is visited by the user of said mobile device by choosing an identifier that matches a signature of each application's screen, wherein created identifiers are used for generating an active model of the user's actual usage; g) storing said tracked model into an active Task Model database being in data communication with said CPU; and h) comparing said active Task Model to said passive Task Model and generating usage patterns for said user; wherein the static and dynamic models are in the form of an Entity Relationship Diagram (ERD), and implemented in a relational database. | 1. A method for modeling interactive sequential applications for smart mobile devices, comprising the steps of: a) generating in a central processing unit (CPU) a static model describing all goals of target applications using their screens, Screen Input Elements (SIEs), transitions between screens, sub-goals and the links between them; b) building in said CPU a dynamic model based on said static model by tracking the use of the application screens over an actual device while using an inheritance mechanism whereby model entities having a parent-child relationship are reusable in different models; c) creating instances of said static and dynamic models specifically generated for a variety of devices; d) storing said static and dynamic models with their instances into a passive Task Model database, being in data communication with said CPU; e) downloading relevant passive Task Models to user's device according its type and the application supported by said user's device; f) tracking in real-time user's actions during user-system interactions and generating a unique identifier for each application's screen that is visited by the user of said mobile device by choosing an identifier that matches a signature of each application's screen, wherein created identifiers are used for generating an active model of the user's actual usage; g) storing said tracked model into an active Task Model database being in data communication with said CPU; and h) comparing said active Task Model to said passive Task Model and generating usage patterns for said user; wherein the static and dynamic models are in the form of an Entity Relationship Diagram (ERD), and implemented in a relational database. 3. The method according to claim 1 , further comprising offering the client real-time help, marketing and content determined by the provider, based on the tracked data and relevant passive Task Models downloaded to client's device. | 0.695251 |
9,936,063 | 2 | 3 | 2. The mobile data processing device of claim 1 , wherein the processor further executes the program instructions to: continue to display the set of application display icons corresponding to the determined first subset of mobile applications having the matching natural language keywords within the generated front application display panel in response to the mobile data processing device not exiting the first defined geographic area based on the currently received geographic location data of the mobile data processing device. | 2. The mobile data processing device of claim 1 , wherein the processor further executes the program instructions to: continue to display the set of application display icons corresponding to the determined first subset of mobile applications having the matching natural language keywords within the generated front application display panel in response to the mobile data processing device not exiting the first defined geographic area based on the currently received geographic location data of the mobile data processing device. 3. The mobile data processing device of claim 2 , wherein the processor further executes the program instructions to: receive from the server device via the network another notification indicating that the mobile data processing device entered a second defined geographic area based on the the currently received geographic location data of the mobile data processing device, wherein the second defined geographic area is another one of the plurality of defined geographic areas that are predefined and delineated by geographic coordinates stored on the server device; and send a request to the server device via the network for a second set of geolocation keyword tags corresponding to the second defined geographic area in response to receiving the another notification. | 0.5 |
9,542,441 | 8 | 12 | 8. A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a first query; receiving a second, follow-up query; determining that a pronoun in the second, follow-up query is an anaphor by determining that the pronoun refers to an entity that is not present in the second, follow-up query; in response to determining that the pronoun in the second, follow-up query is an anaphor, determining that the first query is associated with a plurality of possible entities; generating a plurality of candidate queries, wherein each candidate query of the plurality of candidate queries is generated by replacing the pronoun in the second, follow-up query with a corresponding possible entity; ranking, using at least past query logs stored in a data repository, the plurality of candidate queries; and providing a highest-ranked candidate query of the plurality of candidate queries to a search engine and obtaining search results for the highest-ranked candidate query from the search engine. | 8. A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a first query; receiving a second, follow-up query; determining that a pronoun in the second, follow-up query is an anaphor by determining that the pronoun refers to an entity that is not present in the second, follow-up query; in response to determining that the pronoun in the second, follow-up query is an anaphor, determining that the first query is associated with a plurality of possible entities; generating a plurality of candidate queries, wherein each candidate query of the plurality of candidate queries is generated by replacing the pronoun in the second, follow-up query with a corresponding possible entity; ranking, using at least past query logs stored in a data repository, the plurality of candidate queries; and providing a highest-ranked candidate query of the plurality of candidate queries to a search engine and obtaining search results for the highest-ranked candidate query from the search engine. 12. The system of claim 8 , wherein determining that the first query is associated with a plurality of possible entities comprises: analyzing results of the first query for a presence of an entity associated with the anaphor. | 0.753829 |
8,204,881 | 1 | 6 | 1. A method, comprising: a computing device receiving search criteria from a user; the computing device searching at least one information system using the search criteria; the computing device transmitting one or more search results in response to the search criteria; the computing device receiving a plurality of content distillation parameters from the user, wherein the plurality of content distillation parameters indicate at least two different content extraction types; upon selection of at least one of the one or more of the search results by a user, the computing device presenting a reduced-content version of the selected at least one search result to the user in accordance with the received plurality of content distillation parameters, wherein the reduced-content version includes first and second content corresponding to the at least two different content extraction types. | 1. A method, comprising: a computing device receiving search criteria from a user; the computing device searching at least one information system using the search criteria; the computing device transmitting one or more search results in response to the search criteria; the computing device receiving a plurality of content distillation parameters from the user, wherein the plurality of content distillation parameters indicate at least two different content extraction types; upon selection of at least one of the one or more of the search results by a user, the computing device presenting a reduced-content version of the selected at least one search result to the user in accordance with the received plurality of content distillation parameters, wherein the reduced-content version includes first and second content corresponding to the at least two different content extraction types. 6. The method of claim 1 , wherein a first of the plurality of content distillation parameters includes an indication that a user-defined content type is one of the at least two different content extraction types. | 0.765934 |
7,523,440 | 33 | 48 | 33. A method for generating a formatted user interface for editing information associated with entities in model loaded in a modeling environment, the method comprising: loading one or more models in the modeling environment; displaying a first user interface element displaying entities of the one or more models loaded in the modeling environment, wherein the first user interface element enables users to select multiple entities displayed in the first interface element; selecting a plurality of entities in the loaded models in response to user input in the first user interface element; identifying editable information associated with the selected plurality of entities; identifying common data associated with the selected plurality of entities, the identifying including classifying data in an intersection of data associated with the selected plurality of entities as common data; and dynamically generating from the identified editable information and the identified common data using a computational device a formatted second user interface element displaying at least a portion of the identified editable information and the identified common data associated with the selected plurality of entities, the formatted second user interface element enabling the users to distinguish data associated with the selected plurality of entities that is common data from data associated with the selected plurality of entities that in not common data, the formatted second user interface element enabling the users to edit data that is common data. | 33. A method for generating a formatted user interface for editing information associated with entities in model loaded in a modeling environment, the method comprising: loading one or more models in the modeling environment; displaying a first user interface element displaying entities of the one or more models loaded in the modeling environment, wherein the first user interface element enables users to select multiple entities displayed in the first interface element; selecting a plurality of entities in the loaded models in response to user input in the first user interface element; identifying editable information associated with the selected plurality of entities; identifying common data associated with the selected plurality of entities, the identifying including classifying data in an intersection of data associated with the selected plurality of entities as common data; and dynamically generating from the identified editable information and the identified common data using a computational device a formatted second user interface element displaying at least a portion of the identified editable information and the identified common data associated with the selected plurality of entities, the formatted second user interface element enabling the users to distinguish data associated with the selected plurality of entities that is common data from data associated with the selected plurality of entities that in not common data, the formatted second user interface element enabling the users to edit data that is common data. 48. The method of claim 33 wherein the identified editable information associated with the selected plurality of entities includes results from performing an arbitrary number of set operations on information associated with the selected plurality of entities. | 0.5 |
8,583,628 | 11 | 16 | 11. A system comprising: a processor; and a memory coupled with and readable by the processor and having stored therein a set of instructions which, when executed by the processor, causes the processor to retrieve information from a database of relationally linked documents by: receiving search parameters from a user; locating an entry point document responsive to said search parameters, the entry point document comprising a root document in a hierarchy of a plurality of related documents; returning a search result including said entry point document and one or more manual relational links and one or more learned relational links between said entry point document and one or more related documents in the plurality of related documents, wherein the manual relational links comprise relational links between documents within the hierarchy manually encoded in the documents and wherein the learned relational links comprise dynamic links between documents within the hierarchy that are not manually encoded in the documents, that are not known at a time of creation of the documents, and that are generated automatically based on text of the documents; initiating one of said learned relational links in response to at least one user link selection; returning the document from the plurality of related documents that corresponds to said learned initiated relational link; updating a connection strength rating to said learned initiated relational link based on the user link selection and indicating navigation of the user through the hierarchy; associating said learned initiated relational link with said search parameters; storing in said database said learned relationally linked documents, said updated connection strength and said learned initiated relational link with said parameters; returning additional documents from the plurality of related documents; and recursively associating initiated relational links with said search parameters, wherein at least one of said returning steps include using a clustering algorithm on the hierarchy of the plurality of related documents. | 11. A system comprising: a processor; and a memory coupled with and readable by the processor and having stored therein a set of instructions which, when executed by the processor, causes the processor to retrieve information from a database of relationally linked documents by: receiving search parameters from a user; locating an entry point document responsive to said search parameters, the entry point document comprising a root document in a hierarchy of a plurality of related documents; returning a search result including said entry point document and one or more manual relational links and one or more learned relational links between said entry point document and one or more related documents in the plurality of related documents, wherein the manual relational links comprise relational links between documents within the hierarchy manually encoded in the documents and wherein the learned relational links comprise dynamic links between documents within the hierarchy that are not manually encoded in the documents, that are not known at a time of creation of the documents, and that are generated automatically based on text of the documents; initiating one of said learned relational links in response to at least one user link selection; returning the document from the plurality of related documents that corresponds to said learned initiated relational link; updating a connection strength rating to said learned initiated relational link based on the user link selection and indicating navigation of the user through the hierarchy; associating said learned initiated relational link with said search parameters; storing in said database said learned relationally linked documents, said updated connection strength and said learned initiated relational link with said parameters; returning additional documents from the plurality of related documents; and recursively associating initiated relational links with said search parameters, wherein at least one of said returning steps include using a clustering algorithm on the hierarchy of the plurality of related documents. 16. The system according to claim 11 further comprising assigning a path rating to all of said initiated relational links. | 0.797342 |
9,609,127 | 1 | 10 | 1. A method comprising: detecting, by a system including a processor, input incompatible with an original script for an interactive communication over a communication network, wherein the detecting is performed during the interactive communication; modifying, by the system, the original script during the interactive communication into a dynamically updated script different from the original script in accordance with a type of the incompatible input; and providing, by the system over the communication network, information to a device participating in the interactive communication in accordance with the dynamically updated script, wherein at least a portion of a remainder of the interactive communication is conducted in accordance with the dynamically updated script. | 1. A method comprising: detecting, by a system including a processor, input incompatible with an original script for an interactive communication over a communication network, wherein the detecting is performed during the interactive communication; modifying, by the system, the original script during the interactive communication into a dynamically updated script different from the original script in accordance with a type of the incompatible input; and providing, by the system over the communication network, information to a device participating in the interactive communication in accordance with the dynamically updated script, wherein at least a portion of a remainder of the interactive communication is conducted in accordance with the dynamically updated script. 10. The method of claim 1 , wherein the modifying of the original script comprises providing an instruction to not provide speech input. | 0.728 |
8,819,055 | 15 | 17 | 15. A non-transitory computer readable storage medium including instructions for managing logical people groups (LPGs), which instructions, when executed by a computer, cause the computer to perform steps comprising: maintaining a user directory which includes a first plurality of attribute values for each of a plurality of users and the user directory maps the plurality of users to a plurality of groups; maintaining an attribute directory, separate from the user directory, which includes a second plurality of attribute values for each of the plurality of users, which second plurality of attribute values are not recorded in said user directory and the attribute directory maps a plurality of business attributes to the plurality of users; maintaining a security layer, separate from the user directory and attribute directory, which includes a third plurality of attribute values for each of the plurality of users, which third plurality of attribute values are not recorded in said user directory or attribute directory and the security layer includes a plurality of roles, wherein each role is associated with an application and includes one or more users from the plurality of users; providing a query module executing on a computer including a memory, and a processor; providing a query cache which stores, for a user-definable period, LPGs based on previously received complex queries; receiving a complex query with the query module, wherein the complex query includes a first parameter operable on the first plurality of attribute values, a second parameter operable on the second plurality of attribute values, and a third parameter operable on the third plurality of attribute values; searching the user directory with the query module and identifying a first subset of the plurality users having attribute values satisfying the first parameter, searching the attribute directory with the query module and identifying a second subset of the plurality of users having attribute values satisfying the second parameter; searching the security layer with the query module and identifying a third subset of the plurality of users having attribute values satisfying the third parameter; comparing the first subset, the second subset, and the third subset; returning a logical group of users (LPG) including a plurality of users present in all of the first subset, the second subset, and the third subset, wherein the LPG is defined by the complex query, and storing the LPG in the query cache. | 15. A non-transitory computer readable storage medium including instructions for managing logical people groups (LPGs), which instructions, when executed by a computer, cause the computer to perform steps comprising: maintaining a user directory which includes a first plurality of attribute values for each of a plurality of users and the user directory maps the plurality of users to a plurality of groups; maintaining an attribute directory, separate from the user directory, which includes a second plurality of attribute values for each of the plurality of users, which second plurality of attribute values are not recorded in said user directory and the attribute directory maps a plurality of business attributes to the plurality of users; maintaining a security layer, separate from the user directory and attribute directory, which includes a third plurality of attribute values for each of the plurality of users, which third plurality of attribute values are not recorded in said user directory or attribute directory and the security layer includes a plurality of roles, wherein each role is associated with an application and includes one or more users from the plurality of users; providing a query module executing on a computer including a memory, and a processor; providing a query cache which stores, for a user-definable period, LPGs based on previously received complex queries; receiving a complex query with the query module, wherein the complex query includes a first parameter operable on the first plurality of attribute values, a second parameter operable on the second plurality of attribute values, and a third parameter operable on the third plurality of attribute values; searching the user directory with the query module and identifying a first subset of the plurality users having attribute values satisfying the first parameter, searching the attribute directory with the query module and identifying a second subset of the plurality of users having attribute values satisfying the second parameter; searching the security layer with the query module and identifying a third subset of the plurality of users having attribute values satisfying the third parameter; comparing the first subset, the second subset, and the third subset; returning a logical group of users (LPG) including a plurality of users present in all of the first subset, the second subset, and the third subset, wherein the LPG is defined by the complex query, and storing the LPG in the query cache. 17. The non-transitory computer readable storage medium of claim 15 , which includes instructions which cause the computer to perform steps further comprising: maintaining a reverse lookup directory for a plurality of current LPGs associated with a plurality of complex searches wherein the reverse lookup directory identifies to which of said plurality of current LPGs each of said plurality of users belongs; executing each of the complex searches associated with said plurality of current LPGs and storing results in said query cache; and updating the query cache, at a user-definable interval by re-executing each of the complex searches associated with said plurality of current LPGs and storing updated results in said query cache. | 0.5 |
10,032,127 | 14 | 15 | 14. At least one non-transitory computer-readable storage medium encoded with computer-executable instructions that, when executed, perform a method comprising: processing, using natural language understanding, a first free-form narration, narrated by a clinician, of an encounter with a patient, the processing comprising: detecting a mention in the first free-form narration of an orderable item of a type selected from the group consisting of a medication, a clinical procedure, and a laboratory test; performing a first semantic analysis of at least a part of the first free-form narration, wherein performing the first semantic analysis comprises: determining a type of the first orderable item detected in the first free-form narration, wherein the determining is performed by the natural language understanding engine; in response to determining that the type of the first orderable item is one of one or more first types, performing the first semantic analysis by applying a trained statistical model; and in response to determining that the type of the first orderable item is one of one or more second types, performing the first semantic analysis by applying a rules-based system; determining, based on the first semantic analysis, whether the detected mention of the orderable item is in a statement expressing that the clinician intends to order the orderable item; in response to determining that the detected mention of the orderable item in the first free-form narration is in a statement expressing that the clinician intends to order the orderable item, generating an order for the orderable item; and in response to determining that the detected mention of the orderable item in the first free-form narration is in a statement not expressing that the clinician intends to order the orderable item, not generating an order for the orderable item. | 14. At least one non-transitory computer-readable storage medium encoded with computer-executable instructions that, when executed, perform a method comprising: processing, using natural language understanding, a first free-form narration, narrated by a clinician, of an encounter with a patient, the processing comprising: detecting a mention in the first free-form narration of an orderable item of a type selected from the group consisting of a medication, a clinical procedure, and a laboratory test; performing a first semantic analysis of at least a part of the first free-form narration, wherein performing the first semantic analysis comprises: determining a type of the first orderable item detected in the first free-form narration, wherein the determining is performed by the natural language understanding engine; in response to determining that the type of the first orderable item is one of one or more first types, performing the first semantic analysis by applying a trained statistical model; and in response to determining that the type of the first orderable item is one of one or more second types, performing the first semantic analysis by applying a rules-based system; determining, based on the first semantic analysis, whether the detected mention of the orderable item is in a statement expressing that the clinician intends to order the orderable item; in response to determining that the detected mention of the orderable item in the first free-form narration is in a statement expressing that the clinician intends to order the orderable item, generating an order for the orderable item; and in response to determining that the detected mention of the orderable item in the first free-form narration is in a statement not expressing that the clinician intends to order the orderable item, not generating an order for the orderable item. 15. The at least one computer-readable storage medium of claim 14 , wherein the method further comprises identifying one or more missing information fields in a set of information fields that have not been extracted from the first free-form narration. | 0.662634 |
8,725,511 | 1 | 2 | 1. A method comprising: comparing, via a processor, received speech to a first grammar based on a database, to yield a comparison; and when the comparison is below a threshold: compiling a second grammar based on data added to the database after compilation of the first grammar; and comparing the received speech to the second grammar. | 1. A method comprising: comparing, via a processor, received speech to a first grammar based on a database, to yield a comparison; and when the comparison is below a threshold: compiling a second grammar based on data added to the database after compilation of the first grammar; and comparing the received speech to the second grammar. 2. The method of claim 1 , wherein the second grammar is stored separately from the first grammar. | 0.664384 |
6,029,167 | 9 | 10 | 9. The apparatus of claim 6, wherein said database documents contain passages that are similar to said known passage. | 9. The apparatus of claim 6, wherein said database documents contain passages that are similar to said known passage. 10. The apparatus of claim 9, wherein said first text passage is compared with said database documents using a sequential string search of said first marker sequence against said plurality of database marker sequences. | 0.5 |
9,087,122 | 10 | 11 | 10. The computer program product of claim 9 , wherein the normalized search term is based on at least one of: (i) at least one variant of the at least one key term, and (ii) a context of the at least one key term. | 10. The computer program product of claim 9 , wherein the normalized search term is based on at least one of: (i) at least one variant of the at least one key term, and (ii) a context of the at least one key term. 11. The computer program product of claim 10 , wherein the set of normalized terms comprises two or more normalized terms, wherein the corpus of evidence is further indexed by: associating the set of normalized terms with the respective item of evidence; and storing the association. | 0.5 |
8,793,277 | 1 | 5 | 1. A forensic system configured to acquire digital information recorded on a plurality of computers or a server to analyze the acquired digital information, the forensic system comprising: a digital information acquiring unit configured to acquire digital information containing digital document information composed of a plurality of document files, and to acquire user information about users using the plurality of computers or the server; a recording unit configured to record therein the digital information acquired by the digital information acquiring unit; a display unit configured to display the recorded digital information; a user-specifying information setting unit configured to set user-specifying information showing which one of users contained in the user-specifying information each of the plurality of document files is related with, to set ranking information showing a first relative degree of relationship a first user from among the users has with litigation, and showing a second relative degree of relationship a second user from among the users has with the litigation, and configured to cause the recording unit to record the set user-specifying information, via the display unit; a user selecting unit configured to select at least one user via the display unit; a control unit, comprising: a searching unit configured to search a document file where the user-specifying information corresponding to the selected user was set, and to provide a book-mark function allowing book-mark search for material set with a hierarchy structure book-mark; a highlight display function configured to highlight, on the display unit, a searched word or phrase; a managing unit including an access right control function configured to set one or more rights for each of a plurality of accounts associated with a browser, wherein the one or more rights set by the managing unit includes a manager right associated with the browser; a statistical data producing unit configured to produce statistical data represented by data size for each data format of the acquired digital document information or statistical data represented by data size for each data format of the digital document information; a digital document extracting unit configured to select a kind of file to be searched; a data converting unit configured to preserve a selected file as a separate file; an additional information setting unit configured to set additional information showing whether or not the searched document file is related with the litigation, wherein the additional information includes at least one of a first tag indicating that the searched document file is related with the litigation, a second tag indicating that the searched document file is potentially related with the litigation, and a third tag indicating that the searched document file is not related with the litigation; and an output unit configured to output the document file which is related with the litigation, based on the first relative degree of relationship the first user from among the users has with the litigation, the second relative degree of relationship the second user from among the users has with the litigation, and the at least one of the first tag indicating that the searched document file is related with the litigation, the second tag indicating that the searched document file is potentially related with the litigation, and the third tag indicating that the searched document file is not related with the litigation. | 1. A forensic system configured to acquire digital information recorded on a plurality of computers or a server to analyze the acquired digital information, the forensic system comprising: a digital information acquiring unit configured to acquire digital information containing digital document information composed of a plurality of document files, and to acquire user information about users using the plurality of computers or the server; a recording unit configured to record therein the digital information acquired by the digital information acquiring unit; a display unit configured to display the recorded digital information; a user-specifying information setting unit configured to set user-specifying information showing which one of users contained in the user-specifying information each of the plurality of document files is related with, to set ranking information showing a first relative degree of relationship a first user from among the users has with litigation, and showing a second relative degree of relationship a second user from among the users has with the litigation, and configured to cause the recording unit to record the set user-specifying information, via the display unit; a user selecting unit configured to select at least one user via the display unit; a control unit, comprising: a searching unit configured to search a document file where the user-specifying information corresponding to the selected user was set, and to provide a book-mark function allowing book-mark search for material set with a hierarchy structure book-mark; a highlight display function configured to highlight, on the display unit, a searched word or phrase; a managing unit including an access right control function configured to set one or more rights for each of a plurality of accounts associated with a browser, wherein the one or more rights set by the managing unit includes a manager right associated with the browser; a statistical data producing unit configured to produce statistical data represented by data size for each data format of the acquired digital document information or statistical data represented by data size for each data format of the digital document information; a digital document extracting unit configured to select a kind of file to be searched; a data converting unit configured to preserve a selected file as a separate file; an additional information setting unit configured to set additional information showing whether or not the searched document file is related with the litigation, wherein the additional information includes at least one of a first tag indicating that the searched document file is related with the litigation, a second tag indicating that the searched document file is potentially related with the litigation, and a third tag indicating that the searched document file is not related with the litigation; and an output unit configured to output the document file which is related with the litigation, based on the first relative degree of relationship the first user from among the users has with the litigation, the second relative degree of relationship the second user from among the users has with the litigation, and the at least one of the first tag indicating that the searched document file is related with the litigation, the second tag indicating that the searched document file is potentially related with the litigation, and the third tag indicating that the searched document file is not related with the litigation. 5. The forensic system according to claim 1 , wherein the digital information acquiring unit is configured to acquire second digital information containing second digital document information and second user information, the second digital information being recorded in a second server different from the server; and the forensic system is configured to search not only the digital document information but also a plurality of document files including the second digital document information. | 0.610143 |
8,600,758 | 6 | 11 | 6. The method of claim 4 , wherein the at least one stutter type is at least one of syllable repetition, phone elongation and silence/breath. | 6. The method of claim 4 , wherein the at least one stutter type is at least one of syllable repetition, phone elongation and silence/breath. 11. The method of claim 6 , further comprising detecting phone elongation via detecting at least one of fricatives exceeding a predetermined threshold, voice-bars exceeding a predetermined threshold, and vocalic sounds exceeding a predetermined threshold; wherein elongated phones include phones with or without a formant structure. | 0.5 |
10,140,979 | 13 | 14 | 13. The speech recognition system of claim 12 , wherein the scalar representation of Q f for a given f comprises: r f ( x ) = ∑ k = 1 V q k f * E k - 1 where q k f represents the k th feature of Q f . | 13. The speech recognition system of claim 12 , wherein the scalar representation of Q f for a given f comprises: r f ( x ) = ∑ k = 1 V q k f * E k - 1 where q k f represents the k th feature of Q f . 14. The speech recognition system of claim 13 , wherein the posterior probability for a given (x, b) pair comprises: P f ( x , b ) = U f [ r f ( x ) ] [ b ] ∑ d = 1 M U f [ r f ( x ) ] [ b ] . | 0.5 |
6,069,622 | 1 | 10 | 1. In a network including a plurality of data processing systems each having an associated display device, a method comprising: (a) receiving at each of the data processing systems an interaction event generated by any of the data processing systems; (b) automatically generating a comic panel based on the received interaction event, the comic panel providing a graphical representation of an instance in time of a sequential course of events; (c) displaying the generated comic panel on each of the display devices associated with the data processing systems; (d) when an input associated with a graphical representation of a character is received, automatically generating a balloon that includes text that corresponds to the received input associated with the character and automatically generating a tail that is positioned between a position of the balloon and another position for the graphical representation of the character in a current comic panel, the balloon, tail and graphical representation of the character being automatically disposed at positions that are non-overlapping of any other positions for balloons, tails and graphical representations of characters that were previously positioned for display in the current comic panel; and (e) when the input associated with the character is received and non-overlapping positions for displaying the balloon, tail and graphical representation of the character in the current comic panels are unavailable, automatically displaying a new comic panel that includes the balloon, tail and graphical representation of the character, wherein the balloon, tail and graphical representation of the character are disposed at separate positions that are non-overlapping in the display of the new comic panel. | 1. In a network including a plurality of data processing systems each having an associated display device, a method comprising: (a) receiving at each of the data processing systems an interaction event generated by any of the data processing systems; (b) automatically generating a comic panel based on the received interaction event, the comic panel providing a graphical representation of an instance in time of a sequential course of events; (c) displaying the generated comic panel on each of the display devices associated with the data processing systems; (d) when an input associated with a graphical representation of a character is received, automatically generating a balloon that includes text that corresponds to the received input associated with the character and automatically generating a tail that is positioned between a position of the balloon and another position for the graphical representation of the character in a current comic panel, the balloon, tail and graphical representation of the character being automatically disposed at positions that are non-overlapping of any other positions for balloons, tails and graphical representations of characters that were previously positioned for display in the current comic panel; and (e) when the input associated with the character is received and non-overlapping positions for displaying the balloon, tail and graphical representation of the character in the current comic panels are unavailable, automatically displaying a new comic panel that includes the balloon, tail and graphical representation of the character, wherein the balloon, tail and graphical representation of the character are disposed at separate positions that are non-overlapping in the display of the new comic panel. 10. The method of claim 1, wherein generating a comic panel further comprises: (a) determining whether to generate a new comic panel that reflects the interaction event; (b) when the determination to generate the new comic panel is affirmative, generating the new comic panel incorporating the modification indicated by the interaction event; and (c) when the determination to generate the new comic panel is negative, incorporating the modification indicated by the interaction event into a last generated comic panel in the plurality of comic panels. | 0.5 |
8,264,502 | 1 | 7 | 1. A computer-implemented method for facilitating accurate review of a document comprising the steps of: manipulating, by the computer a scanned image of the document, indicating to a reader portions of the document which have been already reviewed in a previous or master document, and manipulating the image of the document while preserving its fidelity, wherein the step of manipulating the image includes highlighting or de-emphasizing portions of the image, wherein the step of highlighting or de-emphasizing portions of the image includes putting a colored or textured background behind the image in 3-dimensional space. | 1. A computer-implemented method for facilitating accurate review of a document comprising the steps of: manipulating, by the computer a scanned image of the document, indicating to a reader portions of the document which have been already reviewed in a previous or master document, and manipulating the image of the document while preserving its fidelity, wherein the step of manipulating the image includes highlighting or de-emphasizing portions of the image, wherein the step of highlighting or de-emphasizing portions of the image includes putting a colored or textured background behind the image in 3-dimensional space. 7. The method of claim 1 wherein the step of highlighting or de-emphasizing portions of the image includes greying-out portions of the image by reducing the contrast on those portions. | 0.5 |
8,005,681 | 11 | 18 | 11. A method of controlling a speech dialog system, comprising: receiving, with at least one processor, an input signal in a first language; converting, with the at least one processor, the input signal into a control instruction that corresponds to the input signal and that has a language that is different from the input signal; outputting, with the at least one processor, an output acoustic signal; and actuating mechanically a push-to-talk button of the speech dialog system before outputting output acoustic signal. | 11. A method of controlling a speech dialog system, comprising: receiving, with at least one processor, an input signal in a first language; converting, with the at least one processor, the input signal into a control instruction that corresponds to the input signal and that has a language that is different from the input signal; outputting, with the at least one processor, an output acoustic signal; and actuating mechanically a push-to-talk button of the speech dialog system before outputting output acoustic signal. 18. The method of claim 11 , where the input signal is a machine language signal. | 0.653846 |
9,854,315 | 1 | 4 | 1. A method for broadcast audience interaction, comprising: broadcasting, by a first device associated with a media output device to a portable device, a discovery signal, receipt of the discovery signal causing the portable device to activate a microphone of the portable device; receiving, by the first device, a segment of audio output by the media output device and an audio interaction of a user recorded by the microphone of the portable device; identifying, by the first device an existence of the portable device based on correlation between the segment of audio output by the media output device and the audio interaction of the user; determining, by the first device, that the audio interaction of the user is not output by the media output device based on identifying the existence of the portable device; generating, by the first device, a first identifier of the audio interaction of the user and a second identifier of the segment of audio output by the media device; and transmitting, by the first device to a measurement system, the first identifier and the second identifier, the measurement system recording an identification of an item of content corresponding to the segment of audio output by the media device and an interaction with the item of content. | 1. A method for broadcast audience interaction, comprising: broadcasting, by a first device associated with a media output device to a portable device, a discovery signal, receipt of the discovery signal causing the portable device to activate a microphone of the portable device; receiving, by the first device, a segment of audio output by the media output device and an audio interaction of a user recorded by the microphone of the portable device; identifying, by the first device an existence of the portable device based on correlation between the segment of audio output by the media output device and the audio interaction of the user; determining, by the first device, that the audio interaction of the user is not output by the media output device based on identifying the existence of the portable device; generating, by the first device, a first identifier of the audio interaction of the user and a second identifier of the segment of audio output by the media device; and transmitting, by the first device to a measurement system, the first identifier and the second identifier, the measurement system recording an identification of an item of content corresponding to the segment of audio output by the media device and an interaction with the item of content. 4. The method of claim 1 , wherein transmitting the first identifier and the second identifier to the measurement system further causes the measurement system to compare the first identifier to a plurality of identifiers of items of content; and wherein the measurement system records the identification of the item of content corresponding to the segment of audio output by the media device responsive to the comparison. | 0.511601 |
9,055,384 | 15 | 19 | 15. A computing device, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the processor to: obtain at least one image of an advertisement associated with an event, the at least one image being captured by a camera of the computing device; process the at least one image of the advertisement to locate at least one region having properties of text; analyze the at least one region using an optical character recognition algorithm to recognize the text associated with the event; identify a text pattern corresponding to the recognized text; determine an application associated with the text pattern; and cause the recognized text to be sent to the application for performing an action with the text pattern associated with the event. | 15. A computing device, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the processor to: obtain at least one image of an advertisement associated with an event, the at least one image being captured by a camera of the computing device; process the at least one image of the advertisement to locate at least one region having properties of text; analyze the at least one region using an optical character recognition algorithm to recognize the text associated with the event; identify a text pattern corresponding to the recognized text; determine an application associated with the text pattern; and cause the recognized text to be sent to the application for performing an action with the text pattern associated with the event. 19. The computing device of claim 15 , wherein the action is at least one of dialing an event phone number in response to the recognized text indicating a phone number, opening an email application for composing an email in response to the recognized text indicating an email, navigating to a URL for the event in response to the recognized text indicates a web address, or displaying a map to show an address for the event in response to the recognized text indicating a physical address. | 0.5 |
8,095,565 | 7 | 8 | 7. The computer-readable storage medium of claim 6 , wherein the binding expression further includes a path to data. | 7. The computer-readable storage medium of claim 6 , wherein the binding expression further includes a path to data. 8. The computer-readable storage medium of claim 7 , wherein the data source comprises at least one of an object data source and an XML data source. | 0.681034 |
7,730,072 | 20 | 21 | 20. The computer readable storage medium of claim 19 including: means for aging said relationship links; and means for pruning said relationship links. | 20. The computer readable storage medium of claim 19 including: means for aging said relationship links; and means for pruning said relationship links. 21. The computer readable storage medium of claim 20 including means for merging the resulting output of said algorithms into a knowledge network. | 0.5 |
8,856,132 | 10 | 15 | 10. The method of claim 1 wherein receiving the knowledge tip in the tips repository further comprises: a. creating a new category in the tips repository if a required category does not exist among a plurality of predefined categories in the tips repository; and b. storing the knowledge tip to the new category. | 10. The method of claim 1 wherein receiving the knowledge tip in the tips repository further comprises: a. creating a new category in the tips repository if a required category does not exist among a plurality of predefined categories in the tips repository; and b. storing the knowledge tip to the new category. 15. The method of claim 10 further comprising deleting an existing knowledge tip in the tips repository, wherein an author of the knowledge tip or an administrator are allowed to delete the knowledge tip if the knowledge tip is not scheduled to be shared. | 0.656334 |
8,762,857 | 1 | 18 | 1. A portable dataport for document retrieving, inter-relating, annotating and management comprising: an electronic document storage device associated with the dataport, for storing a plurality of related electronic documents associated with a project, wherein the plurality of related electronic documents are at least a one dimensional grid; and a view manager having a plurality of scrollable image viewers in communication with the electronic document storage device, wherein a related electronic document of the plurality of related electronic documents is loaded into one scrollable image viewer of the plurality of scrollable image viewers for immediate viewing as a currently viewed document, wherein a scale of the currently viewed document is saved in the view manager, wherein an (x, y) coordinate of a corner of a viewable area of the currently viewed document is saved in the view manager, wherein the scale of the currently viewed document and the (x, y) coordinate of the corner of the viewable area of the currently viewed document are applied to a subsequently viewed document when the subsequently viewed document is painted in another scrollable image viewer of the plurality of scrollable image viewers such that a viewable area of the subsequently viewed document is the same as the viewable area of the currently viewed document, wherein the subsequently viewed document is another related electronic document of the plurality of related electronic documents associated with the project, and wherein the dataport, using the view manager, takes a snapshot of a particular portion of the currently viewed document, wherein the snapshot identifies a location and a magnification of detail of a portion of the currently viewed document, creates a copy of the document portion, and permits a user to directly annotate on the document portion copy. | 1. A portable dataport for document retrieving, inter-relating, annotating and management comprising: an electronic document storage device associated with the dataport, for storing a plurality of related electronic documents associated with a project, wherein the plurality of related electronic documents are at least a one dimensional grid; and a view manager having a plurality of scrollable image viewers in communication with the electronic document storage device, wherein a related electronic document of the plurality of related electronic documents is loaded into one scrollable image viewer of the plurality of scrollable image viewers for immediate viewing as a currently viewed document, wherein a scale of the currently viewed document is saved in the view manager, wherein an (x, y) coordinate of a corner of a viewable area of the currently viewed document is saved in the view manager, wherein the scale of the currently viewed document and the (x, y) coordinate of the corner of the viewable area of the currently viewed document are applied to a subsequently viewed document when the subsequently viewed document is painted in another scrollable image viewer of the plurality of scrollable image viewers such that a viewable area of the subsequently viewed document is the same as the viewable area of the currently viewed document, wherein the subsequently viewed document is another related electronic document of the plurality of related electronic documents associated with the project, and wherein the dataport, using the view manager, takes a snapshot of a particular portion of the currently viewed document, wherein the snapshot identifies a location and a magnification of detail of a portion of the currently viewed document, creates a copy of the document portion, and permits a user to directly annotate on the document portion copy. 18. The dataport of claim 1 , wherein the view manager in connection with document loading and retrieval: retrieves the plurality of related electronic documents associated with the project from the electronic document storage device; creates a data structure that contains coordinate data and navigations keys for each related electronic document of the plurality of related electronic documents; creates a scrollable image viewer for the each related electronic document of the plurality of related electronic documents based upon the coordinate data; creates a first hash map for containing the scrollable image viewers; and creates a second hash map for containing cardinality keys corresponding to the coordinate data. | 0.756729 |
9,373,030 | 29 | 32 | 29. A system comprising: a processor; and a memory communicatively coupled to the processor, the memory storing instructions executable to perform a method, the method including: receiving an image of an identity document, the image being produced using a video stream; recognizing a plurality of text elements in the image using optical character recognition; finding a document template of a plurality of templates having a high degree of coincidence with the image using a substantially rectangular shape of the image overall, at least one of the text elements, and a respective location in the image for the at least one text element, wherein the respective location in the image for each of the text elements includes Cartesian coordinates where the origin lies at a corner of the image and a distance from another location in the image for another text element and a distance from an edge of the image, the distance determined using respective Cartesian coordinates of each of the text elements, the another text element, and the edge of the image; associating each of the text elements with a respective field of the document template using the text elements and a respective location in the image for each of the text elements; placing at least one of the associated text elements in a respective field of a form, the respective field of the form corresponding to the respective associated field of the document template; and making the completed form accessible on the system. | 29. A system comprising: a processor; and a memory communicatively coupled to the processor, the memory storing instructions executable to perform a method, the method including: receiving an image of an identity document, the image being produced using a video stream; recognizing a plurality of text elements in the image using optical character recognition; finding a document template of a plurality of templates having a high degree of coincidence with the image using a substantially rectangular shape of the image overall, at least one of the text elements, and a respective location in the image for the at least one text element, wherein the respective location in the image for each of the text elements includes Cartesian coordinates where the origin lies at a corner of the image and a distance from another location in the image for another text element and a distance from an edge of the image, the distance determined using respective Cartesian coordinates of each of the text elements, the another text element, and the edge of the image; associating each of the text elements with a respective field of the document template using the text elements and a respective location in the image for each of the text elements; placing at least one of the associated text elements in a respective field of a form, the respective field of the form corresponding to the respective associated field of the document template; and making the completed form accessible on the system. 32. The system of claim 29 wherein the method further includes: placing at least one of the associated text elements in a respective field of a second form, the respective field of the second form corresponding to the respective associated field of the document template; and making the second completed form accessible on the system. | 0.5 |
8,331,739 | 13 | 18 | 13. A computer system for correcting Optical Character Recognition (OCR) errors, the computer system comprising: a non-transitory computer-readable storage medium storing executable computer program instructions for correcting Optical Character Recognition (OCR) errors, the computer program instructions comprising instructions for: converting a graphical representation of an original segment of text into a first segment of text using a first OCR engine; converting the graphical representation of the original segment of text into a second segment of text using a second OCR engine; estimating an error probability for the first segment of text by matching the first segment of text with the second segment of text; responsive to the error probability exceeding a predetermined threshold value, generating a suspect interpretation for the first segment of text; grouping the suspect interpretation with other similar suspect interpretations to form a cluster of suspect interpretations by: comparing the first segment of text with another segment of text of another suspect interpretation; responsive to the first segment of text matching the other segment of text, comparing the graphical representation of the original segment of text with a graphical representation of the other segment of text; and responsive to the graphical representation of the original segment of text being sufficiently similar to the graphical representation of the other segment of text, grouping the suspect interpretation with the other suspect interpretation in the cluster; generating a representative question for the cluster; determining a correct answer for the representative question; and generating a corrected segment of text based on the correct answer, the corrected segment of text matching the original segment of text; and a processor configured to execute the computer program instructions stored on the non-transitory computer-readable storage medium. | 13. A computer system for correcting Optical Character Recognition (OCR) errors, the computer system comprising: a non-transitory computer-readable storage medium storing executable computer program instructions for correcting Optical Character Recognition (OCR) errors, the computer program instructions comprising instructions for: converting a graphical representation of an original segment of text into a first segment of text using a first OCR engine; converting the graphical representation of the original segment of text into a second segment of text using a second OCR engine; estimating an error probability for the first segment of text by matching the first segment of text with the second segment of text; responsive to the error probability exceeding a predetermined threshold value, generating a suspect interpretation for the first segment of text; grouping the suspect interpretation with other similar suspect interpretations to form a cluster of suspect interpretations by: comparing the first segment of text with another segment of text of another suspect interpretation; responsive to the first segment of text matching the other segment of text, comparing the graphical representation of the original segment of text with a graphical representation of the other segment of text; and responsive to the graphical representation of the original segment of text being sufficiently similar to the graphical representation of the other segment of text, grouping the suspect interpretation with the other suspect interpretation in the cluster; generating a representative question for the cluster; determining a correct answer for the representative question; and generating a corrected segment of text based on the correct answer, the corrected segment of text matching the original segment of text; and a processor configured to execute the computer program instructions stored on the non-transitory computer-readable storage medium. 18. The computer system of claim 13 , wherein estimating the error probability for the first segment of text further comprises: responsive to the first segment of text not matching the second segment of text, calculating the error probability for the first segment of text using a confidence level of the first segment of text and a confidence level of the second segment of text. | 0.542169 |
6,014,559 | 10 | 17 | 10. A method of delivering a voice mail notification to a subscriber of a voice mail system to indicate that a voice mail message is waiting in a subscriber mailbox, comprising the steps of receiving within a cellular phone network a plurality of voice mail notifications from a voice mail system that indicates different voice mail messages are waiting for respective subscribers, and forwarding, without subscriber intervention, the voice mail notifications through the cellular phone network to a private base station used by the subscribers to indicate that voice mail message are waiting in respective subscriber mailboxes, and including the step of incorporating within each voice mail notification forwarded to the private base station for respective subscribers a calling number of the calling party that left the voice mail message, a name of the calling party, if known, and the index of the voice mail messages waiting in the subscriber mailbox. | 10. A method of delivering a voice mail notification to a subscriber of a voice mail system to indicate that a voice mail message is waiting in a subscriber mailbox, comprising the steps of receiving within a cellular phone network a plurality of voice mail notifications from a voice mail system that indicates different voice mail messages are waiting for respective subscribers, and forwarding, without subscriber intervention, the voice mail notifications through the cellular phone network to a private base station used by the subscribers to indicate that voice mail message are waiting in respective subscriber mailboxes, and including the step of incorporating within each voice mail notification forwarded to the private base station for respective subscribers a calling number of the calling party that left the voice mail message, a name of the calling party, if known, and the index of the voice mail messages waiting in the subscriber mailbox. 17. A method according to claim 10 including the step of storing an index of all voice mail messages stored within a subscriber mailbox of the private base station. | 0.655462 |
8,515,811 | 7 | 8 | 7. The method of claim 6 , wherein calculating the match value begins upon selection by the user of the online advertisement. | 7. The method of claim 6 , wherein calculating the match value begins upon selection by the user of the online advertisement. 8. The method of claim 7 , wherein the personalization vector is derived at least in part from an online search and click history of the user. | 0.5 |
6,101,461 | 21 | 22 | 21. A command inputting method used when inputting characters using software for Kana-to-Chinese character conversion comprising the steps of: receiving a string comprising a plurality of characters through a keyboard; retrieving first Chinese character information or second Chinese character information corresponding to the string by looking up the string in a Chinese character dictionary in which the first Chinese character information, comprising at least one Chinese character correlated to a character string, and second Chinese character information, comprising a command and at least one Chinese character correlated to a character string: are previously stored; displaying in a list the retrieved first Chinese character information and second Chinese character information as candidates for conversion; receiving input for selecting a desired Chinese character or a macro command from the first Chinese character information or second Chinese character information displayed in a list; determining which of a Chinese character or a macro command has been selected or not according to a result of selection in said selecting step; replacing the string with at least one Chinese character and displaying the at least one Chinese character when it is determined in said determining step that a Chinese character has been selected; and executing the corresponding macro command when it is determined in said determining step that a macro command has been selected. | 21. A command inputting method used when inputting characters using software for Kana-to-Chinese character conversion comprising the steps of: receiving a string comprising a plurality of characters through a keyboard; retrieving first Chinese character information or second Chinese character information corresponding to the string by looking up the string in a Chinese character dictionary in which the first Chinese character information, comprising at least one Chinese character correlated to a character string, and second Chinese character information, comprising a command and at least one Chinese character correlated to a character string: are previously stored; displaying in a list the retrieved first Chinese character information and second Chinese character information as candidates for conversion; receiving input for selecting a desired Chinese character or a macro command from the first Chinese character information or second Chinese character information displayed in a list; determining which of a Chinese character or a macro command has been selected or not according to a result of selection in said selecting step; replacing the string with at least one Chinese character and displaying the at least one Chinese character when it is determined in said determining step that a Chinese character has been selected; and executing the corresponding macro command when it is determined in said determining step that a macro command has been selected. 22. A command inputting method used when inputting characters using software for Kana-to-Chinese character conversion according to claim 21; wherein a command or a macro command can be selected only just after carriage return is entered. | 0.5 |
8,374,874 | 9 | 13 | 9. An apparatus for establishing a vocal demeanor for an application having a speech interface that presents speech content according to the vocal demeanor, the apparatus comprising: a computer processor; and a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions to cause the computer processor to carry out acts comprising: determining, from input of a user, at least one first attribute of the user's interaction with the application; specifying, based on an evaluation of the at least one first attribute of the user's interaction with the application, a particular voice family to be used by the application in presenting speech to the user via a speech interface, wherein the particular voice family identifies a particular person's voice by describing an overall nature and timbre of the particular person's voice in specific terms; selecting the vocal demeanor for the application using the specified particular voice family as a criterion for the selecting, wherein the vocal demeanor that is selected is configured to present speech using the particular voice family that was specified based on the evaluation of the at least one first attribute of the user's interaction; and incorporating the vocal demeanor into the application by presenting at least some speech content via the application in the voice family. | 9. An apparatus for establishing a vocal demeanor for an application having a speech interface that presents speech content according to the vocal demeanor, the apparatus comprising: a computer processor; and a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions to cause the computer processor to carry out acts comprising: determining, from input of a user, at least one first attribute of the user's interaction with the application; specifying, based on an evaluation of the at least one first attribute of the user's interaction with the application, a particular voice family to be used by the application in presenting speech to the user via a speech interface, wherein the particular voice family identifies a particular person's voice by describing an overall nature and timbre of the particular person's voice in specific terms; selecting the vocal demeanor for the application using the specified particular voice family as a criterion for the selecting, wherein the vocal demeanor that is selected is configured to present speech using the particular voice family that was specified based on the evaluation of the at least one first attribute of the user's interaction; and incorporating the vocal demeanor into the application by presenting at least some speech content via the application in the voice family. 13. The apparatus of claim 9 , wherein incorporating the vocal demeanor into the application further comprises linking at least one markup element of a markup document of the application to a style of a cascading style sheet. | 0.716625 |
5,471,610 | 9 | 11 | 9. A text search system for deciding en bloc whether or not a plurality of user-designated search terms exist in a text composed of characters expressed in the form of character codes, characterized in that said system comprises: character string storage means for storing a text; concatenate filtering means for fetching character codes sequentially from the text read out from said character string storage means to thereby make decision as to whether or not n, where n represents an integer not smaller than 2, character codes as fetched are included in said search terms as a concatenate character string and output said n concatenate character codes only when said codes are included in said search terms; character string matching means for deciding by matching en bloc whether or not said search terms exist in a compound character string composed of a chain of the character strings each constituted by n concatenate character codes outputted from said concatenate filtering means; and synchronizing means provided between said concatenate filtering means and said character string matching means for buffering differences in processing speed while transferring data from said concatenate filtering means to said character string matching means. | 9. A text search system for deciding en bloc whether or not a plurality of user-designated search terms exist in a text composed of characters expressed in the form of character codes, characterized in that said system comprises: character string storage means for storing a text; concatenate filtering means for fetching character codes sequentially from the text read out from said character string storage means to thereby make decision as to whether or not n, where n represents an integer not smaller than 2, character codes as fetched are included in said search terms as a concatenate character string and output said n concatenate character codes only when said codes are included in said search terms; character string matching means for deciding by matching en bloc whether or not said search terms exist in a compound character string composed of a chain of the character strings each constituted by n concatenate character codes outputted from said concatenate filtering means; and synchronizing means provided between said concatenate filtering means and said character string matching means for buffering differences in processing speed while transferring data from said concatenate filtering means to said character string matching means. 11. A text search system set forth in claim 9, characterized in that said concatenate filtering means is comprised of a pointer table for storing order numbers, referred to as serial numbers, allotted in correspondence to the character codes included in the search term designated previously in slots which can be accessed with addresses indicated by said character codes, and a concatenate filtering table storing flags indicating "ON" in slots accessed by using as addresses therefor codes each represented by a string of the serial numbers corresponding to n concatenate character codes, respectively, which are included in the designated search term while storing "OFF" in the other slots. | 0.826577 |
7,523,440 | 1 | 75 | 1. A method for generating a formatted user interface for editing information associated with entities in software development projects loaded in a software development environment, the method comprising: loading one or more software development projects in the software development environment; displaying a first user interface element displaying entities of the one or more software development projects loaded in the software development environment, wherein the first user interface element enables users to select multiple entities displayed in the first user interface element; receiving a selection of a plurality of entities in the one or more loaded software development projects with the first user interface element; identifying editable information associated with the selected plurality of entities; identifying common data associated with the selected plurality of entities, the identifying including classifying data in an intersection of data associated with the selected plurality of entities as common data; and dynamically generating from the identified editable information and the identified common data using a computational device a formatted second user interface element displaying at least a portion of the identified editable information and the identified common data associated with the selected plurality of entities, the formatted second user interface element enabling the users to distinguish data associated with the selected plurality of entities that is not common data, the formatted second user interface element enabling the users to edit data that is common data. | 1. A method for generating a formatted user interface for editing information associated with entities in software development projects loaded in a software development environment, the method comprising: loading one or more software development projects in the software development environment; displaying a first user interface element displaying entities of the one or more software development projects loaded in the software development environment, wherein the first user interface element enables users to select multiple entities displayed in the first user interface element; receiving a selection of a plurality of entities in the one or more loaded software development projects with the first user interface element; identifying editable information associated with the selected plurality of entities; identifying common data associated with the selected plurality of entities, the identifying including classifying data in an intersection of data associated with the selected plurality of entities as common data; and dynamically generating from the identified editable information and the identified common data using a computational device a formatted second user interface element displaying at least a portion of the identified editable information and the identified common data associated with the selected plurality of entities, the formatted second user interface element enabling the users to distinguish data associated with the selected plurality of entities that is not common data, the formatted second user interface element enabling the users to edit data that is common data. 75. The method of claim 1 , wherein the selected plurality of editable entities is selected from two or more of the loaded software development projects. | 0.703488 |
8,397,165 | 10 | 11 | 10. The method of claim 1 , wherein the first group of calendar events is identified by a first unique visual property and the second group of calendar events is identified by a second unique visual property. | 10. The method of claim 1 , wherein the first group of calendar events is identified by a first unique visual property and the second group of calendar events is identified by a second unique visual property. 11. The method of claim 10 , wherein the first unique visual property and the second unique visual property are each a different color, shading, or other visual characteristic. | 0.5 |
8,086,548 | 1 | 3 | 1. A method, comprising: selecting a collection of documents which include a first set of passages; constructing a passage-sequence model based on the first set of passages, wherein the passage-sequence model is a hidden Markov model (HMM), wherein constructing the passage-sequence model involves determining transition probabilities between states of the HMM based on a sequential relationship associated with the first set of passages; receiving a new document which includes a second set of passages; and determining a sequence of operations associated with the new document in relation to the collection of documents based on the constructed passage-sequence model. | 1. A method, comprising: selecting a collection of documents which include a first set of passages; constructing a passage-sequence model based on the first set of passages, wherein the passage-sequence model is a hidden Markov model (HMM), wherein constructing the passage-sequence model involves determining transition probabilities between states of the HMM based on a sequential relationship associated with the first set of passages; receiving a new document which includes a second set of passages; and determining a sequence of operations associated with the new document in relation to the collection of documents based on the constructed passage-sequence model. 3. The method of claim 1 , wherein the method further comprises generating fingerprints for the first set of passages, and wherein at least one fingerprint corresponds to a state of the HMM. | 0.5 |
8,108,216 | 17 | 18 | 17. A non-transitory computer readable storage medium storing instructions of a computer program which when executed by a computer results in performance of steps comprising: dividing a phoneme string corresponding to target speech into a plurality of segments to generate a first segment sequence; generating a plurality of first speech unit strings corresponding to the first segment sequence by combining a plurality of speech units based on the first segment sequence and selecting one speech unit string from said plurality of first speech unit strings; and concatenating a plurality of speech units included in the selected speech unit string to generate synthetic speech, the generating/selecting including performing repeatedly a first processing and a second processing, the first processing generating, based on maximum W, wherein W is a predetermined value, second speech unit strings corresponding to a second segment sequence as a partial sequence of the first segment sequence, a plurality of third speech unit strings corresponding to a third segment sequence as a partial sequence obtained by adding a segment to the second segment sequence, and the second processing selecting maximum W third speech unit strings from said plurality of third speech unit strings, calculating a total cost of each of said plurality of third speech unit strings, calculating a penalty coefficient corresponding to the total cost for each of said plurality of third speech unit strings based on a restriction concerning quickness of speech unit data acquisition, wherein the penalty coefficient depending on extent in which the restriction is approached, and calculating a evaluation value of each of said plurality of third speech unit strings by correcting the total cost with the penalty coefficient, wherein the second processing including selecting the maximum W third speech unit strings from said plurality of third speech unit strings based on the evaluation value of each of said plurality of third speech unit strings. | 17. A non-transitory computer readable storage medium storing instructions of a computer program which when executed by a computer results in performance of steps comprising: dividing a phoneme string corresponding to target speech into a plurality of segments to generate a first segment sequence; generating a plurality of first speech unit strings corresponding to the first segment sequence by combining a plurality of speech units based on the first segment sequence and selecting one speech unit string from said plurality of first speech unit strings; and concatenating a plurality of speech units included in the selected speech unit string to generate synthetic speech, the generating/selecting including performing repeatedly a first processing and a second processing, the first processing generating, based on maximum W, wherein W is a predetermined value, second speech unit strings corresponding to a second segment sequence as a partial sequence of the first segment sequence, a plurality of third speech unit strings corresponding to a third segment sequence as a partial sequence obtained by adding a segment to the second segment sequence, and the second processing selecting maximum W third speech unit strings from said plurality of third speech unit strings, calculating a total cost of each of said plurality of third speech unit strings, calculating a penalty coefficient corresponding to the total cost for each of said plurality of third speech unit strings based on a restriction concerning quickness of speech unit data acquisition, wherein the penalty coefficient depending on extent in which the restriction is approached, and calculating a evaluation value of each of said plurality of third speech unit strings by correcting the total cost with the penalty coefficient, wherein the second processing including selecting the maximum W third speech unit strings from said plurality of third speech unit strings based on the evaluation value of each of said plurality of third speech unit strings. 18. The computer readable storage medium according to claim 17 , wherein the steps further comprising: preparing in advance a first storage unit including a plurality of storage mediums with different data acquisition speeds, which store a plurality of speech units, respectively; preparing in advance a second storage unit configured to store information indicating in which one of said plurality of storage mediums each of the speech units is stored; and acquiring the plurality of speech units from the first storage unit in accordance with the information before concatenating the plurality of speech units, and wherein the calculating the penalty coefficient including calculating the penalty coefficient for each of said plurality of third speech unit strings based on a restriction concerning quickness of data acquisition which is to be satisfied when the speech units included in the first speech unit string are acquired from the first storage unit by the concatenation unit and a statistic determined depending on which one of said plurality of storage mediums each of all speech units included in the third speech unit string is stored in. | 0.5 |
6,052,693 | 1 | 3 | 1. A method for combining types of items of information from a plurality of text-based information sources in a plurality of formats, into items in a database, with at least one information source including unstructured written text and structured text, and at least one item of information including one or more attributes, with each attribute having at least one value, the method comprising the steps of: for each information source, extracting and organizing items of information from the structured and unstructured written text of the information source, to generate an index plan, with each item in the plan organized as a hierarchic data structure representing the item's attributes, their values and the locations of the text in the information source supporting those values; and researching and consolidating the items of information in the index plan into items in the database to avoid duplication of items in the database. | 1. A method for combining types of items of information from a plurality of text-based information sources in a plurality of formats, into items in a database, with at least one information source including unstructured written text and structured text, and at least one item of information including one or more attributes, with each attribute having at least one value, the method comprising the steps of: for each information source, extracting and organizing items of information from the structured and unstructured written text of the information source, to generate an index plan, with each item in the plan organized as a hierarchic data structure representing the item's attributes, their values and the locations of the text in the information source supporting those values; and researching and consolidating the items of information in the index plan into items in the database to avoid duplication of items in the database. 3. The method as recited in claim 1 wherein each information source can include zero or more items of information. | 0.676136 |
10,032,448 | 15 | 17 | 15. A system comprising: a memory; one or more processor in communication with memory; and program instructions executable by the one or more processor via the memory to perform a method for expanding a language model corresponding to a domain, comprising: determining that one or more word of a feature vector more supports than negates a language model corresponding to the domain based on a sensitivity of respective word, the determining comprising: (i) calculating an individual confidence score for a dictionary definition corresponding to each word of the feature vector, (ii) calculating a collective confidence score based on the individual confidence score for each word and a respective half-decay; (iii) calculating a respective sensitivity of each word as a weighted measure representing how each word supports or negates the language model, based on the collective confidence score; (iv) ascertaining that the sensitivity of one of each word is greater than or equal to a sensitivity threshold; and (v) updating the language model in the corpora by adding the one of each word from the ascertaining to the language model; adding the one or more word to the language model, wherein the language model is stored in a corpora coupled to a cloud; enhancing the language model by machine learning such that the language model accurately and comprehensively facilitates an automatic speech recognition (ASR) system for the domain; and performing speech recognition on a received speech input utilizing at least the enhanced language model. | 15. A system comprising: a memory; one or more processor in communication with memory; and program instructions executable by the one or more processor via the memory to perform a method for expanding a language model corresponding to a domain, comprising: determining that one or more word of a feature vector more supports than negates a language model corresponding to the domain based on a sensitivity of respective word, the determining comprising: (i) calculating an individual confidence score for a dictionary definition corresponding to each word of the feature vector, (ii) calculating a collective confidence score based on the individual confidence score for each word and a respective half-decay; (iii) calculating a respective sensitivity of each word as a weighted measure representing how each word supports or negates the language model, based on the collective confidence score; (iv) ascertaining that the sensitivity of one of each word is greater than or equal to a sensitivity threshold; and (v) updating the language model in the corpora by adding the one of each word from the ascertaining to the language model; adding the one or more word to the language model, wherein the language model is stored in a corpora coupled to a cloud; enhancing the language model by machine learning such that the language model accurately and comprehensively facilitates an automatic speech recognition (ASR) system for the domain; and performing speech recognition on a received speech input utilizing at least the enhanced language model. 17. The system of claim 15 , the enhancing comprising: crawling the live content from one or more subject website; parsing, tokenizing and tagging part-of-speech each word sequence of the live content, responsive to determining that the language of the live content is supported and that the live content is grammatically correct; assessing relevancy of each word sequence of the live content to the domain, wherein each word sequence includes one or more word; deriving the one or more secondary term from each word sequence of the live content; assessing relevancy of each secondary term from the deriving; and expanding the language model stored in the corpora with each secondary term that more supports than negates the language model, based on respective sensitivity of each secondary term and a sensitivity threshold. | 0.641427 |
7,774,195 | 9 | 11 | 9. The operating system of claim 1 wherein the at least one input source external to the localization platform includes a community of input sources, the community comprising a plurality of input sources external to the localization platform. | 9. The operating system of claim 1 wherein the at least one input source external to the localization platform includes a community of input sources, the community comprising a plurality of input sources external to the localization platform. 11. The operating system of claim 9 wherein the data gathering component receives applications from the input sources for localization by the localization platform. | 0.556757 |
4,841,478 | 11 | 13 | 11. A document processor comprising: input means for inputting character information; memory means for storing the character information input by said input means; a carrier having a print head mounted thereon; a first scale; print means, having a scale indicator for indicating the position of said carrier relative to said first scale, for moving said carrier in the direction of said scale as indicated by said scale indicator and causing said print head to print the characters onto a print medium; display means for displaying a second scale indicating the carrier position in correspondence with said first scale as indicated by said scale indicator; and control means for controlling said print means such that said carrier is moved, and for controlling said display means such that said second scale of said display means is displayed in correspondence with the characters to be printed. | 11. A document processor comprising: input means for inputting character information; memory means for storing the character information input by said input means; a carrier having a print head mounted thereon; a first scale; print means, having a scale indicator for indicating the position of said carrier relative to said first scale, for moving said carrier in the direction of said scale as indicated by said scale indicator and causing said print head to print the characters onto a print medium; display means for displaying a second scale indicating the carrier position in correspondence with said first scale as indicated by said scale indicator; and control means for controlling said print means such that said carrier is moved, and for controlling said display means such that said second scale of said display means is displayed in correspondence with the characters to be printed. 13. A document processor according to claim 11, wherein said display means comprises a one-line display. | 0.845697 |
8,515,786 | 14 | 16 | 14. A non-transitory machine-readable medium comprising a software program for rule generation, the software program comprising instructions executable with a processor to: generate a graphical user interface for creation of a navigation rule, the navigation rule indicative of where to navigate to when leaving a page of the software program; receive a first expression parameter, a logical operator, and at least one expression parameter value entered through the graphical user interface in response to user input at runtime of the software program, the first expression parameter identifying a question, the at least one expression parameter value including at least one potential answer to the question, wherein the first expression parameter and the at least one expression parameter value are operands of the logical operator; generate the navigation rule, the navigation rule comprising an evaluative expression comprising the first expression parameter, the operator, the at least one expression parameter value, and a second expression parameter; store the evaluative expression in a database; receive an answer to the question from user input at runtime of the software program; evaluate the evaluative expression retrieved from the database at runtime of the software program, the first expression parameter set to the answer in the evaluation of the evaluative expression; and navigate away from the page to a next page of the software program based on the evaluation of the evaluative expression of the navigation rule without a stop of the software program after the receipt of the first expression parameter, the logical operator, and the at least one expression parameter value from the graphical user interface. | 14. A non-transitory machine-readable medium comprising a software program for rule generation, the software program comprising instructions executable with a processor to: generate a graphical user interface for creation of a navigation rule, the navigation rule indicative of where to navigate to when leaving a page of the software program; receive a first expression parameter, a logical operator, and at least one expression parameter value entered through the graphical user interface in response to user input at runtime of the software program, the first expression parameter identifying a question, the at least one expression parameter value including at least one potential answer to the question, wherein the first expression parameter and the at least one expression parameter value are operands of the logical operator; generate the navigation rule, the navigation rule comprising an evaluative expression comprising the first expression parameter, the operator, the at least one expression parameter value, and a second expression parameter; store the evaluative expression in a database; receive an answer to the question from user input at runtime of the software program; evaluate the evaluative expression retrieved from the database at runtime of the software program, the first expression parameter set to the answer in the evaluation of the evaluative expression; and navigate away from the page to a next page of the software program based on the evaluation of the evaluative expression of the navigation rule without a stop of the software program after the receipt of the first expression parameter, the logical operator, and the at least one expression parameter value from the graphical user interface. 16. The non-transitory machine-readable medium of claim 14 , wherein the instructions are further configured to: generate a second graphical user interface that includes a name of a page display rule selectable for inclusion in evaluative expressions of rules other than the page display rule, the page display rule indicative of whether to display the question on the page; and receive an expiration date for the page display rule from a third graphical user interface in response to user input, the expiration date indicative of when to stop including the name of the page display rule in the second graphical user interface. | 0.5 |
9,501,763 | 2 | 3 | 2. The method of claim 1 , further comprising: further determining a value for a different social collaborative criterion; and, weighting each of the values into a single value for transformation into the priority. | 2. The method of claim 1 , further comprising: further determining a value for a different social collaborative criterion; and, weighting each of the values into a single value for transformation into the priority. 3. The method of claim 2 , further comprising disabling a determination of one of the social collaborative criterion. | 0.819444 |
8,214,196 | 14 | 15 | 14. The apparatus of claim 10 , wherein the insertion module includes an insertion table including the probability associated with inserting the additional word in a position relative to one of the child nodes. | 14. The apparatus of claim 10 , wherein the insertion module includes an insertion table including the probability associated with inserting the additional word in a position relative to one of the child nodes. 15. The apparatus of claim 14 , wherein the insertion probability is associated with a label pair including the label of said one or more child node and the label of the parent node associated with said child node. | 0.5 |
8,099,244 | 13 | 15 | 13. A computer system comprising: an input for selecting a plurality of diseases; an interface for interactively subjecting a subject to a plurality of questions relevant to the plurality of diseases; a data acquisition interface for acquiring respective answers from the subject to the said plurality of questions; a programmed processor including a computer-readable medium having computer executable instructions for computing a risk factor for the subject for the plurality of diseases using said answers and an accessible database comprising a plurality of respective deterministically established partial risk factors for diseases, said partial risk factors being assigned to the said acquired answers; and a database comprising a plurality of respective deterministically established partial risk factors for diseases, said partial risk factors being assigned to the said acquired answers. | 13. A computer system comprising: an input for selecting a plurality of diseases; an interface for interactively subjecting a subject to a plurality of questions relevant to the plurality of diseases; a data acquisition interface for acquiring respective answers from the subject to the said plurality of questions; a programmed processor including a computer-readable medium having computer executable instructions for computing a risk factor for the subject for the plurality of diseases using said answers and an accessible database comprising a plurality of respective deterministically established partial risk factors for diseases, said partial risk factors being assigned to the said acquired answers; and a database comprising a plurality of respective deterministically established partial risk factors for diseases, said partial risk factors being assigned to the said acquired answers. 15. The computer system according to claim 13 , wherein the programmed processor is further arranged for: feeding-back results of diagnosis of a plurality of subjects for respective diseases to the database of deterministically established risk factors; and adjusting said deterministically established risk factors based on said feeding-back. | 0.501453 |
8,631,116 | 1 | 4 | 1. A web site performance monitoring system comprising: a performance module configured to allow a user to utilize a graphical interface to define and associate performance operational rules with a web site, wherein the performance module includes a module configured to assign site metric attributes to a single pixel on a page within the website, the site metric attributes comprising marketing information; a storage device configured to store data representative of the performance operational rules; a monitoring module configured to assess the effectiveness of the website at achieving performance criteria defined by the performance operational rules, wherein the monitoring module transmits alerts in response to the website failing to achieve the performance criteria defined by the website performance operational rules; and a report module configured to generate reports on operational performance and to display site level pixel metrics from the single pixel. | 1. A web site performance monitoring system comprising: a performance module configured to allow a user to utilize a graphical interface to define and associate performance operational rules with a web site, wherein the performance module includes a module configured to assign site metric attributes to a single pixel on a page within the website, the site metric attributes comprising marketing information; a storage device configured to store data representative of the performance operational rules; a monitoring module configured to assess the effectiveness of the website at achieving performance criteria defined by the performance operational rules, wherein the monitoring module transmits alerts in response to the website failing to achieve the performance criteria defined by the website performance operational rules; and a report module configured to generate reports on operational performance and to display site level pixel metrics from the single pixel. 4. The website performance monitoring system of claim 1 wherein defining performance operational rules include setting performance operational thresholds and alerts. | 0.807692 |
9,122,540 | 16 | 17 | 16. A computer system comprising one or more processors, a memory coupled to the one or more processors, and one or more computer readable hardware storage devices coupled to the processors, said one or more computer readable hardware storage devices containing program code which, upon being executed by the one or more processors via the memory, implements a method for transforming a first computer program having a plurality of program statements to a second computer program, said method comprising: translating, by the one or more processors, a parsed first computer program to the second computer program, wherein the first computer program was parsed without interruption, wherein the first computer program comprises a first program statement that includes a first error and has thrown a parsing exception with respect to the first error, wherein said translating comprises: (i) identifying a second program statement in the parsed first computer program that includes a second error and has thrown a translation exception with respect to the second error prior to said translating, (ii) rolling back said translating to a predefined check point prior to the second program statement in the parsed first computer program, wherein the predefined check point is associated with a statement in the parsed first computer program that was successfully translated during said translating, and (iii) generating an executable equivalent translation for the second statement that does not throw a translation exception; and after said translating, generating, by the one or more processors, a mapping of one or more statements in the second computer program to one or more statements in the first computer program. | 16. A computer system comprising one or more processors, a memory coupled to the one or more processors, and one or more computer readable hardware storage devices coupled to the processors, said one or more computer readable hardware storage devices containing program code which, upon being executed by the one or more processors via the memory, implements a method for transforming a first computer program having a plurality of program statements to a second computer program, said method comprising: translating, by the one or more processors, a parsed first computer program to the second computer program, wherein the first computer program was parsed without interruption, wherein the first computer program comprises a first program statement that includes a first error and has thrown a parsing exception with respect to the first error, wherein said translating comprises: (i) identifying a second program statement in the parsed first computer program that includes a second error and has thrown a translation exception with respect to the second error prior to said translating, (ii) rolling back said translating to a predefined check point prior to the second program statement in the parsed first computer program, wherein the predefined check point is associated with a statement in the parsed first computer program that was successfully translated during said translating, and (iii) generating an executable equivalent translation for the second statement that does not throw a translation exception; and after said translating, generating, by the one or more processors, a mapping of one or more statements in the second computer program to one or more statements in the first computer program. 17. The computer system of claim 16 , said method further comprising: prior to said generating, parsing, by the one or more processors, each program statement in the first computer program to generate the parsed first computer program. | 0.5 |
8,990,080 | 11 | 12 | 11. The article of claim 9 , the medium further comprising instructions that when executed cause the system to: persist the normalization cache on a non-volatile computer-readable storage medium. | 11. The article of claim 9 , the medium further comprising instructions that when executed cause the system to: persist the normalization cache on a non-volatile computer-readable storage medium. 12. The article of claim 11 , the medium further comprising instructions that when executed cause the system to: assign an expiration date to the normalization cache; and rebuild the normalization cache when a date exceeds the expiration date. | 0.670732 |
8,375,014 | 1 | 5 | 1. A system comprising: one or more processors; a database schema including a plurality of data sources, each data source including one or more fields for storing data, and metadata defining relationships amongst the fields within or between data sources; a schema parser executed by at least one of the processors and configured to determine one or more datasets of data stored within or referenced from the database schema, wherein a dataset includes one or more fields from the database schema and represents the data stored in the one or more fields; an input handler executed by at least one of the processors and configured to receive a user's selection of one or more of the datasets via a graphical user interface, wherein the input handler is configured to determine that a first graphical icon representing a first dataset is graphically associated within the graphical user interface with a second graphical icon representing a second dataset; a translation engine executed by at least one of the processors and configured to provide, responsive to the graphical association of the first and second icons, operations for refining the data of the selected datasets into a result set via a query, wherein the translation engine is configured to determine which operations to provide based on the relationships of the selected datasets as stored or derived from the metadata, wherein the translation engine is configured to provide the operations to a user via the interface, wherein the operations are provided in a natural language expression corresponding to the relationships as determined from the metadata, wherein the input handler is configured to receive a selection of one of the operations provided by the translation engine; a query engine executed by at least one of the processors and configured to provide a graphical depiction of the query via the interface, the graphical query including operational flow indicators indicating a directional flow of the query from the selected datasets with the selected operation resulting in the result set; and a logic engine executed by at least one of the processors and configured to assemble a machine readable structured query language (SQL) query based on the graphical depiction of the query, wherein the logic engine comprises a plurality of different subroutines, each different subroutine being configured to process a different type of operation represented by a particular type of element in the graphical query to generate a SQL substatement of the elements's operation wherein the logic engine is further configured to incorporate the SQL substatements into a complete machine readable SQL query. | 1. A system comprising: one or more processors; a database schema including a plurality of data sources, each data source including one or more fields for storing data, and metadata defining relationships amongst the fields within or between data sources; a schema parser executed by at least one of the processors and configured to determine one or more datasets of data stored within or referenced from the database schema, wherein a dataset includes one or more fields from the database schema and represents the data stored in the one or more fields; an input handler executed by at least one of the processors and configured to receive a user's selection of one or more of the datasets via a graphical user interface, wherein the input handler is configured to determine that a first graphical icon representing a first dataset is graphically associated within the graphical user interface with a second graphical icon representing a second dataset; a translation engine executed by at least one of the processors and configured to provide, responsive to the graphical association of the first and second icons, operations for refining the data of the selected datasets into a result set via a query, wherein the translation engine is configured to determine which operations to provide based on the relationships of the selected datasets as stored or derived from the metadata, wherein the translation engine is configured to provide the operations to a user via the interface, wherein the operations are provided in a natural language expression corresponding to the relationships as determined from the metadata, wherein the input handler is configured to receive a selection of one of the operations provided by the translation engine; a query engine executed by at least one of the processors and configured to provide a graphical depiction of the query via the interface, the graphical query including operational flow indicators indicating a directional flow of the query from the selected datasets with the selected operation resulting in the result set; and a logic engine executed by at least one of the processors and configured to assemble a machine readable structured query language (SQL) query based on the graphical depiction of the query, wherein the logic engine comprises a plurality of different subroutines, each different subroutine being configured to process a different type of operation represented by a particular type of element in the graphical query to generate a SQL substatement of the elements's operation wherein the logic engine is further configured to incorporate the SQL substatements into a complete machine readable SQL query. 5. The system of claim 1 , wherein, in response to the input handler receiving a selection of one of the provided operations, the query engine is configured to provide a graphical depiction of the query via the interface, the graphical query including a third icon representing a third dataset formed in response to the selected operation, the third icon being connected to the first and second icons by one or more operational flow indicators indicating a directional flow of the query from the first and second datasets to the third dataset. | 0.5 |
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