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8,897,495 | 1 | 12 | 1. A method for tracking a user, comprising: receiving a depth image that was captured by a depth camera; identifying an estimated location or position of a part of the user in the depth image; adjusting a model of the user based on the estimated location or position of the part of the user; and in response to a failure to identify a location or position of the part of the user in a second depth image, associating the part of the user with a portion of the second depth image based on a location or position of a default position of the part of the user. | 1. A method for tracking a user, comprising: receiving a depth image that was captured by a depth camera; identifying an estimated location or position of a part of the user in the depth image; adjusting a model of the user based on the estimated location or position of the part of the user; and in response to a failure to identify a location or position of the part of the user in a second depth image, associating the part of the user with a portion of the second depth image based on a location or position of a default position of the part of the user. 12. The method of claim 1 , further comprising: downsampling pixels in the depth image before identifying the estimated location or position of the part of the user. | 0.791139 |
9,020,244 | 19 | 20 | 19. An apparatus comprising: one or more processors; and one or more memories communicatively coupled to the one or more processors and storing instructions which, when processed by the one or more processors, cause: generating a plurality of model-generated scores; wherein each model-generated score of the plurality of model-generated scores corresponds to a candidate image from a plurality of candidate images for a particular video item; wherein generating the plurality of model-generated scores includes, for each candidate image of the plurality of candidate images, using a set of input parameter values with a trained machine learning engine to produce the model-generated score that corresponds to the candidate image, wherein the set of input parameter values include at least one input parameter value for an activity feature that reflects one or more actions that one or more users have performed, during playback of the particular video item, relative to a frame that corresponds to the particular candidate image; establishing a ranking of the candidate images, from the plurality of candidate images, for the particular video item based, at least in part, on the model-generated scores that correspond to the candidate images; and selecting a candidate image, from the plurality of candidate images, as a representative image for the particular video item based, at least in part, on the ranking. | 19. An apparatus comprising: one or more processors; and one or more memories communicatively coupled to the one or more processors and storing instructions which, when processed by the one or more processors, cause: generating a plurality of model-generated scores; wherein each model-generated score of the plurality of model-generated scores corresponds to a candidate image from a plurality of candidate images for a particular video item; wherein generating the plurality of model-generated scores includes, for each candidate image of the plurality of candidate images, using a set of input parameter values with a trained machine learning engine to produce the model-generated score that corresponds to the candidate image, wherein the set of input parameter values include at least one input parameter value for an activity feature that reflects one or more actions that one or more users have performed, during playback of the particular video item, relative to a frame that corresponds to the particular candidate image; establishing a ranking of the candidate images, from the plurality of candidate images, for the particular video item based, at least in part, on the model-generated scores that correspond to the candidate images; and selecting a candidate image, from the plurality of candidate images, as a representative image for the particular video item based, at least in part, on the ranking. 20. The apparatus of claim 19 , wherein using a set of input parameter values with the trained machine learning engine includes using with the trained machine learning engine at least one input parameter for one or more of a request-specific feature, a temporal feature, or a naturalness features. | 0.688679 |
8,458,179 | 13 | 17 | 13. A non-transitory computer-readable medium storing instructions which when executed by a computer cause the computer to perform a method for augmenting a privacy policy, the method comprising: obtaining a set of training documents and a seed keyword associated with the privacy policy; extracting a candidate keyword from the training documents; issuing at least one query comprising the candidate keyword to a corpus; receiving a set of result documents; evaluating an inference strength between the candidate keyword and a respective seed keyword, wherein evaluating the inference strength comprises evaluating a ratio between the number of search hits from a query containing both the candidate keyword and the respective seed keyword, and the number of search hits from a query containing only the candidate keyword; determining that the evaluated inference strength is greater than a predetermined threshold ratio; responsive to the evaluated inference strength being greater than the predetermined threshold ratio, augmenting the privacy policy by associating the candidate keyword with the privacy policy; and applying the augmented privacy policy to a subject document to determine whether the subject document triggers the privacy policy, wherein applying the augmented privacy policy comprises searching the subject document for occurrences of any of the candidate keywords associated with the augmented privacy policy. | 13. A non-transitory computer-readable medium storing instructions which when executed by a computer cause the computer to perform a method for augmenting a privacy policy, the method comprising: obtaining a set of training documents and a seed keyword associated with the privacy policy; extracting a candidate keyword from the training documents; issuing at least one query comprising the candidate keyword to a corpus; receiving a set of result documents; evaluating an inference strength between the candidate keyword and a respective seed keyword, wherein evaluating the inference strength comprises evaluating a ratio between the number of search hits from a query containing both the candidate keyword and the respective seed keyword, and the number of search hits from a query containing only the candidate keyword; determining that the evaluated inference strength is greater than a predetermined threshold ratio; responsive to the evaluated inference strength being greater than the predetermined threshold ratio, augmenting the privacy policy by associating the candidate keyword with the privacy policy; and applying the augmented privacy policy to a subject document to determine whether the subject document triggers the privacy policy, wherein applying the augmented privacy policy comprises searching the subject document for occurrences of any of the candidate keywords associated with the augmented privacy policy. 17. The computer-readable medium of claim 13 , wherein obtaining the set of training documents comprises receiving one or more documents that are known to pertain to sensitive subject matter. | 0.857036 |
7,669,183 | 6 | 7 | 6. The system as claimed in claim 1 , further comprising an initialization function for directing the processing of one or more behavior elements in a document object model, the initialization function having instructions for traversing each node in the document object model and for searching and calling functions associated with behavior elements having names following the predetermined naming convention. | 6. The system as claimed in claim 1 , further comprising an initialization function for directing the processing of one or more behavior elements in a document object model, the initialization function having instructions for traversing each node in the document object model and for searching and calling functions associated with behavior elements having names following the predetermined naming convention. 7. The system as claimed in claim 6 , further comprising: a collection of behavior attributes for adding to existing regular extensible markup language elements in a document object model, the behavior attributes following the predetermined naming convention; and a collection of scripts for performing actions associated with the collection of behavior attributes, each script associated with a behavior attribute. | 0.850397 |
9,389,729 | 7 | 12 | 7. A non-transitory computer readable storage medium storing executable program instructions, which, when executed by an electronic with one or more processors, memory and a touch-sensitive display, cause the electronic device to: receive proximity data from a proximity sensor of the electronic device, wherein the proximity sensor is configured to obtain proximity data corresponding to a location of a user relative to the electronic device; receive a touch input on the touch-sensitive display; determine whether the electronic device is in one of a first or second proximity state based on the received proximity data, wherein the second proximity state occurs when the electronic device is proximate to the user; upon determining that the electronic device is in the first proximity state, process the touch input as an intentional touch input; upon determining that the electronic device is in the second proximity state, process the touch input as an unintentional touch input; and in response to a change in the received proximity data, change the processing of the touch input. | 7. A non-transitory computer readable storage medium storing executable program instructions, which, when executed by an electronic with one or more processors, memory and a touch-sensitive display, cause the electronic device to: receive proximity data from a proximity sensor of the electronic device, wherein the proximity sensor is configured to obtain proximity data corresponding to a location of a user relative to the electronic device; receive a touch input on the touch-sensitive display; determine whether the electronic device is in one of a first or second proximity state based on the received proximity data, wherein the second proximity state occurs when the electronic device is proximate to the user; upon determining that the electronic device is in the first proximity state, process the touch input as an intentional touch input; upon determining that the electronic device is in the second proximity state, process the touch input as an unintentional touch input; and in response to a change in the received proximity data, change the processing of the touch input. 12. The non-transitory computer readable storage medium of claim 7 , wherein: the electronic device includes a radio frequency transceiver for communicating with one or more other electronic devices; and the executable program instructions further cause the electronic device to: determine whether the radio frequency transceiver is communicating with another electronic device; and wherein: the touch input is processed as an intentional touch input when the electronic device is in the first proximity state and the radio frequency transceiver is not communicating with another electronic device; and the touch input is processed as an unintentional touch input when the electronic device is in the second proximity state and the radio frequency transceiver is communicating with another electronic device. | 0.500618 |
8,224,642 | 16 | 17 | 16. The computer program product of claim 14 further comprising: program code for defining an impostor profile for a language L in the plurality of candidate languages and storing the impostor profile for the language L in a data store. | 16. The computer program product of claim 14 further comprising: program code for defining an impostor profile for a language L in the plurality of candidate languages and storing the impostor profile for the language L in a data store. 17. The computer program product of claim 16 wherein the program code for defining the impostor profile for the language L includes program code for analyzing a set of training documents known to be in the language L to determine an alternative score for each document in the set of training documents under the language model for a language other than the language L. | 0.901867 |
7,493,555 | 20 | 21 | 20. A computer implemented batch import apparatus for integrating a plurality of electronic files into data store, the apparatus comprising: a data store comprising a repository configured to receive the electronic files and the descriptions of the files; the electronic files and the description generated responsive to a set of input documents and a specification comprising instructions for describing attributes of the files and syntax rules for the descriptions; a file import module adapted to locate the electronic files based on location information contained within the descriptions of the files and import the electronic files into the data store; and an indexing module adapted to index the electronic files in the data store responsive to the indexing extracted from the descriptions of the electronic files. | 20. A computer implemented batch import apparatus for integrating a plurality of electronic files into data store, the apparatus comprising: a data store comprising a repository configured to receive the electronic files and the descriptions of the files; the electronic files and the description generated responsive to a set of input documents and a specification comprising instructions for describing attributes of the files and syntax rules for the descriptions; a file import module adapted to locate the electronic files based on location information contained within the descriptions of the files and import the electronic files into the data store; and an indexing module adapted to index the electronic files in the data store responsive to the indexing extracted from the descriptions of the electronic files. 21. The apparatus of claim 20 further comprising a user application module configured to access an electronic file in the data store. | 0.895276 |
9,420,204 | 12 | 13 | 12. The information processing apparatus according to claim 7 , wherein the object selection unit selects the characteristic object in accordance with contents of the talk of each of the one of the plurality of objects, and wherein the textual information generation unit generates the textual information indicating contents of the talk. | 12. The information processing apparatus according to claim 7 , wherein the object selection unit selects the characteristic object in accordance with contents of the talk of each of the one of the plurality of objects, and wherein the textual information generation unit generates the textual information indicating contents of the talk. 13. The information processing apparatus according to claim 12 , wherein the object selection unit selects the characteristic object in accordance with a magnitude of a voice of the talk or a speed of the talk of each of the one or the plurality of objects. | 0.914162 |
9,305,091 | 3 | 5 | 3. The system of claim 1 , further including: generating a layered set of sorted anchor maps, wherein each sorted map in the layered set of anchor maps is associated with a production time. | 3. The system of claim 1 , further including: generating a layered set of sorted anchor maps, wherein each sorted map in the layered set of anchor maps is associated with a production time. 5. The system of claim 3 , wherein at least one record in at least one sorted anchor map in the layered set of anchor maps contains a delete entry. | 0.970576 |
9,542,453 | 19 | 25 | 19. A computer system for producing personalized search results, comprising: memory; one or more processors; one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs including: instructions for receiving a search query from a user; instructions for identifying search results associated with the search query; instructions for identifying a user profile associated with the user, wherein the user profile includes a set of user-preferred search results determined, at least in part, by: instructions for identifying a set of candidate search results in a search history of the user, wherein each of the candidate search results has been selected by the user for at least a predefined minimum number of times; instructions for determining a popularity metric for each of the candidate search results; and instructions for selecting a subset of the candidate search results whose associated popularity metrics exceed a predefined threshold as the set of user-preferred search results; instructions for identifying in the search results, one or more search results that are associated with at least one of the user-preferred search results; instructions for ordering the search results based at least in part on the identification, in the search results, of the one or more search results that are associated with at least one of the user-preferred search results; and instructions for providing the ordered list of search results to the user. | 19. A computer system for producing personalized search results, comprising: memory; one or more processors; one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs including: instructions for receiving a search query from a user; instructions for identifying search results associated with the search query; instructions for identifying a user profile associated with the user, wherein the user profile includes a set of user-preferred search results determined, at least in part, by: instructions for identifying a set of candidate search results in a search history of the user, wherein each of the candidate search results has been selected by the user for at least a predefined minimum number of times; instructions for determining a popularity metric for each of the candidate search results; and instructions for selecting a subset of the candidate search results whose associated popularity metrics exceed a predefined threshold as the set of user-preferred search results; instructions for identifying in the search results, one or more search results that are associated with at least one of the user-preferred search results; instructions for ordering the search results based at least in part on the identification, in the search results, of the one or more search results that are associated with at least one of the user-preferred search results; and instructions for providing the ordered list of search results to the user. 25. The computer system of claim 19 , wherein the predefined number of times is at least two. | 0.892111 |
8,346,590 | 21 | 22 | 21. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: receiving a calendar search request to schedule a calendar event including a plurality of constraints including at least one participant and a time of meeting constraint; obtaining information identifying one or more preferences associated with the at least one participant, at least one of the preferences based on the at least one participant's historical calendar activity over a predetermined period of time; searching one or more databases in a calendaring system to obtain a set of candidate calendar events that meet at least a subset of the plurality of constraints; ranking the set of candidate calendar events based on the plurality of constraints and the one or more preferences; and preparing for presentation at least a subset of the ranked set of candidate calendar events, each candidate calendar event including a specified start time. | 21. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: receiving a calendar search request to schedule a calendar event including a plurality of constraints including at least one participant and a time of meeting constraint; obtaining information identifying one or more preferences associated with the at least one participant, at least one of the preferences based on the at least one participant's historical calendar activity over a predetermined period of time; searching one or more databases in a calendaring system to obtain a set of candidate calendar events that meet at least a subset of the plurality of constraints; ranking the set of candidate calendar events based on the plurality of constraints and the one or more preferences; and preparing for presentation at least a subset of the ranked set of candidate calendar events, each candidate calendar event including a specified start time. 22. The non-transitory computer readable storage medium of claim 21 , wherein the request to schedule a calendar event is a request to re-schedule an existing calendar event. | 0.857377 |
8,115,089 | 1 | 3 | 1. A singing synthesizing database creation apparatus comprising: an input section to which are input learning waveform data representative of sound waveforms of singing voices of a singing music piece and learning score data representative of a musical score of the singing music piece; a melody component extraction section which analyzes the learning waveform data to identify variation over time in fundamental frequency component presumed to represent a melody in the singing voices and then generates melody component data indicative of the variation over time in fundamental frequency component; and a learning section which generates, in association with a combination of notes constituting the melody of the singing music piece, melody component parameters by performing predetermined machine learning using the learning score data and the melody component data, said melody component parameters defining a melody component model that represents a variation component presumed to be representative of the melody among the variation over time in fundamental frequency component between notes in the singing voices, and which stores, into a singing synthesizing database, the generated melody component parameters and an identifier indicative of the combination of notes to be associated with the melody component parameters. | 1. A singing synthesizing database creation apparatus comprising: an input section to which are input learning waveform data representative of sound waveforms of singing voices of a singing music piece and learning score data representative of a musical score of the singing music piece; a melody component extraction section which analyzes the learning waveform data to identify variation over time in fundamental frequency component presumed to represent a melody in the singing voices and then generates melody component data indicative of the variation over time in fundamental frequency component; and a learning section which generates, in association with a combination of notes constituting the melody of the singing music piece, melody component parameters by performing predetermined machine learning using the learning score data and the melody component data, said melody component parameters defining a melody component model that represents a variation component presumed to be representative of the melody among the variation over time in fundamental frequency component between notes in the singing voices, and which stores, into a singing synthesizing database, the generated melody component parameters and an identifier indicative of the combination of notes to be associated with the melody component parameters. 3. The singing synthesizing database creation apparatus as claimed in claim 1 , wherein said melody component extraction section successively detects pitches of the singing voices, represented by the learning waveform data, in accordance with passage of time, and said melody component extraction section generates the melody component data on the basis of detected time-serial pitch data. | 0.755653 |
8,463,769 | 21 | 23 | 21. A non-transitory computer readable medium embodying a program executable by a computing device, comprising: logic that associates at least one search term with an item in an electronic repository based at least upon behavior of interactions of at least one user with the at least one computing device; logic that determines whether a search of the electronic repository surfaces the item; logic that calculates a plurality of weight values representing a degree of association between the at least one search term and the item; logic that identifies at least one search term associated with a weight value that exceeds a threshold; logic that identifies the at least one search term as a missing search phrase if a search of the electronic repository does not associate the at least one search term with the item; and logic that takes remedial measures if the at least one search does not surface the item by adding the at least one search term to at least one attribute associated with the item in the electronic repository without user intervention. | 21. A non-transitory computer readable medium embodying a program executable by a computing device, comprising: logic that associates at least one search term with an item in an electronic repository based at least upon behavior of interactions of at least one user with the at least one computing device; logic that determines whether a search of the electronic repository surfaces the item; logic that calculates a plurality of weight values representing a degree of association between the at least one search term and the item; logic that identifies at least one search term associated with a weight value that exceeds a threshold; logic that identifies the at least one search term as a missing search phrase if a search of the electronic repository does not associate the at least one search term with the item; and logic that takes remedial measures if the at least one search does not surface the item by adding the at least one search term to at least one attribute associated with the item in the electronic repository without user intervention. 23. The non-transitory computer readable medium of claim 21 , further comprising logic that takes remedial measures if the at least one search term is identified as a potential missing at least one search term. | 0.754673 |
8,762,963 | 11 | 22 | 11. A system for converting a source application to a platform-independent application, the system comprising: at least one computing device; and at least one memory device coupled to the at least one computing device, wherein the at least one memory device contains executable instructions that, if executed on the at least one computing device, result in the implementation of operations comprising: translating source programming language code of the source application to target programming language code of the platform-independent application, wherein the source programming language code comprises Connected Limited Device Configuration (CLDC) code, and wherein the target programming language code of the platform-independent application is in a platform-independent programming language that is independent of one or more device platforms; converting one or more source resources associated with and configured to be used by the source application to one or more target resources configured to be used by the platform-independent application, wherein the source resources are not included within the source programming language code of the source application and the target resources are not included within the target programming language code of the platform-independent application; and providing a configuration of the source application to the platform-independent application, wherein the configuration includes data defining settings of the source application; wherein the translating is implemented by a first series of steps; wherein the converting is implemented by a second series of steps; and wherein the first series of steps for the translating are different from, and independent from, the second series of steps for the converting. | 11. A system for converting a source application to a platform-independent application, the system comprising: at least one computing device; and at least one memory device coupled to the at least one computing device, wherein the at least one memory device contains executable instructions that, if executed on the at least one computing device, result in the implementation of operations comprising: translating source programming language code of the source application to target programming language code of the platform-independent application, wherein the source programming language code comprises Connected Limited Device Configuration (CLDC) code, and wherein the target programming language code of the platform-independent application is in a platform-independent programming language that is independent of one or more device platforms; converting one or more source resources associated with and configured to be used by the source application to one or more target resources configured to be used by the platform-independent application, wherein the source resources are not included within the source programming language code of the source application and the target resources are not included within the target programming language code of the platform-independent application; and providing a configuration of the source application to the platform-independent application, wherein the configuration includes data defining settings of the source application; wherein the translating is implemented by a first series of steps; wherein the converting is implemented by a second series of steps; and wherein the first series of steps for the translating are different from, and independent from, the second series of steps for the converting. 22. The system of claim 11 , wherein the configuration includes one or more of a connection string or a refresh time. | 0.916785 |
7,965,891 | 1 | 4 | 1. A method of distilling information from a hard copy business card to generate a structured electronic file having the distilled information therein, comprising: (a) electronically scanning a platen area of a network citizen, having a business card thereon, to create a bitmap of the scanned platen area; (b) transferring the bitmap of the scanned platen area to a network processor; (c) segmenting the bitmap of the scanned platen area, using the network processor, into a bitmap object, the bitmap object corresponding to the scanned business card; (d) converting, using the network processor, the bitmap object into a block of text; (e) processing, using the network processor, the block of text to generate a structured representation of semantic entities corresponding to the scanned business card; and (f) converting, using the network processor, the structured representation into a structure text file. | 1. A method of distilling information from a hard copy business card to generate a structured electronic file having the distilled information therein, comprising: (a) electronically scanning a platen area of a network citizen, having a business card thereon, to create a bitmap of the scanned platen area; (b) transferring the bitmap of the scanned platen area to a network processor; (c) segmenting the bitmap of the scanned platen area, using the network processor, into a bitmap object, the bitmap object corresponding to the scanned business card; (d) converting, using the network processor, the bitmap object into a block of text; (e) processing, using the network processor, the block of text to generate a structured representation of semantic entities corresponding to the scanned business card; and (f) converting, using the network processor, the structured representation into a structure text file. 4. The method as claimed in claim 1 , wherein the structure text file is structure text file with a vcf extension. | 0.952854 |
7,712,118 | 8 | 9 | 8. A broadcast program retrieval method for retrieving a desired broadcast program among a plurality of broadcast programs, comprising: configuring a user server to receive and store broadcast program information, which includes at least one program retrieval identification code and other information related to said plurality of broadcast programs, wherein the program retrieval identification code is a function of content and a time slot; configuring a data server to receive and store the broadcast program information, wherein the user server that receives the program retrieval codes previously received the broadcast program information, and wherein each program identification code is included in an event information table appended to the broadcast program information, wherein said broadcast program information stored on said data server is identical to said broadcast program information stored on said user server; transmitting from the user server to the data server at least one keyword; searching the broadcast program information in the data server using at least one searching function; transmitting from the data server to the user server only program retrieval identification codes, wherein only a select number of program retrieval identification codes are transmitted, each of the program retrieval identification codes related to said at least one keyword; retrieving a select number of broadcast program information stored in the user server using the select number of program retrieval identification codes received from the data server; reviewing the select number of broadcast program information; and selecting the desired broadcast program from among a select number of broadcast programs corresponding to the reviewed select number of broadcast program information, wherein said broadcast programs broadcast by digital satellite. | 8. A broadcast program retrieval method for retrieving a desired broadcast program among a plurality of broadcast programs, comprising: configuring a user server to receive and store broadcast program information, which includes at least one program retrieval identification code and other information related to said plurality of broadcast programs, wherein the program retrieval identification code is a function of content and a time slot; configuring a data server to receive and store the broadcast program information, wherein the user server that receives the program retrieval codes previously received the broadcast program information, and wherein each program identification code is included in an event information table appended to the broadcast program information, wherein said broadcast program information stored on said data server is identical to said broadcast program information stored on said user server; transmitting from the user server to the data server at least one keyword; searching the broadcast program information in the data server using at least one searching function; transmitting from the data server to the user server only program retrieval identification codes, wherein only a select number of program retrieval identification codes are transmitted, each of the program retrieval identification codes related to said at least one keyword; retrieving a select number of broadcast program information stored in the user server using the select number of program retrieval identification codes received from the data server; reviewing the select number of broadcast program information; and selecting the desired broadcast program from among a select number of broadcast programs corresponding to the reviewed select number of broadcast program information, wherein said broadcast programs broadcast by digital satellite. 9. A broadcast program retrieval method according to claim 8 , wherein each of said at least one program retrieval identification code is assigned a different identification number even when a first broadcast program identified by a first program retrieval identification code is a rebroadcast of a second broadcast program, such that the second program broadcast program is assigned a second program retrieval identification code. | 0.650729 |
9,361,375 | 25 | 30 | 25. A machine-readable tangible and non-transitory medium having information recorded thereon for generating a document, wherein the information, when read by the machine, causes the machine to perform the following: obtaining first information related to one or more queries submitted by a user; obtaining second information related to behavior of the user with respect to one or more documents accessed by the user and identified in response to the one or more queries; identifying a research topic based on the first information; identifying at least one of the one or more documents related to the research topic based on the second information; and estimating an amount of time that a user spends reviewing the at least one of the one or more documents; generating a research document including information associated with the research topic and the at least one document, wherein generating the research document comprises including, based on the estimated time, each document in the one or more documents in either a first set of documents, or a second set of documents, and the research document is provided to the user by providing a display area comprising a link for the user to review information about the second set of documents, and in a separate display area by providing the user access to information about the first set of documents via a plurality of user interface elements. | 25. A machine-readable tangible and non-transitory medium having information recorded thereon for generating a document, wherein the information, when read by the machine, causes the machine to perform the following: obtaining first information related to one or more queries submitted by a user; obtaining second information related to behavior of the user with respect to one or more documents accessed by the user and identified in response to the one or more queries; identifying a research topic based on the first information; identifying at least one of the one or more documents related to the research topic based on the second information; and estimating an amount of time that a user spends reviewing the at least one of the one or more documents; generating a research document including information associated with the research topic and the at least one document, wherein generating the research document comprises including, based on the estimated time, each document in the one or more documents in either a first set of documents, or a second set of documents, and the research document is provided to the user by providing a display area comprising a link for the user to review information about the second set of documents, and in a separate display area by providing the user access to information about the first set of documents via a plurality of user interface elements. 30. The medium of claim 25 , wherein generating a research document comprises including each query in the one or more queries in either a first set of queries deemed related to the research topic or in a second set of queries deemed unrelated to the research topic, and the research document is provided to the user by providing a display area for the user to review the first set of queries and a user interface element for providing the user access to the second set of queries. | 0.726962 |
7,634,409 | 12 | 13 | 12. The system of claim 11 , the acoustic elements including at least an unstressed central vowel and a plurality of phonemic elements associated with the acoustic speech model, wherein the acoustic grammar uses the unstressed central vowel as a linking element between sequential phonemic elements. | 12. The system of claim 11 , the acoustic elements including at least an unstressed central vowel and a plurality of phonemic elements associated with the acoustic speech model, wherein the acoustic grammar uses the unstressed central vowel as a linking element between sequential phonemic elements. 13. The system of claim 12 , the unstressed central vowel including a schwa acoustic element. | 0.962379 |
7,526,476 | 7 | 10 | 7. A method for generating attribute-based selectable search extensions, wherein a processor is provided to carry out the method comprising: receiving a set of search terms; accessing a set of initial search results based on the set of search terms; identifying at least one attribute of at least one result in the set of initial search results, wherein the at least one attribute identifies a type of file associated with the at least one result; and generating a set of attribute-based selectable search extensions associated with the set of initial search results that reflect outlying attributes within the set of initial search results, wherein generating comprises: (1) assigning the at least one attribute a point in attribute space, wherein the attribute space is defined by axes that are each associated with a respective attribute identified within the set of initial search results, and wherein at least one of the axes represents the type of file; (2) comparing the point associated with the at least one attribute of the at least one result in the set of initial results against an average of points, each associated with attributes identified within other results in the set of initial search results, along an axis of the axes within the attribute space to determine a distance from the average of points; (3) comparing the distance against a threshold; and (4) identifying the at least one attribute as one of the outlying attributes based on the comparison. | 7. A method for generating attribute-based selectable search extensions, wherein a processor is provided to carry out the method comprising: receiving a set of search terms; accessing a set of initial search results based on the set of search terms; identifying at least one attribute of at least one result in the set of initial search results, wherein the at least one attribute identifies a type of file associated with the at least one result; and generating a set of attribute-based selectable search extensions associated with the set of initial search results that reflect outlying attributes within the set of initial search results, wherein generating comprises: (1) assigning the at least one attribute a point in attribute space, wherein the attribute space is defined by axes that are each associated with a respective attribute identified within the set of initial search results, and wherein at least one of the axes represents the type of file; (2) comparing the point associated with the at least one attribute of the at least one result in the set of initial results against an average of points, each associated with attributes identified within other results in the set of initial search results, along an axis of the axes within the attribute space to determine a distance from the average of points; (3) comparing the distance against a threshold; and (4) identifying the at least one attribute as one of the outlying attributes based on the comparison. 10. The method according to claim 7 , wherein the set of attribute-based selectable search extensions comprises search extensions based on attributes of at least one of file type, presence of image data, match in result title, quality of match, freshness of match, presence of address data and presence of contact data. | 0.879167 |
4,773,009 | 31 | 32 | 31. A method according to claim 30, further including the step of displaying an interpretive message with the readability output. | 31. A method according to claim 30, further including the step of displaying an interpretive message with the readability output. 32. A method according to claim 31, wherein the readability output includes a linear function of at least one of the measures. | 0.941121 |
5,499,319 | 20 | 21 | 20. The fuzzy logic controller of claim 15 wherein said defuzzifier means comprises means for selecting a clearness distribution from said knowledge-base corresponding to each of said control action fuzzy patterns, and means for utilizing each said control action fuzzy pattern clearness distribution to map said representation of a control action clearness degree to a value for one of said process control signals. | 20. The fuzzy logic controller of claim 15 wherein said defuzzifier means comprises means for selecting a clearness distribution from said knowledge-base corresponding to each of said control action fuzzy patterns, and means for utilizing each said control action fuzzy pattern clearness distribution to map said representation of a control action clearness degree to a value for one of said process control signals. 21. The fuzzy logic controller of claim 20 wherein each clearness distribution has an x-axis representing the range of control action values for the fuzzy pattern which is associated with the control action and which corresponds with said each clearness distribution and a y-axis representing clearness degrees and wherein said means for utilizing each said control action fuzzy pattern clearness distribution to map said representation of a control action clearness degree to a value for one of said control signals comprises means for locating said control action clearness degree on the y-axis of said control action fuzzy pattern clearness distribution and for projecting said control action clearness degree onto the x-axis of said control action fuzzy pattern clearness distribution. | 0.829663 |
8,645,372 | 19 | 22 | 19. A computing system comprising: a memory; a processor; an enhancement level setter module stored in the memory and configured, when executed by the processor, to: determine whether a name of a designated entity is likely to lead to relevancy errors when used in a search by performing a test to determine if the name of the designated entity matches a word that is not an entity, the name of the designated entity is a substring of a different entity's name, the name of the designated entity matches a name of a different entity having a facet that is not shared by the designated entity, or the name of the designated entity matches a name of a different entity with a facet that is shared with the designated entity; and when determined that the name of the designated entity is likely to lead to relevancy errors, determine an enhancement level for an initial query designated to be run against a keyword-based search engine API by performing a test to determine if a name of a designated entity matches a word that is not an entity, the name of the designated entity is a substring of a different entity's name, the name of the designated entity matches a name of a different entity having a facet that is not shared by the designated entity, or the name of the designated entity matches a name of a different entity with a facet that is shared with the designated entity; one or more enhancer modules stored in the memory and configured, when executed by the processor, to receive the determined enhancement level from the enhancement level setter module and produce a query strategy containing one or more subqueries that enhance the initial query using one or more of an entity-specific enhancement and/or a facet-specific enhancement to reduce ambiguity such that more on-topic results will be more likely to be produced; and a result retriever module stored in the memory and configured, when executed by the processor, to: receive the query strategy from the one or more enhancer modules and formulate enhanced subqueries in the syntax of the keyword-based search engine API; run the formulated enhanced subqueries using the keyword-based search engine API until sufficient results are obtained; and return the results. | 19. A computing system comprising: a memory; a processor; an enhancement level setter module stored in the memory and configured, when executed by the processor, to: determine whether a name of a designated entity is likely to lead to relevancy errors when used in a search by performing a test to determine if the name of the designated entity matches a word that is not an entity, the name of the designated entity is a substring of a different entity's name, the name of the designated entity matches a name of a different entity having a facet that is not shared by the designated entity, or the name of the designated entity matches a name of a different entity with a facet that is shared with the designated entity; and when determined that the name of the designated entity is likely to lead to relevancy errors, determine an enhancement level for an initial query designated to be run against a keyword-based search engine API by performing a test to determine if a name of a designated entity matches a word that is not an entity, the name of the designated entity is a substring of a different entity's name, the name of the designated entity matches a name of a different entity having a facet that is not shared by the designated entity, or the name of the designated entity matches a name of a different entity with a facet that is shared with the designated entity; one or more enhancer modules stored in the memory and configured, when executed by the processor, to receive the determined enhancement level from the enhancement level setter module and produce a query strategy containing one or more subqueries that enhance the initial query using one or more of an entity-specific enhancement and/or a facet-specific enhancement to reduce ambiguity such that more on-topic results will be more likely to be produced; and a result retriever module stored in the memory and configured, when executed by the processor, to: receive the query strategy from the one or more enhancer modules and formulate enhanced subqueries in the syntax of the keyword-based search engine API; run the formulated enhanced subqueries using the keyword-based search engine API until sufficient results are obtained; and return the results. 22. The system of claim 19 wherein the keyword-based search engine API is an API for searching one or more of text, images, music, sound, video, objects, web pages. | 0.860307 |
9,460,207 | 12 | 14 | 12. A system comprising: at least one processor; and memory that comprises instructions that, when executed by the at least one processor, cause the at least one processor to generate a computer-readable index, wherein generating the computer-readable index comprises: locating a table in source code of a page, the table comprises an attribute identity of an entity and an attribute value for the attribute identity and the entity, wherein the table is free of an identity of the entity; responsive to locating the table in the source code of the web page, inferring the identity of the entity, wherein inferring the identity of the entity comprises: determining that a title of the page and a header of the page comprise a same keyword; and inferring that the keyword is at least a portion of the identity of the entity based upon the keyword being included in both the title of the page and the header of the page; and responsive to inferring the identity of the entity, in the computer-readable index, indexing the attribute value by the entity identity and the attribute identity. | 12. A system comprising: at least one processor; and memory that comprises instructions that, when executed by the at least one processor, cause the at least one processor to generate a computer-readable index, wherein generating the computer-readable index comprises: locating a table in source code of a page, the table comprises an attribute identity of an entity and an attribute value for the attribute identity and the entity, wherein the table is free of an identity of the entity; responsive to locating the table in the source code of the web page, inferring the identity of the entity, wherein inferring the identity of the entity comprises: determining that a title of the page and a header of the page comprise a same keyword; and inferring that the keyword is at least a portion of the identity of the entity based upon the keyword being included in both the title of the page and the header of the page; and responsive to inferring the identity of the entity, in the computer-readable index, indexing the attribute value by the entity identity and the attribute identity. 14. The system of claim 12 , wherein the page belongs to a domain with other pages, and wherein inferring the identity of the entity further comprises: receiving data indicative of a known schema for pages belonging to the domain; and inferring the identity of the entity based upon the known schema. | 0.763033 |
8,122,011 | 15 | 17 | 15. A computer program product, stored on a non-transitory machine readable storage device, comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: identifying a first group of predicate queries that have preceded a first query; identifying a second group of predicate queries that have preceded a second query; identifying an intersection set size associated with an intersection set of the first group of predicate queries and the second group of predicate queries, the intersection set defining a set of overlapping predicate queries; identifying a union set size associated with a union set of the first group of predicate queries and the second group of predicate queries; and assigning a quotient of the intersection set size over the union set size as a query intersect frequency for the first query and the second query; deriving a query map value based on the intersect frequency; determining whether the query map value is greater than a threshold query map value; and identifying the first query and second query as suggestions for one another based upon determining that the query map value is greater than the threshold query map value. | 15. A computer program product, stored on a non-transitory machine readable storage device, comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: identifying a first group of predicate queries that have preceded a first query; identifying a second group of predicate queries that have preceded a second query; identifying an intersection set size associated with an intersection set of the first group of predicate queries and the second group of predicate queries, the intersection set defining a set of overlapping predicate queries; identifying a union set size associated with a union set of the first group of predicate queries and the second group of predicate queries; and assigning a quotient of the intersection set size over the union set size as a query intersect frequency for the first query and the second query; deriving a query map value based on the intersect frequency; determining whether the query map value is greater than a threshold query map value; and identifying the first query and second query as suggestions for one another based upon determining that the query map value is greater than the threshold query map value. 17. The computer program product of claim 15 , wherein the query map value comprises a count of a number of intersecting predicate queries between the first group of predicate queries and the second group of predicate queries. | 0.918996 |
8,117,191 | 13 | 20 | 13. A method for processing an XQuery of a user to retrieve XML data from an XML database using an XML database management system (XDMBS), the XML database comprising XML documents, each XML document comprising one or more structural elements and adhering to an XML schema, wherein at least one of the structural elements is protected against access of a user, the XDBMS, the method comprising: processing, via an optimizer under control of at least one computer, an XQuery of the user comprising one or more XQuery expressions; generating an optimized XQuery execution plan; and executing the optimized XQuery execution plan to retrieve XML data from the XML database, wherein the optimized XQuery execution plan is generated so that all XQuery expressions relating to one or more of the structural elements that are protected against access of the user are ignored by the optimizer. | 13. A method for processing an XQuery of a user to retrieve XML data from an XML database using an XML database management system (XDMBS), the XML database comprising XML documents, each XML document comprising one or more structural elements and adhering to an XML schema, wherein at least one of the structural elements is protected against access of a user, the XDBMS, the method comprising: processing, via an optimizer under control of at least one computer, an XQuery of the user comprising one or more XQuery expressions; generating an optimized XQuery execution plan; and executing the optimized XQuery execution plan to retrieve XML data from the XML database, wherein the optimized XQuery execution plan is generated so that all XQuery expressions relating to one or more of the structural elements that are protected against access of the user are ignored by the optimizer. 20. The method of claim 13 , further comprising: generating an access privilege index from the structure-based and/or instance-based access privileges, and scanning the access privilege index. | 0.7 |
4,566,078 | 1 | 2 | 1. A method of providing a distributed, interactive data processing system with concurrent multi-lingual use by a plurality of users, said data processing system including a message composition service, said method comprising the steps of: establishing a message model data collection by storing message models, said message models being stored with a message identifier primary key that is common for all usage and a secondary key that is a national language index, establishing for each user who signs onto said system a national language index corresponding to said secondary key, requesting said message composition service to compose a message for use by an interactive program run on said system, said message being identified by said primary key for the specific message requested and said secondary key established for the user for which the message is intended, retrieving from said message model data collection message models using said primary and secondary keys in response to a request to compose a message, composing said message from said message models retrieved from said message model data collection, and storing the composed message so that it can be used by said interactive program to communicate the message to the user. | 1. A method of providing a distributed, interactive data processing system with concurrent multi-lingual use by a plurality of users, said data processing system including a message composition service, said method comprising the steps of: establishing a message model data collection by storing message models, said message models being stored with a message identifier primary key that is common for all usage and a secondary key that is a national language index, establishing for each user who signs onto said system a national language index corresponding to said secondary key, requesting said message composition service to compose a message for use by an interactive program run on said system, said message being identified by said primary key for the specific message requested and said secondary key established for the user for which the message is intended, retrieving from said message model data collection message models using said primary and secondary keys in response to a request to compose a message, composing said message from said message models retrieved from said message model data collection, and storing the composed message so that it can be used by said interactive program to communicate the message to the user. 2. The method recited in claim 1 further comprising the steps of: assigning values to substitutable variables in said message at the time said message composition service is requested to compose said message, and replacing any substitutable variable in the message models retrieved from said message model data base with current values of the variables at the time said message is composed. | 0.880368 |
8,219,615 | 1 | 23 | 1. A computer program product embodied on a non-transitory computer readable medium, comprising: computer code for causing display of, utilizing a website, a stock-related field; computer code for allowing receipt of a plurality of characters of text as a user is typing the plurality of characters of text utilizing the stock-related field; computer code for dynamically determining, after the user types each of the plurality of characters of text, whether at least a portion of characters typed so far match one or more text strings in at least one of a plurality of n-tuples including at least two text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; computer code for indicating to the user that a match has been found, utilizing the website, if it is determined that the at least portion of characters typed so far match the one or more text strings in the at least one of the plurality of n-tuples; computer code for causing display of, utilizing the website, a plurality of message summaries, wherein the plurality of message summaries comprise first information associated with a first message of a plurality of first messages and second information associated with a second message of a plurality of second messages associated with at least one online forum; computer code for causing display of, utilizing the website, a first set of representations representing a first set of hyperlinks, where the first set of representations are each representative of a predetermined category of content; computer code for allowing receipt of first input initiated by the user indicating a selection of one of the first set of representations; computer code for causing display of a second set of representations representing a second set of hyperlinks, utilizing the website, in response to receiving the first input, where the second set of representations are each representative of at least one of a plurality of subcategories of content associated with the predetermined category and are displayed in a menu format; computer code for allowing receipt of second input initiated by the user indicating a selection of one of the second set of representations; and computer code for causing display of destination content associated with the selected one of the second set of representations, in response to receiving the second input; wherein the computer program product is operable such that a new message is capable of being generated by the user utilizing the website for posting in association with at least one of the plurality of first messages. | 1. A computer program product embodied on a non-transitory computer readable medium, comprising: computer code for causing display of, utilizing a website, a stock-related field; computer code for allowing receipt of a plurality of characters of text as a user is typing the plurality of characters of text utilizing the stock-related field; computer code for dynamically determining, after the user types each of the plurality of characters of text, whether at least a portion of characters typed so far match one or more text strings in at least one of a plurality of n-tuples including at least two text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; computer code for indicating to the user that a match has been found, utilizing the website, if it is determined that the at least portion of characters typed so far match the one or more text strings in the at least one of the plurality of n-tuples; computer code for causing display of, utilizing the website, a plurality of message summaries, wherein the plurality of message summaries comprise first information associated with a first message of a plurality of first messages and second information associated with a second message of a plurality of second messages associated with at least one online forum; computer code for causing display of, utilizing the website, a first set of representations representing a first set of hyperlinks, where the first set of representations are each representative of a predetermined category of content; computer code for allowing receipt of first input initiated by the user indicating a selection of one of the first set of representations; computer code for causing display of a second set of representations representing a second set of hyperlinks, utilizing the website, in response to receiving the first input, where the second set of representations are each representative of at least one of a plurality of subcategories of content associated with the predetermined category and are displayed in a menu format; computer code for allowing receipt of second input initiated by the user indicating a selection of one of the second set of representations; and computer code for causing display of destination content associated with the selected one of the second set of representations, in response to receiving the second input; wherein the computer program product is operable such that a new message is capable of being generated by the user utilizing the website for posting in association with at least one of the plurality of first messages. 23. The computer program product of claim 1 , wherein the computer program product is operable such that the first input includes hovering a cursor and the first set of representations are associated with separate hyperlinks associated with separate web pages and are displayed in connection with an initial web page associated with the website that includes the second set of representations preloaded and initially hidden, and later displayed in response to receiving the first input initiated by the user. | 0.804163 |
9,519,462 | 15 | 16 | 15. The method of claim 14 , wherein the object model is a customized object model. | 15. The method of claim 14 , wherein the object model is a customized object model. 16. The method of claim 15 , wherein the automatically forming of each reread portion of the dynamic COBOL construct subset as a portion of the object instance is based on the customized object model. | 0.954296 |
8,181,163 | 1 | 10 | 1. At a computer system, a method for synthesizing one or more code fragments in a software routine using one or more known inputs and corresponding expected outputs for portions of the software routine, the method comprising: an act of providing a software routine with one or more known inputs and corresponding one or more expected outputs for the software routine; an act of inferring software routine instructions based on the known inputs and corresponding expected outputs; and an act of synthesizing a correctly functioning code fragment based on the inferred instructions for use in the software routine. | 1. At a computer system, a method for synthesizing one or more code fragments in a software routine using one or more known inputs and corresponding expected outputs for portions of the software routine, the method comprising: an act of providing a software routine with one or more known inputs and corresponding one or more expected outputs for the software routine; an act of inferring software routine instructions based on the known inputs and corresponding expected outputs; and an act of synthesizing a correctly functioning code fragment based on the inferred instructions for use in the software routine. 10. The method of claim 1 , wherein the known inputs and expected outputs are provided by a computer user. | 0.896484 |
6,122,661 | 31 | 36 | 31. A method according to claim 19, wherein the computer display information comprises one or more data fields. | 31. A method according to claim 19, wherein the computer display information comprises one or more data fields. 36. A method according to claim 31, further comprising: converting the one or more data fields into one or more function key fields within the markup language document using a translator within the host extension of the server application framework of the server computer. | 0.933071 |
5,475,738 | 10 | 11 | 10. A messaging system interface node for use in storing a voice message in a voice messaging system, the voice messaging system having a human operator interface associated therewith, the voice message based on a text message from a text messaging system, the text messaging system comprising one or more addressable nodes including the messaging system interface node, the text messaging system and the voice messaging system coupled by a communications network, the messaging system interface node comprising: means for receiving the text message from the text messaging system based on an address of the messaging system interface node; means for generating a voice message responsive to the text message; means for generating interface signals and communicating said interface signals over the communications network to access the voice messaging system, the interface signals for simulating human operation of the voice messaging system in accordance with the human operator interface associated therewith; and means for communicating the voice message over the communications network to the voice messaging system for storage. | 10. A messaging system interface node for use in storing a voice message in a voice messaging system, the voice messaging system having a human operator interface associated therewith, the voice message based on a text message from a text messaging system, the text messaging system comprising one or more addressable nodes including the messaging system interface node, the text messaging system and the voice messaging system coupled by a communications network, the messaging system interface node comprising: means for receiving the text message from the text messaging system based on an address of the messaging system interface node; means for generating a voice message responsive to the text message; means for generating interface signals and communicating said interface signals over the communications network to access the voice messaging system, the interface signals for simulating human operation of the voice messaging system in accordance with the human operator interface associated therewith; and means for communicating the voice message over the communications network to the voice messaging system for storage. 11. The messaging system interface node according to claim 10 wherein the communications network comprises a telephone network. | 0.793831 |
10,109,274 | 10 | 11 | 10. A recognition system device comprising: processing circuitry coupled to a memory, the processing circuitry being configured to: receive a first model that converts subwords serving as elements of words into the words, the subwords being one or more phonemes or one or more syllables; produce, on the basis of the first model, a first finite state transducer that includes a first path having transitions converting one or more first subwords into one or more first words and a second path having cyclic paths to which one or more second subwords are assigned and a transition to which a class is assigned, a first state of the second path being the same as a first state of the first path; produce a third finite state transducer by composing the first finite state transducer with a second finite state transducer produced on the basis of a language model that includes the class; and produce a fifth finite state transducer by composing a seventh finite state transducer with a fourth finite state transducer, the fourth finite state transducer being produced on the basis of a second model and including a third path, the second model including an additional word, one or more subwords and the class that correspond to the additional word, the seventh finite state transducer being produced by composing the third finite state transducer with a sixth finite state transducer that includes a transition provided with an input symbol and an output symbol to both of which the class is assigned and a transition provided with the input and output symbols to both of which at least one of starting information indicating a start of the cyclic paths and ending information indicating an end of the cyclic paths is assigned; and a searcher configured to recognize a second word corresponding to an input speech by using the fifth finite state transducer, wherein the searcher outputs the second word other than the additional word, without performing conversion by the fourth finite state transducer, and outputs the additional word that is an output symbol on a fourth path of the fifth finite state transducer, the fourth path is generated by composing a fifth path of the seventh finite state transducer with the third path, one of the output symbols on the third path is the additional word, an input symbol string on the third path includes one or more third subwords and the class, and corresponds to an output symbol string of the fifth path, and the class which appears in the input symbol string on the third path and appears in the output symbol string of the fifth path controls an appearance location of the additional word. | 10. A recognition system device comprising: processing circuitry coupled to a memory, the processing circuitry being configured to: receive a first model that converts subwords serving as elements of words into the words, the subwords being one or more phonemes or one or more syllables; produce, on the basis of the first model, a first finite state transducer that includes a first path having transitions converting one or more first subwords into one or more first words and a second path having cyclic paths to which one or more second subwords are assigned and a transition to which a class is assigned, a first state of the second path being the same as a first state of the first path; produce a third finite state transducer by composing the first finite state transducer with a second finite state transducer produced on the basis of a language model that includes the class; and produce a fifth finite state transducer by composing a seventh finite state transducer with a fourth finite state transducer, the fourth finite state transducer being produced on the basis of a second model and including a third path, the second model including an additional word, one or more subwords and the class that correspond to the additional word, the seventh finite state transducer being produced by composing the third finite state transducer with a sixth finite state transducer that includes a transition provided with an input symbol and an output symbol to both of which the class is assigned and a transition provided with the input and output symbols to both of which at least one of starting information indicating a start of the cyclic paths and ending information indicating an end of the cyclic paths is assigned; and a searcher configured to recognize a second word corresponding to an input speech by using the fifth finite state transducer, wherein the searcher outputs the second word other than the additional word, without performing conversion by the fourth finite state transducer, and outputs the additional word that is an output symbol on a fourth path of the fifth finite state transducer, the fourth path is generated by composing a fifth path of the seventh finite state transducer with the third path, one of the output symbols on the third path is the additional word, an input symbol string on the third path includes one or more third subwords and the class, and corresponds to an output symbol string of the fifth path, and the class which appears in the input symbol string on the third path and appears in the output symbol string of the fifth path controls an appearance location of the additional word. 11. The recognition system according to claim 10 , wherein the processing circuitry produces the fifth finite state transducer while the searcher performs the search processing. | 0.63278 |
7,752,082 | 17 | 24 | 17. An apparatus comprising: means for verifying that a subject-owner is authorized to dominate a plurality of reviews of a reviewed subject; means for accepting input from said subject-owner related to one or more functions to be applied to a review-provider server; means for controlling enablement of said one or more functions responsive to input; and means for storing said input. | 17. An apparatus comprising: means for verifying that a subject-owner is authorized to dominate a plurality of reviews of a reviewed subject; means for accepting input from said subject-owner related to one or more functions to be applied to a review-provider server; means for controlling enablement of said one or more functions responsive to input; and means for storing said input. 24. The apparatus as claimed in claim 17 , wherein said plurality of reviews includes a review and wherein said one or more functions enables one or more operations selected from a group consisting of marking said review as an editorial review, marking said review as written by an expert user-author, marking said review as authorized by said subject-owner, marking said review responsive to whether an identity of a user-author of said review has been verified, marking said review as certified by a third-party certification agency, formatting said review, assigning an access right for said review to a requesting user, and enabling said requesting user to supplement said review. | 0.647059 |
7,634,397 | 1 | 9 | 1. A computer program product operative to provide multi-lingual support, comprising a computer-usable storage medium having embodied therein computer-readable program codes executable by a computer system for identifying a first set of objects in response to the computer system receiving an indication of a first language to be used for a first session, wherein each object in the first set is associated with a language independent representation, determining whether a store comprising language dependent representations of at least some of the objects of the first set for each of a plurality of languages includes language dependent representations corresponding to the first language for at least some of the objects of the first set; from the store, retrieving first language dependent representations of the first set of objects for the first language in response to determining that the store includes language dependent representations corresponding to the first language for at least some of the objects of the first set, wherein the retrieving comprises accessing a mapping table, and the mapping table comprises language dependent representations; building a translation table in response to the retrieving, wherein the translation table comprises a set of language dependent representations, the set of language dependent representations comprises the retrieved first language dependent representations, the set language dependent representations comprises all language dependent representations contained in the translation table, and the set of language dependent representations is a subset of the language dependent representations contained in the mapping table; and without modifying the first set of objects, rendering output reports provided for the first session, wherein the rendering comprises using some or all of the retrieved first language dependent representations by accessing the translation table. | 1. A computer program product operative to provide multi-lingual support, comprising a computer-usable storage medium having embodied therein computer-readable program codes executable by a computer system for identifying a first set of objects in response to the computer system receiving an indication of a first language to be used for a first session, wherein each object in the first set is associated with a language independent representation, determining whether a store comprising language dependent representations of at least some of the objects of the first set for each of a plurality of languages includes language dependent representations corresponding to the first language for at least some of the objects of the first set; from the store, retrieving first language dependent representations of the first set of objects for the first language in response to determining that the store includes language dependent representations corresponding to the first language for at least some of the objects of the first set, wherein the retrieving comprises accessing a mapping table, and the mapping table comprises language dependent representations; building a translation table in response to the retrieving, wherein the translation table comprises a set of language dependent representations, the set of language dependent representations comprises the retrieved first language dependent representations, the set language dependent representations comprises all language dependent representations contained in the translation table, and the set of language dependent representations is a subset of the language dependent representations contained in the mapping table; and without modifying the first set of objects, rendering output reports provided for the first session, wherein the rendering comprises using some or all of the retrieved first language dependent representations by accessing the translation table. 9. The computer program product of claim 1 , wherein the computer-usable storage medium is further embodied with computer-readable program codes for binding the language independent representation for each object to the corresponding first language dependent representation for the object. | 0.694503 |
7,574,428 | 1 | 7 | 1. A computer-implemented method for determining a requested map location, comprising: providing a database holding a plurality of map objects having respective descriptors and loci; accepting a search query comprising one or more query terms that describe the requested map location; identifying in the database two or more matched map objects such that the respective descriptors of the matched map objects each match at least one of the query terms; rendering the matched map objects onto a common grid using the loci; identifying grid cells overlapped by at least one of the rendered map objects; assigning respective scores to the identified grid cells based on a number of the matched map objects that overlap each of the identified grid cells; and determining the requested map location responsively to the scores. | 1. A computer-implemented method for determining a requested map location, comprising: providing a database holding a plurality of map objects having respective descriptors and loci; accepting a search query comprising one or more query terms that describe the requested map location; identifying in the database two or more matched map objects such that the respective descriptors of the matched map objects each match at least one of the query terms; rendering the matched map objects onto a common grid using the loci; identifying grid cells overlapped by at least one of the rendered map objects; assigning respective scores to the identified grid cells based on a number of the matched map objects that overlap each of the identified grid cells; and determining the requested map location responsively to the scores. 7. The method according to claim 1 , wherein accepting the search query comprises accepting free text input comprising the one or more query terms. | 0.851515 |
9,286,289 | 2 | 3 | 2. The computer system of claim 1 , wherein selecting the first subset of edges of the lexicon network comprises including a target edge into the first subset of edges according to a direction of the target edge. | 2. The computer system of claim 1 , wherein selecting the first subset of edges of the lexicon network comprises including a target edge into the first subset of edges according to a direction of the target edge. 3. The computer system of claim 2 , wherein the second node is assigned to a second level of the plurality of levels, and wherein assigning the first node comprises: when the first node points to the second node, selecting the first level so that the first level precedes the second level in the ordered sequence; and when the second node points to the first node, selecting the first level so that the second level precedes the first level in the ordered sequence. | 0.899481 |
9,515,979 | 1 | 7 | 1. A system for providing a personalized network based dialogue, comprising: a data store; a dialog system coupled to the data store and a network, the dialog system comprising a dialog computer comprising a processor and a memory storing computer program code, the dialog computer configured to: provide a user interface to allow a first user to specify a second user to participate in an automated dialog, specific response option, and a maximum time period for responding; access the data store to determine an address for the second user; execute a first instruction associated with the dialog to send a first communication to the second user from a server via a first communications channel, the first communication containing the specific response option; determine if a first event has occurred in conjunction with the second user, wherein the first event comprises a response by the second user according to the specific response option within the maximum time period for responding; assign a value to a variable associated with the first event based on the determination; branch the dialog based on the value of the variable associated with the first event, wherein: in a first branch, the dialog system is configured to execute a second instruction associated with the dialog to send a second communication to the second user using a second communications channel, the second communication containing the specific response option; in a second branch, the dialog system is further configured to execute a third instruction associated with the dialog. | 1. A system for providing a personalized network based dialogue, comprising: a data store; a dialog system coupled to the data store and a network, the dialog system comprising a dialog computer comprising a processor and a memory storing computer program code, the dialog computer configured to: provide a user interface to allow a first user to specify a second user to participate in an automated dialog, specific response option, and a maximum time period for responding; access the data store to determine an address for the second user; execute a first instruction associated with the dialog to send a first communication to the second user from a server via a first communications channel, the first communication containing the specific response option; determine if a first event has occurred in conjunction with the second user, wherein the first event comprises a response by the second user according to the specific response option within the maximum time period for responding; assign a value to a variable associated with the first event based on the determination; branch the dialog based on the value of the variable associated with the first event, wherein: in a first branch, the dialog system is configured to execute a second instruction associated with the dialog to send a second communication to the second user using a second communications channel, the second communication containing the specific response option; in a second branch, the dialog system is further configured to execute a third instruction associated with the dialog. 7. The system of claim 1 , wherein the user interface presents a set of function shapes corresponding to functions of the dialog and allows the first user to interconnect the function shapes to define a flow of the dialog. | 0.502242 |
8,365,092 | 1 | 3 | 1. A method for loading media, the method comprising: providing a maximum number of layers per page of a collage document, the collage document including at least one page having a plurality of layers, each layer being associated with a media object, wherein the layers of a page form a non-overlapping sequential series of discrete media objects; loading a first page of the collage document to a client device; creating a list of layers of the loaded page, each layer indexed by at least a position in the collage document; filtering the list of layers based on at least the position in the collage document and a visual window of a user interface to thereby display visible layers of the loaded page within the visual window, wherein the user interface is configured to enable the discrete media objects to be moved into and out of the visual window while still maintaining the discrete media objects as part of the collage document; and automatically populating user selected discrete media objects into a user selected style for the collage document from a plurality of predefined styles. | 1. A method for loading media, the method comprising: providing a maximum number of layers per page of a collage document, the collage document including at least one page having a plurality of layers, each layer being associated with a media object, wherein the layers of a page form a non-overlapping sequential series of discrete media objects; loading a first page of the collage document to a client device; creating a list of layers of the loaded page, each layer indexed by at least a position in the collage document; filtering the list of layers based on at least the position in the collage document and a visual window of a user interface to thereby display visible layers of the loaded page within the visual window, wherein the user interface is configured to enable the discrete media objects to be moved into and out of the visual window while still maintaining the discrete media objects as part of the collage document; and automatically populating user selected discrete media objects into a user selected style for the collage document from a plurality of predefined styles. 3. The method of claim 1 , wherein each layer includes a layer-specific attribute selected from the group consisting of the position in the collage document, scale, visual bounds, and an associated annotation. | 0.718329 |
9,087,299 | 4 | 5 | 4. The medium of claim 1 , wherein the program causes the processor to: consolidate the sets of configuration data associated with a third hierarchical level to identify connections at the third hierarchical level, and after the connectivity graph has been modified to include the identified connections at the second hierarchical: for each identified connection at the third hierarchical level: determine whether the identified connection at the third hierarchical level is consistent with the connectivity graph, and if consistent, further modify the connectivity graph to include the identified connection at the third hierarchical level. | 4. The medium of claim 1 , wherein the program causes the processor to: consolidate the sets of configuration data associated with a third hierarchical level to identify connections at the third hierarchical level, and after the connectivity graph has been modified to include the identified connections at the second hierarchical: for each identified connection at the third hierarchical level: determine whether the identified connection at the third hierarchical level is consistent with the connectivity graph, and if consistent, further modify the connectivity graph to include the identified connection at the third hierarchical level. 5. The medium of claim 4 , wherein the program causes the processor to infer an additional connection at the first hierarchical level to enable the identified connection at the third hierarchical level, and modify the connectivity graph by including the inferred additional connection. | 0.908183 |
9,092,400 | 1 | 6 | 1. A user terminal, comprising: a processor; a messaging system configured to receive messages, each message being of a type selected from the list of: an email, an instant message, a short message service (SMS) message, and a multimedia service (MMS) message; a contact identification system configured to identify language in the text of a message that matches a contact name in a contact storage system; and a link conversion system configured to convert each respective identified instance of language into a link that, when actuated, initiates an action relating to the contact name that matched the respective identified instance of language, wherein at least one of the links is configured to cause a list of selectable actions for the matched contact name to be displayed when actuated. | 1. A user terminal, comprising: a processor; a messaging system configured to receive messages, each message being of a type selected from the list of: an email, an instant message, a short message service (SMS) message, and a multimedia service (MMS) message; a contact identification system configured to identify language in the text of a message that matches a contact name in a contact storage system; and a link conversion system configured to convert each respective identified instance of language into a link that, when actuated, initiates an action relating to the contact name that matched the respective identified instance of language, wherein at least one of the links is configured to cause a list of selectable actions for the matched contact name to be displayed when actuated. 6. The user terminal of claim 1 wherein the contact identification system is configured to identify language that matches contact names using fuzzy logic. | 0.895522 |
8,321,224 | 15 | 20 | 15. A computer program product comprising computer readable instructions embodied on a non-transitory computer readable medium and configured, when executed on one or more computer processors, to facilitate text-to-speech conversion of a text in a first language having sections in at least one second language by: converting the second language sections into phonemes; and processing similarity tests configured to perform category-to-category comparisons of respective vector representatives of phonetic categories of a set of phonemes of the second language and respective vector representatives of phonetic categories of a set of candidate mapping phonemes of the first language, the similarity tests being independent of the first and second languages. | 15. A computer program product comprising computer readable instructions embodied on a non-transitory computer readable medium and configured, when executed on one or more computer processors, to facilitate text-to-speech conversion of a text in a first language having sections in at least one second language by: converting the second language sections into phonemes; and processing similarity tests configured to perform category-to-category comparisons of respective vector representatives of phonetic categories of a set of phonemes of the second language and respective vector representatives of phonetic categories of a set of candidate mapping phonemes of the first language, the similarity tests being independent of the first and second languages. 20. The computer program product of claim 15 , wherein the computer readable instructions are further configured, when executed on one or more processors, to: use results of the similarity tests to map at least part of the second language phonemes to sets of phonemes of the first language by: assigning respective scores to results of the similarity tests; and mapping one or more of the second language phonemes to a set of mapping phonemes of the first language, the set of mapping phonemes being selected from the candidate mapping phonemes as a function of the scores; and include the first language sets of phonemes resulting from the mapping in a stream of phonemes of the first language representative of the text to produce a resulting stream of phonemes that are used to generate a speech signal. | 0.50062 |
9,153,231 | 1 | 2 | 1. A method of updating speech recognition neural networks, the method comprising: receiving a first audio signal comprising a first speech utterance; performing speech recognition on the first audio signal based at least in part on an acoustic model neural network to obtain a lattice of speech recognition results, wherein the lattice comprises a first path associated with a first score a second path associate with a second score; updating first weights of the acoustic model neural network substantially in real time, wherein updating the first weights comprises performing a first update using information associated with the first path and performing a second update using information associated with the second path; receiving a second audio signal comprising a second speech utterance; and performing speech recognition on the second audio signal based at least in part on the acoustic model neural network and the updated first weights. | 1. A method of updating speech recognition neural networks, the method comprising: receiving a first audio signal comprising a first speech utterance; performing speech recognition on the first audio signal based at least in part on an acoustic model neural network to obtain a lattice of speech recognition results, wherein the lattice comprises a first path associated with a first score a second path associate with a second score; updating first weights of the acoustic model neural network substantially in real time, wherein updating the first weights comprises performing a first update using information associated with the first path and performing a second update using information associated with the second path; receiving a second audio signal comprising a second speech utterance; and performing speech recognition on the second audio signal based at least in part on the acoustic model neural network and the updated first weights. 2. The method of claim 1 wherein performing speech recognition on the first audio signal is further based at least in part on a language model neural network; the method further comprising updating second weights of the language model neural network substantially in real time, wherein updating the second weights comprises performing a third update using information associated with the first path and performing a fourth update using information associated with the second path; and wherein performing speech recognition on the second audio signal is further based at least in part on the language model neural network and the updated weights of the language model neural network. | 0.500732 |
9,734,138 | 1 | 9 | 1. A computer implemented method of tagging utterances with Named Entity Recognition (“NER”) labels using an unmanaged crowd, the method being implemented in an end user device having one or more physical processors programmed with computer program instructions that, when executed by the one or more physical processors, cause the end user device to perform the method, the method comprising: obtaining, by the computer system, a plurality of utterances relating to a domain, the domain being associated with a plurality of entities, each entity relating to a category of information in the domain; generating, by the computer system, a first annotation job configured to request that at least a first portion of the utterance be assigned to one of a first set of entities, from among the plurality of entities, wherein a number of the first set of entities does not exceed a maximum number such that cognitive load imposed on a user to whom the first annotation job is provided is controlled; generating, by the computer system, a second annotation job configured to request that at least a second portion of the utterance be assigned to one of a second set of entities, from among the plurality of entities, wherein: a number of the second set of entities does not exceed the maximum number such that cognitive load imposed on a user to whom the second annotation job is provided is controlled, the first portion and the second portion are the same or different and the first set of entities is different than the second set of entities, and the user to whom the first annotation job is provided is the same or different from the user to whom the second annotation job is provided; causing, by the computer system, the first annotation job and the second annotation job to be deployed to the unmanaged crowd; and receiving, by the computer system, a plurality of annotations provided by the unmanaged crowd, the plurality of annotations comprising a first annotation relating to the first annotation job and a second annotation relating to the second annotation job. | 1. A computer implemented method of tagging utterances with Named Entity Recognition (“NER”) labels using an unmanaged crowd, the method being implemented in an end user device having one or more physical processors programmed with computer program instructions that, when executed by the one or more physical processors, cause the end user device to perform the method, the method comprising: obtaining, by the computer system, a plurality of utterances relating to a domain, the domain being associated with a plurality of entities, each entity relating to a category of information in the domain; generating, by the computer system, a first annotation job configured to request that at least a first portion of the utterance be assigned to one of a first set of entities, from among the plurality of entities, wherein a number of the first set of entities does not exceed a maximum number such that cognitive load imposed on a user to whom the first annotation job is provided is controlled; generating, by the computer system, a second annotation job configured to request that at least a second portion of the utterance be assigned to one of a second set of entities, from among the plurality of entities, wherein: a number of the second set of entities does not exceed the maximum number such that cognitive load imposed on a user to whom the second annotation job is provided is controlled, the first portion and the second portion are the same or different and the first set of entities is different than the second set of entities, and the user to whom the first annotation job is provided is the same or different from the user to whom the second annotation job is provided; causing, by the computer system, the first annotation job and the second annotation job to be deployed to the unmanaged crowd; and receiving, by the computer system, a plurality of annotations provided by the unmanaged crowd, the plurality of annotations comprising a first annotation relating to the first annotation job and a second annotation relating to the second annotation job. 9. The method of claim 1 , the method further comprising: generating, by the computer system, a plurality of domain classification jobs configured to request that an utterance be classified according to a domain; causing, by the computer system, the plurality of domain classification jobs to be provided to the unmanaged crowd; and receiving, by the computer system, results of the plurality of domain classification jobs, wherein the plurality of utterances are determined to be related to the domain based on the results of the plurality of domain classification jobs. | 0.500874 |
9,298,869 | 1 | 17 | 1. A method for showing hierarchical structure for a given power intent described in a power intent description language with a design described in a hardware design description language, the method comprising the steps of: retrieving, by utilizing a processing circuit of an electronic device, hardware design description contents written in the hardware design description language from a hardware design description file, and retrieving, by utilizing the processing circuit, power intent description contents written in the power intent description language from a power intent description file; creating, by utilizing the processing circuit, a data structure of a power domain hierarchy according to the power intent description contents and the hardware design description contents respectively retrieved from the power intent description file and the hardware design description file; creating, by utilizing the processing circuit, the power domain hierarchy for coverage annotation, debugging, or design review according to the data structure of the power domain hierarchy; and controlling, by utilizing the processing circuit, a display module to display the power domain hierarchy associated with the power intent description contents and the hardware design description contents respectively retrieved from the power intent description file and the hardware design description file, wherein the power domain hierarchy comprises at least one power domain. | 1. A method for showing hierarchical structure for a given power intent described in a power intent description language with a design described in a hardware design description language, the method comprising the steps of: retrieving, by utilizing a processing circuit of an electronic device, hardware design description contents written in the hardware design description language from a hardware design description file, and retrieving, by utilizing the processing circuit, power intent description contents written in the power intent description language from a power intent description file; creating, by utilizing the processing circuit, a data structure of a power domain hierarchy according to the power intent description contents and the hardware design description contents respectively retrieved from the power intent description file and the hardware design description file; creating, by utilizing the processing circuit, the power domain hierarchy for coverage annotation, debugging, or design review according to the data structure of the power domain hierarchy; and controlling, by utilizing the processing circuit, a display module to display the power domain hierarchy associated with the power intent description contents and the hardware design description contents respectively retrieved from the power intent description file and the hardware design description file, wherein the power domain hierarchy comprises at least one power domain. 17. The method of claim 1 , wherein the step of creating the data structure of the power domain hierarchy according to the power intent description contents and the hardware design description contents respectively retrieved from the power intent description file and the hardware design description file further comprises: based on the hardware design description contents retrieved from the hardware design description file, determining a plurality of design instances in the data structure of the power domain hierarchy. | 0.500954 |
8,094,122 | 1 | 7 | 1. A non-transitory computer readable medium having computer readable program code embodied therein for causing a computer to control the position of a visual pointer using an eye tracking apparatus by: receiving input from the eye tracking apparatus; moving a visual pointer from a first location to a second location that corresponds to a user's gaze position based on the input received from the eye tracking apparatus; providing a visual indicator between the first location and the second location; automatically changing the visual indicator to a reading guide in response to the eye tracking apparatus recognizing a user's gaze position pattern as a read mode, where the reading guide is located in a margin at the beginning of a line of text that is read; repositioning the reading guide in response to the eye tracking apparatus determining that the user approaches the end of a line of text; and in response to the eye tracking apparatus determining that the user's gaze positions are one of slowing down or stopping on a link in the text, exiting the read mode and changing the visual indicator to a pointer for a pointing device to enable the user to click on the link. | 1. A non-transitory computer readable medium having computer readable program code embodied therein for causing a computer to control the position of a visual pointer using an eye tracking apparatus by: receiving input from the eye tracking apparatus; moving a visual pointer from a first location to a second location that corresponds to a user's gaze position based on the input received from the eye tracking apparatus; providing a visual indicator between the first location and the second location; automatically changing the visual indicator to a reading guide in response to the eye tracking apparatus recognizing a user's gaze position pattern as a read mode, where the reading guide is located in a margin at the beginning of a line of text that is read; repositioning the reading guide in response to the eye tracking apparatus determining that the user approaches the end of a line of text; and in response to the eye tracking apparatus determining that the user's gaze positions are one of slowing down or stopping on a link in the text, exiting the read mode and changing the visual indicator to a pointer for a pointing device to enable the user to click on the link. 7. A computer readable medium as in claim 1 , wherein the visual indicator comprises a graphic animation of a spatial relationship between the first location and the second location of the visual pointer. | 0.685185 |
9,137,401 | 9 | 10 | 9. The non-transitory computer-readable recording medium according to claim 5 , the display program further comprising tenth program code that causes, when displaying the second language screen on the touch panel, the computer to gray out one or more items on the first language selection screen other than the specified item. | 9. The non-transitory computer-readable recording medium according to claim 5 , the display program further comprising tenth program code that causes, when displaying the second language screen on the touch panel, the computer to gray out one or more items on the first language selection screen other than the specified item. 10. The non-transitory computer-readable recording medium according to claim 9 , the display program further comprising eleventh program code that causes, when displaying at least one of the first language selection screen and the second language selection screen on the touch panel, the computer to gray out a screen that had been displayed on the touch panel before the first language selection screen has been displayed. | 0.91 |
8,103,669 | 16 | 19 | 16. The method of claim 12 , wherein the defining of the synonymy rules includes generating, for at least one of the extracted candidate synonymy pairs, a context restriction, the synonymy rule comprising the candidate pair and the context restriction. | 16. The method of claim 12 , wherein the defining of the synonymy rules includes generating, for at least one of the extracted candidate synonymy pairs, a context restriction, the synonymy rule comprising the candidate pair and the context restriction. 19. The method of claim 16 , further comprising presenting candidate contexts and candidate pairs to an editor for definition of the synonymy rules. | 0.943939 |
7,778,632 | 1 | 3 | 1. A multi-modal multi-lingual mobile device that facilitates automating an action, comprising: a detection component that employs a plurality of integrated sensors to obtain at least one criterion from an auxiliary act through passive observation, the auxiliary act is a conversation of a user with an entity that is not the mobile device, wherein the at least one criterion is an environmental context that relates to a weather condition, and a schedule manipulation action is performed at least partially in view of at least one of expected travel complications or venue incompatibility with the weather condition; and an analyzer component that evaluates the at least one criterion to infer a user intent and automatically implements the action based at least in part upon operation of a rules-based logic component, wherein the rules based logic component automatically allows execution of the action based at least in part upon satisfaction of a defined rule, and based at least in part upon operation of an implementation component configured to identify an individual, the implementation component using an algorithm together with a desired degree of certainty, and based at least in part upon operation of an artificial intelligence component that comprises a classifier function that maps an input attribute vector x=(x 1 , x 2 , x 3 , x 4 , x n ) to a confidence that input associated with the vector belongs to a class, wherein the x i , are input attributes, wherein the confidence that the input belongs to the class is expressed as f(x)=confidence(class), and wherein the class to which an input belongs infers the action that the user desires to be automatically performed; wherein the auxiliary act is not for an explicit purpose of implementing the action. | 1. A multi-modal multi-lingual mobile device that facilitates automating an action, comprising: a detection component that employs a plurality of integrated sensors to obtain at least one criterion from an auxiliary act through passive observation, the auxiliary act is a conversation of a user with an entity that is not the mobile device, wherein the at least one criterion is an environmental context that relates to a weather condition, and a schedule manipulation action is performed at least partially in view of at least one of expected travel complications or venue incompatibility with the weather condition; and an analyzer component that evaluates the at least one criterion to infer a user intent and automatically implements the action based at least in part upon operation of a rules-based logic component, wherein the rules based logic component automatically allows execution of the action based at least in part upon satisfaction of a defined rule, and based at least in part upon operation of an implementation component configured to identify an individual, the implementation component using an algorithm together with a desired degree of certainty, and based at least in part upon operation of an artificial intelligence component that comprises a classifier function that maps an input attribute vector x=(x 1 , x 2 , x 3 , x 4 , x n ) to a confidence that input associated with the vector belongs to a class, wherein the x i , are input attributes, wherein the confidence that the input belongs to the class is expressed as f(x)=confidence(class), and wherein the class to which an input belongs infers the action that the user desires to be automatically performed; wherein the auxiliary act is not for an explicit purpose of implementing the action. 3. The multi-modal multi-lingual mobile device of claim 1 , the analyzer component evaluates the criterion based at least upon existing personal information manager (PIM) data. | 0.877437 |
9,904,536 | 8 | 11 | 8. The information handling system of claim 7 , wherein the discovering attributes comprises: determining data sources of the widget instances on a per widget-instance basis; determining configuration properties of the widget instances on a per widget-instance basis; and determining network paths of the widget instances on a per widget-instance basis. | 8. The information handling system of claim 7 , wherein the discovering attributes comprises: determining data sources of the widget instances on a per widget-instance basis; determining configuration properties of the widget instances on a per widget-instance basis; and determining network paths of the widget instances on a per widget-instance basis. 11. The information handling system of claim 8 , the method comprising: identifying unique data sources among the determined data sources; aggregating the widget instances by the unique data sources; and generating a report comprising information related to the aggregated widget instances. | 0.907584 |
9,515,979 | 8 | 9 | 8. A method for personalized network dialogs comprising: providing a graphical user interface to allow a first user to specify to a dialog system a second user to participate in an automated dialog, specific response option, and a maximum time period for responding; accessing a data store to determine an address for the second user; executing a first instruction associated with the dialog at the dialog system to send a first communication to the second user from a server via a first communications channel, the first communication containing the specific response option; determining at the dialog system if a first event has occurred in conjunction with the second user, wherein the first event comprises a response by the second user according to the specific response option within the maximum time period for responding; assigning a value to a variable associated with the first event based on the determination; branching the dialog based on the value of the variable associated with the first event, wherein: in a first branch, executing at the dialog system a second instruction associated with the dialog to send a second communication to the second user using a second communications channel; in a second branch, executing at the dialog system a third instruction associated with the dialog. | 8. A method for personalized network dialogs comprising: providing a graphical user interface to allow a first user to specify to a dialog system a second user to participate in an automated dialog, specific response option, and a maximum time period for responding; accessing a data store to determine an address for the second user; executing a first instruction associated with the dialog at the dialog system to send a first communication to the second user from a server via a first communications channel, the first communication containing the specific response option; determining at the dialog system if a first event has occurred in conjunction with the second user, wherein the first event comprises a response by the second user according to the specific response option within the maximum time period for responding; assigning a value to a variable associated with the first event based on the determination; branching the dialog based on the value of the variable associated with the first event, wherein: in a first branch, executing at the dialog system a second instruction associated with the dialog to send a second communication to the second user using a second communications channel; in a second branch, executing at the dialog system a third instruction associated with the dialog. 9. The method of claim 8 , wherein the second instruction is determined based on a permission associated with the second user. | 0.867925 |
6,012,072 | 1 | 2 | 1. An apparatus suitable for simultaneously displaying multiple documents, said apparatus comprising: a display device; memory means comprising a plurality of documents, each said document comprising one or more associated attributes stored internally to said document; processor means coupled with said memory means and with said display device, said processor means for displaying a plurality of document display outlines in a workspace, each said document display outline corresponding to one said document; and document rendering means coupled with said memory means, for rendering each said document within a corresponding said document display outline, said document rendering means responsive to said document attributes for restricting a view of said selected document in said workspace by selectively defining a contiguous portion of said corresponding document for display within said corresponding document display outline. | 1. An apparatus suitable for simultaneously displaying multiple documents, said apparatus comprising: a display device; memory means comprising a plurality of documents, each said document comprising one or more associated attributes stored internally to said document; processor means coupled with said memory means and with said display device, said processor means for displaying a plurality of document display outlines in a workspace, each said document display outline corresponding to one said document; and document rendering means coupled with said memory means, for rendering each said document within a corresponding said document display outline, said document rendering means responsive to said document attributes for restricting a view of said selected document in said workspace by selectively defining a contiguous portion of said corresponding document for display within said corresponding document display outline. 2. An apparatus as in claim 1 wherein said associated attributes comprise: a CLIP-LEFT attribute and a CLIP-RIGHT attribute for describing clipping on the sides of said documents; and a CLIP-TOP attribute and a CLIP-BOTTOM attribute for describing clipping on the top and the bottom of said documents. | 0.761867 |
10,157,226 | 15 | 18 | 15. A method, comprising: receiving, by a device, training data and an ontology for the training data, the training data including information associated with a subject of the ontology, and the ontology including: classes, and properties; generating, by the device, a knowledge graph based on the training data and the ontology; converting, by the device, the knowledge graph into knowledge graph embeddings, the knowledge graph embeddings including points in a k-dimensional metric space; receiving, by the device, additional ontology information; identifying, by the device, a new entity in the additional ontology information that is not present in the knowledge graph embeddings; generating, by the device, revised knowledge graph embeddings that include a new embedding for the new entity based on: a first average quantity of entities that are related to the knowledge graph and the new entity, and a second average quantity of entities that are related to the new entity and are not related to the knowledge graph; and utilizing, by the device, the revised knowledge graph embeddings to perform an action. | 15. A method, comprising: receiving, by a device, training data and an ontology for the training data, the training data including information associated with a subject of the ontology, and the ontology including: classes, and properties; generating, by the device, a knowledge graph based on the training data and the ontology; converting, by the device, the knowledge graph into knowledge graph embeddings, the knowledge graph embeddings including points in a k-dimensional metric space; receiving, by the device, additional ontology information; identifying, by the device, a new entity in the additional ontology information that is not present in the knowledge graph embeddings; generating, by the device, revised knowledge graph embeddings that include a new embedding for the new entity based on: a first average quantity of entities that are related to the knowledge graph and the new entity, and a second average quantity of entities that are related to the new entity and are not related to the knowledge graph; and utilizing, by the device, the revised knowledge graph embeddings to perform an action. 18. The method of claim 15 , further comprising: approximating the new embedding for the new entity based on a weight; and where generating the revised knowledge graph embeddings comprises: generating the revised knowledge graph embeddings based on approximating the new embedding for the new entity. | 0.833148 |
7,644,066 | 1 | 16 | 1. A method for querying a durably stored collection of XML documents, the method comprising: storing said collection of XML documents in one or more base database structures managed by a database system for storing said collection of XML documents; wherein each XML document of said collection of XML documents is stored, within the one or more base database structures, in an unshredded form; based on pattern data that indicates elements defined for a particular XML document type, creating a table for the particular XML document type separate from said one or more base database structures in which said collection of XML documents are stored; wherein said table includes a plurality of columns; wherein each column of said plurality of columns corresponds to a different element indicated in the pattern data; wherein each column contains only values of the element of the XML document type to which the column corresponds; wherein each row of said table corresponds to a corresponding XML document in said collection; wherein each row of said table stores values for elements from the corresponding XML document; wherein said pattern data indicates, for each column of said plurality of columns, the different element, of the particular XML document type, that corresponds to the column; using said table to answer a first query requesting data from said collection of XML documents; responding to said first query without accessing said one or more base database structures; and responding to a second query requesting data from said collection of XML documents by providing one or more unshredded XML documents from said one or more base database structures; wherein said method is performed by one or more computing devices. | 1. A method for querying a durably stored collection of XML documents, the method comprising: storing said collection of XML documents in one or more base database structures managed by a database system for storing said collection of XML documents; wherein each XML document of said collection of XML documents is stored, within the one or more base database structures, in an unshredded form; based on pattern data that indicates elements defined for a particular XML document type, creating a table for the particular XML document type separate from said one or more base database structures in which said collection of XML documents are stored; wherein said table includes a plurality of columns; wherein each column of said plurality of columns corresponds to a different element indicated in the pattern data; wherein each column contains only values of the element of the XML document type to which the column corresponds; wherein each row of said table corresponds to a corresponding XML document in said collection; wherein each row of said table stores values for elements from the corresponding XML document; wherein said pattern data indicates, for each column of said plurality of columns, the different element, of the particular XML document type, that corresponds to the column; using said table to answer a first query requesting data from said collection of XML documents; responding to said first query without accessing said one or more base database structures; and responding to a second query requesting data from said collection of XML documents by providing one or more unshredded XML documents from said one or more base database structures; wherein said method is performed by one or more computing devices. 16. The method of claim 1 , further comprising: intercepting a user-submitted query on the collection of XML documents; rewriting the user-submitted query on the collection of XML documents to access the table. | 0.79572 |
8,875,306 | 1 | 10 | 1. A method for restricting the customizability of a base metadata document, the base metadata document defining one or more characteristics of at least a portion of a software application, the method comprising: receiving, by a computer system, a type-level customization policy defined for a first object type of an object included in the base metadata document, the type-level customization policy indicating whether instances of objects having the object type may be customized by a first set of one or more users of the software application; receiving an instance-level customization policy defined for the object included in the base metadata document, the instance-level customization policy indicating whether an instance of the object may be customized by a second set of one or more users of the software application; and enforcing, by the computer system, the type-level customization policy and the instance-level customization policy at runtime of the software application to create or update a customization, the customization defining modifications to the base metadata document, the enforcing comprising: determining whether the instance of the object may be customized by a current user, based on how the object is instantiated, the type-level customization policy, the instance-level customization policy, and a set of precedence rules for the type-level customization policy and the instance-level customization policy, wherein how the object is instantiated comprises whether the object is instantiated as the first object type or as a second object type that is based on the first object type, and wherein the set of precedence rules for the type-level customization policy and the instance-level customization policy comprises one or more rules providing for a first case where the type-level customization policy and the instance-level customization policy apply without conflict, and one or more rules providing for a second case where the type-level customization policy and the instance-level customization policy apply with conflicting restrictions; determining whether a restriction of one of the type-level customization policy or the instance-level customization policy takes a higher precedence with respect to a conflicting restriction of the other of the type-level customization policy or the instance-level customization policy; wherein the customization is stored separately from the base metadata document, and wherein the customization is applied to the base metadata document to generate a customized metadata document used by the software application. | 1. A method for restricting the customizability of a base metadata document, the base metadata document defining one or more characteristics of at least a portion of a software application, the method comprising: receiving, by a computer system, a type-level customization policy defined for a first object type of an object included in the base metadata document, the type-level customization policy indicating whether instances of objects having the object type may be customized by a first set of one or more users of the software application; receiving an instance-level customization policy defined for the object included in the base metadata document, the instance-level customization policy indicating whether an instance of the object may be customized by a second set of one or more users of the software application; and enforcing, by the computer system, the type-level customization policy and the instance-level customization policy at runtime of the software application to create or update a customization, the customization defining modifications to the base metadata document, the enforcing comprising: determining whether the instance of the object may be customized by a current user, based on how the object is instantiated, the type-level customization policy, the instance-level customization policy, and a set of precedence rules for the type-level customization policy and the instance-level customization policy, wherein how the object is instantiated comprises whether the object is instantiated as the first object type or as a second object type that is based on the first object type, and wherein the set of precedence rules for the type-level customization policy and the instance-level customization policy comprises one or more rules providing for a first case where the type-level customization policy and the instance-level customization policy apply without conflict, and one or more rules providing for a second case where the type-level customization policy and the instance-level customization policy apply with conflicting restrictions; determining whether a restriction of one of the type-level customization policy or the instance-level customization policy takes a higher precedence with respect to a conflicting restriction of the other of the type-level customization policy or the instance-level customization policy; wherein the customization is stored separately from the base metadata document, and wherein the customization is applied to the base metadata document to generate a customized metadata document used by the software application. 10. The method of claim 1 , wherein the steps of enforcing the type-level customization policy and enforcing the instance-level customization policy comprise: determining, based on a policy value, the type-level customization policy, the instance-level customization policy, the set of precedence rules, and a set of default behavior rules, whether the instance of the object may be customized by the current user. | 0.598058 |
7,574,672 | 4 | 9 | 4. The method of claim 1 , wherein the sequentially scrolling through the set is in accordance with one or more navigation commands received from a click wheel. | 4. The method of claim 1 , wherein the sequentially scrolling through the set is in accordance with one or more navigation commands received from a click wheel. 9. The method of claim 4 , wherein a scrolling rate is slower for a pre-determined time interval of the contact just after the scrolling is started, just prior to stopping the scrolling, and when a direction of the scrolling is reversed, than for other time intervals. | 0.860562 |
8,909,513 | 4 | 5 | 4. The method of claim 1 wherein providing one or more of the candidate emoticons for user selection comprises displaying the set of candidate emoticons on a physical input device or a virtual input device, wherein the physical input device and the virtual input device are configured to receive the entry selection. | 4. The method of claim 1 wherein providing one or more of the candidate emoticons for user selection comprises displaying the set of candidate emoticons on a physical input device or a virtual input device, wherein the physical input device and the virtual input device are configured to receive the entry selection. 5. The method of claim 4 wherein the virtual input device is displayed in close proximity to the text field. | 0.963215 |
8,892,417 | 1 | 3 | 1. A computer program product for story evaluation comprising: a plurality of instructions that are executable by a processor to (1) access an angle set data structure in a memory, the angle set data structure comprising (i) data representative of at least one story angle and (ii) data associated with the at least one story angle that is representative of at least one applicability condition for the associated at least one story angle, (2) process data against the angle set data structure to determine whether at least one applicability condition for at least one story angle has been satisfied by the processed data, and (3) in response to the processing operation, generate an evaluation indicator, the evaluation indicator being indicative of whether a narrative story relating to the processed data is to be generated; and wherein the plurality of instructions are resident on a non-transitory computer-readable storage medium. | 1. A computer program product for story evaluation comprising: a plurality of instructions that are executable by a processor to (1) access an angle set data structure in a memory, the angle set data structure comprising (i) data representative of at least one story angle and (ii) data associated with the at least one story angle that is representative of at least one applicability condition for the associated at least one story angle, (2) process data against the angle set data structure to determine whether at least one applicability condition for at least one story angle has been satisfied by the processed data, and (3) in response to the processing operation, generate an evaluation indicator, the evaluation indicator being indicative of whether a narrative story relating to the processed data is to be generated; and wherein the plurality of instructions are resident on a non-transitory computer-readable storage medium. 3. The computer program product of claim 1 wherein the plurality of instructions are further configured for (1) receiving source data relating to a subject, (2) computing a plurality of derived features based at least in part on the received source data, wherein the processed data comprises the source data and the derived features, and (3) generating an evaluation indicator indicative of whether a narrative story relating to the processed data that incorporates a story angle of the angle set data structure whose applicability conditions were satisfied by the processed data is to be generated. | 0.500833 |
8,024,174 | 1 | 2 | 1. A method for training a prosody statistic model with a raw corpus that includes a plurality of sentences with punctuation, comprising: transforming said plurality of sentences in said raw corpus into a plurality of token sequences respectively; counting frequency of each adjacent token pair occurring in said plurality of token sequences and frequency of punctuation that represents a pause occurring at associated positions of said each token pair; calculating pause probabilities at said associated positions of said each token pair, based on the frequency of each adjacent token pair and the frequency of punctuation; and constructing said prosody statistic model based on said token pairs and said pause probabilities at associated positions thereof, wherein the transforming, the counting, the calculating and the constructing, are executed by a computer. | 1. A method for training a prosody statistic model with a raw corpus that includes a plurality of sentences with punctuation, comprising: transforming said plurality of sentences in said raw corpus into a plurality of token sequences respectively; counting frequency of each adjacent token pair occurring in said plurality of token sequences and frequency of punctuation that represents a pause occurring at associated positions of said each token pair; calculating pause probabilities at said associated positions of said each token pair, based on the frequency of each adjacent token pair and the frequency of punctuation; and constructing said prosody statistic model based on said token pairs and said pause probabilities at associated positions thereof, wherein the transforming, the counting, the calculating and the constructing, are executed by a computer. 2. The method for training a prosody statistic model according to claim 1 , wherein said associated positions of said each token pair include: before, after and amid said token pair. | 0.733918 |
9,075,846 | 1 | 4 | 1. A computer-implemented method for retrieval of Arabic historical manuscripts, comprising the steps of: entering Arabic historical manuscript images into a computer for processing; extracting circular polar grid features from the Arabic historical manuscript images stored in the computer, wherein the step of extracting circular polar grid features comprises: building a circular polar grid from a multiline-axis including an intersection of a 0° line, a 45° line, a 90° line and a 135° line; overlaying concentric circles centered about the intersection point of said multiline-axis, the concentric circles having radial values of r, 2r, 3r, . . . nr; and centering said circular polar grid at a centroid of an image term to be indexed; constructing a Latent Semantic Index based on the extracted circular polar grid features, the Latent Semantic Index having a reduced dimension m×n Term-by-Document matrix obtained from a Singular Value Decomposition of a higher dimensional Term-by-Document matrix constructed by the computer from the extracted circular polar grid features, wherein m rows represent the features and n columns represent the images; accepting a user query against the stored Arabic historical manuscript images, the computer forming the user query as a query vector derived from features extraction of a query image supplied by the user; performing query matching based on comparison between the query vector and the Term-by-Document matrix; weighing each term of said Term-by-Document matrix by a value representing an occurrence frequency of a feature of said term in said document, wherein the step of weighing each term of said Term-by-Document matrix comprises: picking a comprehensive training set of said document for each said feature; calculating a mean μ f and a standard deviation σ f of the features f's value across the training set; and for each image in the collection, defining an occurrence count O fj of feature f according to the relation: O fj = { ⌈ val fj - μ f σ f ⌉ if val fj > μ f 0 otherwise where val fj is the value of the feature f in image j; and displaying Arabic historical document images returned by the query matching process performed by the computer, the returned document images being ranked by similarity to the user query according to a predetermined distance measurement between the query vector and the Term-by-Document matrix, wherein the computer determines a plurality of image features defined by a count of black image pixels found in regions of intersection between said multilines and said concentric circles. | 1. A computer-implemented method for retrieval of Arabic historical manuscripts, comprising the steps of: entering Arabic historical manuscript images into a computer for processing; extracting circular polar grid features from the Arabic historical manuscript images stored in the computer, wherein the step of extracting circular polar grid features comprises: building a circular polar grid from a multiline-axis including an intersection of a 0° line, a 45° line, a 90° line and a 135° line; overlaying concentric circles centered about the intersection point of said multiline-axis, the concentric circles having radial values of r, 2r, 3r, . . . nr; and centering said circular polar grid at a centroid of an image term to be indexed; constructing a Latent Semantic Index based on the extracted circular polar grid features, the Latent Semantic Index having a reduced dimension m×n Term-by-Document matrix obtained from a Singular Value Decomposition of a higher dimensional Term-by-Document matrix constructed by the computer from the extracted circular polar grid features, wherein m rows represent the features and n columns represent the images; accepting a user query against the stored Arabic historical manuscript images, the computer forming the user query as a query vector derived from features extraction of a query image supplied by the user; performing query matching based on comparison between the query vector and the Term-by-Document matrix; weighing each term of said Term-by-Document matrix by a value representing an occurrence frequency of a feature of said term in said document, wherein the step of weighing each term of said Term-by-Document matrix comprises: picking a comprehensive training set of said document for each said feature; calculating a mean μ f and a standard deviation σ f of the features f's value across the training set; and for each image in the collection, defining an occurrence count O fj of feature f according to the relation: O fj = { ⌈ val fj - μ f σ f ⌉ if val fj > μ f 0 otherwise where val fj is the value of the feature f in image j; and displaying Arabic historical document images returned by the query matching process performed by the computer, the returned document images being ranked by similarity to the user query according to a predetermined distance measurement between the query vector and the Term-by-Document matrix, wherein the computer determines a plurality of image features defined by a count of black image pixels found in regions of intersection between said multilines and said concentric circles. 4. The computer-implemented method according to claim 1 , further comprising the step of calculating said predetermined distance measurement as a cosine between said query vector, and said Term-by Document matrix. | 0.97398 |
9,424,351 | 10 | 15 | 10. A method for utilizing a hybrid-distribution system for identifying relevant documents based on a search query, the method comprising: allocating a group of documents to a segment, the group of documents being indexed by atom in a reverse index and indexed by document in a forward index, atoms in the reverse index are accessed in a matching process and a preliminary ranking process and documents in the forward index are accessed in a final ranking process; storing a different portion of the reverse index and the forward index on each of a plurality of nodes that form the segment; first, accessing the reverse index portion stored on each of a first set of nodes having portions of the reverse index; identifying a first set of documents that is relevant to the search query, wherein the first set of documents is identified as being relevant to the search query by way of the matching process and the preliminary ranking process; second, based on document identifications associated with the first set of documents, accessing the forward index portion stored on each of a second set of nodes having portions of the forward index; identifying a second set of documents from the first set of documents, wherein the second set of documents is identified by way of the final ranking process; limiting a quantity of relevant documents in the first set of documents identified to the second set of documents; and communicating for presentation search results for the search query based on the second set of documents. | 10. A method for utilizing a hybrid-distribution system for identifying relevant documents based on a search query, the method comprising: allocating a group of documents to a segment, the group of documents being indexed by atom in a reverse index and indexed by document in a forward index, atoms in the reverse index are accessed in a matching process and a preliminary ranking process and documents in the forward index are accessed in a final ranking process; storing a different portion of the reverse index and the forward index on each of a plurality of nodes that form the segment; first, accessing the reverse index portion stored on each of a first set of nodes having portions of the reverse index; identifying a first set of documents that is relevant to the search query, wherein the first set of documents is identified as being relevant to the search query by way of the matching process and the preliminary ranking process; second, based on document identifications associated with the first set of documents, accessing the forward index portion stored on each of a second set of nodes having portions of the forward index; identifying a second set of documents from the first set of documents, wherein the second set of documents is identified by way of the final ranking process; limiting a quantity of relevant documents in the first set of documents identified to the second set of documents; and communicating for presentation search results for the search query based on the second set of documents. 15. The method of claim 10 , wherein the forward index portion stored on each node in the second set of nodes contains at least one of the document identifications associated with the first set of documents. | 0.779318 |
7,685,512 | 34 | 35 | 34. The computer readable medium of claim 30 , wherein (b) comprises, if it is determined in (a) that said target namespace of said referenced global element declaration is neither null nor the same as the target namespace of an XML schema containing said element reference: creating a new global element declaration with a derived type based on a determined type of said referenced global element declaration and a target namespace matching said target namespace of said referenced global element declaration; and setting said element reference to reference said new global element declaration. | 34. The computer readable medium of claim 30 , wherein (b) comprises, if it is determined in (a) that said target namespace of said referenced global element declaration is neither null nor the same as the target namespace of an XML schema containing said element reference: creating a new global element declaration with a derived type based on a determined type of said referenced global element declaration and a target namespace matching said target namespace of said referenced global element declaration; and setting said element reference to reference said new global element declaration. 35. The computer readable medium of claim 34 , wherein said rendering option further specifies a target namespace for said additional attribute, and wherein said computer-executable instructions further cause said computing device to, if said target namespace for said additional attribute is null or the same as a target namespace of said derived type, add to said derived type a local attribute having said specified attribute name and said determined type of said referenced global element declaration. | 0.853793 |
8,374,864 | 9 | 14 | 9. An apparatus comprising: memory for storing an audio file comprising an audio communication and a text file comprising a transcribed text created from the audio communication; and a processor for generating a mapping of the text file comprising the transcribed text to the audio file comprising the audio communication independent of transcribing the audio communication, said mapping identifying locations of portions of the text in the audio communication; and a speech recognition engine, wherein generating said mapping comprises processing the audio file at the speech recognition engine to match words in the text file to sounds in the audio file. | 9. An apparatus comprising: memory for storing an audio file comprising an audio communication and a text file comprising a transcribed text created from the audio communication; and a processor for generating a mapping of the text file comprising the transcribed text to the audio file comprising the audio communication independent of transcribing the audio communication, said mapping identifying locations of portions of the text in the audio communication; and a speech recognition engine, wherein generating said mapping comprises processing the audio file at the speech recognition engine to match words in the text file to sounds in the audio file. 14. The apparatus of claim 9 wherein the processor is configured to transmit the audio communication to a transcription center and receive the transcribed text from the transcription center. | 0.62 |
8,849,665 | 17 | 18 | 17. A computer-readable storage device having instructions stored which, when executed by a computing device, causes the computing device to perform operations comprising: receiving a source language sentence; selecting, via a lexical classifier, a bag of target language n-grams associated with the source language sentence, wherein the bag of target language n-grams comprises a beginning n-gram having a start token in a first word position, and an ending n-gram having an end token in a second word position, the end token connecting a history node to a final state node; combining the bag of target language n-grams to yield an n-gram network; ranking N strings in the n-gram network using a language model to yield an n-best list of target sentences; and generating a target sentence based on the n-best list. | 17. A computer-readable storage device having instructions stored which, when executed by a computing device, causes the computing device to perform operations comprising: receiving a source language sentence; selecting, via a lexical classifier, a bag of target language n-grams associated with the source language sentence, wherein the bag of target language n-grams comprises a beginning n-gram having a start token in a first word position, and an ending n-gram having an end token in a second word position, the end token connecting a history node to a final state node; combining the bag of target language n-grams to yield an n-gram network; ranking N strings in the n-gram network using a language model to yield an n-best list of target sentences; and generating a target sentence based on the n-best list. 18. The computer-readable storage device of claim 17 , wherein the lexical classifier generates a classification score for each of a plurality of n-grams in a set of training data. | 0.502762 |
7,676,521 | 12 | 14 | 12. A keyword search volume forecasting system having a processor and system memory for forecasting keyword search volume, the system comprising: keyword categorizer to determine a forecastability category of a keyword based on measured keyword search volumes, wherein the keyword categorizer categorizes keywords into directly forecastable and non-directly forecastable categories, and wherein a directly forecastable keyword is associated with at least a predefined amount of accumulated historical search volume data and a non-directly forecastable keyword is associated with less than the predefined amount of accumulated historical search volume data; a seasonality detector to detect a seasonality of keywords and keyword categories, wherein the seasonality is based on trends identified from historical search volume data associated with the the directly forecastable keywords, wherein the seasonality of each non-directly forecastable keyword is determined based on the seasonality of one or more directly forecastable keywords with which the non-directly forecastable keyword is associated; and a forecasting engine to forecast a keyword search volume corresponding to the non-directly forecastable keyword, wherein the forecasted search volume for the non-directly forecastable keyword is based at least on the seasonality and one or more of the historical search volume data of the non-directly forecastable keyword and the historical search volume data of the one or more directly forecastable keywords with which the non-directly forecastable keyword is associated. | 12. A keyword search volume forecasting system having a processor and system memory for forecasting keyword search volume, the system comprising: keyword categorizer to determine a forecastability category of a keyword based on measured keyword search volumes, wherein the keyword categorizer categorizes keywords into directly forecastable and non-directly forecastable categories, and wherein a directly forecastable keyword is associated with at least a predefined amount of accumulated historical search volume data and a non-directly forecastable keyword is associated with less than the predefined amount of accumulated historical search volume data; a seasonality detector to detect a seasonality of keywords and keyword categories, wherein the seasonality is based on trends identified from historical search volume data associated with the the directly forecastable keywords, wherein the seasonality of each non-directly forecastable keyword is determined based on the seasonality of one or more directly forecastable keywords with which the non-directly forecastable keyword is associated; and a forecasting engine to forecast a keyword search volume corresponding to the non-directly forecastable keyword, wherein the forecasted search volume for the non-directly forecastable keyword is based at least on the seasonality and one or more of the historical search volume data of the non-directly forecastable keyword and the historical search volume data of the one or more directly forecastable keywords with which the non-directly forecastable keyword is associated. 14. The forecasting system of claim 12 , wherein the seasonality detector further comprises a calculation engine for determining a category level seasonal variation pattern for a keyword category. | 0.502538 |
7,860,811 | 8 | 9 | 8. A computer-based recommendation system comprising: means to generate an affinity vector between a first user of a computer-based system and a plurality of computer-based objects based, at least in part, on the first user's behaviors; means to generate a similarity metric between the first user and a second user of the computer-based system based, at least in part, on the affinity vector of the first user and an affinity vector of the second user; means to generate a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric; and means to generate an explanation for the recommendation comprising one or more phrases, wherein the selection of the one or more phrases is based, at least in part, on a plurality of user behaviors and in accordance with a computer-implemented syntactical structure. | 8. A computer-based recommendation system comprising: means to generate an affinity vector between a first user of a computer-based system and a plurality of computer-based objects based, at least in part, on the first user's behaviors; means to generate a similarity metric between the first user and a second user of the computer-based system based, at least in part, on the affinity vector of the first user and an affinity vector of the second user; means to generate a recommendation for delivery to the first user based, at least in part, on the affinity vector of the first user and the similarity metric; and means to generate an explanation for the recommendation comprising one or more phrases, wherein the selection of the one or more phrases is based, at least in part, on a plurality of user behaviors and in accordance with a computer-implemented syntactical structure. 9. The system of claim 8 wherein means to generate an affinity vector between a first user of a computer-based system and a plurality of computer-based objects based, at least in part, on the first user's behaviors comprises: means to generate affinities between the user and a plurality of topic objects. | 0.654977 |
9,183,535 | 16 | 22 | 16. A non-transitory computer-readable storage medium storing executable computer program instructions for updating a user's social network model, the computer program instructions comprising instructions for: receiving a set of documents associated with a user; accessing the user's contact data, the contact data identifying a plurality of entities; analyzing the documents, using the contact data, to identify references to entities therein; identifying relationships among the referenced entities; determining a strength of a first relationship between a first entity and a second entity responsive to a volume of documents in which both the first entity and the second entity appear, wherein the first and second entities are a subset of the referenced entities; building a social network model for the user responsive to the identified relationships among the referenced entities and the strength of the first relationship; storing the social network model; receiving a new document associated with the user; identifying, in the new document, a reference to an ambiguous entity; performing the name disambiguation using the social network model to determine which of the at least two candidate entities from the social network model is an intended entity for the ambiguous entity; identifying other entities referenced by the new document; and updating the social network model by modifying relationship strengths in the social network model between the intended entity and the other entities referenced by the new document. | 16. A non-transitory computer-readable storage medium storing executable computer program instructions for updating a user's social network model, the computer program instructions comprising instructions for: receiving a set of documents associated with a user; accessing the user's contact data, the contact data identifying a plurality of entities; analyzing the documents, using the contact data, to identify references to entities therein; identifying relationships among the referenced entities; determining a strength of a first relationship between a first entity and a second entity responsive to a volume of documents in which both the first entity and the second entity appear, wherein the first and second entities are a subset of the referenced entities; building a social network model for the user responsive to the identified relationships among the referenced entities and the strength of the first relationship; storing the social network model; receiving a new document associated with the user; identifying, in the new document, a reference to an ambiguous entity; performing the name disambiguation using the social network model to determine which of the at least two candidate entities from the social network model is an intended entity for the ambiguous entity; identifying other entities referenced by the new document; and updating the social network model by modifying relationship strengths in the social network model between the intended entity and the other entities referenced by the new document. 22. The non-transitory computer-readable storage medium of claim 16 wherein updating the social networking model comprises modifying a relationship strength between the intended entity and one of the other identified entities based on an elapsed time before the intended entity responds to messages from the one other identified entity. | 0.693989 |
9,916,386 | 1 | 5 | 1. A method for presenting a search result in response to a current search term, comprising: determining a pre-established first model corresponding to preselected user information and including historical user search data; identifying a selected historical search term in the historical user search data that corresponds with the current search term; identifying a selected historical selection result in the historical user search data that corresponds with the identified historical search term; determining the search result based upon the identified historical selection result, said determining the search result comprising determining an online recommendation result based upon the identified historical selection result; processing the online recommendation result to generate a generated recommendation result; and presenting the generated recommendation result, wherein said processing comprises: calculating a literal association degree between the online recommendation result and the current search term according to a logistic regression process such that the online recommendation result has the literal association degree that is greater than a preselected third threshold value; calculating a semantic association degree between the online recommendation result and the current search term according to a gradient boost decision tree such that the online recommendation result has the semantic association degree that is greater than a preselected fourth threshold value; or a combination thereof. | 1. A method for presenting a search result in response to a current search term, comprising: determining a pre-established first model corresponding to preselected user information and including historical user search data; identifying a selected historical search term in the historical user search data that corresponds with the current search term; identifying a selected historical selection result in the historical user search data that corresponds with the identified historical search term; determining the search result based upon the identified historical selection result, said determining the search result comprising determining an online recommendation result based upon the identified historical selection result; processing the online recommendation result to generate a generated recommendation result; and presenting the generated recommendation result, wherein said processing comprises: calculating a literal association degree between the online recommendation result and the current search term according to a logistic regression process such that the online recommendation result has the literal association degree that is greater than a preselected third threshold value; calculating a semantic association degree between the online recommendation result and the current search term according to a gradient boost decision tree such that the online recommendation result has the semantic association degree that is greater than a preselected fourth threshold value; or a combination thereof. 5. The method of claim 1 , further comprising presenting the online recommendation result. | 0.945848 |
8,117,242 | 2 | 6 | 2. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information configured to allow access to a plurality of different online applications in association with an online application system, the different online applications including a first online application that provides access to a first one or more files stored at one or more servers associated with the first online application, a second online application that provides access to a second one or more files stored at one or more servers associated with the second online application, a third online application that provides access to a third one or more files stored at one or more servers associated with the third online application, and a fourth online application that provides access to a fourth one or more files stored at one or more servers associated with the fourth online application; code for receiving the global unique user login information in connection with a user logging in; code for identifying at least one first online application identifier associated with the first online application for registration purposes; code for identifying at least one second online application identifier associated with the second online application for registration purposes; code for identifying at least one third online application identifier associated with the third online application for registration purposes; code for identifying at least one fourth online application identifier associated with the fourth online application for registration purposes; code for receiving an indication to add access to the first online application for registration purposes; code for receiving an indication to add access to the second online application for registration purposes; code for receiving an indication to add access to the third online application for registration purposes; code for receiving an indication to add access to the fourth online application for registration purposes; code for, in connection with the at least one first online application identifier associated with the first online application, allowing registration of the first online application by: utilizing data required for the first online application, and receiving preference information associated with the first online application; code for, in connection with the at least one second online application identifier associated with the second online application, allowing registration of the second online application by: utilizing data required for the second online application, and receiving preference information associated with the second online application; code for, in connection with the at least one third online application identifier associated with the third online application, allowing registration of the third online application by: utilizing data required for the third online application, and receiving preference information associated with the third online application; code for, in connection with the at least one fourth online application identifier associated with the fourth online application, allowing registration of the fourth online application by: utilizing data required for the fourth online application, and receiving preference information associated with the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application, utilizing the data required for the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application, utilizing the data required for the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application, utilizing the data required for the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application, utilizing the data required for the fourth online application; code for identifying a document in association with the online application system; code for receiving a request from a logged-in user; code for, in response to the request, displaying an interface for receiving an indication of one or more tags, the interface including: at least one text box for receiving manually inserted tags, and a list of potential tags; code for, utilizing the interface, receiving the indication of the one or more tags; and code for correlating the one or more tags with the document. | 2. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information configured to allow access to a plurality of different online applications in association with an online application system, the different online applications including a first online application that provides access to a first one or more files stored at one or more servers associated with the first online application, a second online application that provides access to a second one or more files stored at one or more servers associated with the second online application, a third online application that provides access to a third one or more files stored at one or more servers associated with the third online application, and a fourth online application that provides access to a fourth one or more files stored at one or more servers associated with the fourth online application; code for receiving the global unique user login information in connection with a user logging in; code for identifying at least one first online application identifier associated with the first online application for registration purposes; code for identifying at least one second online application identifier associated with the second online application for registration purposes; code for identifying at least one third online application identifier associated with the third online application for registration purposes; code for identifying at least one fourth online application identifier associated with the fourth online application for registration purposes; code for receiving an indication to add access to the first online application for registration purposes; code for receiving an indication to add access to the second online application for registration purposes; code for receiving an indication to add access to the third online application for registration purposes; code for receiving an indication to add access to the fourth online application for registration purposes; code for, in connection with the at least one first online application identifier associated with the first online application, allowing registration of the first online application by: utilizing data required for the first online application, and receiving preference information associated with the first online application; code for, in connection with the at least one second online application identifier associated with the second online application, allowing registration of the second online application by: utilizing data required for the second online application, and receiving preference information associated with the second online application; code for, in connection with the at least one third online application identifier associated with the third online application, allowing registration of the third online application by: utilizing data required for the third online application, and receiving preference information associated with the third online application; code for, in connection with the at least one fourth online application identifier associated with the fourth online application, allowing registration of the fourth online application by: utilizing data required for the fourth online application, and receiving preference information associated with the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application, utilizing the data required for the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application, utilizing the data required for the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application, utilizing the data required for the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application, utilizing the data required for the fourth online application; code for identifying a document in association with the online application system; code for receiving a request from a logged-in user; code for, in response to the request, displaying an interface for receiving an indication of one or more tags, the interface including: at least one text box for receiving manually inserted tags, and a list of potential tags; code for, utilizing the interface, receiving the indication of the one or more tags; and code for correlating the one or more tags with the document. 6. The computer program product of claim 2 , wherein the computer program product is configured to cooperate with at least one mobile application configured to access at least one of the different online applications utilizing a mobile device, the computer program product further configured to allow the at least one mobile application to provide at least a portion of a functionality of the at least one of the different online applications. | 0.921869 |
9,876,848 | 1 | 7 | 1. A computer-executed method comprising: accessing an image comprising an unidentified key phrase in image format; processing a portion of the image associated with the unidentified key phrase using a character recognition algorithm to generate a list of candidate key phrases in text format; accessing, by a computer processor, a plurality of social media content items in text format authored by users of a social networking system, the social media content items each comprising at least one key phrase previously associated with the image and at least one of the candidate key phrases; determining, by the computer processor, for each candidate key phrase, a count of the number of the content items comprising that candidate key phrase and at least one of the key phrases previously associated with the image; selecting, by the computer processor, one of the candidate key phrases as being the unidentified key phrase based on the determined count of the content items in each set; and sending content associated with the image to one or more users of the social networking system based on the social media content items including the selected candidate key phrase. | 1. A computer-executed method comprising: accessing an image comprising an unidentified key phrase in image format; processing a portion of the image associated with the unidentified key phrase using a character recognition algorithm to generate a list of candidate key phrases in text format; accessing, by a computer processor, a plurality of social media content items in text format authored by users of a social networking system, the social media content items each comprising at least one key phrase previously associated with the image and at least one of the candidate key phrases; determining, by the computer processor, for each candidate key phrase, a count of the number of the content items comprising that candidate key phrase and at least one of the key phrases previously associated with the image; selecting, by the computer processor, one of the candidate key phrases as being the unidentified key phrase based on the determined count of the content items in each set; and sending content associated with the image to one or more users of the social networking system based on the social media content items including the selected candidate key phrase. 7. The computer-executed method of claim 1 , wherein the image is associated with an airing time stamp, and wherein each social media content item in the plurality of social media content items comprises a broadcast time stamp within a threshold amount of time from the airing time stamp. | 0.631714 |
9,223,850 | 10 | 14 | 10. A method of speech processing, the method comprising: selecting a first training corpora according to claim 9 ; training a language model for speech processing using said first selected corpora; and processing speech using said language model. | 10. A method of speech processing, the method comprising: selecting a first training corpora according to claim 9 ; training a language model for speech processing using said first selected corpora; and processing speech using said language model. 14. The speech processing method according to claim 10 , wherein training the language model further includes: expressing the probability of a current word w i in a language model as: P ( w i ❘ h , d ) = P ( w i , d ❘ h ) ∑ w P ( w , d ❘ h ) where d is a document, h is the word history and: P ( w i , d ❘ h ) = P ( w i ❘ h ) · P ( d ❘ w i , h ) ≈ P ( w i ❘ h ) · P ( d ❘ w i ) such that P ( w i ❘ h , d ) = P ( w i ❘ h ) P ( w i ❘ d ) P ( w i ) ∑ w P ( w ❘ h ) P ( w ❘ d ) P ( w ) and deriving p(w i |d) by comparing a vector constructed for the document expressing the document as a file vector with components of the vector indicating the frequency of feature groups within the corpus. | 0.689772 |
7,730,009 | 1 | 13 | 1. A method for providing enhanced research capabilities, said method comprising: providing an interface; providing enhanced computer implemented search and research capabilities executable on one or more computers, said capabilities comprising: Receiving at least one inquiry from at least one user; Evaluating the at least one inquiry relative to an archetype structure or archetype process or both; Determining at least one of a suggested inquiry area or a suggested inquiry construct, or both, related to the at least one inquiry; Generating at least one search argument related to at least one of the at least one suggested inquiry area, the at least one suggested inquiry construct, and the at least one inquiry, or any combination thereof; Providing in display or output or both, at least one of the suggested inquiry area, suggested inquiry construct, or generated search argument, or any combination thereof. | 1. A method for providing enhanced research capabilities, said method comprising: providing an interface; providing enhanced computer implemented search and research capabilities executable on one or more computers, said capabilities comprising: Receiving at least one inquiry from at least one user; Evaluating the at least one inquiry relative to an archetype structure or archetype process or both; Determining at least one of a suggested inquiry area or a suggested inquiry construct, or both, related to the at least one inquiry; Generating at least one search argument related to at least one of the at least one suggested inquiry area, the at least one suggested inquiry construct, and the at least one inquiry, or any combination thereof; Providing in display or output or both, at least one of the suggested inquiry area, suggested inquiry construct, or generated search argument, or any combination thereof. 13. The method of claim 1 in which multiple suggested inquiry areas, suggested inquiry constructs or search arguments are generated, or any combination thereof. | 0.886525 |
7,801,722 | 16 | 17 | 16. The computer-readable storage medium of claim 9 , further comprising additional instructions that are executable and, responsive to executing the additional instructions, the computer creates a dynamic help file to document the phonetic scheme created by a user. | 16. The computer-readable storage medium of claim 9 , further comprising additional instructions that are executable and, responsive to executing the additional instructions, the computer creates a dynamic help file to document the phonetic scheme created by a user. 17. The computer-readable storage medium of claim 16 , further comprising additional instructions that are executable and, responsive to executing the additional instructions, the computer receives input to customize a set of contents contained in the dynamic help file. | 0.893112 |
9,444,907 | 15 | 16 | 15. A computer-implemented method comprising: obtaining keywords from user profiles of a group of users of a social networking system who previously responded to an invitation; extracting a set of keywords from a subject user profile of a subject user of a social networking system; comparing the set of keywords to the keywords from the user profiles of the group of users of the social networking system who previously responded to the invitation; and predicting a response to the invitation by the subject user based on the comparison. | 15. A computer-implemented method comprising: obtaining keywords from user profiles of a group of users of a social networking system who previously responded to an invitation; extracting a set of keywords from a subject user profile of a subject user of a social networking system; comparing the set of keywords to the keywords from the user profiles of the group of users of the social networking system who previously responded to the invitation; and predicting a response to the invitation by the subject user based on the comparison. 16. The method of claim 15 , wherein comparing the set of keywords to the keywords from the user profiles of the group of users of the social networking system who previously responded to the invitation comprises: determining a first occurrence, in a first group of user profiles corresponding to a group of other users who responded positively to the invitation, of keywords from the set of keywords; determining a second occurrence, in a second group of user profiles corresponding to a group of other users who responded negatively to the invitation, of keywords from the set of the keywords; and computing a score for each of the keywords from the set of keywords based on a comparison of the first occurrence of the keywords and the second occurrence of the keywords. | 0.573951 |
8,554,537 | 19 | 28 | 19. An electronic device comprising: a receiver configured to receive text input in a source language from a user; a processor configured to create source language sub-phonetic units for each word in the text input, convert the source language sub-phonetic units for the each word in the text input to target language sub-phonetic units, retrieve ranking of each of the target language sub-phonetic units from a database, create target language words based on the target language sub-phonetic units and the ranking of the each of the target language sub-phonetic units, and identify candidate target language words performing a reverse transliteration for the created target language words; and a display configured to display the candidate target language words to the user. | 19. An electronic device comprising: a receiver configured to receive text input in a source language from a user; a processor configured to create source language sub-phonetic units for each word in the text input, convert the source language sub-phonetic units for the each word in the text input to target language sub-phonetic units, retrieve ranking of each of the target language sub-phonetic units from a database, create target language words based on the target language sub-phonetic units and the ranking of the each of the target language sub-phonetic units, and identify candidate target language words performing a reverse transliteration for the created target language words; and a display configured to display the candidate target language words to the user. 28. The electronic device of claim 19 , wherein the processor validates the candidate target language words based on a target language corpus. | 0.897989 |
6,167,117 | 39 | 41 | 39. The apparatus of claim 26, wherein the generating means includes: means for selecting a name associated with one of the telephone numbers in the set; means for presenting the selected name to the user; and means for waiting for a response from the user indicating whether the selected name corresponds to the desired telephone number. | 39. The apparatus of claim 26, wherein the generating means includes: means for selecting a name associated with one of the telephone numbers in the set; means for presenting the selected name to the user; and means for waiting for a response from the user indicating whether the selected name corresponds to the desired telephone number. 41. The apparatus of claim 39, wherein the waiting step includes: means for interpreting a lack of response as meaning that the selected name corresponds to the desired telephone number. | 0.858232 |
8,204,950 | 1 | 2 | 1. A method of providing an in-page search of contents of a webpage, the method comprising: displaying, with a web browser, a visible portion of a webpage, the webpage comprising: markup text comprising text and formatting tags that format the text according to a markup language; executable code that performs an in-page search of contents of the webpage, the executable code being independent of search functionality of the web browser and included in the markup text; and an element that receives a user's search criteria; reading the user's search criteria with the executable code; searching contents of the webpage with the executable code to identify text matching the search criteria; providing on the webpage, with the executable code, a set of user interface controls for the user to select text formatting options for text identified as matching the search criteria; modifying, with the executable code, a set of markup tags corresponding to the identified text in accordance with the text formatting options selected by the user, based on a determination that the identified text matches the search criteria, to change the appearance of the identified text relative to other text on the webpage, wherein the modified set of markup tags make the identified text a hyperlink allowing the user to jump to a next match on the webpage, wherein modifying the set of markup tags corresponding to the identified text comprises: removing the identified text from the webpage using the executable code; adding formatting instructions in front of and behind the removed identified text using the executable code; and reinserting the removed identified text and the added formatting instructions into the webpage at an original location of the removed identified text; and redisplaying, with the executable code, the visible portion of the webpage with the modified set of markup tags. | 1. A method of providing an in-page search of contents of a webpage, the method comprising: displaying, with a web browser, a visible portion of a webpage, the webpage comprising: markup text comprising text and formatting tags that format the text according to a markup language; executable code that performs an in-page search of contents of the webpage, the executable code being independent of search functionality of the web browser and included in the markup text; and an element that receives a user's search criteria; reading the user's search criteria with the executable code; searching contents of the webpage with the executable code to identify text matching the search criteria; providing on the webpage, with the executable code, a set of user interface controls for the user to select text formatting options for text identified as matching the search criteria; modifying, with the executable code, a set of markup tags corresponding to the identified text in accordance with the text formatting options selected by the user, based on a determination that the identified text matches the search criteria, to change the appearance of the identified text relative to other text on the webpage, wherein the modified set of markup tags make the identified text a hyperlink allowing the user to jump to a next match on the webpage, wherein modifying the set of markup tags corresponding to the identified text comprises: removing the identified text from the webpage using the executable code; adding formatting instructions in front of and behind the removed identified text using the executable code; and reinserting the removed identified text and the added formatting instructions into the webpage at an original location of the removed identified text; and redisplaying, with the executable code, the visible portion of the webpage with the modified set of markup tags. 2. The method of claim 1 , wherein the markup language comprises HyperText Markup Language (HTML) tags. | 0.850291 |
7,949,728 | 2 | 12 | 2. The method of claim 1 , further comprising: accessing, using the computing device, a fourth database comprising information representative of at least one royalty statement, each royalty statement associated with at least one license agreement; accessing, using the computing device, a fifth database comprising information representative of at least one payment, each payment associated with at least one license agreement; and enabling processing of, using the computing device and at least one of said plurality of user-defined indexes, in a manner specified by a received command, information representative of at least one of: said at least one IP asset; said at least one IP asset package; said at least one license agreement; said at least one royalty statement; or said at least one payment. | 2. The method of claim 1 , further comprising: accessing, using the computing device, a fourth database comprising information representative of at least one royalty statement, each royalty statement associated with at least one license agreement; accessing, using the computing device, a fifth database comprising information representative of at least one payment, each payment associated with at least one license agreement; and enabling processing of, using the computing device and at least one of said plurality of user-defined indexes, in a manner specified by a received command, information representative of at least one of: said at least one IP asset; said at least one IP asset package; said at least one license agreement; said at least one royalty statement; or said at least one payment. 12. The method of claim 2 , wherein accessing the third database comprises generating a payment allocation report comprising information indicative of any payments associated with said at least one license agreement, or allocation of said any payments to terms of said at least one license agreement. | 0.926326 |
8,339,410 | 1 | 10 | 1. A method for analyzing a large set of data objects by auditing an attitude among a target population comprising: providing a first set of information objects to a first group of a target population; providing a deliberately ambiguated signifier prompt to the first group selected from the target population, wherein the deliberately ambiguated signifier prompt comprises a continuum having a plurality of labels and wherein the plurality of labels are identified with particular human attitudes; collecting a first set of responses from the first group characterizing the first set of information objects using the deliberately ambiguated signifier prompt, and analyzing the first set of responses to produce a first quantitative measure-characterizing the first set of responses; storing the first quantitative measure on a computer readable media; providing a second set of information objects to a second group selected from the target population; providing the deliberately ambiguated signifier prompt to the second group; collecting a second set of responses from the second group characterizing the second set of information objects using the deliberately ambiguated signifier prompt, and analyzing the second set of responses to produce a second quantitative measure characterizing the second set of responses; and comparing the first quantitative measure with the second quantitative measure to identify changes in the particular human attitudes of the target population. | 1. A method for analyzing a large set of data objects by auditing an attitude among a target population comprising: providing a first set of information objects to a first group of a target population; providing a deliberately ambiguated signifier prompt to the first group selected from the target population, wherein the deliberately ambiguated signifier prompt comprises a continuum having a plurality of labels and wherein the plurality of labels are identified with particular human attitudes; collecting a first set of responses from the first group characterizing the first set of information objects using the deliberately ambiguated signifier prompt, and analyzing the first set of responses to produce a first quantitative measure-characterizing the first set of responses; storing the first quantitative measure on a computer readable media; providing a second set of information objects to a second group selected from the target population; providing the deliberately ambiguated signifier prompt to the second group; collecting a second set of responses from the second group characterizing the second set of information objects using the deliberately ambiguated signifier prompt, and analyzing the second set of responses to produce a second quantitative measure characterizing the second set of responses; and comparing the first quantitative measure with the second quantitative measure to identify changes in the particular human attitudes of the target population. 10. The method of claim 1 further comprising supplementing the first and second sets of responses with additional signification of the information objects. | 0.777937 |
8,521,769 | 3 | 5 | 3. The system of claim 2 , wherein the value comprises a first number and wherein the plurality of matching attributes comprises a first attribute that matches the value and a second attribute that matches the value, wherein the first attribute comprises a first category associated with the first number, wherein the second attribute comprises a second category associated with the first number, and wherein a determination cannot be made by examining only the first number whether the first number should belong, as perceived by a user or a computer program, to the first category or to the second category. | 3. The system of claim 2 , wherein the value comprises a first number and wherein the plurality of matching attributes comprises a first attribute that matches the value and a second attribute that matches the value, wherein the first attribute comprises a first category associated with the first number, wherein the second attribute comprises a second category associated with the first number, and wherein a determination cannot be made by examining only the first number whether the first number should belong, as perceived by a user or a computer program, to the first category or to the second category. 5. The system of claim 3 , wherein the display module is further configured to display a first category name for the first category and a second category name for the second category. | 0.946366 |
9,519,643 | 1 | 2 | 1. A computer-implemented process for translating map labels, comprising using a computing device for: receiving an entity's map label in a first language that is to be translated into a second language; generating translation candidates for each n-gram in the entity's map label and using these translation candidates to generate translation candidate sequences for the map label; selecting a prescribed number of translation candidate sequences; extracting features from the selected translation candidate sequences and the entity's map label by using geospatial and linguistic context information; using a probabilistic classifier trained at least in part with the extracted features to rank the selected translation candidate sequences; and re-ranking the selected translation candidate sequences using neighboring proximity information of the entity's location to disclose the highest re-ranked translation candidate sequence as the translated map label. | 1. A computer-implemented process for translating map labels, comprising using a computing device for: receiving an entity's map label in a first language that is to be translated into a second language; generating translation candidates for each n-gram in the entity's map label and using these translation candidates to generate translation candidate sequences for the map label; selecting a prescribed number of translation candidate sequences; extracting features from the selected translation candidate sequences and the entity's map label by using geospatial and linguistic context information; using a probabilistic classifier trained at least in part with the extracted features to rank the selected translation candidate sequences; and re-ranking the selected translation candidate sequences using neighboring proximity information of the entity's location to disclose the highest re-ranked translation candidate sequence as the translated map label. 2. The computer-implemented process of claim 1 wherein each translation candidate sequence comprises a translated term for each n-gram of the map label and a probability of transition. | 0.917341 |
7,493,603 | 13 | 19 | 13. A system for validating a markup language document against a markup language schema definition, the system comprising: a markup language schema compilation for generating an annotated automaton encoding corresponding to the markup language schema definition; and a runtime validation engine comprising a markup language schema validation parser, the runtime validation engine to receive the markup language document and the annotated automaton encoding as input, wherein the markup language schema validation parser associated with the runtime validation engine utilizes the annotated automaton encoding to validate the markup language document against the markup language schema definition including ensuring that the markup language document complies with a format specified by the markup language schema definition. | 13. A system for validating a markup language document against a markup language schema definition, the system comprising: a markup language schema compilation for generating an annotated automaton encoding corresponding to the markup language schema definition; and a runtime validation engine comprising a markup language schema validation parser, the runtime validation engine to receive the markup language document and the annotated automaton encoding as input, wherein the markup language schema validation parser associated with the runtime validation engine utilizes the annotated automaton encoding to validate the markup language document against the markup language schema definition including ensuring that the markup language document complies with a format specified by the markup language schema definition. 19. The system of claim 13 , wherein the runtime validation engine further comprises: a generic Extensible Markup Language (XML) parser, to perform a first validation of the markup language document, wherein the markup language schema validation parser performs a second validation of the XML the markup language document. | 0.742812 |
8,612,483 | 3 | 6 | 3. The method claim 1 further comprising determining the recipient user for the request based on a relationship between the user and the recipient user. | 3. The method claim 1 further comprising determining the recipient user for the request based on a relationship between the user and the recipient user. 6. The method of claim 3 , wherein determining the recipient user for the request comprises receiving one or more identifiers of the recipient user from the user and a message from the user. | 0.931109 |
10,083,205 | 11 | 14 | 11. A user device configured to improve performance of a user search interface comprising: a network interface; the user search interface; a processing device in communication with the network interface and the user search interface; and a non-transitory storage device in communication with the processing device, the non-transitory storage device storing instructions that when executed on the processing device cause the processing device to perform operations comprising: transmitting a search query to a search engine via a network; receiving search results from the search engine via the network, the search results including at least one application result object defining an application card and a query result object defining a query card, each application card being a graphical user search interface element that links to a state of one of a plurality of applications and the query card being a graphical user interface element that corresponds to a selected search query and includes a plurality of input elements, and each input element of the plurality of input elements being configured to receive an input from a user via the user search interface; displaying the search results on the user search interface; receiving a value corresponding to each input element receiving the input from the user among the plurality of input elements; receiving a user selection of the query card; updating, by the processing device, the selected search query based on the query card selected by the user and the received value, wherein the selected search query is updated by using a query identifier corresponding to the query card, and a set of query terms known to the search engine is identified by the query identifier, whereby the updating of the selected search query using the known set of query terms improves the performance of the user search interface; and transmitting the selected search query to the search engine. | 11. A user device configured to improve performance of a user search interface comprising: a network interface; the user search interface; a processing device in communication with the network interface and the user search interface; and a non-transitory storage device in communication with the processing device, the non-transitory storage device storing instructions that when executed on the processing device cause the processing device to perform operations comprising: transmitting a search query to a search engine via a network; receiving search results from the search engine via the network, the search results including at least one application result object defining an application card and a query result object defining a query card, each application card being a graphical user search interface element that links to a state of one of a plurality of applications and the query card being a graphical user interface element that corresponds to a selected search query and includes a plurality of input elements, and each input element of the plurality of input elements being configured to receive an input from a user via the user search interface; displaying the search results on the user search interface; receiving a value corresponding to each input element receiving the input from the user among the plurality of input elements; receiving a user selection of the query card; updating, by the processing device, the selected search query based on the query card selected by the user and the received value, wherein the selected search query is updated by using a query identifier corresponding to the query card, and a set of query terms known to the search engine is identified by the query identifier, whereby the updating of the selected search query using the known set of query terms improves the performance of the user search interface; and transmitting the selected search query to the search engine. 14. The user device of claim 11 , wherein the operations further comprise: receiving new search results in response to the selected search query, the new search results including one or more new application cards, each of the new application cards including a set of access mechanisms that is based on the plurality of input elements; and displaying the new search results. | 0.7113 |
8,965,763 | 1 | 4 | 1. A method comprising: determining, by a computing system, a reference transcription of a reference utterance, wherein the reference transcription is derived using a strong acoustic model, a language model and a weight vector, and wherein the reference transcription has a confidence level of at least 70%; based on the reference transcription having the confidence level of at least 70%, determining a secondary transcription of the reference utterance, wherein the secondary transcription is derived using a weak acoustic model, the language model and the weight vector, wherein the secondary transcription has a secondary confidence level, wherein the weak acoustic model has a higher error rate than the strong acoustic model, and wherein the secondary transcription is different from the reference transcription; and based on the secondary transcription being different from the reference transcription, updating the weight vector so that transcribing the reference utterance using the weak acoustic model, the language model and the updated weight vector results in a tertiary transcription with a tertiary confidence level that is greater than the secondary confidence level. | 1. A method comprising: determining, by a computing system, a reference transcription of a reference utterance, wherein the reference transcription is derived using a strong acoustic model, a language model and a weight vector, and wherein the reference transcription has a confidence level of at least 70%; based on the reference transcription having the confidence level of at least 70%, determining a secondary transcription of the reference utterance, wherein the secondary transcription is derived using a weak acoustic model, the language model and the weight vector, wherein the secondary transcription has a secondary confidence level, wherein the weak acoustic model has a higher error rate than the strong acoustic model, and wherein the secondary transcription is different from the reference transcription; and based on the secondary transcription being different from the reference transcription, updating the weight vector so that transcribing the reference utterance using the weak acoustic model, the language model and the updated weight vector results in a tertiary transcription with a tertiary confidence level that is greater than the secondary confidence level. 4. The method of claim 1 , further comprising: receiving an input utterance from a client device; determining an output transcription of the input utterance, wherein the output transcription is derived using the strong acoustic model, the language model, and the updated weight vector; and transmitting the output transcription to the client device. | 0.820288 |
8,374,935 | 17 | 18 | 17. The system of claim 16 , wherein determining one or more characteristics associated with the identified nodes includes: weighting the identified nodes based on a predetermined criteria associated with each node; identifying a node with a highest weight; and determining one or more characteristics associated with the identified node with the highest weight. | 17. The system of claim 16 , wherein determining one or more characteristics associated with the identified nodes includes: weighting the identified nodes based on a predetermined criteria associated with each node; identifying a node with a highest weight; and determining one or more characteristics associated with the identified node with the highest weight. 18. The system of claim 17 , wherein weighting the identified nodes based on a predetermined criteria associated with each node includes weighting the nodes based on a length of text associated with a node. | 0.865885 |
8,874,597 | 1 | 3 | 1. A method comprising: under control of one or more processors configured with executable instructions: storing a semantic keyword in a text filtering system, the semantic keyword comprising at least a basic keyword and a logical operator; finding the basic keyword of the semantic keyword in an input text, the finding comprising: obtaining a character c 1 in the input text; using c 1 as a current character and a root node of a tree-type structure as a current node, the root node corresponding to one of a first character or a last character of the basic keyword; determining whether the current character matches the current node; in an event that the current character matches the current node and the current node has a child node, setting a next character following or preceding the current character to be the current character, setting the child node to be the current node and repeating the determining of whether the current character matches the current node; in an event that the current character does not match the current node and the current node has a sibling node, setting the sibling node to be the current node and repeating the determining of whether the current character matches the current node; in an event that the current character matches the current node and the current node does not have a child node or the current character does not match the current node and the current node does not have a sibling node, connecting the last matched current node to the root node to obtain a matching route; and determining whether the basic keyword is found in the input text based at least in part on whether the matching route includes a successfully matched leaf node of the tree-type structure; in response to finding a text content matching the basic keyword in the input text, conducting a semantic match in the found text content, the semantic match comprising: matching the found text content with the semantic keyword according to the logical operator included in the semantic keyword; and in an event that the semantic match is successful, filtering a matched text context. | 1. A method comprising: under control of one or more processors configured with executable instructions: storing a semantic keyword in a text filtering system, the semantic keyword comprising at least a basic keyword and a logical operator; finding the basic keyword of the semantic keyword in an input text, the finding comprising: obtaining a character c 1 in the input text; using c 1 as a current character and a root node of a tree-type structure as a current node, the root node corresponding to one of a first character or a last character of the basic keyword; determining whether the current character matches the current node; in an event that the current character matches the current node and the current node has a child node, setting a next character following or preceding the current character to be the current character, setting the child node to be the current node and repeating the determining of whether the current character matches the current node; in an event that the current character does not match the current node and the current node has a sibling node, setting the sibling node to be the current node and repeating the determining of whether the current character matches the current node; in an event that the current character matches the current node and the current node does not have a child node or the current character does not match the current node and the current node does not have a sibling node, connecting the last matched current node to the root node to obtain a matching route; and determining whether the basic keyword is found in the input text based at least in part on whether the matching route includes a successfully matched leaf node of the tree-type structure; in response to finding a text content matching the basic keyword in the input text, conducting a semantic match in the found text content, the semantic match comprising: matching the found text content with the semantic keyword according to the logical operator included in the semantic keyword; and in an event that the semantic match is successful, filtering a matched text context. 3. The method as recited in claim 1 , wherein: the semantic keyword further comprises a filtering action; and filtering the matched text context comprises filtering the matched text content according to the filtering action. | 0.8962 |
7,613,602 | 10 | 12 | 10. The system according to claim 9 , wherein the structured document processing apparatus further comprises: a broadening unit configured to broaden a range until a lexical item having not less than a frequency of occurrence is present within the range; and an assignment unit configured to assign a lexical identifier of a lexical item which has a highest frequency of occurrence within the broadened range as a relevant lexical identifier of the lexical item. | 10. The system according to claim 9 , wherein the structured document processing apparatus further comprises: a broadening unit configured to broaden a range until a lexical item having not less than a frequency of occurrence is present within the range; and an assignment unit configured to assign a lexical identifier of a lexical item which has a highest frequency of occurrence within the broadened range as a relevant lexical identifier of the lexical item. 12. The system according to claim 10 , wherein the structured document search apparatus further comprises: a lexical score value assigning unit configured to assign a relative value of one of the lexical items to each of the lexical items as a lexical score value based on the relevant lexical identifiers and the relevant structure model tree identifiers, the value increasing with an increase of number of the lexical items having an identical relevant lexical identifier which matches with the lexical items having an identical relevant structure model tree identifier, and wherein when the query language conducts search processing including a plurality of keywords, and when combining processing of index information is executed in the search processing, the priority calculation unit calculates the priority processing levels of the processes for making the plan based on the lexical score values, the lowest processing cost, and the structure score values. | 0.833736 |
8,478,745 | 1 | 3 | 1. A computer implemented method for generating search result snippets, the method comprising: obtaining a first search results responsive to a first query during a search session, wherein each of the first search results refers to a respective content item; for each first search result, identifying a respective first snippet in the respective content item referred to by the first search result; obtaining a second search results responsive to a different second query during the same search session, wherein each of the second search results refers to a respective content item; identifying a repetitive content item, the repetitive content item being a content item that is referred to by both a particular first search result and a particular second search result; identifying a plurality of different second snippets in the respective content item; comparing the first snippet for the particular first search result with each of the plurality of different second snippets; based on the comparing selecting a particular second snippet different from the first snippet for the particular first search result as a snippet for the particular second search result, where selecting the particular second snippet is based at least in part on one or more weights assigned to each of the plurality of different second snippets; and a particular weight of the one or more assigned weights is determined based at least in part on a number of second search tokens from the second query that occur in the identified particular second snippet. | 1. A computer implemented method for generating search result snippets, the method comprising: obtaining a first search results responsive to a first query during a search session, wherein each of the first search results refers to a respective content item; for each first search result, identifying a respective first snippet in the respective content item referred to by the first search result; obtaining a second search results responsive to a different second query during the same search session, wherein each of the second search results refers to a respective content item; identifying a repetitive content item, the repetitive content item being a content item that is referred to by both a particular first search result and a particular second search result; identifying a plurality of different second snippets in the respective content item; comparing the first snippet for the particular first search result with each of the plurality of different second snippets; based on the comparing selecting a particular second snippet different from the first snippet for the particular first search result as a snippet for the particular second search result, where selecting the particular second snippet is based at least in part on one or more weights assigned to each of the plurality of different second snippets; and a particular weight of the one or more assigned weights is determined based at least in part on a number of second search tokens from the second query that occur in the identified particular second snippet. 3. The method of claim 1 wherein selecting the particular second snippet is based at least in part on one or more weights assigned to each of the plurality of different second snippets; and a particular weight of the one or more assigned weights is determined based at least in part on whether a portion of the second snippet was previously included in the first snippet during the search session. | 0.644902 |
7,970,759 | 1 | 4 | 1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference. | 1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference. 4. The computer implemented method of claim 1 wherein the first inference is further related to identifying a new use for the drug. | 0.91973 |
4,069,393 | 7 | 8 | 7. A method for receiving spoken input training words and a subsequent spoken input command word and generating a correlation function that is indicative of the resemblance of the command word to each training word, comprising the steps of: a. extracting features from received input words and generating digital feature output signals on particular ones of a number of feature output lines, the particular ones being dependent upon the features present in an input word; b. storing, as a time dependent matrix, the presence or absence status of the feature signals which occur during each training word; c. storing, as a time dependent matrix, the presence or absence status of the feature signals which occur during the command word; and d. comparing, member by member, the command word matrix with each training word matrix and generating a correlation figure which reflects each matrix comparison, the member comparison taking account only of the presence of features in the matrices being compared. | 7. A method for receiving spoken input training words and a subsequent spoken input command word and generating a correlation function that is indicative of the resemblance of the command word to each training word, comprising the steps of: a. extracting features from received input words and generating digital feature output signals on particular ones of a number of feature output lines, the particular ones being dependent upon the features present in an input word; b. storing, as a time dependent matrix, the presence or absence status of the feature signals which occur during each training word; c. storing, as a time dependent matrix, the presence or absence status of the feature signals which occur during the command word; and d. comparing, member by member, the command word matrix with each training word matrix and generating a correlation figure which reflects each matrix comparison, the member comparison taking account only of the presence of features in the matrices being compared. 8. The method as defined by claim 7 further comprising a step of time normalizing the training word matrices and the command word matrix before the comparisons thereof. | 0.86 |
10,078,411 | 1 | 9 | 1. A computer program product comprising one or more computer-readable physical storage media having stored thereon computer-executable instructions that are executable by one or more processors of a computing system to cause the computing system to perform a method for supporting an organization mode in which a plurality of user interface elements may be organized within a user interface, the method comprising: an act of displaying a canvas on the user interface, the canvas being subdivided into at least an extendable start board portion and a constituent element portion, the extendable start board portion being displayed simultaneously with the constituent element portion on the canvas, wherein: upon selection of any one user interface element in the extendable start board portion, the constituent element portion is updated to include a group of user interface elements that each corresponds to the selected any one user interface element, a size of the constituent element portion is dependent on a size of the extendable start board portion such that as the size of the extendable start board portion increases, the size of the constituent element portion decreases in response, and when the size of the constituent element portion decreases, an appearance of at least some elements in the group of user interface elements included in the constituent element portion is progressively cutoff to coincide with the decreasing size of the constituent element portion; an act of displaying a plurality of user interface elements on the extendable start board portion of the canvas so as to conform to a grid pattern having a plurality of grid positions on the extendable start board portion, each of the plurality of user interface elements occupying one or more of the grid positions of the plurality of grid positions and having boundaries corresponding to boundaries between grid positions; an act of detecting a user instruction representing an intent to organize one or more of the plurality of user interface elements on the canvas, the user interface entering the organization mode after the user instruction is received; an act of causing an appearance of at least some remaining user interface elements in the plurality to change such that the appearances are deemphasized, the at least some remaining user interface elements being elements that were not associated with the user instruction; an act of causing at least some of the plurality of grid positions to be displayed in response to the act of detecting the user instruction; and while in the organization mode and in response to selecting a particular user interface element, an act of causing a contextual actions menu to appear for the particular user interface element, the contextual actions menu displaying a subset of available commands, the displayed subset of available commands being commands that have been previously identified as being commonly used by a user while the user interacts with the user interface in the organization mode, the contextual actions menu being displayed simultaneously with the particular user interface element. | 1. A computer program product comprising one or more computer-readable physical storage media having stored thereon computer-executable instructions that are executable by one or more processors of a computing system to cause the computing system to perform a method for supporting an organization mode in which a plurality of user interface elements may be organized within a user interface, the method comprising: an act of displaying a canvas on the user interface, the canvas being subdivided into at least an extendable start board portion and a constituent element portion, the extendable start board portion being displayed simultaneously with the constituent element portion on the canvas, wherein: upon selection of any one user interface element in the extendable start board portion, the constituent element portion is updated to include a group of user interface elements that each corresponds to the selected any one user interface element, a size of the constituent element portion is dependent on a size of the extendable start board portion such that as the size of the extendable start board portion increases, the size of the constituent element portion decreases in response, and when the size of the constituent element portion decreases, an appearance of at least some elements in the group of user interface elements included in the constituent element portion is progressively cutoff to coincide with the decreasing size of the constituent element portion; an act of displaying a plurality of user interface elements on the extendable start board portion of the canvas so as to conform to a grid pattern having a plurality of grid positions on the extendable start board portion, each of the plurality of user interface elements occupying one or more of the grid positions of the plurality of grid positions and having boundaries corresponding to boundaries between grid positions; an act of detecting a user instruction representing an intent to organize one or more of the plurality of user interface elements on the canvas, the user interface entering the organization mode after the user instruction is received; an act of causing an appearance of at least some remaining user interface elements in the plurality to change such that the appearances are deemphasized, the at least some remaining user interface elements being elements that were not associated with the user instruction; an act of causing at least some of the plurality of grid positions to be displayed in response to the act of detecting the user instruction; and while in the organization mode and in response to selecting a particular user interface element, an act of causing a contextual actions menu to appear for the particular user interface element, the contextual actions menu displaying a subset of available commands, the displayed subset of available commands being commands that have been previously identified as being commonly used by a user while the user interacts with the user interface in the organization mode, the contextual actions menu being displayed simultaneously with the particular user interface element. 9. The computer program product in accordance with claim 1 , each of the plurality of user interface elements having one of a set of predetermined allowable shapes and sizes, each of the predetermined allowable shapes and sizes fitting over one or more grid positions. | 0.573248 |
8,938,463 | 26 | 27 | 26. The machine-readable storage of claim 19 wherein the search engine is further configured to use comparisons of the predictive outputs of the model with an implicit user feedback model to adjust respective ranking scores of the given search results. | 26. The machine-readable storage of claim 19 wherein the search engine is further configured to use comparisons of the predictive outputs of the model with an implicit user feedback model to adjust respective ranking scores of the given search results. 27. The machine-readable storage of claim 26 wherein the implicit user feedback model is a click fraction, and the search engine is configured to use a comparison of the predicted click through rate and the click fraction to adjust the respective ranking scores of the given search results, the comparison including at least one of a ratio of the predicted click through rate and the click fraction or a value difference between the predicted click through rate and the click fraction. | 0.863841 |
7,882,437 | 2 | 3 | 2. The method of claim 1 wherein identifying presentation documents for a presentation comprises: creating a data structure representing a presentation; and listing at least one presentation document in the data structure representing a presentation. | 2. The method of claim 1 wherein identifying presentation documents for a presentation comprises: creating a data structure representing a presentation; and listing at least one presentation document in the data structure representing a presentation. 3. The method of claim 2 wherein: listing the at least one presentation document includes storing a location of the presentation document in the data structure representing a presentation; and storing each presentation grammar includes retrieving a presentation grammar of the presentation document in dependence upon the location of the presentation document. | 0.864966 |
4,588,665 | 1 | 5 | 1. A micrographic film member comprising, a micrographic image having borders surrounding the image, and a strip of reflective-read direct-read-after-write laser recording material disposed in a border, said strip having laser written indicia thereon, said indicia related to the micrographic image. | 1. A micrographic film member comprising, a micrographic image having borders surrounding the image, and a strip of reflective-read direct-read-after-write laser recording material disposed in a border, said strip having laser written indicia thereon, said indicia related to the micrographic image. 5. The film member of claim 1 wherein said indicia comprises information relating to the sequencing of image portions within the micrographic image. | 0.503356 |
7,801,759 | 15 | 16 | 15. The system of claim 14 wherein the characterization is in the form of a score matrix having the plurality of attributes and wherein the selection of attributes is based on a business unit. | 15. The system of claim 14 wherein the characterization is in the form of a score matrix having the plurality of attributes and wherein the selection of attributes is based on a business unit. 16. The system of claim 15 wherein one of the attributes identifies the enterprise strategic initiative with which the enterprise development concept is aligned. | 0.977608 |
8,438,179 | 7 | 10 | 7. A trouble handling apparatus for putting trouble handling cases occurring in the past in an information system into knowledge data, and for recommending a handling method using a trouble handling knowledge obtained by putting the trouble handling cases into the knowledge data, and a symptom of a trouble when the trouble occurs, the trouble handling apparatus comprising: a storing unit; a processor that performs a process including: obtaining candidates of a handling method for a trouble requested to be handled by searching the trouble handling knowledge; recording to the storing unit a history of handling methods executed for each symptom and a history of candidates of the handling method at the time of the execution as handling history information; assigning priorities to the candidates of the handling method, with reference to the candidates of the handling method in the handling history information stored in the storing unit; returning to a handling request source the handling method for the trouble requested to be handled after assigning a priority to the handling method using assigned priority; and integrating, into one, handling history information having a plurality of common portions in handling history information recorded in the handling history management information, wherein: the assigning step assigns a higher priority to a handling method candidate effective also as to other symptoms being handled, as an appearance frequency of the candidates of the handling method in handling history information of the other symptoms being handled becomes higher, the appearance frequency recognized by referring to handling history information of the other symptoms being handled, the integrating step refers to pieces of handling history information within the handling history management information, compares the pieces of handling history information to determine whether a ratio of common portions to an entire history of handling methods is equal to or larger than a certain value, and determines that there are a plurality of common portions when the ratio of common portions is equal to or larger than the certain value. | 7. A trouble handling apparatus for putting trouble handling cases occurring in the past in an information system into knowledge data, and for recommending a handling method using a trouble handling knowledge obtained by putting the trouble handling cases into the knowledge data, and a symptom of a trouble when the trouble occurs, the trouble handling apparatus comprising: a storing unit; a processor that performs a process including: obtaining candidates of a handling method for a trouble requested to be handled by searching the trouble handling knowledge; recording to the storing unit a history of handling methods executed for each symptom and a history of candidates of the handling method at the time of the execution as handling history information; assigning priorities to the candidates of the handling method, with reference to the candidates of the handling method in the handling history information stored in the storing unit; returning to a handling request source the handling method for the trouble requested to be handled after assigning a priority to the handling method using assigned priority; and integrating, into one, handling history information having a plurality of common portions in handling history information recorded in the handling history management information, wherein: the assigning step assigns a higher priority to a handling method candidate effective also as to other symptoms being handled, as an appearance frequency of the candidates of the handling method in handling history information of the other symptoms being handled becomes higher, the appearance frequency recognized by referring to handling history information of the other symptoms being handled, the integrating step refers to pieces of handling history information within the handling history management information, compares the pieces of handling history information to determine whether a ratio of common portions to an entire history of handling methods is equal to or larger than a certain value, and determines that there are a plurality of common portions when the ratio of common portions is equal to or larger than the certain value. 10. The trouble handling apparatus according to claim 7 , wherein the assigning step assigns a higher priority to a handling method candidate, which is originally assigned with a higher priority, with reference to the handling history information. | 0.726164 |
7,490,288 | 1 | 2 | 1. A method for previewing documents on a computer system comprising the steps of: displaying a main document which contains a first hyperlink; displaying a first preview document, which is referred to by said first hyperlink, in response to an indication of said first hyperlink, whilst retaining said display of the main document, wherein said first preview document contains a second hyperlink; displaying a second preview document, which is referred to by said second hyperlink, in response to an indication of said second hyperlink whilst retaining said display of said first preview document and said display of said main document, wherein indicating each hyperlink to the computer system by positioning a pointer over the hyperlink; wherein each preview document is opened in a corresponding preview window, wherein when each preview document is opened, the pointer automatically moves to within the newly opened preview window, wherein said first preview document window remains open as long as the pointer remains in said second preview document window or a window corresponding to a subsequent preview document derived via a subsequent hyperlink in said second preview document, wherein when the pointer is moved from the second preview document window to the first preview document window, the second preview document window closes, wherein when the pointer is moved to a region not in said first preview document window or said second preview document window, or a window corresponding to a subsequent preview document derived via a subsequent hyperlink in said second preview document, both the first and second preview document windows close. | 1. A method for previewing documents on a computer system comprising the steps of: displaying a main document which contains a first hyperlink; displaying a first preview document, which is referred to by said first hyperlink, in response to an indication of said first hyperlink, whilst retaining said display of the main document, wherein said first preview document contains a second hyperlink; displaying a second preview document, which is referred to by said second hyperlink, in response to an indication of said second hyperlink whilst retaining said display of said first preview document and said display of said main document, wherein indicating each hyperlink to the computer system by positioning a pointer over the hyperlink; wherein each preview document is opened in a corresponding preview window, wherein when each preview document is opened, the pointer automatically moves to within the newly opened preview window, wherein said first preview document window remains open as long as the pointer remains in said second preview document window or a window corresponding to a subsequent preview document derived via a subsequent hyperlink in said second preview document, wherein when the pointer is moved from the second preview document window to the first preview document window, the second preview document window closes, wherein when the pointer is moved to a region not in said first preview document window or said second preview document window, or a window corresponding to a subsequent preview document derived via a subsequent hyperlink in said second preview document, both the first and second preview document windows close. 2. A method according to claim 1 further comprising the step of: in response to an indication of a displayed document being received by the computer system, removing from display any and all preview documents deriving from the indicated document. | 0.55914 |
9,866,516 | 8 | 12 | 8. An apparatus, comprising: a processor configured to: perform a natural language interpretation of a message posted on a website data source from an end user responsive to identifying the message posting being related to a predefined monitored entity; process the message to determine the user's topic of interest; generate a response to the message responsive to the user's topic of interest; and a transmitter configured to send the response to the end user; wherein the end user is identified by matching user specific information included in the message to pre-stored user specific information stored in a database. | 8. An apparatus, comprising: a processor configured to: perform a natural language interpretation of a message posted on a website data source from an end user responsive to identifying the message posting being related to a predefined monitored entity; process the message to determine the user's topic of interest; generate a response to the message responsive to the user's topic of interest; and a transmitter configured to send the response to the end user; wherein the end user is identified by matching user specific information included in the message to pre-stored user specific information stored in a database. 12. The apparatus of claim 8 , wherein the message includes an identification portion and a free format text portion and wherein the predefined monitored entity comprises at least one of a company name and a product name. | 0.721662 |
9,076,448 | 2 | 3 | 2. The method of claim 1 wherein receiving speech utterance signals further comprises receiving speech utterance signals representative of a speech based query issued by the user. | 2. The method of claim 1 wherein receiving speech utterance signals further comprises receiving speech utterance signals representative of a speech based query issued by the user. 3. The method of claim 2 , wherein the user utters the speech based query in response to a prompt issued to the user by the client device. | 0.94422 |
8,023,626 | 32 | 40 | 32. A system for providing language interpretation, comprising: an incoming call telephonic module associated with a language interpretation provider that (i) receives an incoming telephone call from a caller speaking a first language and having a business need that dials a language access telephone number to obtain language interpretation assistance and (ii) identifies, after the telephone call is initiated, the first language from a plurality of languages with a voice recognition system so as to provide the caller with an interpreter that can translate between the first language and a second language; and an outgoing call telephonic module that permits the interpreter to telephonically engage an agent representing a merchant that can serve the business need, wherein the agent speaks a second language and the interpreter translates a conversation between the caller and the agent. | 32. A system for providing language interpretation, comprising: an incoming call telephonic module associated with a language interpretation provider that (i) receives an incoming telephone call from a caller speaking a first language and having a business need that dials a language access telephone number to obtain language interpretation assistance and (ii) identifies, after the telephone call is initiated, the first language from a plurality of languages with a voice recognition system so as to provide the caller with an interpreter that can translate between the first language and a second language; and an outgoing call telephonic module that permits the interpreter to telephonically engage an agent representing a merchant that can serve the business need, wherein the agent speaks a second language and the interpreter translates a conversation between the caller and the agent. 40. The system of claim 32 , wherein the conversation between the caller and the agent relates to a business transaction between the caller and the merchant. | 0.91402 |
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