patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
1
|
|---|---|---|---|---|---|
8,086,594 | 1 | 2 | 1. A computer implemented method for bifurcated document relevance scoring of documents in a document collection, the method comprising: indexing a plurality of documents in the document collection by: providing a set of phrases; for a plurality of documents in the document collection: identifying a plurality of phrases from the set of phrases that occurs in the document; for each phrase in a plurality of the identified phrases, scoring the phrase to produce a phrase relevance score for the phrase with respect to the document, and storing the phrase relevance score for the document in a phrase posting list for the phrase; receiving a search query of three or more words; determining a set of valid phrases in the search query by: decomposing, by at least one processor of a computer system, the query into a plurality of candidate phrasifications, including different groupings of words of the query, each candidate phrasification comprising a disjoint union of component phrases, and each component phrase including at least one word or related word of the query; scoring, by at least one of the processors of the computer system, at least two candidate phrasifications, wherein the candidate phrasifications include one or more component phrases, wherein the scoring is based on a probability of occurrence of each of the candidate phrasification's component phrases in a corpus of documents and is based on the number of component phrases constituting the candidate phrasification, wherein candidate phrasifications having relatively fewer component phrases are weighted higher than candidate phrasifications having relatively more component phrases; comparing, by at least one of the processors of the computer system, a score for each scored candidate phrasification to a threshold value; and selecting, by at least one of the processors of the computer system, at least one candidate phrasification, wherein the scores of each selected candidate phrasification exceed a threshold value and identifying the component phrase(s) of the selected candidate phrasification(s) as valid phrases for the search query; for each valid phrase for the search query, obtaining from the phrase posting list for the valid phrase the phrase relevance score for documents in which the valid phrase occurs; and for documents in which a valid phrase of the query occurs, scoring the document to produce a final relevance score using the phrase relevance scores for the document and based on the valid phrases of the search query. | 1. A computer implemented method for bifurcated document relevance scoring of documents in a document collection, the method comprising: indexing a plurality of documents in the document collection by: providing a set of phrases; for a plurality of documents in the document collection: identifying a plurality of phrases from the set of phrases that occurs in the document; for each phrase in a plurality of the identified phrases, scoring the phrase to produce a phrase relevance score for the phrase with respect to the document, and storing the phrase relevance score for the document in a phrase posting list for the phrase; receiving a search query of three or more words; determining a set of valid phrases in the search query by: decomposing, by at least one processor of a computer system, the query into a plurality of candidate phrasifications, including different groupings of words of the query, each candidate phrasification comprising a disjoint union of component phrases, and each component phrase including at least one word or related word of the query; scoring, by at least one of the processors of the computer system, at least two candidate phrasifications, wherein the candidate phrasifications include one or more component phrases, wherein the scoring is based on a probability of occurrence of each of the candidate phrasification's component phrases in a corpus of documents and is based on the number of component phrases constituting the candidate phrasification, wherein candidate phrasifications having relatively fewer component phrases are weighted higher than candidate phrasifications having relatively more component phrases; comparing, by at least one of the processors of the computer system, a score for each scored candidate phrasification to a threshold value; and selecting, by at least one of the processors of the computer system, at least one candidate phrasification, wherein the scores of each selected candidate phrasification exceed a threshold value and identifying the component phrase(s) of the selected candidate phrasification(s) as valid phrases for the search query; for each valid phrase for the search query, obtaining from the phrase posting list for the valid phrase the phrase relevance score for documents in which the valid phrase occurs; and for documents in which a valid phrase of the query occurs, scoring the document to produce a final relevance score using the phrase relevance scores for the document and based on the valid phrases of the search query. 2. The method of claim 1 , wherein: scoring the phrase to produce a phrase relevance score for the phrase with respect to the document comprises scoring the phrase and the document using a first scoring function; and scoring the document to produce a final relevance score using the phrase relevance scores for the document comprises scoring the document using a second scoring function. | 0.706373 |
7,831,529 | 7 | 8 | 7. The system of claim 1 , further comprising a context input component that analyzes one or more context inputs to determine the user's present context state in order to direct the one or more items in accordance with determined urgency of the one or more items and the user's present context. | 7. The system of claim 1 , further comprising a context input component that analyzes one or more context inputs to determine the user's present context state in order to direct the one or more items in accordance with determined urgency of the one or more items and the user's present context. 8. The system of claim 7 , the one or more context inputs include evidence of at least one selected from the group consisting of keyboard activities, mouse movements, microphone inputs, camera inputs, time inputs and electronic calendar information relating to the user's activity. | 0.867951 |
8,166,386 | 1 | 7 | 1. A method for producing a patent specification, comprising the steps of: inputting a title; entering a set of selection items for selecting the different files of invention from one type of electronic circuit, structural device, software method or biological chemistry; providing a computer-enabled graphic interface according to the selected type, inputting names and functions thereof using the graphic interface, wherein the graphic interface uses blocks to show connecting relationship among the inputted contents, and each block represents the user-input name and function or description thereof, so as to produce an output data section, the output data description changes responsive to the change of the connecting relationship of the blocks; allowing to input basic elements or units using the graphic interfaces based on the technical characteristics and forming the output data section, comprising: (a) combining predetermined texts and symbols of a basic element within the graphic interface having the name for forming a data unit; (b) combining the predetermined texts and symbols of another basic element within the graphic interface having the name for forming another data unit; (c) determining whether the descriptions of the names and functions within the graphic interfaces input by the user form the data unit; (d) combining the data units when the input names and functions form the data unit; (e) forming the output data section to be an independent claim; forming the output data section as a set of claims; operating determinations over the set of claims, comprising: (f) determining whether a negative description is presented in the data section, and deleting the negative description if the determination is positive; (g) determining whether a defining description indicating the minimum, maximum or comprising 0%, 100% is presented in the data section, further comprising a step of determining the description indicating the maximum or minimum whether it is understood by those who refer to this technical field, deleting the description if the determination is negative, and displaying an indicating frame for generating a warning to the user; (h) determining whether an indefinite description is presented in the data section, and deleting such description if the determination is positive; (i) determining whether a description contains relative standard or indefinite level is presented in the data section, and deleting such description if the determination is positive; (j) determining whether the data section satisfies the principle of “single sentence”, and if the determination is negative, modifying the whole description of the data section to correct a description in compliance with requirement of single sentence; (k) completing the output data section; inputting data into multiple sets of text areas, comprising: (l) inputting motivation, objectives, and solutions; (m) combining, transferring and arranging the data section of multiple sets of output data sections as the contents of invention; (n) inputting prior art and drawbacks, wherein the section of prior art has a text area to be filled with reference documents, a patent number to link to a patent search website via Internet and the text file downloaded from the patent search website, and the descriptive texts of the reference are extracted as the contents of the data section of prior art; (o) combining, transferring and arranging the data section of multiple sets of output data sections as the section of prior art; (p) inputting comparison; (q) combining, transferring and arranging the data section of multiple sets of output data sections as detailed description of the invention; (r) arranging the text area of comparison to the last paragraph of the data section in the detailed description of the invention; collocating the input data into the multiple sets of text areas with the output data section, transferring and arranging the input description, thereby forming multiple sets of output data sections; and outputting a document having the multiple sets of output data sections as a patent specification. | 1. A method for producing a patent specification, comprising the steps of: inputting a title; entering a set of selection items for selecting the different files of invention from one type of electronic circuit, structural device, software method or biological chemistry; providing a computer-enabled graphic interface according to the selected type, inputting names and functions thereof using the graphic interface, wherein the graphic interface uses blocks to show connecting relationship among the inputted contents, and each block represents the user-input name and function or description thereof, so as to produce an output data section, the output data description changes responsive to the change of the connecting relationship of the blocks; allowing to input basic elements or units using the graphic interfaces based on the technical characteristics and forming the output data section, comprising: (a) combining predetermined texts and symbols of a basic element within the graphic interface having the name for forming a data unit; (b) combining the predetermined texts and symbols of another basic element within the graphic interface having the name for forming another data unit; (c) determining whether the descriptions of the names and functions within the graphic interfaces input by the user form the data unit; (d) combining the data units when the input names and functions form the data unit; (e) forming the output data section to be an independent claim; forming the output data section as a set of claims; operating determinations over the set of claims, comprising: (f) determining whether a negative description is presented in the data section, and deleting the negative description if the determination is positive; (g) determining whether a defining description indicating the minimum, maximum or comprising 0%, 100% is presented in the data section, further comprising a step of determining the description indicating the maximum or minimum whether it is understood by those who refer to this technical field, deleting the description if the determination is negative, and displaying an indicating frame for generating a warning to the user; (h) determining whether an indefinite description is presented in the data section, and deleting such description if the determination is positive; (i) determining whether a description contains relative standard or indefinite level is presented in the data section, and deleting such description if the determination is positive; (j) determining whether the data section satisfies the principle of “single sentence”, and if the determination is negative, modifying the whole description of the data section to correct a description in compliance with requirement of single sentence; (k) completing the output data section; inputting data into multiple sets of text areas, comprising: (l) inputting motivation, objectives, and solutions; (m) combining, transferring and arranging the data section of multiple sets of output data sections as the contents of invention; (n) inputting prior art and drawbacks, wherein the section of prior art has a text area to be filled with reference documents, a patent number to link to a patent search website via Internet and the text file downloaded from the patent search website, and the descriptive texts of the reference are extracted as the contents of the data section of prior art; (o) combining, transferring and arranging the data section of multiple sets of output data sections as the section of prior art; (p) inputting comparison; (q) combining, transferring and arranging the data section of multiple sets of output data sections as detailed description of the invention; (r) arranging the text area of comparison to the last paragraph of the data section in the detailed description of the invention; collocating the input data into the multiple sets of text areas with the output data section, transferring and arranging the input description, thereby forming multiple sets of output data sections; and outputting a document having the multiple sets of output data sections as a patent specification. 7. The method for producing a patent specification according to claim 1 , wherein the inputting is achieved by inputting via voice and then performing voice identification, or scanning a word file directly and then performing word identification. | 0.903378 |
7,996,211 | 25 | 26 | 25. The computer program product of claim 21 , wherein the method further comprises: adding the best sentence annotation in association with the first sentence to a set of training data that includes sentences annotated by a human annotator; and annotating a second sentence using the set of training data. | 25. The computer program product of claim 21 , wherein the method further comprises: adding the best sentence annotation in association with the first sentence to a set of training data that includes sentences annotated by a human annotator; and annotating a second sentence using the set of training data. 26. The computer program product of claim 25 , wherein the method further comprises: automatically annotating each sentence of subsequent corpuses using a set of training data that includes correctly annotated sentences from at least one previous round of annotation. | 0.92571 |
8,391,603 | 23 | 32 | 23. A computer-implemented method of segmenting images comprising the steps of: a. Receiving an image; b. Receiving at least one initial segmentation parameter; c. Receiving an initial segment in relation to the image from the at least one initial segmentation parameter; d. Receiving at least one segment feature in relation to the initial segment; e. Providing the at least one initial segmentation parameter and the at least one segment feature to a learning model, said learning model thereby generating a revised at least one segmentation parameter; f. Generating a revised segment from the revised at least one segmentation parameter; g. Displaying the image and the revised segment; h. Receiving observer feedback in relation to the revised segment to create a modified segment; i. Recalculating the at least one segmentation parameter from the modified segment; j. Updating the learning model from the recalculated at least one segmentation parameter, the at least one segment feature, and the at least one initial segmentation parameter. | 23. A computer-implemented method of segmenting images comprising the steps of: a. Receiving an image; b. Receiving at least one initial segmentation parameter; c. Receiving an initial segment in relation to the image from the at least one initial segmentation parameter; d. Receiving at least one segment feature in relation to the initial segment; e. Providing the at least one initial segmentation parameter and the at least one segment feature to a learning model, said learning model thereby generating a revised at least one segmentation parameter; f. Generating a revised segment from the revised at least one segmentation parameter; g. Displaying the image and the revised segment; h. Receiving observer feedback in relation to the revised segment to create a modified segment; i. Recalculating the at least one segmentation parameter from the modified segment; j. Updating the learning model from the recalculated at least one segmentation parameter, the at least one segment feature, and the at least one initial segmentation parameter. 32. A computer-implemented method of segmenting images according to claim 23 in which the learning model comprises a reinforcement learning model. | 0.803235 |
9,547,480 | 5 | 7 | 5. The method of claim 1 , wherein receiving the inputs identifying each of one or more semantic constructs of the application model with at least one of the application model subsets comprises receiving identifying constructs in the semantic constructs, wherein each of the identifying constructs contains an identifier of one of the application model subsets. | 5. The method of claim 1 , wherein receiving the inputs identifying each of one or more semantic constructs of the application model with at least one of the application model subsets comprises receiving identifying constructs in the semantic constructs, wherein each of the identifying constructs contains an identifier of one of the application model subsets. 7. The method of claim 5 , further comprising: identifying at least one additional semantic construct of the application model with a default application model subset from the application model subsets, in response to the at least one additional semantic construct lacking an identifying construct and lacking an ancestor semantic construct that contains an identifying construct. | 0.898178 |
4,846,693 | 11 | 19 | 11. An interactive video-based instructional and entertainment system, comprising: a picture and sound presentation provided by a video and audio signal source containing digital control data embedded in said video signal; a television set capable of displaying said picture presentation; a microprocessor controller receiving said embedded data; a manually actuable keyboard connected to said microprocessor; at least one animated figure having at least one articulated component capable of motion and where said motion is related to said control data; a first loudspeaker located internal to said animated figure, where said loudspeaker reproduces at least a portion of said sound presentation and where said portion is selected by said microprocessor in response to said digital control data and to entries to said manually actuable keyboard by a human participant; a second loudspeaker located intenal to said system, where said second loudspeaker reproduces said portion of the sound presentation not delivered by said first loudspeaker; whereby said system allows real-time interaction between said animated figure and at least one said human participant using said keyboard to respond to said video and sound presentation and to said loudspeaker reproductions; and where said real-time interaction results from selective playback of said portions of said sound source. | 11. An interactive video-based instructional and entertainment system, comprising: a picture and sound presentation provided by a video and audio signal source containing digital control data embedded in said video signal; a television set capable of displaying said picture presentation; a microprocessor controller receiving said embedded data; a manually actuable keyboard connected to said microprocessor; at least one animated figure having at least one articulated component capable of motion and where said motion is related to said control data; a first loudspeaker located internal to said animated figure, where said loudspeaker reproduces at least a portion of said sound presentation and where said portion is selected by said microprocessor in response to said digital control data and to entries to said manually actuable keyboard by a human participant; a second loudspeaker located intenal to said system, where said second loudspeaker reproduces said portion of the sound presentation not delivered by said first loudspeaker; whereby said system allows real-time interaction between said animated figure and at least one said human participant using said keyboard to respond to said video and sound presentation and to said loudspeaker reproductions; and where said real-time interaction results from selective playback of said portions of said sound source. 19. The system of claim 11, wherein said microprocessor scores responses by the human participant. | 0.577586 |
9,516,038 | 10 | 14 | 10. A method, comprising: transmitting to a group of users, by a computing device of an unauthorized disclosure identification system, a first document including a data item field, the group of users including a first portion of users including a first plurality of users and a second portion of users including a second plurality of users different from the first plurality of users; receiving, by the computing device of the system and from a first user of the group of users, first user input accessing the first document; providing, by the computing device of the system and to the first user of the group of users, access to the first document and the data item field, the data item field including a first data item, wherein the first data item is a first numerical item that is visible in the first document; receiving, by the computing device of the system and from a second user of the group of users, second user input accessing the first document; providing, by the computing device of the system and to the second user of the group of users, access to the first document and the data item field, the data item field including a second data item different from the first data item, wherein the second data item is a second numerical item that is visible in the first document, wherein alternating users accessing the first document and the data item field access data items in the data item field alternating between the first data item and the second data item, and wherein users accessing the first document with the first data item in the data item field form the first plurality of users forming the first portion of the group of users and users accessing the first document with the second data item in the data item field form the second plurality of users forming the second portion of the group of users; receiving, by the computing device of the system, data identifying a disclosure, the disclosure including one of the first data item and the second data item; responsive to receiving data identifying disclosure of the first data item, identifying, by the computing device of the system, users of the first plurality of users as a potential source of the disclosure; and responsive to receiving data identifying disclosure of the second data item, identifying, by the computing device of the system, the users of the second plurality of users as a potential source of the disclosure. | 10. A method, comprising: transmitting to a group of users, by a computing device of an unauthorized disclosure identification system, a first document including a data item field, the group of users including a first portion of users including a first plurality of users and a second portion of users including a second plurality of users different from the first plurality of users; receiving, by the computing device of the system and from a first user of the group of users, first user input accessing the first document; providing, by the computing device of the system and to the first user of the group of users, access to the first document and the data item field, the data item field including a first data item, wherein the first data item is a first numerical item that is visible in the first document; receiving, by the computing device of the system and from a second user of the group of users, second user input accessing the first document; providing, by the computing device of the system and to the second user of the group of users, access to the first document and the data item field, the data item field including a second data item different from the first data item, wherein the second data item is a second numerical item that is visible in the first document, wherein alternating users accessing the first document and the data item field access data items in the data item field alternating between the first data item and the second data item, and wherein users accessing the first document with the first data item in the data item field form the first plurality of users forming the first portion of the group of users and users accessing the first document with the second data item in the data item field form the second plurality of users forming the second portion of the group of users; receiving, by the computing device of the system, data identifying a disclosure, the disclosure including one of the first data item and the second data item; responsive to receiving data identifying disclosure of the first data item, identifying, by the computing device of the system, users of the first plurality of users as a potential source of the disclosure; and responsive to receiving data identifying disclosure of the second data item, identifying, by the computing device of the system, the users of the second plurality of users as a potential source of the disclosure. 14. The method of claim 10 , wherein the data item provided is unique to the plurality associated with the user accessing the first document. | 0.853734 |
8,832,080 | 1 | 4 | 1. A system for generating a dynamic representation of relations among individuals, the system comprising: a memory for storing computer executable instructions; and a processing unit coupled to the memory, operable to execute the computer executable instructions, and based at least in part on the execution of the computer executable instructions operable to perform operations comprising: classifying main characters of images in an image collection based on assignments of respective groups of the images in which the main characters appear to respective events, wherein each image has a time stamp, and wherein each main character is characterized by at least one attribute; determining relation circles of the main characters based on the event assignments; and constructing a dynamic relation tree representative of relations among the main characters, wherein the dynamic relation tree provides representations of the positions of the main characters in the relation circles, and wherein views and constituents of the dynamic relation tree change when different time periods are specified during display. | 1. A system for generating a dynamic representation of relations among individuals, the system comprising: a memory for storing computer executable instructions; and a processing unit coupled to the memory, operable to execute the computer executable instructions, and based at least in part on the execution of the computer executable instructions operable to perform operations comprising: classifying main characters of images in an image collection based on assignments of respective groups of the images in which the main characters appear to respective events, wherein each image has a time stamp, and wherein each main character is characterized by at least one attribute; determining relation circles of the main characters based on the event assignments; and constructing a dynamic relation tree representative of relations among the main characters, wherein the dynamic relation tree provides representations of the positions of the main characters in the relation circles, and wherein views and constituents of the dynamic relation tree change when different time periods are specified during display. 4. The system of claim 1 , wherein based at least in part on the execution of the computer executable instructions the processing unit is operable to perform operations comprising generating an event-people graph based on the assignments of the groups of images to respective events, and displaying the event-people graph. | 0.752688 |
8,612,932 | 1 | 6 | 1. A server including a processor, the server comprising: a communication application being executed on a Java virtual machine on said server; a unified application framework for call control and media control for building application components of the communication application a call control API for providing a standardized Java interface for call control, said call control API defining a set of class object primitives for call control; a media control API for providing a standardized Java interface for media server control, said media control API defining a set of class object primitives for media control; a unified call control and media control API defining a set of unified class objects constructed from the class object primitives of the call control API and the media control API; and wherein the application components are built from the unified class objects including: a Call object for connecting a leg of communication between an endpoint and the communication application; a Participant object representing an abstract party involved in a conversation; a Join object for effecting an asynchronous join operation on the Participant object; a MediaService object for media control available to a call; an Eventsource object for representing an event source that serializes events from call control and events from media control such that the application component listening said event source only has to deal with one event at a time; and an Observer object for a listener that listen to events from the event source. | 1. A server including a processor, the server comprising: a communication application being executed on a Java virtual machine on said server; a unified application framework for call control and media control for building application components of the communication application a call control API for providing a standardized Java interface for call control, said call control API defining a set of class object primitives for call control; a media control API for providing a standardized Java interface for media server control, said media control API defining a set of class object primitives for media control; a unified call control and media control API defining a set of unified class objects constructed from the class object primitives of the call control API and the media control API; and wherein the application components are built from the unified class objects including: a Call object for connecting a leg of communication between an endpoint and the communication application; a Participant object representing an abstract party involved in a conversation; a Join object for effecting an asynchronous join operation on the Participant object; a MediaService object for media control available to a call; an Eventsource object for representing an event source that serializes events from call control and events from media control such that the application component listening said event source only has to deal with one event at a time; and an Observer object for a listener that listen to events from the event source. 6. The server as in claim 1 , wherein said unified class objects include the Observer object as a unified event handler that ignores events inappropriate to a context of the specific object model. | 0.570175 |
10,146,884 | 1 | 6 | 1. A method implemented on a computer having at least one processor, storage, and communication platform for updating an URL, comprising the steps of: accessing from an Internet source, via a publicly available network path, a first webpage in a first language; identifying, from the first webpage in the first language, a link represented by an original URL, wherein the original URL is associated with a second webpage in the first language; obtaining an updated URL corresponding to the original URL, wherein the updated URL is associated with a translated second webpage in a second language; generating a search engine optimized path to be included in the updated URL based on one or more search engine relevant elements present in the content of the translated second webpage in the second language; and providing the updated URL in a translated first webpage in the second language. | 1. A method implemented on a computer having at least one processor, storage, and communication platform for updating an URL, comprising the steps of: accessing from an Internet source, via a publicly available network path, a first webpage in a first language; identifying, from the first webpage in the first language, a link represented by an original URL, wherein the original URL is associated with a second webpage in the first language; obtaining an updated URL corresponding to the original URL, wherein the updated URL is associated with a translated second webpage in a second language; generating a search engine optimized path to be included in the updated URL based on one or more search engine relevant elements present in the content of the translated second webpage in the second language; and providing the updated URL in a translated first webpage in the second language. 6. The method of claim 1 , wherein the updated URL was pre-generated. | 0.949561 |
9,734,143 | 1 | 8 | 1. A method for generating a language processing model, comprising: obtaining multiple content items, wherein each content item is associated with one or more multi-media items and comprises one or more n-grams, wherein an n-gram is a digital representation of one or more words or groups of characters; for each selected content item of the multiple content items: identifying one or more multi-media labels for the one or more multi-media items associated with the selected content item; assigning to the identified one or more multi-media labels at least some of the one or more n-grams of the selected content item; and including, in a language corpus, the one or more n-grams of the selected content item; and generating the language processing model comprising a probability distribution by computing, for each selected n-gram of multiple n-grams in the language corpus, a frequency that the selected n-gram occurs in the language corpus, wherein the probability distribution can take representations of multi-media labels as parameters, and wherein at least some probabilities provided by the probability distribution are multi-media context probabilities indicating a probability of a chosen n-gram occurring, given that the chosen n-gram is associated with provided multi-media labels, wherein the multi-media context probabilities are based on the assigning of the identified one or more multi-media labels. | 1. A method for generating a language processing model, comprising: obtaining multiple content items, wherein each content item is associated with one or more multi-media items and comprises one or more n-grams, wherein an n-gram is a digital representation of one or more words or groups of characters; for each selected content item of the multiple content items: identifying one or more multi-media labels for the one or more multi-media items associated with the selected content item; assigning to the identified one or more multi-media labels at least some of the one or more n-grams of the selected content item; and including, in a language corpus, the one or more n-grams of the selected content item; and generating the language processing model comprising a probability distribution by computing, for each selected n-gram of multiple n-grams in the language corpus, a frequency that the selected n-gram occurs in the language corpus, wherein the probability distribution can take representations of multi-media labels as parameters, and wherein at least some probabilities provided by the probability distribution are multi-media context probabilities indicating a probability of a chosen n-gram occurring, given that the chosen n-gram is associated with provided multi-media labels, wherein the multi-media context probabilities are based on the assigning of the identified one or more multi-media labels. 8. The method of claim 1 , wherein the one or more multi-media items that at least one of the content items is associated with comprises an image. | 0.883573 |
9,031,863 | 1 | 10 | 1. A computer-implemented method, comprising: collecting user activity information for a plurality of users, wherein the user activity information that has been collected for the plurality of users includes at least one of web pages that have been viewed by the plurality of users, content of the web pages that have been viewed by the plurality of users, advertisements that have been clicked on by the plurality of users, or user search results that have been selected by the plurality of users; generating by a processor a mapping model, wherein generating a mapping model includes mapping each one of a plurality of different user characteristics to a corresponding set of terms based, at least in part, on the user activity information that has been collected for the plurality of users and user profiles of the plurality of users, wherein each set of terms include advertisement terms that are a subset of an advertisement term list, the advertisement term list being separate from the user profiles, wherein the plurality of different user characteristics include a plurality of different categories that represent user interest or expertise in such different categories and/or a plurality of different user demographics; receiving a request for an advertisement to be displayed in a web page that has been requested by a user, wherein the user is associated with one or more user characteristics from the plurality of different user characteristics, the one or more user characteristics including one of the plurality of categories and/or one of the plurality of different user demographics, the one or more user characteristics being indicated by one of the user profiles; using the mapping model, for each one of the one or more user characteristics of the user, obtaining the corresponding set of terms; and providing the obtained terms for selecting one of a plurality of advertisements for displaying via the web page, wherein the advertisement term list is separate from the plurality of advertisements. | 1. A computer-implemented method, comprising: collecting user activity information for a plurality of users, wherein the user activity information that has been collected for the plurality of users includes at least one of web pages that have been viewed by the plurality of users, content of the web pages that have been viewed by the plurality of users, advertisements that have been clicked on by the plurality of users, or user search results that have been selected by the plurality of users; generating by a processor a mapping model, wherein generating a mapping model includes mapping each one of a plurality of different user characteristics to a corresponding set of terms based, at least in part, on the user activity information that has been collected for the plurality of users and user profiles of the plurality of users, wherein each set of terms include advertisement terms that are a subset of an advertisement term list, the advertisement term list being separate from the user profiles, wherein the plurality of different user characteristics include a plurality of different categories that represent user interest or expertise in such different categories and/or a plurality of different user demographics; receiving a request for an advertisement to be displayed in a web page that has been requested by a user, wherein the user is associated with one or more user characteristics from the plurality of different user characteristics, the one or more user characteristics including one of the plurality of categories and/or one of the plurality of different user demographics, the one or more user characteristics being indicated by one of the user profiles; using the mapping model, for each one of the one or more user characteristics of the user, obtaining the corresponding set of terms; and providing the obtained terms for selecting one of a plurality of advertisements for displaying via the web page, wherein the advertisement term list is separate from the plurality of advertisements. 10. The method of claim 1 , wherein the plurality of user characteristics comprise the plurality of different categories, the method further comprising: ascertaining, for the user, one or more of the plurality of categories that represent user interest or expertise of the user in such categories, wherein the one or more user characteristics include the one or more of the plurality of categories. | 0.508642 |
9,965,552 | 15 | 16 | 15. A computer-readable storage device having instructions stored which, when executed by a processor, cause the processor to perform operations comprising: receiving data corresponding to a text query from a user; retrieving, based on the text query, a spoken document; searching a word index of the spoken document associated with the text query using the text query, to yield first search results; searching a sub-word index of the spoken document associated with the text query using the text query, to yield second search results; and returning, via a computer network and according to the first search results and the second search results, audio segments from the spoken document associated with the text query which correspond to the text query. | 15. A computer-readable storage device having instructions stored which, when executed by a processor, cause the processor to perform operations comprising: receiving data corresponding to a text query from a user; retrieving, based on the text query, a spoken document; searching a word index of the spoken document associated with the text query using the text query, to yield first search results; searching a sub-word index of the spoken document associated with the text query using the text query, to yield second search results; and returning, via a computer network and according to the first search results and the second search results, audio segments from the spoken document associated with the text query which correspond to the text query. 16. The computer-readable storage device of claim 15 , having additional instructions stored which result in operations comprising combining the first search results and the second search results to yield combined results. | 0.597826 |
9,256,680 | 1 | 4 | 1. A system, comprising: a relevance component associated with each result of a results page, the relevance component having an interactive positive relevance as a “more” link configured to enable positive feedback as to each result and an interactive negative relevance as a “none” link configured to enable negative feedback as to each result, the results page related to an original query; an analysis component configured to automatically analyze metadata associated with each result and automatically select a topical term from each result; a query formulation component configured to automatically reformulate for each result of the relevance component a new query associated with the “more” link and a new query associated with the “none” link; a query processing component configured to automatically process the new query associated with selection of the “more” link or the new query associated with selection of the “none” link for each result of the results page, and return new results for the new query, such that selection of the “more” link includes the topical term in the processing of the new search results, or selection of the “none” link indicates negation of the topical term from the processing of the new search results to ensure the new search results do not contain the topical term; and a microprocessor configured to execute computer-executable instructions in a memory, the execution of the instructions enables at least one of the relevance component, analysis component, query formulation component, or query processing component. | 1. A system, comprising: a relevance component associated with each result of a results page, the relevance component having an interactive positive relevance as a “more” link configured to enable positive feedback as to each result and an interactive negative relevance as a “none” link configured to enable negative feedback as to each result, the results page related to an original query; an analysis component configured to automatically analyze metadata associated with each result and automatically select a topical term from each result; a query formulation component configured to automatically reformulate for each result of the relevance component a new query associated with the “more” link and a new query associated with the “none” link; a query processing component configured to automatically process the new query associated with selection of the “more” link or the new query associated with selection of the “none” link for each result of the results page, and return new results for the new query, such that selection of the “more” link includes the topical term in the processing of the new search results, or selection of the “none” link indicates negation of the topical term from the processing of the new search results to ensure the new search results do not contain the topical term; and a microprocessor configured to execute computer-executable instructions in a memory, the execution of the instructions enables at least one of the relevance component, analysis component, query formulation component, or query processing component. 4. The system of claim 1 , wherein the query formulation component is configured to construct the new queries from the original query by at least one of adding new terms or removing old terms. | 0.625 |
9,350,857 | 1 | 4 | 1. A method for use with an assisted user's communication device that includes a display, the method comprising the steps of: providing a processor programmed to perform the steps of, upon placement of an emergency call to a hearing user: recognizing the call as an emergency call; automatically initiating a captioning service to provide text transcription of voice messages from the hearing user and maintaining the captioning service for at least a time out period irrespective of actions by the assisted user; and upon placement of a non-emergency call, only starting the captioning service after a request for the captioning service from the assisted user is received. | 1. A method for use with an assisted user's communication device that includes a display, the method comprising the steps of: providing a processor programmed to perform the steps of, upon placement of an emergency call to a hearing user: recognizing the call as an emergency call; automatically initiating a captioning service to provide text transcription of voice messages from the hearing user and maintaining the captioning service for at least a time out period irrespective of actions by the assisted user; and upon placement of a non-emergency call, only starting the captioning service after a request for the captioning service from the assisted user is received. 4. The method of claim 1 further including the step of providing some indication to the assisted user that captioning has been automatically commenced. | 0.503289 |
9,966,078 | 1 | 4 | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: generating, by the processor, a plurality of information elements based upon a voice conversation between a first entity and a second entity over a communication network; constructing a current conversation pattern from the plurality of information elements, wherein the current conversation pattern specifies an order of the plurality of information elements based upon the voice conversation; identifying one or more deceptive conversation properties of the current conversation pattern based upon analyzing the order of the plurality of information elements in the current conversation pattern against one or more domain-based conversation patterns; and sending an alert message to the first entity based upon the identified one or more deceptive conversation properties. | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: generating, by the processor, a plurality of information elements based upon a voice conversation between a first entity and a second entity over a communication network; constructing a current conversation pattern from the plurality of information elements, wherein the current conversation pattern specifies an order of the plurality of information elements based upon the voice conversation; identifying one or more deceptive conversation properties of the current conversation pattern based upon analyzing the order of the plurality of information elements in the current conversation pattern against one or more domain-based conversation patterns; and sending an alert message to the first entity based upon the identified one or more deceptive conversation properties. 4. The method of claim 1 further comprising: retrieving sensitive data corresponding to a first entity user of the first entity; generating a validation question based upon the retrieved sensitive data, wherein the validation question is configured to be asked by the first entity to validate a second entity user of the second entity; and sending the validation question to the first entity. | 0.719198 |
7,668,787 | 20 | 22 | 20. The computer program product of claim 19 , wherein said entity/relationship object includes a reference to said electronic document. | 20. The computer program product of claim 19 , wherein said entity/relationship object includes a reference to said electronic document. 22. The computer program product of claim 20 , wherein said relationship data structure further comprises a second composite object that includes a reference to said electronic document and further comprising: matching said entity/relationship object and said second composite object with respect to their respective references to said electronic document; adding said entity/relationship object to said second composite object. | 0.893691 |
7,831,534 | 2 | 26 | 2. A computer-implemented method for building a polyhierarchical classification of objects, comprising: a) identifying a plurality of criteria for specializing the objects based on their properties, wherein each criterion of the plurality of criteria is defined by a set of mutually exclusive attributes, wherein each attribute describes one or more properties of the objects; b) recurrently defining a root category for each criterion in terms of an attributive expression representing a logical composition of one or more attributes of criteria whose root categories have been previously defined in the recurrent sequence, or the empty attributive expression; wherein no one criterion participates in the definition of its own root category, and each attributive expression encodes a sequence of specializations by criteria so that the root category of each following criterion includes the category represented by the sequence of all previous specializations; c) storing in a computer-readable medium the plurality of criteria and their root categories in the form of attributive expressions; and d) using the stored plurality of criteria for polyhierachically structuring, updating and accessing information associated with the objects. | 2. A computer-implemented method for building a polyhierarchical classification of objects, comprising: a) identifying a plurality of criteria for specializing the objects based on their properties, wherein each criterion of the plurality of criteria is defined by a set of mutually exclusive attributes, wherein each attribute describes one or more properties of the objects; b) recurrently defining a root category for each criterion in terms of an attributive expression representing a logical composition of one or more attributes of criteria whose root categories have been previously defined in the recurrent sequence, or the empty attributive expression; wherein no one criterion participates in the definition of its own root category, and each attributive expression encodes a sequence of specializations by criteria so that the root category of each following criterion includes the category represented by the sequence of all previous specializations; c) storing in a computer-readable medium the plurality of criteria and their root categories in the form of attributive expressions; and d) using the stored plurality of criteria for polyhierachically structuring, updating and accessing information associated with the objects. 26. The method of claim 2 , further comprising: a) inserting a second polyhierarchical classification into the polyhierarchical classification; b) identifying a root category from which the second classification is to originate from in the given classification, c) redefining original root category of the unconditional criteria of the second classification to the identified root category in the classification, and d) replacing original attributive expressions of root categories of all the conditional criteria and all other permanent categories of the second classification with their intersections with the attributive expression of the identified root category in the classification. | 0.65653 |
7,650,286 | 225 | 229 | 225. A computer program product, to be used on a computer, for identifying a matching resume for a job description, comprising: a computer readable medium storing: program code for receiving the job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; program code for storing the job description; program code for associating, for each said at least one job requirement, the required skill or experience-related phrase with at least one implying skill or experience-related phrase; program code for storing at least one searchable phrase for each said at least one job requirement, one of said at least one searchable phrase including the required skill or experience-related phrase, and said at least one searchable phrase including each said at least one implying skill or experience-related phrase; program code for receiving at least one resume; program code for parsing each said at least one resume to: locate at least one of said at least one searchable phrase in the resume; determine an experience range for each searchable phrase located in the resume by examining a use of each searchable phrase in the resume; and compute a term of experience for each searchable phrase located in the resume based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; program code for storing each said at least one resume; program code for computing, for each said at least one resume, a term of experience for the required skill or experience-related phrase for each said at least one job requirement; and program code for determining whether each said at least one resume is the matching resume that satisfies the job description. | 225. A computer program product, to be used on a computer, for identifying a matching resume for a job description, comprising: a computer readable medium storing: program code for receiving the job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; program code for storing the job description; program code for associating, for each said at least one job requirement, the required skill or experience-related phrase with at least one implying skill or experience-related phrase; program code for storing at least one searchable phrase for each said at least one job requirement, one of said at least one searchable phrase including the required skill or experience-related phrase, and said at least one searchable phrase including each said at least one implying skill or experience-related phrase; program code for receiving at least one resume; program code for parsing each said at least one resume to: locate at least one of said at least one searchable phrase in the resume; determine an experience range for each searchable phrase located in the resume by examining a use of each searchable phrase in the resume; and compute a term of experience for each searchable phrase located in the resume based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; program code for storing each said at least one resume; program code for computing, for each said at least one resume, a term of experience for the required skill or experience-related phrase for each said at least one job requirement; and program code for determining whether each said at least one resume is the matching resume that satisfies the job description. 229. The computer program product of claim 225 , wherein at least one of each said at least one implying skill or experience-related phrase comprises a narrower skill or experience-related phrase. | 0.797521 |
7,831,913 | 1 | 3 | 1. A computer-readable storage medium having stored thereon computer-executable components of a system that facilitates tagging of computerized data, the system comprising: a graphical user interface having a window to display information regarding at least one file of a file system and including at least one element of a graphical user interface that, when the window is in a tagging state, displays information regarding at least one suggested tag that may be applied to at least one first file, wherein the window enters into the tagging state upon detecting a selection of the at least one first file by the user and detecting at least one user input corresponding to successive characters of a tag that is desired to be applied to the at least one first file, wherein the window enters into the tagging state without requiring the user to enter a separate user interface or to provide user inputs other than the user inputs corresponding to the successive characters of the tag desired to be applied to the at least one first file; and a tagging component to provide dynamically, when the window enters the tagging state, the at least one suggested tag to the user via the window in response to the at least one user input, the at least one suggested tag being suggested based on, at least in part, the user input, and to associate at least one first tag with the at least one first file upon selection of the at least one first tag by the user. | 1. A computer-readable storage medium having stored thereon computer-executable components of a system that facilitates tagging of computerized data, the system comprising: a graphical user interface having a window to display information regarding at least one file of a file system and including at least one element of a graphical user interface that, when the window is in a tagging state, displays information regarding at least one suggested tag that may be applied to at least one first file, wherein the window enters into the tagging state upon detecting a selection of the at least one first file by the user and detecting at least one user input corresponding to successive characters of a tag that is desired to be applied to the at least one first file, wherein the window enters into the tagging state without requiring the user to enter a separate user interface or to provide user inputs other than the user inputs corresponding to the successive characters of the tag desired to be applied to the at least one first file; and a tagging component to provide dynamically, when the window enters the tagging state, the at least one suggested tag to the user via the window in response to the at least one user input, the at least one suggested tag being suggested based on, at least in part, the user input, and to associate at least one first tag with the at least one first file upon selection of the at least one first tag by the user. 3. The computer-readable storage medium of claim 1 , wherein the tagging component heuristically determines the at least one suggested tag based on at least one of a first file of the at least one first file, a tag associated with a file similar to the at least one first file, a recently-utilized tag, a commonly-used tag, a rule-based criterion, or a heuristic-based criterion. | 0.770024 |
7,680,812 | 21 | 25 | 21. The method of claim 5 , further comprising: inputting a keyword into a search interface; feeding the keyword to a hit list generator; and outputting a hit list of same hits, accompanied by a corresponding list of text relevance scores. | 21. The method of claim 5 , further comprising: inputting a keyword into a search interface; feeding the keyword to a hit list generator; and outputting a hit list of same hits, accompanied by a corresponding list of text relevance scores. 25. The method of claim 21 , said step of calculating an importance score comprising: calculating an importance score W for each document, wherein
W=a ( TR )+ b ( LA )+ c ( FQS ) TR=text relevance score from text analysis, LA=link analysis score, FQS=file quality score, and a, b, and c are tuning parameter weights. | 0.878067 |
9,679,250 | 11 | 12 | 11. The method of claim 1 further comprising utilizing a plurality of fact checking implementations initially, wherein each fact checking implementation utilizes a different set of source information, and comparing results of each fact checking implementation, and iteratively eliminating a fact checking implementation of the plurality of fact checking implementations with a lowest confidence score until a single fact checking implementation remains. | 11. The method of claim 1 further comprising utilizing a plurality of fact checking implementations initially, wherein each fact checking implementation utilizes a different set of source information, and comparing results of each fact checking implementation, and iteratively eliminating a fact checking implementation of the plurality of fact checking implementations with a lowest confidence score until a single fact checking implementation remains. 12. The method of claim 11 wherein utilizing the plurality of fact checking implementations initially occurs in the first minute of a video. | 0.979466 |
9,390,085 | 5 | 7 | 5. The method as claimed in claim 1 , the method further comprising: receiving a speech sample in Oriya English for speech processing; determining values of each of the speech parameters for the received speech sample based on Fujisaki Model; and recognizing the speech sample based on one or more of the speech parameter values and an Oriya English speech corpora through Hidden Markov Model (HMM). | 5. The method as claimed in claim 1 , the method further comprising: receiving a speech sample in Oriya English for speech processing; determining values of each of the speech parameters for the received speech sample based on Fujisaki Model; and recognizing the speech sample based on one or more of the speech parameter values and an Oriya English speech corpora through Hidden Markov Model (HMM). 7. The method as claimed in claim 5 , wherein the method further comprises synthesizing natural speech, wherein the synthesized natural speech is induced with Oriya English accent based on the phonetic variations of Oriya English determined based on the values of each of the speech parameters. | 0.914186 |
7,725,330 | 1 | 5 | 1. A method for processing medical information, comprising the steps of: obtaining a medical record of a patient, wherein the medical record comprises patient information from structured and unstructured data sources; analyzing with a computer the patient information from at least the unstructured data source in the medical record using domain-specific criteria; and automatically extracting billing information from the medical record as part of the analysis. | 1. A method for processing medical information, comprising the steps of: obtaining a medical record of a patient, wherein the medical record comprises patient information from structured and unstructured data sources; analyzing with a computer the patient information from at least the unstructured data source in the medical record using domain-specific criteria; and automatically extracting billing information from the medical record as part of the analysis. 5. The method of claim 1 , wherein extracting billing information comprises extracting all billing codes that are supported by the patient information based on all domain-specific criteria in a domain knowledge base. | 0.741627 |
9,870,591 | 1 | 6 | 1. A blockchain configured distributed architecture-based system in a communication network, said system comprising: a memory circuit communicatively connected to said communication network that stores a plurality of digital profiles associated with a plurality of crowdsourced experts, and further stores a plurality of segmented digital profiles associated with each of said digital profiles, wherein said segmented digital profiles and digital profiles are created based on a plurality of sources distributed and electronically linked across said communication network; a processor coupled with the memory circuit to execute instructions for evaluating an expert, the instructions comprising: a credentialing engine that allows a plurality of crowdsourced respondents to respond to said segmented digital profiles associated with each of said plurality of experts and credential said plurality of experts and determine crowdsourced credentialed expertise, wherein the credentialing of each of said segmented digital profiles associated with an expert of said plurality of experts contribute to credentialing of a digital profile of said expert upon collation of said credentialed segmented digital profiles, and wherein said segmented digital profiles associated with said experts are credentialed from a plurality of respondents using a computerized crowdsourcing index, wherein said computerized crowdsourcing index is indicative of number of respondents credentialing an expert and dynamically increases with an increase in said number of respondents; an expert scoring module to: determine a set of attributes for said experts, said set of attributes including one or more of said crowdsourced credentialed expertise determined based on said credentialing of said segmented digital profiles of said experts by said respondents, reputation of said experts indicative of a trust of a relevant community on said experts, and officiality indicative of a position or a designation of said experts in a relevant job, wherein each of said attributes are assigned varying computer-calculated weights; and determine an aggregate score of an expert based on said one or more attributes in association with the assigned weights; an electronic document scoring engine to receive and process comments and document ratings for an electronic document by said crowdsourced experts, wherein said crowdsourced experts have an aggregate score greater than a defined threshold, the document scoring engine comprising: a natural language processing-based (NLP-based) analysis engine to process textual information-based reviews and comments generated as part of textual review of said electronic document by said crowdsourced experts; a visual scoring engine for processing visual and non-textual feedback and reviews by the crowdsourced experts, wherein the visual scoring engine comprises: an eye tracks processor controlled by a special purpose microprocessor to receive eye track inputs from respective eye tracking systems associated with computing devices of said crowdsourced experts and process said eye track inputs to associate a review score based on predefined eye track patterns; and a micro expressions processor to receive data indicative of micro facial expressions extracted by respective micro expressions sensors associated with said computing devices of said crowdsourced experts, wherein said micro expressions processor comprises an image processing circuitry and an associated memory to interpret said micro facial expressions and compare them with predefined facial patterns to associate a review score based on said extracted micro facial expressions, wherein, the document scoring engine further configured to: associate an aggregate score to said electronic document based on aggregation of individual textual and visual review scores obtained by processing of said textual and said visual reviews by said crowdsourced experts who review the document; and display on a graphical user interface device, an output indicative of an aggregate score of the document reviewed by said crowdsourced experts along with information about who reviewed and how many times reviewed the document; an expert identity validation device to verify identities of the crowdsourced experts during or prior to review, wherein said expert identity validation device comprises: a device patterns assessment device to receive and process device information extracted by respective agent devices associated with said computing devices of said crowdsourced experts and verify the extracted device information with predefined device information for the respective crowdsourced experts; a network patterns assessment device to receive and process network information extracted by said respective agent devices associated with said computing devices of said crowdsourced experts and verify the extracted network information with predefined network information of the respective crowdsourced experts; a geo-spatial mapping device to perform geo-tagging of the crowdsourced experts and the documents reviewed by said crowdsourced experts and compare the geo-tags with pre-stored geo-spatial information about the experts for processing validation, wherein the geo-tagging is performed based on geo-spatial information received from a global positioning system (GPS)-based device; and a facial expression validation device to receive and process facial expressions received from respective facial expression sensors associated with said computing devices of said crowdsourced experts and verify identity in accordance with respective predefined facial patterns of said crowdsourced experts, wherein the facial expression validation device comprises a digital acquisition unit and multichannel amplifiers for pre-processing and amplification of signals transmitted by said facial expression sensors. | 1. A blockchain configured distributed architecture-based system in a communication network, said system comprising: a memory circuit communicatively connected to said communication network that stores a plurality of digital profiles associated with a plurality of crowdsourced experts, and further stores a plurality of segmented digital profiles associated with each of said digital profiles, wherein said segmented digital profiles and digital profiles are created based on a plurality of sources distributed and electronically linked across said communication network; a processor coupled with the memory circuit to execute instructions for evaluating an expert, the instructions comprising: a credentialing engine that allows a plurality of crowdsourced respondents to respond to said segmented digital profiles associated with each of said plurality of experts and credential said plurality of experts and determine crowdsourced credentialed expertise, wherein the credentialing of each of said segmented digital profiles associated with an expert of said plurality of experts contribute to credentialing of a digital profile of said expert upon collation of said credentialed segmented digital profiles, and wherein said segmented digital profiles associated with said experts are credentialed from a plurality of respondents using a computerized crowdsourcing index, wherein said computerized crowdsourcing index is indicative of number of respondents credentialing an expert and dynamically increases with an increase in said number of respondents; an expert scoring module to: determine a set of attributes for said experts, said set of attributes including one or more of said crowdsourced credentialed expertise determined based on said credentialing of said segmented digital profiles of said experts by said respondents, reputation of said experts indicative of a trust of a relevant community on said experts, and officiality indicative of a position or a designation of said experts in a relevant job, wherein each of said attributes are assigned varying computer-calculated weights; and determine an aggregate score of an expert based on said one or more attributes in association with the assigned weights; an electronic document scoring engine to receive and process comments and document ratings for an electronic document by said crowdsourced experts, wherein said crowdsourced experts have an aggregate score greater than a defined threshold, the document scoring engine comprising: a natural language processing-based (NLP-based) analysis engine to process textual information-based reviews and comments generated as part of textual review of said electronic document by said crowdsourced experts; a visual scoring engine for processing visual and non-textual feedback and reviews by the crowdsourced experts, wherein the visual scoring engine comprises: an eye tracks processor controlled by a special purpose microprocessor to receive eye track inputs from respective eye tracking systems associated with computing devices of said crowdsourced experts and process said eye track inputs to associate a review score based on predefined eye track patterns; and a micro expressions processor to receive data indicative of micro facial expressions extracted by respective micro expressions sensors associated with said computing devices of said crowdsourced experts, wherein said micro expressions processor comprises an image processing circuitry and an associated memory to interpret said micro facial expressions and compare them with predefined facial patterns to associate a review score based on said extracted micro facial expressions, wherein, the document scoring engine further configured to: associate an aggregate score to said electronic document based on aggregation of individual textual and visual review scores obtained by processing of said textual and said visual reviews by said crowdsourced experts who review the document; and display on a graphical user interface device, an output indicative of an aggregate score of the document reviewed by said crowdsourced experts along with information about who reviewed and how many times reviewed the document; an expert identity validation device to verify identities of the crowdsourced experts during or prior to review, wherein said expert identity validation device comprises: a device patterns assessment device to receive and process device information extracted by respective agent devices associated with said computing devices of said crowdsourced experts and verify the extracted device information with predefined device information for the respective crowdsourced experts; a network patterns assessment device to receive and process network information extracted by said respective agent devices associated with said computing devices of said crowdsourced experts and verify the extracted network information with predefined network information of the respective crowdsourced experts; a geo-spatial mapping device to perform geo-tagging of the crowdsourced experts and the documents reviewed by said crowdsourced experts and compare the geo-tags with pre-stored geo-spatial information about the experts for processing validation, wherein the geo-tagging is performed based on geo-spatial information received from a global positioning system (GPS)-based device; and a facial expression validation device to receive and process facial expressions received from respective facial expression sensors associated with said computing devices of said crowdsourced experts and verify identity in accordance with respective predefined facial patterns of said crowdsourced experts, wherein the facial expression validation device comprises a digital acquisition unit and multichannel amplifiers for pre-processing and amplification of signals transmitted by said facial expression sensors. 6. The system of claim 1 , further comprises an officiality assessment engine to determine a degree of officiality of an expert. | 0.89491 |
10,152,973 | 7 | 15 | 7. A computer-implemented method comprising: under control of a server system comprising one or more computing devices configured with specific computer executable instructions, receiving audio data from a client device separate from the server system, wherein the audio data comprises data regarding an utterance of a user; producing first speech processing results using a base speech processing model and the audio data, wherein the base speech processing model is stored at the server system; obtaining a specialized speech processing model from a network-accessible data store separate from the server system and separate from the client device, wherein the obtaining is initiated based at least partly on an attribute of the specialized speech processing model and prior to completion of producing the first speech processing results; determining, based at least partly on a time at which the specialized speech processing model is obtained, that the server system is to produce second speech processing results using the specialized speech processing model subsequent to initiating production of the first speech processing results; and producing the second speech processing results using the specialized speech processing model and at least one of the audio data or the first speech processing results. | 7. A computer-implemented method comprising: under control of a server system comprising one or more computing devices configured with specific computer executable instructions, receiving audio data from a client device separate from the server system, wherein the audio data comprises data regarding an utterance of a user; producing first speech processing results using a base speech processing model and the audio data, wherein the base speech processing model is stored at the server system; obtaining a specialized speech processing model from a network-accessible data store separate from the server system and separate from the client device, wherein the obtaining is initiated based at least partly on an attribute of the specialized speech processing model and prior to completion of producing the first speech processing results; determining, based at least partly on a time at which the specialized speech processing model is obtained, that the server system is to produce second speech processing results using the specialized speech processing model subsequent to initiating production of the first speech processing results; and producing the second speech processing results using the specialized speech processing model and at least one of the audio data or the first speech processing results. 15. The computer-implemented method of claim 7 , wherein the determining, based at least partly on the time at which the specialized speech processing model is obtained, that the server system is to produce the second speech processing results using the specialized speech processing model comprises determining that producing the second speech processing results using the specialized speech processing model will cause a delay of less than a threshold amount of time to send speech processing results to the client device. | 0.710817 |
9,558,101 | 2 | 4 | 2. The method of claim 1 , wherein applying the heuristic includes applying at least one of a Jaro distance, Jaro-Winkler, Hamming distance, Levenshtein distance, Damerau-Levenshtein distance, or a phonetic matching technique. | 2. The method of claim 1 , wherein applying the heuristic includes applying at least one of a Jaro distance, Jaro-Winkler, Hamming distance, Levenshtein distance, Damerau-Levenshtein distance, or a phonetic matching technique. 4. The method of claim 2 , wherein applying the heuristic includes applying the Levenshtein distance to the respective preprocessor directive symbols in the set of unused preprocessor directive symbols and the set of undefined preprocessor directive symbols. | 0.959975 |
9,454,729 | 1 | 6 | 1. A computer-implemented method, comprising: selecting automatically a first affinity vector comprising a first plurality of topic affinity level values that are associated with a first user of a computer-implemented system, wherein a plurality of the first plurality of topic affinity level values are each based on an inference from a first one or more usage behaviors; selecting automatically a second affinity vector comprising a second plurality of topic affinity level values that are associated with a second user of the computer-implemented system, wherein a plurality of the second plurality of topic affinity level values are each based on an inference from a second one or more usage behaviors, and wherein the selection of the second affinity vector is in accordance with a determination of a relatively high level of similarity between a plurality of the first plurality of topic affinity level values and a corresponding plurality of the second plurality of topic affinity level values; identifying automatically one or more pairs of contrasting corresponding topic affinity level values by comparing topic affinity level values in the first affinity vector with topic affinity level values in the second affinity vector; and generating automatically a recommendation for delivery to the first user, wherein the recommendation is generated in accordance with the one or more pairs of contrasting corresponding topic affinity level values. | 1. A computer-implemented method, comprising: selecting automatically a first affinity vector comprising a first plurality of topic affinity level values that are associated with a first user of a computer-implemented system, wherein a plurality of the first plurality of topic affinity level values are each based on an inference from a first one or more usage behaviors; selecting automatically a second affinity vector comprising a second plurality of topic affinity level values that are associated with a second user of the computer-implemented system, wherein a plurality of the second plurality of topic affinity level values are each based on an inference from a second one or more usage behaviors, and wherein the selection of the second affinity vector is in accordance with a determination of a relatively high level of similarity between a plurality of the first plurality of topic affinity level values and a corresponding plurality of the second plurality of topic affinity level values; identifying automatically one or more pairs of contrasting corresponding topic affinity level values by comparing topic affinity level values in the first affinity vector with topic affinity level values in the second affinity vector; and generating automatically a recommendation for delivery to the first user, wherein the recommendation is generated in accordance with the one or more pairs of contrasting corresponding topic affinity level values. 6. The method of claim 1 , further comprising: generating automatically the recommendation for delivery to the first user, wherein the recommendation comprises a computer-implemented object that has a relatively high automatically determined affinity with at least one topic that is associated with the one or more pairs of contrasting corresponding topic affinity level values. | 0.639313 |
8,200,485 | 1 | 39 | 1. A method for improving voice recognition accuracy when a user submits a search query by voice to search a domain of items, the method comprising: prompting a user to submit a set of characters of a voice query for searching the domain of items, and receiving the set of characters from the user, wherein the voice query is an utterance by the user of a search query, and the set of characters defines a portion of the search query; in response to receiving the set of characters from the user, identifying a subset of items in the domain that correspond to the set of characters; generating a dynamic grammar based at least in part on the subset of items, said grammar specifying valid utterances for interpreting the voice query; prompting the user to submit the voice query, and receiving the voice query from the user; and interpreting the voice query using the dynamic grammar. | 1. A method for improving voice recognition accuracy when a user submits a search query by voice to search a domain of items, the method comprising: prompting a user to submit a set of characters of a voice query for searching the domain of items, and receiving the set of characters from the user, wherein the voice query is an utterance by the user of a search query, and the set of characters defines a portion of the search query; in response to receiving the set of characters from the user, identifying a subset of items in the domain that correspond to the set of characters; generating a dynamic grammar based at least in part on the subset of items, said grammar specifying valid utterances for interpreting the voice query; prompting the user to submit the voice query, and receiving the voice query from the user; and interpreting the voice query using the dynamic grammar. 39. The method as in claim 1 , wherein the set of characters is a subset of the characters contained in a textual representation of the voice query. | 0.856031 |
8,990,208 | 27 | 34 | 27. One or more computer-readable non-transitory storage media embodying software operable when executed by one or more computer systems to: for each information item of a plurality of information items in a collection of information associated with a first user: construct a vector space model; and adjust the vector space model by an importance score of the information item, wherein the importance score indicates the level of importance the information item is to the first user; calculate a degree of similarity for every two information items in the collection of information; based on the degree of similarity calculated for every two information items in the collection of information, cluster the plurality of information items in the collection of information associated with the first user to generate a plurality of information topics using the adjusted vector space model of each information item; and for each information topic of the plurality of information topics generated from the collection of information associated with the first user, determine an interest score, which indicates a level of interest the first user has in the information topic relative to other information topics within the plurality of information topics; for each information topic of the plurality of information topics, determine a second interest score, which indicates a level of interest a second user has in the information topic relative to other information topics within the plurality of information topics; determining that the first user shares a common interest in a plurality of common-interest information topics with the second user, wherein the determining that the interest is a shared common interest is based on the difference between the first user's level of interest in an information topic and the second user's level of interest in an information topic, as determined by the interest score and the second interest score respectively, being less than a threshold difference; determine a common-interest strength between the first user and the second user, wherein the common-interest strength is calculated based on: the number of common-interest information topics shared between the first user and the second user, a respective level of interest, as determined by the interest score and the second interest score, by each of the first user and the second users in the plurality of common-interest information topics, and a correlation and difference between the respective level of interest in the plurality of common-interest information topics by the first user and the second user, the common-interest strength measuring the strength of connection between the first user and the second user; and establishing a connection in a social network between the first and second users based on the common-interest strength. | 27. One or more computer-readable non-transitory storage media embodying software operable when executed by one or more computer systems to: for each information item of a plurality of information items in a collection of information associated with a first user: construct a vector space model; and adjust the vector space model by an importance score of the information item, wherein the importance score indicates the level of importance the information item is to the first user; calculate a degree of similarity for every two information items in the collection of information; based on the degree of similarity calculated for every two information items in the collection of information, cluster the plurality of information items in the collection of information associated with the first user to generate a plurality of information topics using the adjusted vector space model of each information item; and for each information topic of the plurality of information topics generated from the collection of information associated with the first user, determine an interest score, which indicates a level of interest the first user has in the information topic relative to other information topics within the plurality of information topics; for each information topic of the plurality of information topics, determine a second interest score, which indicates a level of interest a second user has in the information topic relative to other information topics within the plurality of information topics; determining that the first user shares a common interest in a plurality of common-interest information topics with the second user, wherein the determining that the interest is a shared common interest is based on the difference between the first user's level of interest in an information topic and the second user's level of interest in an information topic, as determined by the interest score and the second interest score respectively, being less than a threshold difference; determine a common-interest strength between the first user and the second user, wherein the common-interest strength is calculated based on: the number of common-interest information topics shared between the first user and the second user, a respective level of interest, as determined by the interest score and the second interest score, by each of the first user and the second users in the plurality of common-interest information topics, and a correlation and difference between the respective level of interest in the plurality of common-interest information topics by the first user and the second user, the common-interest strength measuring the strength of connection between the first user and the second user; and establishing a connection in a social network between the first and second users based on the common-interest strength. 34. The media of claim 27 , wherein the plurality of information items is collected by the first user. | 0.930328 |
7,546,295 | 11 | 18 | 11. An apparatus for automatically determining any of importance of an on-line asset and expertise that one or more members of an online community possess, without asking said community members directly, comprising: means for observing usage by a community of peers and experts who show high affinity in connection with online assets; a processor for employing automatic techniques to extract patterns from said usage; said processor comprising a module for identifying usefulness of an online asset by observing user implicit behaviors in connection with said usage patterns of said online asset and by extracting behavioral patterns from said observations; said processor comprising a module for refining said identified online asset usefulness by context, wherein the context of each online asset is automatically detected based on observed terms/topics from individual and group user behaviors when said online asset is determined to be useful based upon said individual and group user behaviors; said processor comprising a module for assigning to each said online asset a document impact factor score for each possible topic/term, said document impact factor representing the importance of each said online asset to each topic; said processor comprising a module for assigning to each user an expert impact factor which is determined by aggregating identified topics of online assets each user has found useful, weighted by the document impact factor and by document rareness, wherein said expert impact factor and other observed patterns of behavior define a user's identified expertise; said processor comprising a module for using said identified expertise of each user to identify a community of experts given a specific topic/term of interest expressed by a user, and to identify a community of peers for a given user based upon a relationship between a target user's identified expertise and all other users; and said observed usage patterns comprising user online search, navigation, and interaction behavior, said behavior including any of searches performed and position in user trail; assets viewed and position in user trail; dwell, range, scrolling, think time, and mouse movement on an asset; anchors and lines used in asset text; virtual bookmarks and virtual printing; and explicit downloading, emailing, printing, saving, and removing. | 11. An apparatus for automatically determining any of importance of an on-line asset and expertise that one or more members of an online community possess, without asking said community members directly, comprising: means for observing usage by a community of peers and experts who show high affinity in connection with online assets; a processor for employing automatic techniques to extract patterns from said usage; said processor comprising a module for identifying usefulness of an online asset by observing user implicit behaviors in connection with said usage patterns of said online asset and by extracting behavioral patterns from said observations; said processor comprising a module for refining said identified online asset usefulness by context, wherein the context of each online asset is automatically detected based on observed terms/topics from individual and group user behaviors when said online asset is determined to be useful based upon said individual and group user behaviors; said processor comprising a module for assigning to each said online asset a document impact factor score for each possible topic/term, said document impact factor representing the importance of each said online asset to each topic; said processor comprising a module for assigning to each user an expert impact factor which is determined by aggregating identified topics of online assets each user has found useful, weighted by the document impact factor and by document rareness, wherein said expert impact factor and other observed patterns of behavior define a user's identified expertise; said processor comprising a module for using said identified expertise of each user to identify a community of experts given a specific topic/term of interest expressed by a user, and to identify a community of peers for a given user based upon a relationship between a target user's identified expertise and all other users; and said observed usage patterns comprising user online search, navigation, and interaction behavior, said behavior including any of searches performed and position in user trail; assets viewed and position in user trail; dwell, range, scrolling, think time, and mouse movement on an asset; anchors and lines used in asset text; virtual bookmarks and virtual printing; and explicit downloading, emailing, printing, saving, and removing. 18. The apparatus of claim 11 , further comprising: said processor identifying communities comprising any of peer groups and expert groups based on an information context; wherein communities are nested and defined by different levels of contexts. | 0.837927 |
8,676,833 | 16 | 27 | 16. A system for requesting social services from group of users, the system comprises of: a central server unit; at least one service provider and/or searcher computer system providing a service and/or performing a search in response to a service request and/or query from a requestor or searching user; at least one search system receiving request that the group service providers and/or group searching is required, presenting a list of groups of service providers and/or groups of searchers having human service providers and/or searcher members with domain specific expertise and rating, receiving selection of a desired service and/or search groups, prompting for and receiving an authentication information from the requestor or searching user, validating the authentication information, determining whether the requestor or searching user may submit the service request and/or query to a human service provider and/or searcher member of the related or selected service providers group and/or searcher group or a service provider or searcher who is not the human service provider or searcher member based on the match making, connections and subscriptions, and accepting the request or query from the requestor or searching user; a service providers and searchers group database including a service providers and search service of searchers service profiles, service name, ID, service types, service details, service categories, taxonomy, ontology, keywords, ranking, hit statistics, comments, service data including request and response resources, list and profile details of group members; a user system including at least one requestor or searching user interface using which the required service providers or searchers group is selected, the list of service providers or searchers groups being presented in an order based at least in part on the ranking of the service providers or searchers groups; a service providers or searchers of groups database including a service provider or searcher profile(s) including name, location, language, resume, qualification, background, experience, identity data, group identity data, authentication information, user data, ranking hit statistics; and an authorized requestors or searching users or registered subscribers database including the service providers or searchers group identity, an authorized user identity and authentication information, and where at least one of the human service provider or searcher members is selected to provide service or perform the search in response to the request or query from the requester or searching user based on a combination of a categories or keywords of the service or search, two way match making preferences, connections and subscriptions. | 16. A system for requesting social services from group of users, the system comprises of: a central server unit; at least one service provider and/or searcher computer system providing a service and/or performing a search in response to a service request and/or query from a requestor or searching user; at least one search system receiving request that the group service providers and/or group searching is required, presenting a list of groups of service providers and/or groups of searchers having human service providers and/or searcher members with domain specific expertise and rating, receiving selection of a desired service and/or search groups, prompting for and receiving an authentication information from the requestor or searching user, validating the authentication information, determining whether the requestor or searching user may submit the service request and/or query to a human service provider and/or searcher member of the related or selected service providers group and/or searcher group or a service provider or searcher who is not the human service provider or searcher member based on the match making, connections and subscriptions, and accepting the request or query from the requestor or searching user; a service providers and searchers group database including a service providers and search service of searchers service profiles, service name, ID, service types, service details, service categories, taxonomy, ontology, keywords, ranking, hit statistics, comments, service data including request and response resources, list and profile details of group members; a user system including at least one requestor or searching user interface using which the required service providers or searchers group is selected, the list of service providers or searchers groups being presented in an order based at least in part on the ranking of the service providers or searchers groups; a service providers or searchers of groups database including a service provider or searcher profile(s) including name, location, language, resume, qualification, background, experience, identity data, group identity data, authentication information, user data, ranking hit statistics; and an authorized requestors or searching users or registered subscribers database including the service providers or searchers group identity, an authorized user identity and authentication information, and where at least one of the human service provider or searcher members is selected to provide service or perform the search in response to the request or query from the requester or searching user based on a combination of a categories or keywords of the service or search, two way match making preferences, connections and subscriptions. 27. The system as claimed in claim 16 , wherein administrator of group(s) is adapted to create one or more domain or subject or project or categories or keyword(s) specific groups and attach, detach, invite, rank, order, publish, allow to searching and subscribing group(s) to one or more related human agents or searchers or users for providing one or more services including search service. | 0.865937 |
8,953,753 | 1 | 7 | 1. A voice messaging system for converting an audio voice message from a caller into text, the voice messaging system comprising: a plurality of conversion resources for converting the audio voice message into the text for an intended recipient, the plurality of conversion resources comprising: at least one automatic speech recognition (ASR) system to automatically recognize at least some of the audio voice message and generate a plurality of candidate words or phrases; and a computer implemented lattice sub-system that generates a lattice of possible words or phrases, enabling an operator to view one or more candidate words or phrases and to either select one of the one or more candidate words or phrases, or, by entering one or more characters of a different word or phrase, to trigger the lattice sub-system to provide at least one alternative word or phrase, wherein the lattice sub-system automatically differentiates between parts of the message based on whether the lattice sub-system determines parts of the message to be important or unimportant. | 1. A voice messaging system for converting an audio voice message from a caller into text, the voice messaging system comprising: a plurality of conversion resources for converting the audio voice message into the text for an intended recipient, the plurality of conversion resources comprising: at least one automatic speech recognition (ASR) system to automatically recognize at least some of the audio voice message and generate a plurality of candidate words or phrases; and a computer implemented lattice sub-system that generates a lattice of possible words or phrases, enabling an operator to view one or more candidate words or phrases and to either select one of the one or more candidate words or phrases, or, by entering one or more characters of a different word or phrase, to trigger the lattice sub-system to provide at least one alternative word or phrase, wherein the lattice sub-system automatically differentiates between parts of the message based on whether the lattice sub-system determines parts of the message to be important or unimportant. 7. The system of claim 1 in which the lattice sub-system receives inputs from a context sub-system that has knowledge of the context of a message. | 0.669683 |
8,731,617 | 1 | 11 | 1. A method for initiating voice calls from a communication device, comprising: causing, without user intervention, each number string in text of a data item which matches first predetermined criteria to be displayed in a first format and each number string in the text of the data item which does not match the first predetermined criteria to be displayed in a second format; causing a voice call to be initiated to a number string displayed in the first format when the number string is selected and first predetermined user input is detected; causing a list of user selectable functions to be displayed in response to detecting second predetermined user input when a position marker is located within a number string, the list of user selectable functions including a voice call function for initiating a voice call to the number string when the number string matches second predetermined criteria, wherein the second predetermined criteria are different from the first predetermined criteria; and causing a voice call to be initiated to a number string when the voice call function for the number string is selected from the list of user selectable functions. | 1. A method for initiating voice calls from a communication device, comprising: causing, without user intervention, each number string in text of a data item which matches first predetermined criteria to be displayed in a first format and each number string in the text of the data item which does not match the first predetermined criteria to be displayed in a second format; causing a voice call to be initiated to a number string displayed in the first format when the number string is selected and first predetermined user input is detected; causing a list of user selectable functions to be displayed in response to detecting second predetermined user input when a position marker is located within a number string, the list of user selectable functions including a voice call function for initiating a voice call to the number string when the number string matches second predetermined criteria, wherein the second predetermined criteria are different from the first predetermined criteria; and causing a voice call to be initiated to a number string when the voice call function for the number string is selected from the list of user selectable functions. 11. The method of claim 1 , wherein the first format is a hyperlinked format and the second format is a non-hyperlinked format. | 0.912894 |
7,555,718 | 1 | 19 | 1. A method for presenting video search results, including one or more videos, comprising the following steps: a) receiving a set of video search results for the one or more videos, wherein the video search results comprise one or more stories for each of the one or more videos; b) selecting from each story a set of shots; c) selecting from each shot one or more representative keyframes, wherein an area of each keyframe in the collage indicates a relevance of the video search results to the shot selection, wherein the relevance is determined by a combination of a search retrieval score of the shot and a search retrieval score of the story comprising the shot; and d) creating for each story a collage comprising the keyframes, wherein the collage can be used to present the video search results. | 1. A method for presenting video search results, including one or more videos, comprising the following steps: a) receiving a set of video search results for the one or more videos, wherein the video search results comprise one or more stories for each of the one or more videos; b) selecting from each story a set of shots; c) selecting from each shot one or more representative keyframes, wherein an area of each keyframe in the collage indicates a relevance of the video search results to the shot selection, wherein the relevance is determined by a combination of a search retrieval score of the shot and a search retrieval score of the story comprising the shot; and d) creating for each story a collage comprising the keyframes, wherein the collage can be used to present the video search results. 19. The method of claim 1 , comprising the additional step of: d) creating a timeline displayed with one or more neighbor stories which are each comprised in the video and which are closest in time of creation to a selected story. | 0.502165 |
9,311,298 | 1 | 8 | 1. A computer implemented method for enabling an application for Conversational Understanding (CU) using assets in a CU service, comprising: receiving a selection of Application Programming Interfaces (APIs) that are associated with a domain to use in the application; automatically updating models for the CU service based on the selection of the APIs and the determined domain; receiving a Natural Language (“NL”) expression, wherein the NL expression may be used to interact with the application; rephrasing the NL expressions to generate at least one additional expression, wherein the at least one additional expression contains a different, way of expressing a meaning of the NL expression; and automatic updating the models for CU service based on the rephrased NL expressions; making the models available to the CU service. | 1. A computer implemented method for enabling an application for Conversational Understanding (CU) using assets in a CU service, comprising: receiving a selection of Application Programming Interfaces (APIs) that are associated with a domain to use in the application; automatically updating models for the CU service based on the selection of the APIs and the determined domain; receiving a Natural Language (“NL”) expression, wherein the NL expression may be used to interact with the application; rephrasing the NL expressions to generate at least one additional expression, wherein the at least one additional expression contains a different, way of expressing a meaning of the NL expression; and automatic updating the models for CU service based on the rephrased NL expressions; making the models available to the CU service. 8. The method of claim 1 , further comprising incorporating the models into the CU service. | 0.911479 |
8,805,686 | 1 | 24 | 1. A method of electronically processing an utterance to locate candidate words at arbitrary positions within the utterance, including: accessing a dictionary of word sets each comprising multiple word representations; for each word representation, searching the utterance for likely instances of the word representation and scoring each likely word instance for a probability of a match to the word representation; wherein, the utterance is searched by multiple processors operating on the multiple word sets; and reporting at least a subset of likely word instances and respective probability scores for further electronic processing. | 1. A method of electronically processing an utterance to locate candidate words at arbitrary positions within the utterance, including: accessing a dictionary of word sets each comprising multiple word representations; for each word representation, searching the utterance for likely instances of the word representation and scoring each likely word instance for a probability of a match to the word representation; wherein, the utterance is searched by multiple processors operating on the multiple word sets; and reporting at least a subset of likely word instances and respective probability scores for further electronic processing. 24. The method of claim 1 , further including reporting for further processing at least three times as many likely word instances as there are distinct words in the dictionary. | 0.939477 |
8,909,810 | 1 | 2 | 1. A multimedia content sharing system, comprising A. a shared content server storing a plurality of items of content, where the stored items of content are any of still, moving images and audio, B. a plurality of nodes, each in communication coupling with the shared content server via one or more networks, C. the shared content server transmitting, via the one or more networks, i. a first set of one or more of the plurality of items of content stored on the server to each node in a first set of said nodes without a request by any user of that node for such item, where the first set comprises one or more of the plurality of nodes, and wherein each node in the first set of said nodes stores the first set of one or more of the plurality of items in a local store associated therewith, ii. a second set of one or more of the plurality of items of content stored on the server to each node in a second set of said nodes without a request by any user of that node for such item, where the second set comprises one or more of the plurality of nodes and where the second set of items may overlap the first set of items, where the second set of nodes may overlap the first set of nodes, and wherein each node in the second set of said nodes stores the second set of one or more of the plurality of items in a local store associated therewith, D. at least one said node (“first peer node”) in at least one of the first and second sets of nodes, (i) presenting any of visually and/or aurally the content of at least one item of content received from the shared content server, (ii) accepting user feedback with respect to that item of content, the user feedback reflecting user input regarding the item of content, and (iii) transmitting that user feedback to the shared content server, E. the shared content server transmitting the user feedback to at least one node (“second peer node”) that is in the set of nodes to which the first peer node belongs without retransmission of the article of content with respect to which the user feedback was accepted, which second peer node alters a presentation on that node of that item of content as stored on the local store associated therewith based on that user feedback. | 1. A multimedia content sharing system, comprising A. a shared content server storing a plurality of items of content, where the stored items of content are any of still, moving images and audio, B. a plurality of nodes, each in communication coupling with the shared content server via one or more networks, C. the shared content server transmitting, via the one or more networks, i. a first set of one or more of the plurality of items of content stored on the server to each node in a first set of said nodes without a request by any user of that node for such item, where the first set comprises one or more of the plurality of nodes, and wherein each node in the first set of said nodes stores the first set of one or more of the plurality of items in a local store associated therewith, ii. a second set of one or more of the plurality of items of content stored on the server to each node in a second set of said nodes without a request by any user of that node for such item, where the second set comprises one or more of the plurality of nodes and where the second set of items may overlap the first set of items, where the second set of nodes may overlap the first set of nodes, and wherein each node in the second set of said nodes stores the second set of one or more of the plurality of items in a local store associated therewith, D. at least one said node (“first peer node”) in at least one of the first and second sets of nodes, (i) presenting any of visually and/or aurally the content of at least one item of content received from the shared content server, (ii) accepting user feedback with respect to that item of content, the user feedback reflecting user input regarding the item of content, and (iii) transmitting that user feedback to the shared content server, E. the shared content server transmitting the user feedback to at least one node (“second peer node”) that is in the set of nodes to which the first peer node belongs without retransmission of the article of content with respect to which the user feedback was accepted, which second peer node alters a presentation on that node of that item of content as stored on the local store associated therewith based on that user feedback. 2. The system of claim 1 , wherein the step of accepting user feedback with respect to the item of content includes one or more of (i) copying the at least one item of content to an album, (ii) rotating the at least one item of content, (iii) requesting that a further node be blocked from presenting the at least one item of content, (iv) requesting that a sender of the at least one item of content be blocked from transmitting one or more items of content. | 0.501087 |
8,688,694 | 1 | 4 | 1. A computer-implemented method, comprising: at a client computer having one or more processors and memory storing programs executed by the one or more processors, receiving user instructions to associate each of a first virtual channel and a second virtual channel with a first content provider, wherein the first virtual channel includes a first set of user-specified search criteria and the second virtual channel includes a second set of user-specified search criteria that is different from the first set of search criteria; continuously performing operations according to a predefined schedule, the operations including: receiving a first set of information items from the first content provider, wherein each information item includes a document title, a document summary, and a document link to a document at a respective remote location; for each of the first set of information items, retrieving the document identified by the corresponding document link from the respective remote location; applying the first set of search criteria to each of the first set of information items and its associated document to generate a first set of search results, wherein the first set of search results includes a first set of chunks within a first document and a third set of chunks within a second document, and each of the first set and the third set of chunks satisfies the first set of search criteria; applying the second set of search criteria to each of the first set of information items and its associated document to generate a second set of search results, wherein the second set of search results includes a second set of chunks within the first document, and each of the second set of chunks satisfies the second set of search criteria, wherein there is at least one difference between the first set of chunks and the second set of chunks; associating the first virtual channel with the first set of search results and the second virtual channel with the second set of search results, wherein there is at least one search result associated with both the first virtual channel and the second virtual channel; displaying the first virtual channel and the second virtual channel on the client computer; in response to a user selection of the first virtual channel, displaying, at least partially, information items associated with the first set of search results and the first set of chunks within the first document and the third set of chunks within the second document to the user; and in response to a user selection of one of the first set of chunks, displaying, at least partially, the first document including the user-selected chunk to the user adjacent to the display of the first set of chunks and the third set of chunks, wherein the user-selected chunk is visually distinguished from the rest of the document. | 1. A computer-implemented method, comprising: at a client computer having one or more processors and memory storing programs executed by the one or more processors, receiving user instructions to associate each of a first virtual channel and a second virtual channel with a first content provider, wherein the first virtual channel includes a first set of user-specified search criteria and the second virtual channel includes a second set of user-specified search criteria that is different from the first set of search criteria; continuously performing operations according to a predefined schedule, the operations including: receiving a first set of information items from the first content provider, wherein each information item includes a document title, a document summary, and a document link to a document at a respective remote location; for each of the first set of information items, retrieving the document identified by the corresponding document link from the respective remote location; applying the first set of search criteria to each of the first set of information items and its associated document to generate a first set of search results, wherein the first set of search results includes a first set of chunks within a first document and a third set of chunks within a second document, and each of the first set and the third set of chunks satisfies the first set of search criteria; applying the second set of search criteria to each of the first set of information items and its associated document to generate a second set of search results, wherein the second set of search results includes a second set of chunks within the first document, and each of the second set of chunks satisfies the second set of search criteria, wherein there is at least one difference between the first set of chunks and the second set of chunks; associating the first virtual channel with the first set of search results and the second virtual channel with the second set of search results, wherein there is at least one search result associated with both the first virtual channel and the second virtual channel; displaying the first virtual channel and the second virtual channel on the client computer; in response to a user selection of the first virtual channel, displaying, at least partially, information items associated with the first set of search results and the first set of chunks within the first document and the third set of chunks within the second document to the user; and in response to a user selection of one of the first set of chunks, displaying, at least partially, the first document including the user-selected chunk to the user adjacent to the display of the first set of chunks and the third set of chunks, wherein the user-selected chunk is visually distinguished from the rest of the document. 4. The method of claim 1 , further comprising: displaying a search box associated with the user-selected first virtual channel; receiving one or more user-specified search keywords; for each information item associated with the first set of search results, retrieving the document identified by the corresponding document link from a respective remote location; identifying chunks satisfying the user-specified search keywords within the retrieved documents; and displaying the identified chunks and their corresponding information items to the user. | 0.691358 |
10,133,560 | 8 | 13 | 8. A system for optimizing source code, the system comprising: a processor and a memory configured to implement a linker and a compiler arranged in a link-time optimization tool flow to produce a link-time optimized executable computer program; a customized linker script, wherein the customized linker script is provided by an embedded application developer and overrides a default linker script existing within the linker, and wherein the customized liker script instructs the linker how to arrange output sections in the link-time optimized executable computer program; and an application program interface that enables communication between the linker and compiler and configured to facilitate the arrangement of the output sections of the link-time optimized executable according to the customized linker script, wherein the linker, compiler, and application program interface are configured to perform a method comprising: adding, by the compiler, to intermediate representation files having global or local symbols, metadata comprising default section assignment information for the symbols; recording, by the linker, for symbols in machine code files, an origin path and an output section; sending, from the linker to the compiler, detailed global scope and use information, then; parsing, by the compiler, based on a request and the detailed global scope and use information from the linker via the application program interface, the intermediate representation files; recording, by the compiler, the symbols and related symbol information comprising the default section assignment information and dependency information of the intermediate representation files, then; assigning output sections to the symbols based on both the default section assignment information and instructions from the customized linker script; and linking optimized code of the files of the computer program based on the assigned output sections. | 8. A system for optimizing source code, the system comprising: a processor and a memory configured to implement a linker and a compiler arranged in a link-time optimization tool flow to produce a link-time optimized executable computer program; a customized linker script, wherein the customized linker script is provided by an embedded application developer and overrides a default linker script existing within the linker, and wherein the customized liker script instructs the linker how to arrange output sections in the link-time optimized executable computer program; and an application program interface that enables communication between the linker and compiler and configured to facilitate the arrangement of the output sections of the link-time optimized executable according to the customized linker script, wherein the linker, compiler, and application program interface are configured to perform a method comprising: adding, by the compiler, to intermediate representation files having global or local symbols, metadata comprising default section assignment information for the symbols; recording, by the linker, for symbols in machine code files, an origin path and an output section; sending, from the linker to the compiler, detailed global scope and use information, then; parsing, by the compiler, based on a request and the detailed global scope and use information from the linker via the application program interface, the intermediate representation files; recording, by the compiler, the symbols and related symbol information comprising the default section assignment information and dependency information of the intermediate representation files, then; assigning output sections to the symbols based on both the default section assignment information and instructions from the customized linker script; and linking optimized code of the files of the computer program based on the assigned output sections. 13. The system of claim 8 , wherein the method further comprises: optimizing, at the compiler, each of the intermediate representation files based on the output section information for each symbol associated with the intermediate representation files. | 0.501984 |
7,624,013 | 1 | 9 | 1. A computer implemented method for recognizing speech patterns, the method comprising: segmenting a word into a string of consecutive phonemes; storing a plurality of sequences of the phonemes, at least one of the sequences of phonemes being associated with a mispronunciation of the word; associating a correctness indication with at least some of the sequences of the phonemes; providing a plurality of levels, at least some of the levels having multiple sequences of the phonemes associated with the level and at least some of the sequences of phonemes being associated with multiple ones of the plurality of levels with the correctness indication varying based on the level; comparing, by a computer system, an utterance with the plurality of sequences of phonemes; determining, by the computer system, if a match exists between the utterance and a particular one of the sequences of phonemes; and determining, by the computer system, an accuracy of the utterance based on the determined match, the level, and the correctness indication. | 1. A computer implemented method for recognizing speech patterns, the method comprising: segmenting a word into a string of consecutive phonemes; storing a plurality of sequences of the phonemes, at least one of the sequences of phonemes being associated with a mispronunciation of the word; associating a correctness indication with at least some of the sequences of the phonemes; providing a plurality of levels, at least some of the levels having multiple sequences of the phonemes associated with the level and at least some of the sequences of phonemes being associated with multiple ones of the plurality of levels with the correctness indication varying based on the level; comparing, by a computer system, an utterance with the plurality of sequences of phonemes; determining, by the computer system, if a match exists between the utterance and a particular one of the sequences of phonemes; and determining, by the computer system, an accuracy of the utterance based on the determined match, the level, and the correctness indication. 9. The method of claim 1 , wherein storing a plurality of sequences of the phonemes comprises storing at least one sequence of phonemes omitting at least one phoneme that is preceding a last one of the phonemes in the string and succeeding a first one of the phonemes in the string. | 0.682432 |
9,852,217 | 5 | 6 | 5. The method according to claim 1 , wherein performing OCR of the ROI comprises using a statistical language model. | 5. The method according to claim 1 , wherein performing OCR of the ROI comprises using a statistical language model. 6. The method according to claim 5 , wherein the statistical model is associated with a programming language of the code segment. | 0.957057 |
7,616,342 | 20 | 21 | 20. The system of claim 19 wherein at least one standard attribute among said plurality of attributes comprises a natural size of said at least one object of said at least one object type or a natural orientation of said at least one object of said at least one object type. | 20. The system of claim 19 wherein at least one standard attribute among said plurality of attributes comprises a natural size of said at least one object of said at least one object type or a natural orientation of said at least one object of said at least one object type. 21. The system of claim 20 wherein said processor processes each callout among said plurality of callouts separately from each object among said plurality of objects utilizing said plurality of attributes associated with an object among said plurality of objects in order to determine place and size data for each callout thereof. | 0.879474 |
8,990,211 | 1 | 3 | 1. A computer-implemented method for managing information about entities, the method comprising: generating, by one or more processors of an entity management system, a user interface document that, when rendered by a user device, presents a plurality of attribute values associated with an entity to a user and allows the user to modify one or more of the plurality of attribute values; generating, by one or more processors of the entity management system, an immutable observation that includes a user-modified value of one of the plurality of attribute values and a context, wherein the context is generated based on one or more of the plurality of attribute values sent to the user device for presentation, wherein the immutable observation is not modifiable after generation of the immutable observation; identifying, by one or more processors of the entity management system, a cluster of immutable observations that represent the entity using the context; associating, by one or more processors of the entity management system, the immutable observation with the cluster that represents the entity; and determining, by one or more processors of a summarization system, a summarized cluster to represent the current state of the entity, the summarized cluster comprising a subset of the cluster of immutable observations. | 1. A computer-implemented method for managing information about entities, the method comprising: generating, by one or more processors of an entity management system, a user interface document that, when rendered by a user device, presents a plurality of attribute values associated with an entity to a user and allows the user to modify one or more of the plurality of attribute values; generating, by one or more processors of the entity management system, an immutable observation that includes a user-modified value of one of the plurality of attribute values and a context, wherein the context is generated based on one or more of the plurality of attribute values sent to the user device for presentation, wherein the immutable observation is not modifiable after generation of the immutable observation; identifying, by one or more processors of the entity management system, a cluster of immutable observations that represent the entity using the context; associating, by one or more processors of the entity management system, the immutable observation with the cluster that represents the entity; and determining, by one or more processors of a summarization system, a summarized cluster to represent the current state of the entity, the summarized cluster comprising a subset of the cluster of immutable observations. 3. The computer-implemented method of claim 1 , wherein identifying, by one or more processors of an entity management system, a cluster of immutable observations that represents the entity using the context comprises: generating a query from one or more of the plurality of attribute values; identifying a plurality of candidate clusters responsive to the query; calculating a respective score for each of the plurality of candidate clusters based on comparison of at least one of the plurality of attribute values to an attribute value of respective candidate cluster; and identify the candidate cluster with the highest score as the cluster that represents the entity. | 0.62472 |
7,689,412 | 6 | 14 | 6. The computer readable storage medium of claim 1 and further comprising translating candidate synonymous collocations to construct a translation set comprising collocation translations for each candidate synonymous collocation. | 6. The computer readable storage medium of claim 1 and further comprising translating candidate synonymous collocations to construct a translation set comprising collocation translations for each candidate synonymous collocation. 14. The computer readable storage medium of claim 6 wherein selecting synonymous collocations comprises generating feature vectors of the candidate synonymous collocations as a function of the translation sets and the translation information. | 0.807018 |
8,825,698 | 20 | 21 | 20. The system of claim 12 , wherein determining a second set of authoritative users based on the first set of authoritative users comprises applying one or more rules to the first set of authoritative users. | 20. The system of claim 12 , wherein determining a second set of authoritative users based on the first set of authoritative users comprises applying one or more rules to the first set of authoritative users. 21. The system of claim 20 , wherein each authoritative user of the first set of authoritative users is associated with a score to provide a plurality of scores, and a rule of the one or more rules comprises selecting a sub-set of authoritative users from the first set of authoritative users based on the plurality of scores, the second set of authoritative users being at least partially populated with the sub-set of authoritative users. | 0.859425 |
9,799,333 | 9 | 11 | 9. A method for performing speech processing comprising steps of: a) receiving a signal including speech; b) accessing a database of keyword models, wherein the database of keyword models includes an ensemble of filters describing an evolution of phonetic events associated with each keyword in the database; c) decomposing, with an electronic system, the signal including speech into a sparse set of impulses; d) accessing, with an electronic system, the database of keywords and process the sparse set of impulses with information from the database of keyword models; e) identifying, with an electronic system, keywords within the signal including speech based on step d); and f) controlling operation the electronic system based on the keywords identified in step e). | 9. A method for performing speech processing comprising steps of: a) receiving a signal including speech; b) accessing a database of keyword models, wherein the database of keyword models includes an ensemble of filters describing an evolution of phonetic events associated with each keyword in the database; c) decomposing, with an electronic system, the signal including speech into a sparse set of impulses; d) accessing, with an electronic system, the database of keywords and process the sparse set of impulses with information from the database of keyword models; e) identifying, with an electronic system, keywords within the signal including speech based on step d); and f) controlling operation the electronic system based on the keywords identified in step e). 11. The method of claim 9 wherein step c) includes generating a representation of speech as a sparse set of temporal phonetic events. | 0.812676 |
10,055,686 | 1 | 6 | 1. A method performed by a computing device, the method comprising: obtaining a query comprising one or more words from a vocabulary having a first dimension; transforming the one or more words of the query into a phonetic representation of the one or more words; processing the phonetic representation to obtain a lower-dimension representation comprising a plurality of n-grams in an n-gram space having a second dimension that is smaller than the first dimension; performing a natural language processing operation on the lower-dimension representation, the natural language processing operation comprising determining similarity measures reflecting similarity of the one or more words of the query to a plurality of documents; based at least on the similarity measures, selecting a subset of the documents that are relevant to the query; and outputting the selected subset of documents in response to the query. | 1. A method performed by a computing device, the method comprising: obtaining a query comprising one or more words from a vocabulary having a first dimension; transforming the one or more words of the query into a phonetic representation of the one or more words; processing the phonetic representation to obtain a lower-dimension representation comprising a plurality of n-grams in an n-gram space having a second dimension that is smaller than the first dimension; performing a natural language processing operation on the lower-dimension representation, the natural language processing operation comprising determining similarity measures reflecting similarity of the one or more words of the query to a plurality of documents; based at least on the similarity measures, selecting a subset of the documents that are relevant to the query; and outputting the selected subset of documents in response to the query. 6. The method of claim 1 , wherein the processing comprises adding tokens to the phonetic representation, individual n-grams of the lower-dimension representation comprising individual tokens. | 0.857143 |
7,676,742 | 1 | 2 | 1. A system for processing of markup language information, the system comprising: a first computer including a first data processor for receiving markup language information, identifying a part thereof for compression, assigning a label representative of the part to form compressed information representative of the mark up language information comprising the label; and a second computer including a second data processor, in communication with the first data processor, for receiving the compressed information from the first data processor, decompressing the information, identifying the label and associating the label with the part of markup language information. | 1. A system for processing of markup language information, the system comprising: a first computer including a first data processor for receiving markup language information, identifying a part thereof for compression, assigning a label representative of the part to form compressed information representative of the mark up language information comprising the label; and a second computer including a second data processor, in communication with the first data processor, for receiving the compressed information from the first data processor, decompressing the information, identifying the label and associating the label with the part of markup language information. 2. A system of claim 1 wherein the first data processor comprises a compressor comprising: an identifier for identifying the part of the markup language information for compression and assigning the label; an encoder for encoding the markup language information into compressed information; and an embedder for embedding the label in the compressed information. | 0.501381 |
8,396,878 | 20 | 27 | 20. A computer-implemented method of generating automated tags for a video file, the method comprising: receiving one or more manually generated tags associated with a video file; based at least in part on the one or more manually entered tags, determining a preliminary category for the video file; based on the preliminary category, generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generating one or more automated tags associated with the video file; establishing a top concepts threshold value; determining that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associating information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file, wherein the plurality of scoring factors consists of two or more of: distribution of words throughout the targeted transcript of the video file, words related to the plurality of words throughout the targeted transcript of the video file, occurrence age of the related words, information associated with the one or more manually entered tags, vernacular meaning of the plurality of words, or colloquial considerations of the meaning of the plurality of words. | 20. A computer-implemented method of generating automated tags for a video file, the method comprising: receiving one or more manually generated tags associated with a video file; based at least in part on the one or more manually entered tags, determining a preliminary category for the video file; based on the preliminary category, generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generating one or more automated tags associated with the video file; establishing a top concepts threshold value; determining that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associating information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file, wherein the plurality of scoring factors consists of two or more of: distribution of words throughout the targeted transcript of the video file, words related to the plurality of words throughout the targeted transcript of the video file, occurrence age of the related words, information associated with the one or more manually entered tags, vernacular meaning of the plurality of words, or colloquial considerations of the meaning of the plurality of words. 27. The computer-implemented method of generating automated tags for the video file as in claim 20 , further comprising: receiving a second video file; receiving one or more manually generated tags associated with the second video file; based at least in part on the one or more manually entered tags associated with the second video file, determining a preliminary category for the second video file; based on the preliminary category of the second video file, generating a targeted transcript of the second video file, wherein the targeted transcript of the second video file includes a second plurality of words; generating an ontology of the second plurality of words based on the targeted transcript of the second video file; ranking the plurality of words and the second plurality of words based on the plurality of scoring factors; and based on the ranking of the plurality of words and the second plurality of words, generating one or more automated tags associated with both the video file and the second video file. | 0.569689 |
8,407,169 | 19 | 21 | 19. The system according to claim 15 wherein said system further comprises: a quality attribute type. | 19. The system according to claim 15 wherein said system further comprises: a quality attribute type. 21. The system according to claim 19 wherein said quality attribute type further comprises: an abstract representation of behavioral potential. | 0.946562 |
9,916,829 | 1 | 4 | 1. A method comprising: receiving a first voice query from a first user from a first device; converting the first voice query to a corresponding text query; querying a knowledge base based on the text query; receiving a response from the knowledge base that at least partially answers the text query; determining a quality score for the response from the knowledge base that represents a degree to which the response from the knowledge base is determined to answer the text query; determining that the quality score is below a threshold value; sending the text query to a second device, the second device associated with an agent; receiving a response statement from the second device; providing the response statement to the first device; storing the response statement in the knowledge base with the response from the knowledge base; updating the quality score for the response from the knowledge base to increase the degree to which the response is determined to answer the text query in response to storing the response statement in the knowledge base; receiving a second voice query from a second user from a third device; providing the response statement from the knowledge base to the third device responsive to the second voice query; requesting a response rating from the second user of the third device for the response statement provided to the third device; receiving the response rating for the response statement provided to the third device from the second user of the third device; and updating the quality score for the response from the knowledge base with the response rating for the response statement received from the second user of the third device. | 1. A method comprising: receiving a first voice query from a first user from a first device; converting the first voice query to a corresponding text query; querying a knowledge base based on the text query; receiving a response from the knowledge base that at least partially answers the text query; determining a quality score for the response from the knowledge base that represents a degree to which the response from the knowledge base is determined to answer the text query; determining that the quality score is below a threshold value; sending the text query to a second device, the second device associated with an agent; receiving a response statement from the second device; providing the response statement to the first device; storing the response statement in the knowledge base with the response from the knowledge base; updating the quality score for the response from the knowledge base to increase the degree to which the response is determined to answer the text query in response to storing the response statement in the knowledge base; receiving a second voice query from a second user from a third device; providing the response statement from the knowledge base to the third device responsive to the second voice query; requesting a response rating from the second user of the third device for the response statement provided to the third device; receiving the response rating for the response statement provided to the third device from the second user of the third device; and updating the quality score for the response from the knowledge base with the response rating for the response statement received from the second user of the third device. 4. The method of claim 1 , wherein the step of receiving a response from the knowledge base includes comparing one or more words associated with the voice query or text statement to one or more words associated with an answer in the knowledge base. | 0.648725 |
6,012,030 | 27 | 34 | 27. A system for dynamic adjustment of audio prompts in response to a users interaction modality with a communications device having a multimodal interface comprising a speech interface for accessing a speech recognizer and another interface, comprising: means for determining the mode of user input modality and selecting a corresponding one of a foreground state and a background state of the speech interface. | 27. A system for dynamic adjustment of audio prompts in response to a users interaction modality with a communications device having a multimodal interface comprising a speech interface for accessing a speech recognizer and another interface, comprising: means for determining the mode of user input modality and selecting a corresponding one of a foreground state and a background state of the speech interface. 34. A system according to claim 27 comprising means for selecting an appropriate foreground state or background state of the speech interface based on a sequence of previous user inputs. | 0.778571 |
7,639,257 | 8 | 10 | 8. The method of claim 7 , wherein: the identified reference includes one or more of the out-of-band values. | 8. The method of claim 7 , wherein: the identified reference includes one or more of the out-of-band values. 10. The method of claim 8 , wherein: identifying a glyphlet based on the identified reference includes identifying one or more target attributes based on the identified reference and identifying a glyphlet in a collection of glyphlets based on the identified target attributes. | 0.930646 |
8,676,627 | 3 | 4 | 3. The method as claimed in claim 1 wherein the first business process model project is a business modeler project, the second business process model project is an integration developer project and the new business process model project is a new business modeler project. | 3. The method as claimed in claim 1 wherein the first business process model project is a business modeler project, the second business process model project is an integration developer project and the new business process model project is a new business modeler project. 4. The method as claimed in claim 3 wherein the business modeler project includes the first business modeler language. | 0.980405 |
8,516,606 | 1 | 12 | 1. A computer-implemented method comprising: receiving a request for protected content from a client, the protected content comprising data; determining a challenge phrase comprising a plurality of characters; dividing, using a computer processor, the challenge phrase into at least two character subsets selected from the plurality of characters comprising the challenge phrase, each of the at least two character subsets comprising less than all of the characters comprising the challenge phrase, wherein a first character subset and a second character subset of the at least two character subsets comprise one or more common characters, and the first character subset includes at least one character not included in the second character subset; obscuring a first part of a common character in the first character subset; obscuring a second part of the common character in the second character subset, the second part of the common character being different than the first part of the common character; sending the at least two character subsets to the client in response to the request; and receiving, from the client and in response to the at least two character subsets, an answer to the challenge phrase, wherein access to the protected content is limited based on whether the answer correctly solves the challenge phrase. | 1. A computer-implemented method comprising: receiving a request for protected content from a client, the protected content comprising data; determining a challenge phrase comprising a plurality of characters; dividing, using a computer processor, the challenge phrase into at least two character subsets selected from the plurality of characters comprising the challenge phrase, each of the at least two character subsets comprising less than all of the characters comprising the challenge phrase, wherein a first character subset and a second character subset of the at least two character subsets comprise one or more common characters, and the first character subset includes at least one character not included in the second character subset; obscuring a first part of a common character in the first character subset; obscuring a second part of the common character in the second character subset, the second part of the common character being different than the first part of the common character; sending the at least two character subsets to the client in response to the request; and receiving, from the client and in response to the at least two character subsets, an answer to the challenge phrase, wherein access to the protected content is limited based on whether the answer correctly solves the challenge phrase. 12. The computer-implemented method according to claim 1 , wherein at least one of the characters comprising the challenge phrase is included in only a single one of the at least two subsets. | 0.857036 |
8,827,708 | 1 | 9 | 1. A method for controlling a computer simulation, comprising: running a first computer simulation of a system based on a model of said system, said model having a plurality of state variables; receiving input data from a first user input interface, said input being representative of user interaction with said first computer simulation to change values of one or more of said state variables in a manner consistent with an interaction with the simulated system; running, contemporaneously with said first computer simulation, a second computer simulation of said system based on the same model as said first simulation, said second simulation being accelerated relative to said first simulation so as to be running at further progression than said first simulation at a current time under the assumption of no further user interaction than those represented by the input data received from the first user input interface; using said second computer simulation to output information representing expected future events in said first simulation via a second user input interface; receiving input data from the second user input interface while said first computer simulation is running and said information representing expected future events is outputted, said input data received by the second user input interface adjusting the extent to which a condition is present in said first simulation; and translating, while said first computer simulation is running, said input from said second user input interface to values for one or more state variables in said first computer simulation consistent with a description of said condition in terms of rules embodied in the model, wherein output from said first computer simulation is delivered by a first data output device, and output from said second computer simulation, including said information representing expected future events, is delivered by a second data output device. | 1. A method for controlling a computer simulation, comprising: running a first computer simulation of a system based on a model of said system, said model having a plurality of state variables; receiving input data from a first user input interface, said input being representative of user interaction with said first computer simulation to change values of one or more of said state variables in a manner consistent with an interaction with the simulated system; running, contemporaneously with said first computer simulation, a second computer simulation of said system based on the same model as said first simulation, said second simulation being accelerated relative to said first simulation so as to be running at further progression than said first simulation at a current time under the assumption of no further user interaction than those represented by the input data received from the first user input interface; using said second computer simulation to output information representing expected future events in said first simulation via a second user input interface; receiving input data from the second user input interface while said first computer simulation is running and said information representing expected future events is outputted, said input data received by the second user input interface adjusting the extent to which a condition is present in said first simulation; and translating, while said first computer simulation is running, said input from said second user input interface to values for one or more state variables in said first computer simulation consistent with a description of said condition in terms of rules embodied in the model, wherein output from said first computer simulation is delivered by a first data output device, and output from said second computer simulation, including said information representing expected future events, is delivered by a second data output device. 9. The method of claim 1 , wherein said model is a flight simulator, and said condition is a malfunction of a plane or a severe weather condition. | 0.766026 |
8,280,823 | 139 | 140 | 139. The system of claim 138 , wherein to satisfy the search criteria, the parsed resume associated with each said at least one matching resume includes, for each said at least one job requirement, the required skill or experience-related phrase or at least one implying phrase of the required skill or experience-related phrase, and wherein the term of experience for the required skill or experience-related phrase or said at least one implying phrase of the required skill or experience-related phrase is greater than or equal to the required term of experience. | 139. The system of claim 138 , wherein to satisfy the search criteria, the parsed resume associated with each said at least one matching resume includes, for each said at least one job requirement, the required skill or experience-related phrase or at least one implying phrase of the required skill or experience-related phrase, and wherein the term of experience for the required skill or experience-related phrase or said at least one implying phrase of the required skill or experience-related phrase is greater than or equal to the required term of experience. 140. The system of claim 139 , wherein the term of experience is rounded down to a unit of time. | 0.97235 |
7,966,625 | 15 | 20 | 15. A data processing system for extending Web services to include call flow interactions, comprising: a processor; and a memory coupled to the processor, wherein the memory contains instructions which, when executed by the processor, cause the processor to: receive a description language document that describes one or more Web services interface components; associate a Web services interface component within the one or more Web services interface components with one or more call flow segments; insert a call flow binding into the description language document to form an extended description language document, wherein the call flow binding associates an interaction operation with a binding point in a given call flow segment within the one or more call flow segments; and execute a converged application based on the extended description language document. | 15. A data processing system for extending Web services to include call flow interactions, comprising: a processor; and a memory coupled to the processor, wherein the memory contains instructions which, when executed by the processor, cause the processor to: receive a description language document that describes one or more Web services interface components; associate a Web services interface component within the one or more Web services interface components with one or more call flow segments; insert a call flow binding into the description language document to form an extended description language document, wherein the call flow binding associates an interaction operation with a binding point in a given call flow segment within the one or more call flow segments; and execute a converged application based on the extended description language document. 20. The data processing system of claim 15 , wherein the interaction operation is an act operation, wherein the instructions further causes the processor to: responsive to receiving an invocation from a service oriented architecture integration platform, initiate execution of the given call flow segment. | 0.597625 |
8,244,752 | 8 | 12 | 8. A system for classifying search query traffic, said system comprising: memory storing computer-executable modules including: a feature set module that receives, from a search engine, labeled sample search query traffic and search query traffic associated with a plurality of search queries submitted by a particular user identifier, said labeled sample search traffic being labeled as human generated search query traffic or automatically generated search query traffic, said labeled sample search query traffic including one or more keywords for each search query submitted to said search engine and request times for said plurality of search queries submitted to said search engine within distinct user sessions, said feature set module extracting features from said labeled sample search query traffic in accordance with a set of feature definitions partitioned into physical features related to physical limitations of human generated search queries and behavioral features of automatically generated search queries and keywords of the automatically generated search queries, said feature set module generating a feature set comprising said features extracted from said labeled sample search query traffic; a classifier module that builds a model using said labeled sample search query traffic and said feature set, said classifier module using the model to classify said search query traffic associated with a said plurality of search queries submitted by said particular user identifier as human generated search query traffic or automatically generated search query traffic; and a quality of service module that changes a quality of service provided by said search engine to said particular user identifier when said search query traffic associated with said plurality of search queries submitted by said particular user identifier is classified as automatically generated search query traffic; and a processor that executes said computer-executable modules stored in said memory, wherein said feature set comprises a behavioral feature related to query word length entropy (WLE) that is calculated as: WL E ( l ij ) = - ∑ i ∑ j l ij log ( l ij ) , and wherein i is an index for each separate query submitted to a search engine by a single user ID and I ij a length of an individual query term j in the ith query. | 8. A system for classifying search query traffic, said system comprising: memory storing computer-executable modules including: a feature set module that receives, from a search engine, labeled sample search query traffic and search query traffic associated with a plurality of search queries submitted by a particular user identifier, said labeled sample search traffic being labeled as human generated search query traffic or automatically generated search query traffic, said labeled sample search query traffic including one or more keywords for each search query submitted to said search engine and request times for said plurality of search queries submitted to said search engine within distinct user sessions, said feature set module extracting features from said labeled sample search query traffic in accordance with a set of feature definitions partitioned into physical features related to physical limitations of human generated search queries and behavioral features of automatically generated search queries and keywords of the automatically generated search queries, said feature set module generating a feature set comprising said features extracted from said labeled sample search query traffic; a classifier module that builds a model using said labeled sample search query traffic and said feature set, said classifier module using the model to classify said search query traffic associated with a said plurality of search queries submitted by said particular user identifier as human generated search query traffic or automatically generated search query traffic; and a quality of service module that changes a quality of service provided by said search engine to said particular user identifier when said search query traffic associated with said plurality of search queries submitted by said particular user identifier is classified as automatically generated search query traffic; and a processor that executes said computer-executable modules stored in said memory, wherein said feature set comprises a behavioral feature related to query word length entropy (WLE) that is calculated as: WL E ( l ij ) = - ∑ i ∑ j l ij log ( l ij ) , and wherein i is an index for each separate query submitted to a search engine by a single user ID and I ij a length of an individual query term j in the ith query. 12. The system of claim 8 , wherein said feature set comprises a behavioral feature related to entropy of categories associated with single user identifier. | 0.749196 |
9,146,904 | 15 | 20 | 15. An apparatus, comprising: a processor to be operatively coupled to a memory and to execute a content generation module; and the content generation module to receive an instruction to define a content portion, the content generation module to select, based on a statistic indicative of a tone, a narrative tone type, the content generation module to select, a narrative template that includes a set of phrases, the content generation module to select, based on the narrative tone type, a phrase variation from a set of phrase variations associated with a first phrase from the set of phrases to define a first selected phrase, the content generation module to select, based on the narrative tone type, a phrase variation from a set of phrase variations associated with a second phrase from the set of phrases to define a second selected phrase, the content generation module to send a signal indicative of the content portion that includes the first selected phrase and the second selected phrase, the content generation module to send a signal such that the narrative content portion is output to a display. | 15. An apparatus, comprising: a processor to be operatively coupled to a memory and to execute a content generation module; and the content generation module to receive an instruction to define a content portion, the content generation module to select, based on a statistic indicative of a tone, a narrative tone type, the content generation module to select, a narrative template that includes a set of phrases, the content generation module to select, based on the narrative tone type, a phrase variation from a set of phrase variations associated with a first phrase from the set of phrases to define a first selected phrase, the content generation module to select, based on the narrative tone type, a phrase variation from a set of phrase variations associated with a second phrase from the set of phrases to define a second selected phrase, the content generation module to send a signal indicative of the content portion that includes the first selected phrase and the second selected phrase, the content generation module to send a signal such that the narrative content portion is output to a display. 20. The apparatus of claim 15 , wherein the content generation module to send a signal indicative of the content portion in response to an e-mail request. | 0.841237 |
9,391,902 | 18 | 20 | 18. A non-transitory machine-readable medium comprising a first plurality of machine-readable instructions which when executed by one or more processors associated with an application server are adapted to cause the one or more processors to perform a method comprising: periodically determining a load factor for a data source; receiving a data source query; estimating a complexity of the data source query; adjusting the estimated complexity by the load factor; in response to determining that the adjusted complexity is above a threshold, iteratively removing one or more query elements from the data source query to form one or more abbreviated queries until there are no query elements that can be removed from the data source query or a second adjusted complexity of the one or more abbreviated queries falls below the threshold; forming a query plan where the removed query elements are designated for processing outside the data source in a query engine; and performing the query plan by sending the one or more abbreviated queries to the data source and processing the removed query elements in the query engine. | 18. A non-transitory machine-readable medium comprising a first plurality of machine-readable instructions which when executed by one or more processors associated with an application server are adapted to cause the one or more processors to perform a method comprising: periodically determining a load factor for a data source; receiving a data source query; estimating a complexity of the data source query; adjusting the estimated complexity by the load factor; in response to determining that the adjusted complexity is above a threshold, iteratively removing one or more query elements from the data source query to form one or more abbreviated queries until there are no query elements that can be removed from the data source query or a second adjusted complexity of the one or more abbreviated queries falls below the threshold; forming a query plan where the removed query elements are designated for processing outside the data source in a query engine; and performing the query plan by sending the one or more abbreviated queries to the data source and processing the removed query elements in the query engine. 20. The non-transitory machine-readable medium of claim 18 wherein estimating the complexity comprises: counting a number of each of various types of query elements in the data source query; and computing a weighted sum based on the counting and respective costs of each of the various types of query elements. | 0.684959 |
10,061,752 | 1 | 2 | 1. A method for generating a font based on a METAFONT consisting of a letter drawing function and a style parameter, the method performed by an apparatus including a processor, the method comprising: (a) setting a fixed style parameter, wherein the fixed style parameter is included in the style parameter and corresponds to an intrinsic frame of the font designed by a font producer, and a value of the fixed style parameter is not changed; (b) generating an intermediate code by inputting the fixed style parameter in the letter drawing function; and (c) generating an output font by combining the intermediate code with a variable style parameter, wherein the variable style parameter is included in the style parameter and is set by a request from a user, and a value of the variable style parameter is changed. | 1. A method for generating a font based on a METAFONT consisting of a letter drawing function and a style parameter, the method performed by an apparatus including a processor, the method comprising: (a) setting a fixed style parameter, wherein the fixed style parameter is included in the style parameter and corresponds to an intrinsic frame of the font designed by a font producer, and a value of the fixed style parameter is not changed; (b) generating an intermediate code by inputting the fixed style parameter in the letter drawing function; and (c) generating an output font by combining the intermediate code with a variable style parameter, wherein the variable style parameter is included in the style parameter and is set by a request from a user, and a value of the variable style parameter is changed. 2. The method of claim 1 , wherein in the step of (c), the intermediate code and the variable style parameter are combined by using a parameter mapping table. | 0.503145 |
7,523,079 | 8 | 9 | 8. The computer-implemented network structure of claim 1 , wherein The first node monitors nodes within a vicinity to be monitored, wherein the first node performs the operations on nodes within a vicinity to be shaped, and wherein the first node determines a new time-variable state based on the existing time-variable state and on the nodes within the vicinity to be monitored. | 8. The computer-implemented network structure of claim 1 , wherein The first node monitors nodes within a vicinity to be monitored, wherein the first node performs the operations on nodes within a vicinity to be shaped, and wherein the first node determines a new time-variable state based on the existing time-variable state and on the nodes within the vicinity to be monitored. 9. The computer-implemented network structure of claim 8 , wherein a plurality of nodes is linked to The first node, and wherein the vicinity to be monitored encompasses a subset of the plurality of nodes. | 0.879127 |
7,827,169 | 1 | 13 | 1. A data processing method, comprising: receiving, at a data extractor, information identifying an enterprise resource planning system; selecting, from a table of the data extractor, one or more predefined resource description framework (RDF) queries based on the received identification information and a type of data source linked to a Semantic Web; extracting, using a processor, data from the data source linked to the Semantic Web by executing one or more of the selected predefined resource description framework (RDF) queries, wherein an extraction procedure is selected based on a type of the data source such that a feed reader is used to extract the data when the data source is of a first type and a data extractor is used to extract the data when the data source is of a second type, the first type being a Really Simple Syndication (RSS) feed; processing the extracted data by the enterprise resource planning system; determining when the extracted data includes new data that is of interest to a service customer; using the data extracted as a trigger for processing the data for performance of the enterprise resource planning system; sending an event message, alerting the service customer of the new data, to the service customer when it is determined that the new data is of interest to the service customer; and storing information indicating one or more sources from the semantic web that contained the new data causing the event message to be sent, wherein the table further stores an update frequency for the one or more resource description framework (RDF) queries, the update frequency specifies the periodicity with which a given query is to be performed, and the update frequency is determined respective to the proportion to the frequency of change of the data to be extracted from the Semantic Web. | 1. A data processing method, comprising: receiving, at a data extractor, information identifying an enterprise resource planning system; selecting, from a table of the data extractor, one or more predefined resource description framework (RDF) queries based on the received identification information and a type of data source linked to a Semantic Web; extracting, using a processor, data from the data source linked to the Semantic Web by executing one or more of the selected predefined resource description framework (RDF) queries, wherein an extraction procedure is selected based on a type of the data source such that a feed reader is used to extract the data when the data source is of a first type and a data extractor is used to extract the data when the data source is of a second type, the first type being a Really Simple Syndication (RSS) feed; processing the extracted data by the enterprise resource planning system; determining when the extracted data includes new data that is of interest to a service customer; using the data extracted as a trigger for processing the data for performance of the enterprise resource planning system; sending an event message, alerting the service customer of the new data, to the service customer when it is determined that the new data is of interest to the service customer; and storing information indicating one or more sources from the semantic web that contained the new data causing the event message to be sent, wherein the table further stores an update frequency for the one or more resource description framework (RDF) queries, the update frequency specifies the periodicity with which a given query is to be performed, and the update frequency is determined respective to the proportion to the frequency of change of the data to be extracted from the Semantic Web. 13. The data processing method of claim 1 wherein selecting, from the table of the data extractor, the one or more predefined resource description framework (RDF) queries based on the received identification information further comprises: using the received identification information as a key to retrieve the one or more predefined resource description framework (RDF) queries. | 0.501319 |
8,775,165 | 6 | 9 | 6. A non-transitory computer-readable storage medium having instructions stored thereon that, when executed by a server computer, cause the server computer to perform operations comprising: communicating with a user interface on a client device, the user interface being configured to receive an input word in a first language from a user, to provide to the user candidate words in a second language that are homophones of the input word, and to receive a user annotation associated with a candidate word; receiving, from the client device, the user annotation associated with the candidate word; and storing the user annotation associated with the candidate word in a server-side memory operably coupled to the server computer, wherein when a candidate list is compiled thereafter, the user annotation is displayed proximate to the candidate word in the candidate list. | 6. A non-transitory computer-readable storage medium having instructions stored thereon that, when executed by a server computer, cause the server computer to perform operations comprising: communicating with a user interface on a client device, the user interface being configured to receive an input word in a first language from a user, to provide to the user candidate words in a second language that are homophones of the input word, and to receive a user annotation associated with a candidate word; receiving, from the client device, the user annotation associated with the candidate word; and storing the user annotation associated with the candidate word in a server-side memory operably coupled to the server computer, wherein when a candidate list is compiled thereafter, the user annotation is displayed proximate to the candidate word in the candidate list. 9. The non-transitory computer-readable storage medium of claim 6 , the operations furthering comprising: associating the user annotation with the candidate word; and providing the candidate words and user annotations associated with the candidate words from the server computer to the client device. | 0.671772 |
8,631,006 | 9 | 10 | 9. A system for producing search results, comprising: memory; one or more processors; and at least one program, stored in the memory and executed by the one or more processors, the at least one program including: instructions for receiving, from a distinct client system, a search request associated with a user, the search request having one or more search terms; instructions for obtaining search results for the search request; instructions for generating a personalized snippet for at least one of the search results in accordance with profile information associated with the user, the snippet comprising a text portion of the search result chosen based on at least one or more search terms and one or more terms of the profile information; and instructions for transmitting the search results and personalized snippet to the client system for display; wherein the instructions for generating including instructions for: identifying content associated with one of the search results; determining a profile similarity score for at least one term in the content; and generating a snippet based in part on the at least one term if the profile similarity score is above a threshold; and wherein the instructions for determining the information similarity score include instructions for: identifying a respective term profile associated with the term; and determining a similarity between the information associated with the user and the respective term profile. | 9. A system for producing search results, comprising: memory; one or more processors; and at least one program, stored in the memory and executed by the one or more processors, the at least one program including: instructions for receiving, from a distinct client system, a search request associated with a user, the search request having one or more search terms; instructions for obtaining search results for the search request; instructions for generating a personalized snippet for at least one of the search results in accordance with profile information associated with the user, the snippet comprising a text portion of the search result chosen based on at least one or more search terms and one or more terms of the profile information; and instructions for transmitting the search results and personalized snippet to the client system for display; wherein the instructions for generating including instructions for: identifying content associated with one of the search results; determining a profile similarity score for at least one term in the content; and generating a snippet based in part on the at least one term if the profile similarity score is above a threshold; and wherein the instructions for determining the information similarity score include instructions for: identifying a respective term profile associated with the term; and determining a similarity between the information associated with the user and the respective term profile. 10. The system of claim 9 , wherein each of the information associated with the user and the respective term profile are represented as a plurality of profile categories and respective weights. | 0.825497 |
9,760,634 | 10 | 14 | 10. A method for defining a content relevance model for a particular category, the method comprising: identifying a set of key word sets for the particular category based on an analysis of (i) a first set of content segments previously defined as relevant to the particular category and (ii) a second set of content segments previously defined as not relevant to the particular category; identifying (i) a set of pairs of word sets that each comprise a key word set and a word set that appears in a defined context of the key word set and (ii) a score for each of the word set pairs, the score for a particular word set pair quantifying a likelihood that a content segment containing the particular word set pair is relevant to the particular category, wherein appearances of the particular word set pair in the first set of content segments increase the score for the particular word set pair and appearances of the particular word set pair in the second set of content segments decrease the score for the particular word set pair; and defining a content relevance model for the particular category, the content relevance model comprising (i) a context definition that indicates when a second word set appears within a context of a key word set and (ii) the set of word set pairs and corresponding scores. | 10. A method for defining a content relevance model for a particular category, the method comprising: identifying a set of key word sets for the particular category based on an analysis of (i) a first set of content segments previously defined as relevant to the particular category and (ii) a second set of content segments previously defined as not relevant to the particular category; identifying (i) a set of pairs of word sets that each comprise a key word set and a word set that appears in a defined context of the key word set and (ii) a score for each of the word set pairs, the score for a particular word set pair quantifying a likelihood that a content segment containing the particular word set pair is relevant to the particular category, wherein appearances of the particular word set pair in the first set of content segments increase the score for the particular word set pair and appearances of the particular word set pair in the second set of content segments decrease the score for the particular word set pair; and defining a content relevance model for the particular category, the content relevance model comprising (i) a context definition that indicates when a second word set appears within a context of a key word set and (ii) the set of word set pairs and corresponding scores. 14. The method of claim 10 , wherein a word set appears in the defined context of a key word set when the word set is in the same paragraph as the key word set. | 0.866444 |
10,108,812 | 4 | 5 | 4. The computer system of claim 1 , wherein the processing system is further configured to: when a blockchain transaction is associated with the digital cryptographic data structure of the approver user, receive, from a computer system associated with the approver user, a reject command for the document. | 4. The computer system of claim 1 , wherein the processing system is further configured to: when a blockchain transaction is associated with the digital cryptographic data structure of the approver user, receive, from a computer system associated with the approver user, a reject command for the document. 5. The computer system of claim 4 , wherein the processing system is further configured to: in response to reception of the rejection command, generate and submit a cancel blockchain transaction to the blockchain, wherein the cancel blockchain transaction is to a blockchain address that is not associated with any of the plurality of intended recipients. | 0.939912 |
9,489,373 | 5 | 6 | 5. The media of claim 1 , the method further comprising dividing at least one of the displayed first data item or the displayed second data item into sections and indicating a section that includes the example of the concept. | 5. The media of claim 1 , the method further comprising dividing at least one of the displayed first data item or the displayed second data item into sections and indicating a section that includes the example of the concept. 6. The media of claim 5 , wherein at least one of the selected first token or the selected second token is within the indicated section, and wherein tokens outside of the indicated section are not utilized for training the segment extractor. | 0.952372 |
7,580,993 | 16 | 20 | 16. Apparatus comprising a computer-readable storage medium tangibly embodying program instructions for distributing a document, the program instructions including instructions operable to cause a computer to: define a hashcode for the document, wherein the hashcode for the document is uniquely defined; distribute the document over one or more distribution channels; update the document with new data at a later scheduled interval; define a hashcode for the updated document, wherein the hashcode for the updated document is uniquely defined; compare the hashcode for the updated document and the hashcode with the distributed document to determine if the hashcodes differ; and if the hashcodes differ, determine that the updated document and the distributed document are different. | 16. Apparatus comprising a computer-readable storage medium tangibly embodying program instructions for distributing a document, the program instructions including instructions operable to cause a computer to: define a hashcode for the document, wherein the hashcode for the document is uniquely defined; distribute the document over one or more distribution channels; update the document with new data at a later scheduled interval; define a hashcode for the updated document, wherein the hashcode for the updated document is uniquely defined; compare the hashcode for the updated document and the hashcode with the distributed document to determine if the hashcodes differ; and if the hashcodes differ, determine that the updated document and the distributed document are different. 20. The apparatus in accordance with claim 16 , wherein the hashcodes differ because a template for the distributed document and a template for the updated document are different. | 0.757453 |
7,634,729 | 20 | 21 | 20. A system, comprising: means for receiving a file save command; means for displaying a file save interface responsive to means for receiving the file save command; means for receiving in electronic ink format in the file save interface a property value of a document or file on or accessible by a computer; means for determining a format for retention of the electronic ink format, the format is a first format of electronic ink format or a second format of machine-generated format; means for storing the property value of the document or file in the determined format for a later display on a display-interface in electronic ink format and retaining metadata pertaining to conversion of the format to the first format if saved in the second format or conversion of the format to the second format if saved in the first format; means for providing operating system access to the stored property value; means for obtaining a request to render the stored property value; means for establishing a format upon how to render the stored property value based upon the request; means for determining if the established format is the same as the saved format and converting the format upon a negative determination; and means for rendering the stored property value in accordance with the determined format as part of a file preview operation, the file preview operation filters information of the document or file such that a portion less than a whole of the document or less than a whole of the file is part of a file preview, the property value in electronic ink format includes an electronic filename for the document or file. | 20. A system, comprising: means for receiving a file save command; means for displaying a file save interface responsive to means for receiving the file save command; means for receiving in electronic ink format in the file save interface a property value of a document or file on or accessible by a computer; means for determining a format for retention of the electronic ink format, the format is a first format of electronic ink format or a second format of machine-generated format; means for storing the property value of the document or file in the determined format for a later display on a display-interface in electronic ink format and retaining metadata pertaining to conversion of the format to the first format if saved in the second format or conversion of the format to the second format if saved in the first format; means for providing operating system access to the stored property value; means for obtaining a request to render the stored property value; means for establishing a format upon how to render the stored property value based upon the request; means for determining if the established format is the same as the saved format and converting the format upon a negative determination; and means for rendering the stored property value in accordance with the determined format as part of a file preview operation, the file preview operation filters information of the document or file such that a portion less than a whole of the document or less than a whole of the file is part of a file preview, the property value in electronic ink format includes an electronic filename for the document or file. 21. A system according to claim 20 , wherein the means for receiving in electronic ink format in the file save interface a property value is configured to receive the property value from a touch-sensitive display or a proximity-sensitive display that receives user input by detecting a user's finger. | 0.501661 |
8,533,078 | 1 | 3 | 1. A redaction system comprising: a system for receiving an electronic version of a first document; a system for generating an electronic version of a second document which is a redacted version of the first document, wherein the system for generating comprises a computer having a redaction engine coupled to a source of redaction rules, wherein the source of redaction rules comprises at least one rule for automatically excluding information in the first document from the second document; and a system for transmitting the second document from the redaction system. | 1. A redaction system comprising: a system for receiving an electronic version of a first document; a system for generating an electronic version of a second document which is a redacted version of the first document, wherein the system for generating comprises a computer having a redaction engine coupled to a source of redaction rules, wherein the source of redaction rules comprises at least one rule for automatically excluding information in the first document from the second document; and a system for transmitting the second document from the redaction system. 3. A redaction system as in claim 1 wherein the information, which the at least one rule excludes, comprises text information. | 0.849282 |
7,831,494 | 6 | 13 | 6. The method of claim 1 further comprising: filtering a list of securities based on the user profile to generate the recommended securities; and presenting the recommended securities to the user for possible security swaps, wherein securities can be added to or removed from the current financial portfolio. | 6. The method of claim 1 further comprising: filtering a list of securities based on the user profile to generate the recommended securities; and presenting the recommended securities to the user for possible security swaps, wherein securities can be added to or removed from the current financial portfolio. 13. The method of claim 6 , further including: displaying, via the computing device, the filtered list of securities in a first column and a second column, wherein securities with positive Beta values are displayed in the first column and securities with negative Beta values are displayed in the second column. | 0.89342 |
10,142,809 | 11 | 15 | 11. A device that prompts one or more indicators to perform actions over context sensitive messages in a user device, the device comprising: at least one processor in electronic communication with at least one traffic management device; and a non-transitory computer-readable medium coupled to the at least one processor which is configured to be capable of executing programmed instructions, which comprise the programmed instructions stored in the non-transitory computer-readable medium to: receive an electronic message; identify a template of a plurality of previously downloaded templates that can be applied to the message based on analyzing a plurality of navigable hyperlinks content of the message, wherein if the identified template is a partly retrieved template then the partly retrieved template is consolidated to form a complete template based on one or more partial responses and a template recovery procedure implemented during syncings and wherein the complete template comprises service metadata to launch a service associated with each of the plurality of navigable hyperlinks in the message, wherein the service metadata comprises a service type and service invocation mechanism to launch the service associated with each of the one or more actionable texts in the message; identify one or more actionable texts from the plurality of navigable hyperlinks of the message using the identified template; retrieve the service metadata from the identified template to associate the service metadata to each of the one or more actionable texts; and prompt the one or more indicators on each of the one or more actionable texts to perform actions based on the service metadata, wherein based on the service type and service invocation mechanism associated with each of the one or more actionable texts, performing by the user device at least one of: automatically detecting an application in the user device for launching the service associated with each of the one or more actionable texts in the message; and invoking a selection mechanism for the user to select an application to launch the service associated with each of the one or more actionable texts in the message. | 11. A device that prompts one or more indicators to perform actions over context sensitive messages in a user device, the device comprising: at least one processor in electronic communication with at least one traffic management device; and a non-transitory computer-readable medium coupled to the at least one processor which is configured to be capable of executing programmed instructions, which comprise the programmed instructions stored in the non-transitory computer-readable medium to: receive an electronic message; identify a template of a plurality of previously downloaded templates that can be applied to the message based on analyzing a plurality of navigable hyperlinks content of the message, wherein if the identified template is a partly retrieved template then the partly retrieved template is consolidated to form a complete template based on one or more partial responses and a template recovery procedure implemented during syncings and wherein the complete template comprises service metadata to launch a service associated with each of the plurality of navigable hyperlinks in the message, wherein the service metadata comprises a service type and service invocation mechanism to launch the service associated with each of the one or more actionable texts in the message; identify one or more actionable texts from the plurality of navigable hyperlinks of the message using the identified template; retrieve the service metadata from the identified template to associate the service metadata to each of the one or more actionable texts; and prompt the one or more indicators on each of the one or more actionable texts to perform actions based on the service metadata, wherein based on the service type and service invocation mechanism associated with each of the one or more actionable texts, performing by the user device at least one of: automatically detecting an application in the user device for launching the service associated with each of the one or more actionable texts in the message; and invoking a selection mechanism for the user to select an application to launch the service associated with each of the one or more actionable texts in the message. 15. The device of claim 11 , wherein the non-transitory computer readable medium coupled to the processor further comprises the programmed instructions stored in the non-transitory computer-readable medium to generate one or more iconic representations associated with the service metadata. | 0.5961 |
9,665,622 | 1 | 10 | 1. A method comprising: performing a matching of an input keyword to one or more inquiry words in a search click log; rewriting the input keyword in response to determining that the input keyword does not match any inquiry word in the search click log; obtaining one or more categories corresponding to at least one inquiry word in the search click log based at least in part on correlation information in response to determining that the rewritten keyword matches the at least one inquiry word in the search click log, wherein the correlation information is calculated between a plurality of inquiry words and a plurality of categories in the search click log by calculating confidence degrees of each category corresponding to a respective inquiry word, and wherein a confidence degree of a respective category corresponding to the respective inquiry word comprises a weighted combination of a first conditional probability between the respective inquiry word and the respective category when the respective category is clicked after the respective inquiry word is received, and a second conditional probability between the respective inquiry word and the respective category when one or more products under the respective category are clicked after the respective inquiry word is received; and publishing product information under the one or more obtained categories. | 1. A method comprising: performing a matching of an input keyword to one or more inquiry words in a search click log; rewriting the input keyword in response to determining that the input keyword does not match any inquiry word in the search click log; obtaining one or more categories corresponding to at least one inquiry word in the search click log based at least in part on correlation information in response to determining that the rewritten keyword matches the at least one inquiry word in the search click log, wherein the correlation information is calculated between a plurality of inquiry words and a plurality of categories in the search click log by calculating confidence degrees of each category corresponding to a respective inquiry word, and wherein a confidence degree of a respective category corresponding to the respective inquiry word comprises a weighted combination of a first conditional probability between the respective inquiry word and the respective category when the respective category is clicked after the respective inquiry word is received, and a second conditional probability between the respective inquiry word and the respective category when one or more products under the respective category are clicked after the respective inquiry word is received; and publishing product information under the one or more obtained categories. 10. A method as recited in claim 1 , wherein the second conditional probability comprises a ratio between a number of times that the one or more products under the respective category are clicked within a period of time when the respective inquiry word is received, and a number of times that the respective inquiry word is received within the period of time. | 0.641717 |
9,798,975 | 3 | 4 | 3. The production rules engine according to claim 1 , wherein ontologies and assertions are loaded into a data structure comprising a logical network of nodes. | 3. The production rules engine according to claim 1 , wherein ontologies and assertions are loaded into a data structure comprising a logical network of nodes. 4. The production rules engine according to claim 3 , wherein the logical network of nodes is a RETE network that utilizes a RETE algorithm. | 0.962884 |
8,706,909 | 5 | 6 | 5. A web server configured to: receive a character string including a first Uniform Resource Locator (URL), a search string, and a search string indicator, the search string indicator string that the search string immediately follows the search string indicator; intercept a URL error message using a process file of the server, the process file including a list of valid search strings and a corresponding URL associated with each valid search string in the list; identify the search string in the character string; identify the search string in the list of valid search strings; and redirect to a second, valid URL corresponding to the search string in the list of valid search strings as function of the first URL, the second URL referencing a webpage having content corresponding to the search string. | 5. A web server configured to: receive a character string including a first Uniform Resource Locator (URL), a search string, and a search string indicator, the search string indicator string that the search string immediately follows the search string indicator; intercept a URL error message using a process file of the server, the process file including a list of valid search strings and a corresponding URL associated with each valid search string in the list; identify the search string in the character string; identify the search string in the list of valid search strings; and redirect to a second, valid URL corresponding to the search string in the list of valid search strings as function of the first URL, the second URL referencing a webpage having content corresponding to the search string. 6. The web server of claim 5 , wherein the web server is further configured to redirect to the same second, valid URL when one or more different search strings are found. | 0.883242 |
8,396,714 | 15 | 16 | 15. The computer-readable medium of claim 14 , wherein the operations further comprise: synthesizing a speech segment based on the modified text string; and providing the speech segment to a user device for playback with the media asset on the user device. | 15. The computer-readable medium of claim 14 , wherein the operations further comprise: synthesizing a speech segment based on the modified text string; and providing the speech segment to a user device for playback with the media asset on the user device. 16. The computer-readable medium of claim 15 , wherein the connecter term type specifies a respective pronunciation version for the connector term, and wherein synthesizing the speech segment based on the modified text string further comprises: selecting a particular pronunciation for the connector term based on the respective pronunciation version; and synthesizing the speech segment in accordance with the particular pronunciation for the connector term and the phonemes obtained for the text string. | 0.679975 |
5,574,844 | 1 | 2 | 1. A computer apparatus for exhibiting the properties and structure of matter comprising: a visual display unit; a data entry device; and a data processing system connected to said visual display unit and said data entry device, said data processing system having atomic structure program means for constructing mathematical atomic models, and a text/graphic interactive user interface having program selection means for permitting a user to interact with and perform operations on said atomic structure program means via said data entry device and said visual display unit, an atomic data base containing atomic information for use by said atomic structure program means for constructing said mathematical atomic models, an atomic data display means for displaying on said visual display unit atomic select buttons and said atomic information in response to selections made by said user via said atomic select buttons and said data entry device, and a graphic display means for displaying graphical representations of said mathematical atomic models on said visual display unit, and wherein said atomic data display means includes a periodic table means for displaying a plurality of said atomic select buttons to form element buttons labeled with said atomic information to form a periodic table of chemical elements on said visual display unit, and an element means for displaying on said visual display unit, in response to selection of one of said element buttons, a plurality of said atomic select buttons to form isotope buttons labeled with isotope information from said atomic information, said isotope information corresponding to the isotopes of said one of said chemical elements. | 1. A computer apparatus for exhibiting the properties and structure of matter comprising: a visual display unit; a data entry device; and a data processing system connected to said visual display unit and said data entry device, said data processing system having atomic structure program means for constructing mathematical atomic models, and a text/graphic interactive user interface having program selection means for permitting a user to interact with and perform operations on said atomic structure program means via said data entry device and said visual display unit, an atomic data base containing atomic information for use by said atomic structure program means for constructing said mathematical atomic models, an atomic data display means for displaying on said visual display unit atomic select buttons and said atomic information in response to selections made by said user via said atomic select buttons and said data entry device, and a graphic display means for displaying graphical representations of said mathematical atomic models on said visual display unit, and wherein said atomic data display means includes a periodic table means for displaying a plurality of said atomic select buttons to form element buttons labeled with said atomic information to form a periodic table of chemical elements on said visual display unit, and an element means for displaying on said visual display unit, in response to selection of one of said element buttons, a plurality of said atomic select buttons to form isotope buttons labeled with isotope information from said atomic information, said isotope information corresponding to the isotopes of said one of said chemical elements. 2. The computer apparatus of claim 1 wherein said atomic data display means further includes isotope means for displaying on said visual display unit, in response to selection of one of said isotope buttons, a properties display means for displaying the values of selected physical properties for the isotope corresponding to said selection of said isotope button. | 0.679577 |
8,209,176 | 1 | 5 | 1. A method comprising: transcribing, via a processor, speech data using a first automatic speech recognition pass, which operates at a first transcription rate, to produce a first transcription data and a first word graph; displaying a displayed part comprising an indication of a second automatic speech recognition pass which is forthcoming and at least part of the first transcription data corresponding to a portion of the speech data; after displaying the displayed part, transcribing the speech data using the second automatic speech recognition pass, wherein the second automatic speech recognition pass uses the first word graph to produce second transcription data and a second word graph, and wherein the second automatic speech recognition pass is slower than the first automatic speech recognition pass; and upon completing the second automatic speech recognition pass, updating the displayed part based at least in part on the second transcription data. | 1. A method comprising: transcribing, via a processor, speech data using a first automatic speech recognition pass, which operates at a first transcription rate, to produce a first transcription data and a first word graph; displaying a displayed part comprising an indication of a second automatic speech recognition pass which is forthcoming and at least part of the first transcription data corresponding to a portion of the speech data; after displaying the displayed part, transcribing the speech data using the second automatic speech recognition pass, wherein the second automatic speech recognition pass uses the first word graph to produce second transcription data and a second word graph, and wherein the second automatic speech recognition pass is slower than the first automatic speech recognition pass; and upon completing the second automatic speech recognition pass, updating the displayed part based at least in part on the second transcription data. 5. The method of claim 1 , wherein the displayed part changes color upon updating. | 0.939971 |
8,572,106 | 12 | 20 | 12. An apparatus for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, comprising: means for storing a record of which sub-expressions match the input string; and means for implementing an unbounded sub-expression without utilizing resources of a deterministic finite state automaton (DFA) engine or a non-deterministic finite state automaton (NFA) engine and for identifying one or more programs responsible for processing a sub-expression that matches the input string, and wherein the means for storing is configured to discard one or more records upon satisfaction of a predetermined condition and wherein the means for implementing the unbounded sub-expression is implemented by at least one processor-based computing device. | 12. An apparatus for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, comprising: means for storing a record of which sub-expressions match the input string; and means for implementing an unbounded sub-expression without utilizing resources of a deterministic finite state automaton (DFA) engine or a non-deterministic finite state automaton (NFA) engine and for identifying one or more programs responsible for processing a sub-expression that matches the input string, and wherein the means for storing is configured to discard one or more records upon satisfaction of a predetermined condition and wherein the means for implementing the unbounded sub-expression is implemented by at least one processor-based computing device. 20. The apparatus of claim 12 , wherein the means for storing is configured to discard records associated with sub-expressions that cannot result in a match across multiple lines when a current character in the input string being examined is a new line character. | 0.751418 |
7,546,295 | 11 | 16 | 11. An apparatus for automatically determining any of importance of an on-line asset and expertise that one or more members of an online community possess, without asking said community members directly, comprising: means for observing usage by a community of peers and experts who show high affinity in connection with online assets; a processor for employing automatic techniques to extract patterns from said usage; said processor comprising a module for identifying usefulness of an online asset by observing user implicit behaviors in connection with said usage patterns of said online asset and by extracting behavioral patterns from said observations; said processor comprising a module for refining said identified online asset usefulness by context, wherein the context of each online asset is automatically detected based on observed terms/topics from individual and group user behaviors when said online asset is determined to be useful based upon said individual and group user behaviors; said processor comprising a module for assigning to each said online asset a document impact factor score for each possible topic/term, said document impact factor representing the importance of each said online asset to each topic; said processor comprising a module for assigning to each user an expert impact factor which is determined by aggregating identified topics of online assets each user has found useful, weighted by the document impact factor and by document rareness, wherein said expert impact factor and other observed patterns of behavior define a user's identified expertise; said processor comprising a module for using said identified expertise of each user to identify a community of experts given a specific topic/term of interest expressed by a user, and to identify a community of peers for a given user based upon a relationship between a target user's identified expertise and all other users; and said observed usage patterns comprising user online search, navigation, and interaction behavior, said behavior including any of searches performed and position in user trail; assets viewed and position in user trail; dwell, range, scrolling, think time, and mouse movement on an asset; anchors and lines used in asset text; virtual bookmarks and virtual printing; and explicit downloading, emailing, printing, saving, and removing. | 11. An apparatus for automatically determining any of importance of an on-line asset and expertise that one or more members of an online community possess, without asking said community members directly, comprising: means for observing usage by a community of peers and experts who show high affinity in connection with online assets; a processor for employing automatic techniques to extract patterns from said usage; said processor comprising a module for identifying usefulness of an online asset by observing user implicit behaviors in connection with said usage patterns of said online asset and by extracting behavioral patterns from said observations; said processor comprising a module for refining said identified online asset usefulness by context, wherein the context of each online asset is automatically detected based on observed terms/topics from individual and group user behaviors when said online asset is determined to be useful based upon said individual and group user behaviors; said processor comprising a module for assigning to each said online asset a document impact factor score for each possible topic/term, said document impact factor representing the importance of each said online asset to each topic; said processor comprising a module for assigning to each user an expert impact factor which is determined by aggregating identified topics of online assets each user has found useful, weighted by the document impact factor and by document rareness, wherein said expert impact factor and other observed patterns of behavior define a user's identified expertise; said processor comprising a module for using said identified expertise of each user to identify a community of experts given a specific topic/term of interest expressed by a user, and to identify a community of peers for a given user based upon a relationship between a target user's identified expertise and all other users; and said observed usage patterns comprising user online search, navigation, and interaction behavior, said behavior including any of searches performed and position in user trail; assets viewed and position in user trail; dwell, range, scrolling, think time, and mouse movement on an asset; anchors and lines used in asset text; virtual bookmarks and virtual printing; and explicit downloading, emailing, printing, saving, and removing. 16. The apparatus of claim 11 , further comprising: said processor generating a set a recommendations that may be applied to a search; and for a given user who may be anonymous, and a given search query, said processor using said recommendations to refine and augment a resulting search. | 0.81168 |
3,982,333 | 1 | 6 | 1. A color coded speller comprising: a surface; a plurality of horizontally disposed lines of alphabet letters on said surface; an equal plurality of horizontally disposed code marking lanes on said surface, each code marking lane disposed directly above a line of alphabet letters; said horizontal code marking lanes adapted to removably receive code marks; a plurality of vertically disposed word and sentence lanes on said surface adapted to removably receive alphabet letters whereby a teacher may place a code mark above a selected letter in some or all of said lines and a pupil may copy said selected letters in one of said vertically disposed lanes to spell words and sentences which were preselected by the teacher. | 1. A color coded speller comprising: a surface; a plurality of horizontally disposed lines of alphabet letters on said surface; an equal plurality of horizontally disposed code marking lanes on said surface, each code marking lane disposed directly above a line of alphabet letters; said horizontal code marking lanes adapted to removably receive code marks; a plurality of vertically disposed word and sentence lanes on said surface adapted to removably receive alphabet letters whereby a teacher may place a code mark above a selected letter in some or all of said lines and a pupil may copy said selected letters in one of said vertically disposed lanes to spell words and sentences which were preselected by the teacher. 6. A color code speller as claimed in claim 1 further comprising: a drawer slidably mounted beneath said surface. | 0.803819 |
8,775,325 | 23 | 25 | 23. A computer-implemented system comprising: a processor; an advertisement request database of a social networking computer system configured for storing an advertisement request from an advertiser to advertise using a social networking system; an advertising server configured for: identifying an indication in the advertisement request indicating an action on an object, the action selectable by the advertiser from a plurality of actions on objects provided to the advertiser by the social networking computer system; and identifying an indication in the advertisement request for providing a message to a viewing user that another user connected to the viewing user in the social networking system has performed the identified action; determining, by the social networking computer system, that the identified action was taken on the object by another user connected to the viewing user; and selecting, by the social networking computer system, a story for the viewing user for display on a client device as a social advertisement, wherein: the story is sponsored by an advertiser and is based on the advertisement request received by the social networking computer system, and the story comprises information about the identified action taken on the object by the other user; and a web server configured for: receiving, at the social networking computer system from a client device of the viewing user, a request for social networking information to be displayed in a web page that is within a domain of an external system that is different from a domain of the social networking system, and sending, by the social networking computer system, the social advertisement to the client device for display in the interface of the web page of the external system. | 23. A computer-implemented system comprising: a processor; an advertisement request database of a social networking computer system configured for storing an advertisement request from an advertiser to advertise using a social networking system; an advertising server configured for: identifying an indication in the advertisement request indicating an action on an object, the action selectable by the advertiser from a plurality of actions on objects provided to the advertiser by the social networking computer system; and identifying an indication in the advertisement request for providing a message to a viewing user that another user connected to the viewing user in the social networking system has performed the identified action; determining, by the social networking computer system, that the identified action was taken on the object by another user connected to the viewing user; and selecting, by the social networking computer system, a story for the viewing user for display on a client device as a social advertisement, wherein: the story is sponsored by an advertiser and is based on the advertisement request received by the social networking computer system, and the story comprises information about the identified action taken on the object by the other user; and a web server configured for: receiving, at the social networking computer system from a client device of the viewing user, a request for social networking information to be displayed in a web page that is within a domain of an external system that is different from a domain of the social networking system, and sending, by the social networking computer system, the social advertisement to the client device for display in the interface of the web page of the external system. 25. The system of claim 23 , further comprising a newsfeed generator for generating a plurality of stories for the viewing user, each story comprising information about an action on an object taken by another user of the social networking system who has a connection to the viewing user, wherein the story selected for display is selected from the plurality of stories, wherein the social advertisement and a plurality of the stories generated are sent for display to the viewing user. | 0.534549 |
9,659,224 | 5 | 17 | 5. A device comprising: one or more processors operable to: send, to one or more servers in communication with the device via a network, at least a portion of a first frame of image data including at least a first captured textual item within a first bounding box corresponding to a region of the first frame; receive, from the one or more servers, first recognized text corresponding to the first captured textual item; send, to the one or more servers, at least a portion of a second frame of image data including at least a second captured textual item within a second bounding box corresponding to a region of the second frame; receive, from the one or more servers, second recognized text corresponding to the second captured textual item; compare first characters of the first recognized text with second characters of the second recognized text, wherein comparing the first characters with the second characters includes: determine an edit distance between the first recognized text and the second recognized text, and determine that the edit distance satisfies an edit distance threshold, wherein the edit distance threshold depends on a type of at least one of the first recognized text or of the second recognized text; determine an overlap of the first bounding box relative to the second bounding box; determine that the first captured textual item matches the second captured textual item based at least in part on (i) the comparison of characters of the first recognized text with characters of the second recognized text and (ii) the overlap; generate merged text based at least in part on the first recognized text and the second recognized text; and display, on a display, the merged text. | 5. A device comprising: one or more processors operable to: send, to one or more servers in communication with the device via a network, at least a portion of a first frame of image data including at least a first captured textual item within a first bounding box corresponding to a region of the first frame; receive, from the one or more servers, first recognized text corresponding to the first captured textual item; send, to the one or more servers, at least a portion of a second frame of image data including at least a second captured textual item within a second bounding box corresponding to a region of the second frame; receive, from the one or more servers, second recognized text corresponding to the second captured textual item; compare first characters of the first recognized text with second characters of the second recognized text, wherein comparing the first characters with the second characters includes: determine an edit distance between the first recognized text and the second recognized text, and determine that the edit distance satisfies an edit distance threshold, wherein the edit distance threshold depends on a type of at least one of the first recognized text or of the second recognized text; determine an overlap of the first bounding box relative to the second bounding box; determine that the first captured textual item matches the second captured textual item based at least in part on (i) the comparison of characters of the first recognized text with characters of the second recognized text and (ii) the overlap; generate merged text based at least in part on the first recognized text and the second recognized text; and display, on a display, the merged text. 17. The device of claim 5 , the one or more processors operable to: determine that the overlap satisfies a designated threshold, wherein determining that the first captured textual item matches the second captured textual item at least in part on the overlap includes determining that the overlap satisfies the designated threshold. | 0.746177 |
9,715,497 | 5 | 6 | 5. A system, comprising: at least one memory storing computer-executable instructions; and at least one processor in communication with the at least one memory, the at least one processor configured to access the at least one memory and execute the computer-executable instructions to: create a framework from at least one previously published work, the framework comprising a first set of entities and one or more rules that constrain a first set of actions associated with the first set of entities within the framework, the first set of actions including one or more of a verb performed by or on at least one of the first set of entities in the framework or a phrase performed by or on the at least one of the first set of entities in the manuscript; access a manuscript submitted for publication; determine the manuscript is associated with the framework; perform natural language analysis of the manuscript submitted for publication to identify a set of nouns described in the manuscript as a second set of entities described in the manuscript, and to identify a second set of actions that corresponds with the second set of entities by at least identifying a verb or phrase described in the manuscript that are performed by or on the second set of entities; generate a set of relationships between the second set of entities and the second set of actions, such that the set of relationships further include one or more additional actions that are synonymous to at least one action associated with at least one entity in the second set of actions; determine an amount of compliancy for each specific entity in the second set of entities by locating the one or more rules that reference the specific entity and determining whether the actions that correspond to the specific entity in the set of relationships comply or do not comply with the actions for the specific entity specified in the located one or more rules; identify the manuscript as compliant with the one or more rules based on determining that a number of actions of the second set of entities in the set of relationships that comply with the one or more rules is greater than a threshold proportion of a total number of the second set of entities; and generate result data that indicates the manuscript complies with the rules. | 5. A system, comprising: at least one memory storing computer-executable instructions; and at least one processor in communication with the at least one memory, the at least one processor configured to access the at least one memory and execute the computer-executable instructions to: create a framework from at least one previously published work, the framework comprising a first set of entities and one or more rules that constrain a first set of actions associated with the first set of entities within the framework, the first set of actions including one or more of a verb performed by or on at least one of the first set of entities in the framework or a phrase performed by or on the at least one of the first set of entities in the manuscript; access a manuscript submitted for publication; determine the manuscript is associated with the framework; perform natural language analysis of the manuscript submitted for publication to identify a set of nouns described in the manuscript as a second set of entities described in the manuscript, and to identify a second set of actions that corresponds with the second set of entities by at least identifying a verb or phrase described in the manuscript that are performed by or on the second set of entities; generate a set of relationships between the second set of entities and the second set of actions, such that the set of relationships further include one or more additional actions that are synonymous to at least one action associated with at least one entity in the second set of actions; determine an amount of compliancy for each specific entity in the second set of entities by locating the one or more rules that reference the specific entity and determining whether the actions that correspond to the specific entity in the set of relationships comply or do not comply with the actions for the specific entity specified in the located one or more rules; identify the manuscript as compliant with the one or more rules based on determining that a number of actions of the second set of entities in the set of relationships that comply with the one or more rules is greater than a threshold proportion of a total number of the second set of entities; and generate result data that indicates the manuscript complies with the rules. 6. The system of claim 5 , wherein the at least one processor is further configured to: create an additional relationship, wherein the additional relationship corresponds to an additional action that is substantially synonymous with a first action of the set of actions. | 0.83125 |
8,069,033 | 9 | 11 | 9. An apparatus comprising: a processor; a storage device coupled to the processor and configurable for storing instructions, which, when executed by the processor, cause the processor to perform operations comprising: searching the document for a character sequence that is separated on its ends by blank spaces, such that one or more adjacent pairs of characters in the character sequence are separated by an amount of white space that is ambiguous because it is larger than a kerning space but smaller than a blank space; creating a solution set for the character sequence, wherein each solution in the solution set is obtained by identifying the ambiguous amount of white space between each pair of characters that is separated by an ambiguous amount of white space as either a blank space or a kerning space; searching a dictionary for each solution in the solution set; and using the results from the dictionary search to identify the ambiguous amount of white space between each pair of characters in the character sequence that is separated by an ambiguous amount of white space as either a blank space or a kerning space. | 9. An apparatus comprising: a processor; a storage device coupled to the processor and configurable for storing instructions, which, when executed by the processor, cause the processor to perform operations comprising: searching the document for a character sequence that is separated on its ends by blank spaces, such that one or more adjacent pairs of characters in the character sequence are separated by an amount of white space that is ambiguous because it is larger than a kerning space but smaller than a blank space; creating a solution set for the character sequence, wherein each solution in the solution set is obtained by identifying the ambiguous amount of white space between each pair of characters that is separated by an ambiguous amount of white space as either a blank space or a kerning space; searching a dictionary for each solution in the solution set; and using the results from the dictionary search to identify the ambiguous amount of white space between each pair of characters in the character sequence that is separated by an ambiguous amount of white space as either a blank space or a kerning space. 11. The apparatus of claim 9 , wherein the result of the dictionary search is to find none of the solutions in the solution set, the storage device further configurable for storing instructions which, when executed by the processor, cause the processor to perform operations comprising: prompting a user to manually identify the ambiguous amount of white space between each pair of characters in the character sequence that is separated by an ambiguous amount of white space as either a blank space or a kerning space. | 0.625181 |
6,064,998 | 11 | 12 | 11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data, calculations required for the simulation and communication information to provide a goal-based educational environment, comprising: (a) a code segment that accesses the information in the spreadsheet object component of the rule-based expert system to retrieve indicia representative of a goal; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate examples into the simulation to provide assistance with achieving the goal; (c) a code segment that monitors answers to questions posed to evaluate progress of a student toward the goal utilizing the spreadsheet object component of the rule-based expert system and provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individual coaching messages that further provides the student with assistance with achieving the goal; and (d) a code segment that provides information to assist with a next step in achieving the goal. | 11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data, calculations required for the simulation and communication information to provide a goal-based educational environment, comprising: (a) a code segment that accesses the information in the spreadsheet object component of the rule-based expert system to retrieve indicia representative of a goal; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate examples into the simulation to provide assistance with achieving the goal; (c) a code segment that monitors answers to questions posed to evaluate progress of a student toward the goal utilizing the spreadsheet object component of the rule-based expert system and provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individual coaching messages that further provides the student with assistance with achieving the goal; and (d) a code segment that provides information to assist with a next step in achieving the goal. 12. A computer program embodied on a computer-readable medium that creates a multimedia business simulation as recited in claim 11, including a code segment that links information that motivates accomplishment of the goal to the simulation. | 0.502075 |
7,849,144 | 8 | 9 | 8. An instant message communications system comprising: a messaging resource configured for detecting an instant message having been sent by a sending party for delivery to a destination party, the instant message expressed in a first language; a presence resource configured for determining a language preference, for the destination party to receive the instant message, independent of whether any translation request has been requested by the sending party, wherein at least one of the messaging resource or the presence resource is configured for selectively clearing a cache that stores translation results of prior transmitted instant messages having been sent by the sending party, based on the messaging resource or the presence resource determining the translation results of the prior transmitted instant messages are no longer viable for context-based translation of the instant message; and a translation resource configured for translating the instant message having been sent by the sending party into a translated instant message, expressed in second language, in response to a translation request from the messaging resource, the messaging resource configured for sending the translation request based on the presence resource having determined the language preference for the destination party is distinct from the first language, wherein the instant message follows a sequence of prior transmitted instant messages having been sent by the sending party and having been translated and sent to the destination party in the second language, the translation resource translating the instant message relative to a context of the sequence of prior transmitted instant messages based on retrieval from the cache of the translation results of the prior transmitted instant messages determined as viable to the context-based translation of the instant message, and initiating the context-based translation of the instant message relative to the translation results; the messaging resource configured for sending the translated instant message in the second language to the destination party. | 8. An instant message communications system comprising: a messaging resource configured for detecting an instant message having been sent by a sending party for delivery to a destination party, the instant message expressed in a first language; a presence resource configured for determining a language preference, for the destination party to receive the instant message, independent of whether any translation request has been requested by the sending party, wherein at least one of the messaging resource or the presence resource is configured for selectively clearing a cache that stores translation results of prior transmitted instant messages having been sent by the sending party, based on the messaging resource or the presence resource determining the translation results of the prior transmitted instant messages are no longer viable for context-based translation of the instant message; and a translation resource configured for translating the instant message having been sent by the sending party into a translated instant message, expressed in second language, in response to a translation request from the messaging resource, the messaging resource configured for sending the translation request based on the presence resource having determined the language preference for the destination party is distinct from the first language, wherein the instant message follows a sequence of prior transmitted instant messages having been sent by the sending party and having been translated and sent to the destination party in the second language, the translation resource translating the instant message relative to a context of the sequence of prior transmitted instant messages based on retrieval from the cache of the translation results of the prior transmitted instant messages determined as viable to the context-based translation of the instant message, and initiating the context-based translation of the instant message relative to the translation results; the messaging resource configured for sending the translated instant message in the second language to the destination party. 9. The system of claim 8 , wherein the presence resource is configured for determining the language preference based on accessing a subscriber attributes record for retrieval of stored language preference attributes having been set by the destination party for receipt of instant messages. | 0.56994 |
8,467,443 | 7 | 9 | 7. The objected priority order compositor as defined by claim 6 , wherein the object rendering sequencer determines object rendering order on a screen. | 7. The objected priority order compositor as defined by claim 6 , wherein the object rendering sequencer determines object rendering order on a screen. 9. The object priority order compositor as defined by claim 7 , wherein case of insert, delete, and replace commands which require reconstruction of scene, the object rendering sequencer adjusts the object rendering order. | 0.919037 |
8,346,548 | 13 | 14 | 13. An aural similarity measuring server comprising: an input/output interface adapted for communication with one or more remote user terminals and further adapted to receive an input text; a data store in which is stored a plurality of reference texts; and a processor adapted to a) convert the input text into a string of phonemes, b) to adjust the phoneme string of the input text and a phoneme string of a reference text from said data store so that the two phoneme strings are equal in length, c) to assign a similarity score to the reference text representative of the similarity of the two phoneme strings, and d) to repeat steps b) and c) for at least one further reference text from said data store, wherein said input/output interface is further adapted to output a plurality of reference texts to which similarity scores have been assigned and their respective assigned similarity scores. | 13. An aural similarity measuring server comprising: an input/output interface adapted for communication with one or more remote user terminals and further adapted to receive an input text; a data store in which is stored a plurality of reference texts; and a processor adapted to a) convert the input text into a string of phonemes, b) to adjust the phoneme string of the input text and a phoneme string of a reference text from said data store so that the two phoneme strings are equal in length, c) to assign a similarity score to the reference text representative of the similarity of the two phoneme strings, and d) to repeat steps b) and c) for at least one further reference text from said data store, wherein said input/output interface is further adapted to output a plurality of reference texts to which similarity scores have been assigned and their respective assigned similarity scores. 14. An aural similarity measuring server as claimed in claim 13 , wherein the data store further contains a plurality of phoneme strings each string being associated with a reference text. | 0.82397 |
8,600,746 | 1 | 4 | 1. A computer-implemented method comprising: receiving audio data that encodes an utterance of a user; determining that the user has been classified as a novice user of a speech recognizer, comprising determining that an amount of training data that has been collected for the user does not satisfy a threshold; in response to determining that the user has been classified as a novice user of a speech recognizer, selecting a speech recognizer setting that is used by the speech recognizer in generating a transcription of the utterance, wherein the selected speech recognizer setting is different than a default speech recognizer setting that is used by the speech recognizer in generating transcriptions of utterances of users that are not classified as novice users, and wherein the selected speech recognizer setting results in increased speech recognition accuracy for the utterance in comparison with the default setting, and wherein the selected speech recognizer setting results in increased speech recognition latency for the utterance in comparison with the default setting; and obtaining a transcription of the utterance that is generated by the speech recognizer using the selected speech recognizer setting. | 1. A computer-implemented method comprising: receiving audio data that encodes an utterance of a user; determining that the user has been classified as a novice user of a speech recognizer, comprising determining that an amount of training data that has been collected for the user does not satisfy a threshold; in response to determining that the user has been classified as a novice user of a speech recognizer, selecting a speech recognizer setting that is used by the speech recognizer in generating a transcription of the utterance, wherein the selected speech recognizer setting is different than a default speech recognizer setting that is used by the speech recognizer in generating transcriptions of utterances of users that are not classified as novice users, and wherein the selected speech recognizer setting results in increased speech recognition accuracy for the utterance in comparison with the default setting, and wherein the selected speech recognizer setting results in increased speech recognition latency for the utterance in comparison with the default setting; and obtaining a transcription of the utterance that is generated by the speech recognizer using the selected speech recognizer setting. 4. The method of claim 1 , wherein selecting the speech recognizer setting comprises using a beam pruning parameter that is larger than the beam pruning parameter of the default setting. | 0.794248 |
4,221,061 | 1 | 3 | 1. An aid for teaching word pronunciation comprising: a set of alphabetical letters in material form, said letters being arrangeable to form words; at least one of said letters having a structural distinction from other letters in said set, in addition to conventional differences of alphabetic configuration; said structural distinction selected from a group of at least three structural distinctions, each distinction denoting a particular pronunciation of said letter in the formed word; one of said distinctions being that the letter is transparent, to denote that the letter is silent in the formed word; another of said distinctions being that the letter is of a greater height than the other letters, to denote that the letter is to be pronounced with a long vowel sound; still another of said distinctions being that the letter is in the shape of an object, to denote that the letter is to be pronounced as in the word for the depicted object. | 1. An aid for teaching word pronunciation comprising: a set of alphabetical letters in material form, said letters being arrangeable to form words; at least one of said letters having a structural distinction from other letters in said set, in addition to conventional differences of alphabetic configuration; said structural distinction selected from a group of at least three structural distinctions, each distinction denoting a particular pronunciation of said letter in the formed word; one of said distinctions being that the letter is transparent, to denote that the letter is silent in the formed word; another of said distinctions being that the letter is of a greater height than the other letters, to denote that the letter is to be pronounced with a long vowel sound; still another of said distinctions being that the letter is in the shape of an object, to denote that the letter is to be pronounced as in the word for the depicted object. 3. A teaching aid in accordance with claim 1 wherein said set of alphabetical letters includes the letter A shaped to represent a saw blade to denote its pronunciation as being that of the letter A in the word SAW. | 0.709239 |
8,394,127 | 10 | 12 | 10. A spine stabilization device comprising: a first element; a second element; and a self-centering joint connecting the first element and the second element; wherein the self-centering joint comprises: a housing having a socket; a rod with a retainer, with the retainer received in the socket; and a centering rod received at least partially within the rod and at least partially within the housing; whereby deflection of the rod bends the centering rod and the centering rod exerts a restoring force on the rod. | 10. A spine stabilization device comprising: a first element; a second element; and a self-centering joint connecting the first element and the second element; wherein the self-centering joint comprises: a housing having a socket; a rod with a retainer, with the retainer received in the socket; and a centering rod received at least partially within the rod and at least partially within the housing; whereby deflection of the rod bends the centering rod and the centering rod exerts a restoring force on the rod. 12. The spine stabilization device of claim 10 , wherein the first element is a bone anchor. | 0.952332 |
8,571,869 | 13 | 21 | 13. A natural language call routing system comprising: at least one processor configured to: obtain first data from a plurality of calls routed by a natural language call routing system that uses a first speech recognition model to recognize speech of the plurality of calls and a first action classification model to route calls based on the recognized speech, the first data comprising audio data from the plurality of calls, a first N-best list of word sequences generated by using the first speech recognition model to recognize at least a portion of the audio data and associated call classification data indicating how each of the plurality of calls were routed by the natural language call routing system; and modify the first speech recognition model and the first action classification model based at least in part on the first data, including using the first N-best list of word sequences, to obtain a second speech recognition model and a second action classification model; and modify the second speech recognition model and the second action classification model based at least in part on the first data to obtain a third speech recognition model and a third action classification model, wherein the modifying comprises modifying the second speech recognition model and the second action classification model by using the first N-best list or a second N-best list of word sequences generated by using the second speech recognition model to recognize at least the portion of the audio data. | 13. A natural language call routing system comprising: at least one processor configured to: obtain first data from a plurality of calls routed by a natural language call routing system that uses a first speech recognition model to recognize speech of the plurality of calls and a first action classification model to route calls based on the recognized speech, the first data comprising audio data from the plurality of calls, a first N-best list of word sequences generated by using the first speech recognition model to recognize at least a portion of the audio data and associated call classification data indicating how each of the plurality of calls were routed by the natural language call routing system; and modify the first speech recognition model and the first action classification model based at least in part on the first data, including using the first N-best list of word sequences, to obtain a second speech recognition model and a second action classification model; and modify the second speech recognition model and the second action classification model based at least in part on the first data to obtain a third speech recognition model and a third action classification model, wherein the modifying comprises modifying the second speech recognition model and the second action classification model by using the first N-best list or a second N-best list of word sequences generated by using the second speech recognition model to recognize at least the portion of the audio data. 21. The system of claim 13 , wherein the first data further comprises call transfer pattern data. | 0.895923 |
8,881,005 | 7 | 8 | 7. The method of claim 6 , wherein the determining the best candidate solution further comprises choosing a sequence of words with a maximum marginal probability via an A * lattice search and m-grams probability estimation. | 7. The method of claim 6 , wherein the determining the best candidate solution further comprises choosing a sequence of words with a maximum marginal probability via an A * lattice search and m-grams probability estimation. 8. The method of claim 7 , wherein the A* lattice search follows a best-first path strategy to select a path through a best candidate trellis, wherein the best-first path strategy is a statistical score of a path until its terminal expansion node. | 0.920116 |
8,774,519 | 1 | 8 | 1. A non-transitory program storage device, readable by a processor and comprising instructions stored thereon to cause the processor to: obtain a face bounding box comprising a first plurality of pixels; generate a candidate vector for each of a second plurality of pixels, the second plurality of pixels comprising a subset of the first plurality of pixels; reduce the dimensionality of each of the candidate vectors; apply positive landmark population statistics to each candidate vector to generate a positive likelihood value for each of the candidate vectors; apply negative landmark population statistics to each candidate vector to generate a negative likelihood value for each of the candidate vectors; combine each of the positive likelihood value and the negative likelihood value, corresponding to the same candidate vector to form an overall likelihood value for each candidate vector; and select at least one pixel from the face bounding box as a landmark pixel based, at least in part, on the overall likelihood values. | 1. A non-transitory program storage device, readable by a processor and comprising instructions stored thereon to cause the processor to: obtain a face bounding box comprising a first plurality of pixels; generate a candidate vector for each of a second plurality of pixels, the second plurality of pixels comprising a subset of the first plurality of pixels; reduce the dimensionality of each of the candidate vectors; apply positive landmark population statistics to each candidate vector to generate a positive likelihood value for each of the candidate vectors; apply negative landmark population statistics to each candidate vector to generate a negative likelihood value for each of the candidate vectors; combine each of the positive likelihood value and the negative likelihood value, corresponding to the same candidate vector to form an overall likelihood value for each candidate vector; and select at least one pixel from the face bounding box as a landmark pixel based, at least in part, on the overall likelihood values. 8. The non-transitory program storage device of claim 1 , further comprising instructions to cause the processor to identify an artifact in the face bounding box based on the selected at least one landmark pixel. | 0.790514 |
8,424,102 | 4 | 5 | 4. A non-transitory machine-readable medium, encoding instructions that, when performed by one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: presenting, by a server of a document control system to a client system, an electronic document tethered to the document control system, wherein the document control system provides persistent document security for documents tethered to the document control system; while presenting the electronic document to the client system, periodically showing the client system a consent query that requests consent to specific auditing actions relating to user interaction with the presented electronic document, the specific auditing actions to be recorded by the document control system for the electronic document; receiving in response to the presented consent query, a consent indication with respect to a consent statement relating to specific auditing actions; sending information corresponding to the consent indication to the document control system, the consent indication information configured to be included with actions-taken information relating to the electronic document; and altering, by the server of the document control system, one or more permissions associated with the electronic document in accordance with the consent indication information. | 4. A non-transitory machine-readable medium, encoding instructions that, when performed by one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: presenting, by a server of a document control system to a client system, an electronic document tethered to the document control system, wherein the document control system provides persistent document security for documents tethered to the document control system; while presenting the electronic document to the client system, periodically showing the client system a consent query that requests consent to specific auditing actions relating to user interaction with the presented electronic document, the specific auditing actions to be recorded by the document control system for the electronic document; receiving in response to the presented consent query, a consent indication with respect to a consent statement relating to specific auditing actions; sending information corresponding to the consent indication to the document control system, the consent indication information configured to be included with actions-taken information relating to the electronic document; and altering, by the server of the document control system, one or more permissions associated with the electronic document in accordance with the consent indication information. 5. The non-transitory machine-readable medium of claim 4 , wherein the consent query includes a predefined list of consent statements, and wherein receiving the consent indication comprises receiving a selection from the predefined list of consent statements. | 0.76875 |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.