patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|---|---|---|
7,529,765 | 14 | 26 | 14. An apparatus having a central processing unit (CPU) and a memory coupled to said CPU comprising: training logic configured to train a probabilistic latent semantic analysis (PLSA) model, the training logic further configured to apply an expectation maximization algorithm utilizing a set of expectation maximization equations corresponding to a PLSA model based on using P(z|w); term identification logic configured to identify at least one new term w from a document d to be added to said trained PLSA model; term addition logic configured to incrementally add said at least one new term to said trained PLSA model, the term addition logic further configured to apply said expectation maximization algorithm utilizing only a subset comprising at least one of said expectation maximization equations, wherein parameters dependent on the new term w and the document d are used by the term addition logic, the set of expectation maximization equations comprising: P ( z ❘ d , w ) = P ( z ❘ d ) P ( z ❘ w ) / P ( z ) ∑ z ′ P ( z ′ ❘ d ) P ( z ′ ❘ w ) / P { z ′ ) ; P ( z ❘ w ) = ∑ d f ( d , w ) P ( z ❘ d , w ) ∑ d , z ′ f ( d , w ) P ( z ′ ❘ d , w ) ; P ( z ❘ d ) = ∑ w f ( d , w ) P ( z ❘ d , w ) ∑ w , z ′ f ( d , w ) P ( z ′ ❘ d , w ) ; and P ( z ) = ∑ d , w f ( d , w ) P ( z ❘ d , w ) ∑ d , w f ( d , w ) , wherein P(z) represents a probability of a latent class z, P(z|d) represents a probability of a latent class z given a document d, P(z|w) represents a probability of a latent class z given a term w, and f(d,w) represents the number of times the term w occurs in the document d, and wherein the term addition logic is further configured to keep track of a total count N when incrementally adding said at least one new term, wherein: N adj = N old + ∑ d new ∈ D new ∑ w ∈ W old ⋃ W new f ( d new , w ) ; P adj ( z ) = N old P old ( z ) + ∑ d new ∈ D new ∑ w ∈ W old ⋃ W new f ( d new , w ) P ( z ❘ d new , w ) N adj ; and wherein N adj represents an adjusted value of N, N old represents the previous value of N, d new represents the new document d, D new represents a collection of new documents D, W old represents a previous set of terms W, W new represents a new set of terms which replaces W, P old (z) represents the previous value of P(z), and P adj (z) represents a new value of P(z) which replaces the previous value of P(z); and presentation logic configured to present a model parameter from said trained PLSA model, the presented model parameter including at least one of an updated P(z|d) value and an updated P(z|w) value. | 14. An apparatus having a central processing unit (CPU) and a memory coupled to said CPU comprising: training logic configured to train a probabilistic latent semantic analysis (PLSA) model, the training logic further configured to apply an expectation maximization algorithm utilizing a set of expectation maximization equations corresponding to a PLSA model based on using P(z|w); term identification logic configured to identify at least one new term w from a document d to be added to said trained PLSA model; term addition logic configured to incrementally add said at least one new term to said trained PLSA model, the term addition logic further configured to apply said expectation maximization algorithm utilizing only a subset comprising at least one of said expectation maximization equations, wherein parameters dependent on the new term w and the document d are used by the term addition logic, the set of expectation maximization equations comprising: P ( z ❘ d , w ) = P ( z ❘ d ) P ( z ❘ w ) / P ( z ) ∑ z ′ P ( z ′ ❘ d ) P ( z ′ ❘ w ) / P { z ′ ) ; P ( z ❘ w ) = ∑ d f ( d , w ) P ( z ❘ d , w ) ∑ d , z ′ f ( d , w ) P ( z ′ ❘ d , w ) ; P ( z ❘ d ) = ∑ w f ( d , w ) P ( z ❘ d , w ) ∑ w , z ′ f ( d , w ) P ( z ′ ❘ d , w ) ; and P ( z ) = ∑ d , w f ( d , w ) P ( z ❘ d , w ) ∑ d , w f ( d , w ) , wherein P(z) represents a probability of a latent class z, P(z|d) represents a probability of a latent class z given a document d, P(z|w) represents a probability of a latent class z given a term w, and f(d,w) represents the number of times the term w occurs in the document d, and wherein the term addition logic is further configured to keep track of a total count N when incrementally adding said at least one new term, wherein: N adj = N old + ∑ d new ∈ D new ∑ w ∈ W old ⋃ W new f ( d new , w ) ; P adj ( z ) = N old P old ( z ) + ∑ d new ∈ D new ∑ w ∈ W old ⋃ W new f ( d new , w ) P ( z ❘ d new , w ) N adj ; and wherein N adj represents an adjusted value of N, N old represents the previous value of N, d new represents the new document d, D new represents a collection of new documents D, W old represents a previous set of terms W, W new represents a new set of terms which replaces W, P old (z) represents the previous value of P(z), and P adj (z) represents a new value of P(z) which replaces the previous value of P(z); and presentation logic configured to present a model parameter from said trained PLSA model, the presented model parameter including at least one of an updated P(z|d) value and an updated P(z|w) value. 26. apparatus of claim 14 , wherein said at least one new term is from a source document having content relating to a news story, an investigation, a transcript, a patent, an advertisement, a statute, a contract, a legal document, a product, an advertisement, a person, a technology, a laboratory, a research center, a technical paper, a device, a policy, a translation, a digital image, a digitized audio, or any information encoded into a series of codes, wherein said source document can be a government document, a newspaper, a printed document, an electronic document, a translated document, a document transcribed from speech, a legal document, an operations manual, a policy manual, a journal, a data file, a web page or an electronic-mail document. | 0.5 |
10,162,308 | 19 | 26 | 19. A non-transitory computer-readable medium including one or more sequences of instructions that, when executed by one or more processors, cause the processors to perform operations comprising: receiving, at a computer device and from an image capturing component, real-time image data; extracting one or more objects or a scene from the real-time image data based on results from real-time adaptive learning and one or more object/scene extraction parameters, wherein the real-time adaptive learning comprises object learning, object recognition, object segmentation, scene learning, scene recognition, scene segmentation, or a combination thereof; extracting one or more human objects from the real-time image data based on results from real-time adaptive human learning and one or more human extraction parameters, wherein the real-time adaptive human learning comprises human characteristic learning, human recognition, human segmentation, human body movement tracking, or a combination thereof; receiving augmented reality (AR) input data; and creating holographic AR image data by projecting, for each image, the extracted object or scene, the extracted human object, and the AR input data using a multi-layered mechanism based on projection parameters. | 19. A non-transitory computer-readable medium including one or more sequences of instructions that, when executed by one or more processors, cause the processors to perform operations comprising: receiving, at a computer device and from an image capturing component, real-time image data; extracting one or more objects or a scene from the real-time image data based on results from real-time adaptive learning and one or more object/scene extraction parameters, wherein the real-time adaptive learning comprises object learning, object recognition, object segmentation, scene learning, scene recognition, scene segmentation, or a combination thereof; extracting one or more human objects from the real-time image data based on results from real-time adaptive human learning and one or more human extraction parameters, wherein the real-time adaptive human learning comprises human characteristic learning, human recognition, human segmentation, human body movement tracking, or a combination thereof; receiving augmented reality (AR) input data; and creating holographic AR image data by projecting, for each image, the extracted object or scene, the extracted human object, and the AR input data using a multi-layered mechanism based on projection parameters. 26. The non-transitory computer-readable medium of claim 19 , wherein the one or more object/scene extraction parameters and the one or more human extraction parameters are the same. | 0.792237 |
9,645,989 | 1 | 10 | 1. An apparatus, comprising: a logic device at least partially implemented in hardware; and an application having a form manager component operative on the logic device to manage One or more forms for a user interface of the application during a run-time mode of the application, the form manner component having a custom prompt module operative to: determine whether an application context interface is available for a dynamic form prompt of a new form of the one or more forms, determine whether a custom language interface is available for the dynamic form prompt when the application context interface is available, and retrieve custom content in a custom presentation language for the dynamic form prompt when the custom language interface is available, the application context interface operative to: receive, from a first device over a network, a form prompt query for the new form, the form prompt query comprising a form prompt identifier and a location identifier, the form prompt identifier to uniquely identify the dynamic form prompt and the location identifier to uniquely identify a geographic location, determine a previous delegate is set for a previous form of the one or more forms, void, via a destroy method, the previous delegate used for the previous form, set a new delegate to automatically retrieve, from a second device over the network, the custom content utilizing the form prompt identifier and the location identifier for the new form, the custom language interface to: automatically retrieve, for the new form, the custom content in a custom presentation language for the dynamic form prompt from custom prompt information managed by a form information source, and send a form prompt response with the custom content to a form viewer arranged to present the new form; and the custom form prompt module to determine a user session has terminated for the new form, and release resources when the user session for the new form has terminated. | 1. An apparatus, comprising: a logic device at least partially implemented in hardware; and an application having a form manager component operative on the logic device to manage One or more forms for a user interface of the application during a run-time mode of the application, the form manner component having a custom prompt module operative to: determine whether an application context interface is available for a dynamic form prompt of a new form of the one or more forms, determine whether a custom language interface is available for the dynamic form prompt when the application context interface is available, and retrieve custom content in a custom presentation language for the dynamic form prompt when the custom language interface is available, the application context interface operative to: receive, from a first device over a network, a form prompt query for the new form, the form prompt query comprising a form prompt identifier and a location identifier, the form prompt identifier to uniquely identify the dynamic form prompt and the location identifier to uniquely identify a geographic location, determine a previous delegate is set for a previous form of the one or more forms, void, via a destroy method, the previous delegate used for the previous form, set a new delegate to automatically retrieve, from a second device over the network, the custom content utilizing the form prompt identifier and the location identifier for the new form, the custom language interface to: automatically retrieve, for the new form, the custom content in a custom presentation language for the dynamic form prompt from custom prompt information managed by a form information source, and send a form prompt response with the custom content to a form viewer arranged to present the new form; and the custom form prompt module to determine a user session has terminated for the new form, and release resources when the user session for the new form has terminated. 10. The apparatus of claim 1 , the custom language interface operative to retrieve the custom content from the form information source storing custom prompt information in a local datastore. | 0.714715 |
10,089,901 | 4 | 5 | 4. The apparatus for bi-directional sign language/speech translation in real time of claim 2 , wherein the sign outputter comprises: a display mode controller configured to control an output based on a display mode to display one of a sign and a text corresponding to the recognized speech; and an outputter configured to output a sign mapped to the generated sign index or a text corresponding to the sign mapped to the generated sign index based on the display mode. | 4. The apparatus for bi-directional sign language/speech translation in real time of claim 2 , wherein the sign outputter comprises: a display mode controller configured to control an output based on a display mode to display one of a sign and a text corresponding to the recognized speech; and an outputter configured to output a sign mapped to the generated sign index or a text corresponding to the sign mapped to the generated sign index based on the display mode. 5. The apparatus for bi-directional sign language/speech translation in real time of claim 4 , wherein the display mode controller is configured to control the display mode of the outputter based on a sign display event or a generation period of the sign mapped to the sign index. | 0.5 |
9,684,908 | 9 | 14 | 9. The server of claim 8 , wherein: the server further comprises a comparison template set comprising at least one comparison template; and the comparison generator further identifies the first comparison as the selected comparison by, among the comparison templates of the comparison template set, identifying a selected comparison template according to comparison relevance scores of comparisons of the comparison set. | 9. The server of claim 8 , wherein: the server further comprises a comparison template set comprising at least one comparison template; and the comparison generator further identifies the first comparison as the selected comparison by, among the comparison templates of the comparison template set, identifying a selected comparison template according to comparison relevance scores of comparisons of the comparison set. 14. The server of claim 9 , wherein: the respective comparison templates comprise a comparison question template. | 0.892992 |
8,433,693 | 1 | 8 | 1. A method, comprising: receiving a request to modify a data file by an application program at a client device; determining a file type for the data file where the file type is one of an immutable file type, a locking required file type, and a locking preferred file type; accessing a set of file access rules based on the file type; and determining whether the application program has permission to modify the data file based on the file access rules, wherein the file access rules require a network connection to a locking server for editing when the file type is the locking required file type, the file access rules do not require the network connection to the locking server for editing when the file type is the immutable file type, and the file access rules for the locking preferred file type only require the network connection to the locking server for editing when the network connection to the locking server is available, wherein a lock is granted to the application program if the file type is the locking preferred file type and the network connection to the locking server is not available. | 1. A method, comprising: receiving a request to modify a data file by an application program at a client device; determining a file type for the data file where the file type is one of an immutable file type, a locking required file type, and a locking preferred file type; accessing a set of file access rules based on the file type; and determining whether the application program has permission to modify the data file based on the file access rules, wherein the file access rules require a network connection to a locking server for editing when the file type is the locking required file type, the file access rules do not require the network connection to the locking server for editing when the file type is the immutable file type, and the file access rules for the locking preferred file type only require the network connection to the locking server for editing when the network connection to the locking server is available, wherein a lock is granted to the application program if the file type is the locking preferred file type and the network connection to the locking server is not available. 8. The method of claim 1 , comprising: determining the file type is a locking preferred file type; determining whether a network connection to a locking server is available; sending a lock request to lock the data file to the locking server when the network connection is available; and denying permission to modify the file when the lock request is denied by the locking server. | 0.502625 |
9,058,315 | 2 | 3 | 2. The method of claim 1 comprising modifying a second value associated with the first parameter to equal the first value associated with the first node. | 2. The method of claim 1 comprising modifying a second value associated with the first parameter to equal the first value associated with the first node. 3. The method of claim 2 , wherein evaluating the second document comprises modifying a third value associated with the second parameter included in the second document based on the second value associated with the first parameter. | 0.524691 |
7,729,913 | 19 | 22 | 19. A method for conducting database searches by telephone, the method comprising: receiving a sequence of N character utterances from a telephone user, said character utterances corresponding to respective characters of a search query; receiving an utterance of the search query from the user; interpreting the sequence of character utterances to generate a sequence of N characters; translating the sequence of N characters to a corresponding sequence of N telephone digits; and selecting a speech recognition grammar that corresponds to the sequence of N telephone digits, said speech recognition grammar corresponding to multiple different possible N-character sequences; and interpreting the utterance of the search query using the selected speech recognition grammar to generate a textual representation of the search query; wherein N is less than the number of characters in the search query as uttered by the user such that the user need not verbally spell the entire search query; wherein the method is performed by a system that comprises computer hardware; wherein the speech recognition grammar is selected from a repository of pre-generated speech recognition grammars in which different speech recognition grammars correspond to different sequences of N telephone digits, said repository of pre-generated speech recognition grammars generated by subdividing a master grammar set based on the first N characters of entries in said master grammar set. | 19. A method for conducting database searches by telephone, the method comprising: receiving a sequence of N character utterances from a telephone user, said character utterances corresponding to respective characters of a search query; receiving an utterance of the search query from the user; interpreting the sequence of character utterances to generate a sequence of N characters; translating the sequence of N characters to a corresponding sequence of N telephone digits; and selecting a speech recognition grammar that corresponds to the sequence of N telephone digits, said speech recognition grammar corresponding to multiple different possible N-character sequences; and interpreting the utterance of the search query using the selected speech recognition grammar to generate a textual representation of the search query; wherein N is less than the number of characters in the search query as uttered by the user such that the user need not verbally spell the entire search query; wherein the method is performed by a system that comprises computer hardware; wherein the speech recognition grammar is selected from a repository of pre-generated speech recognition grammars in which different speech recognition grammars correspond to different sequences of N telephone digits, said repository of pre-generated speech recognition grammars generated by subdividing a master grammar set based on the first N characters of entries in said master grammar set. 22. The method of claim 19 , wherein N=3 or 4. | 0.907631 |
8,838,438 | 11 | 14 | 11. The method of claim 1 , wherein the user-generated text content corresponds to a user feedback of a business establishment or product, and wherein the sentiment value corresponds to a sentiment of a user's experience with the business establishment or product. | 11. The method of claim 1 , wherein the user-generated text content corresponds to a user feedback of a business establishment or product, and wherein the sentiment value corresponds to a sentiment of a user's experience with the business establishment or product. 14. The method of claim 11 , wherein the business establishment or product corresponds to a restaurant or food item. | 0.648485 |
7,580,429 | 4 | 5 | 4. The method of claim 1 further comprising storing a history index which records when the nodes are used to represent subsequent strings of data. | 4. The method of claim 1 further comprising storing a history index which records when the nodes are used to represent subsequent strings of data. 5. The method of claim 4 wherein the deletion and addition of the original fixed sized code word node includes: establishing a priority queue to record nodes in the order they are used to represent subsequent strings of data; updating the history index of the original fixed sized code word node and moving the record of the node to the start of priority queue. | 0.5 |
9,205,557 | 1 | 2 | 1. A system for editing and controlling physical behaviors of at least one robot by a user having access to a graphical interface, comprising: a computer configured to implement a module for editing any text to be spoken by the robot; a sound synthesis device comprising a sound synthesis module for synthesizing said text; a library of command tags stored on the computer for effectuating physical behaviors to be executed by the robot, said command tags being graphic symbols representative of said physical behaviors; and the computer configured to implement a module for inserting said tags into said text and a module for generating and controlling the physical behaviors of said robot, said system being configured to allow a selection of at least one of command tag in the library, said library being distinct from the text to be spoken, and to allow an insertion of said tag in a sequence of words of said text to launch an execution of a behavior defined by a graphic symbol and concomitant with saying said text to be spoken. | 1. A system for editing and controlling physical behaviors of at least one robot by a user having access to a graphical interface, comprising: a computer configured to implement a module for editing any text to be spoken by the robot; a sound synthesis device comprising a sound synthesis module for synthesizing said text; a library of command tags stored on the computer for effectuating physical behaviors to be executed by the robot, said command tags being graphic symbols representative of said physical behaviors; and the computer configured to implement a module for inserting said tags into said text and a module for generating and controlling the physical behaviors of said robot, said system being configured to allow a selection of at least one of command tag in the library, said library being distinct from the text to be spoken, and to allow an insertion of said tag in a sequence of words of said text to launch an execution of a behavior defined by a graphic symbol and concomitant with saying said text to be spoken. 2. The system according to claim 1 , wherein at least some of the command tags are inserted into the text between at least one opening separator and at least one closing separator, which respectively trigger a start of a series of the physical behaviors and an end of said series. | 0.598854 |
9,977,828 | 1 | 11 | 1. A method of handling event data received by a mobile device, comprising: obtaining the event data from a plurality of applications; generating a filtered set of event data by filtering out, from the event data, at least a subset of the event data based on pre-determined filtering rules that are independent of any pre-determined grouping rules; determining whether grouping candidate event data exists in the filtered set of event data; in accordance with a determination that grouping candidate event data exists in the filtered set of event data, applying the pre-determined grouping rules to the filtered set of event data to generate one or more groups within the filtered set of event data; and in accordance with a determination that grouping candidate event data does not exist in the filtered set of event data, foregoing applying the pre-determined grouping rules to the filtered set of event data; applying pre-determined auto-filing rules to the filtered set of event data, wherein the pre-determined auto-filing rules: automatically store a first portion of the filtered set of event data; and generate a remainder set of event data from a second portion of the filtered set of event data, different from the first portion of the filtered set of event data, wherein the second portion of the filtered set of event data is not automatically stored, wherein the pre-determined auto-filing rules are separate from the pre-determined grouping rules, and wherein the pre-determined auto-filing rules are not applied until after the pre-determined grouping rules are applied; and, displaying, on a display of the mobile device, a user interface that displays content that corresponds to one or more events of the remainder set of the event data, wherein the content that corresponds to the one or more events of the remainder set of the event data includes grouped content that corresponds to at least one of the one or more groups within the filtered set of data. | 1. A method of handling event data received by a mobile device, comprising: obtaining the event data from a plurality of applications; generating a filtered set of event data by filtering out, from the event data, at least a subset of the event data based on pre-determined filtering rules that are independent of any pre-determined grouping rules; determining whether grouping candidate event data exists in the filtered set of event data; in accordance with a determination that grouping candidate event data exists in the filtered set of event data, applying the pre-determined grouping rules to the filtered set of event data to generate one or more groups within the filtered set of event data; and in accordance with a determination that grouping candidate event data does not exist in the filtered set of event data, foregoing applying the pre-determined grouping rules to the filtered set of event data; applying pre-determined auto-filing rules to the filtered set of event data, wherein the pre-determined auto-filing rules: automatically store a first portion of the filtered set of event data; and generate a remainder set of event data from a second portion of the filtered set of event data, different from the first portion of the filtered set of event data, wherein the second portion of the filtered set of event data is not automatically stored, wherein the pre-determined auto-filing rules are separate from the pre-determined grouping rules, and wherein the pre-determined auto-filing rules are not applied until after the pre-determined grouping rules are applied; and, displaying, on a display of the mobile device, a user interface that displays content that corresponds to one or more events of the remainder set of the event data, wherein the content that corresponds to the one or more events of the remainder set of the event data includes grouped content that corresponds to at least one of the one or more groups within the filtered set of data. 11. A method, according to claim 1 , including: detecting user input for at least one of: storing first data from the remainder set of the event data; deleting second data from the remainder set of the event data; or grouping third data from the remainder set of the event data with previously stored event data. | 0.504762 |
7,530,021 | 20 | 21 | 20. A computer-readable storage medium having computer-executable instructions for performing a method of generating a meeting preparation document, comprising: receiving a request to generate the meeting preparation document; accessing at least one of a public data source and a private data source to retrieve relevant meeting information; arranging the relevant meeting information into a personalized format for a user present in an organizational chart wherein profiles of attendees are arranged according to their respective decreasing organizational chart distance relative to the user wherein the organizational chart distance is a shortest path between the user and an attendee within the organizational chart, wherein the organizational chart distance is a sum of the attendee's and the user's organizational chart distance to a manager common to the user and the attendee; and generating the meeting preparation document according to the personalized format. | 20. A computer-readable storage medium having computer-executable instructions for performing a method of generating a meeting preparation document, comprising: receiving a request to generate the meeting preparation document; accessing at least one of a public data source and a private data source to retrieve relevant meeting information; arranging the relevant meeting information into a personalized format for a user present in an organizational chart wherein profiles of attendees are arranged according to their respective decreasing organizational chart distance relative to the user wherein the organizational chart distance is a shortest path between the user and an attendee within the organizational chart, wherein the organizational chart distance is a sum of the attendee's and the user's organizational chart distance to a manager common to the user and the attendee; and generating the meeting preparation document according to the personalized format. 21. The medium of claim 20 , the public and private data sources include at least one of e-mail, an image, a shared data source, a user profile, a document relevant to the event, and an e-mail attachment. | 0.5 |
9,678,518 | 19 | 20 | 19. The thermostat of claim 1 , wherein the thermostat includes a gateway to distribute appliance data between the at least one appliance and the remote controller. | 19. The thermostat of claim 1 , wherein the thermostat includes a gateway to distribute appliance data between the at least one appliance and the remote controller. 20. The thermostat of claim 19 , wherein the gateway is housed separately from the thermostat. | 0.5 |
8,606,815 | 7 | 12 | 7. A system for systematically analyzing an electronic text, comprising: a receiver to receive the electronic text from a plurality of sources; a processor coupled to the receiver to: determine an at least one term of interest to be identified in the electronic text; identify a plurality of locations within the electronic text including the at least one term of interest; create for each location within a plurality of locations a snippet from a text segment around the at least one term of interest at the location within the electronic text; create multiple taxonomies for the at least one term of interest from the snippets, wherein the taxonomies include an at least one category, the at least one category including a sentiment based taxonomy; and determine between categories of a different taxonomies of the multiple taxonomies by determining: co-occurrence between the multiple taxonomies; wherein at least one of the taxonomies is a time based taxonomy that is based on the creation date of the electronic text, the time based taxonomy generated by: crawling sources of electronic text to extract the creation dates; attaching an extracted creation date to a respective snippet to generate a dated snippet; and organizing the dated snippets into chronologically contiguous categories; and a module in electrical communication with the processor, the module configured to determine co-occurrences for a single taxonomy against a term feature space to determine significance of the at least one term of interest; and a module to sort the at least one term of interest by significance, wherein the sentiment based taxonomy is determined by: creating a list of positive, negative and neutral terms indicative of different sentiments, respectively; determining the level of sentiment corresponding to the at least one term generated from a respective snippet based on an assigned value; normalizing the values to generate at least one term having a sentiment score corresponding thereto, the sentiment score including at least one of a positive sentiment score and a negative sentiment score; and sorting snippets of the electronic text based on a calculated sentiment score differential between the at least one positive sentiment score and the at least one negative sentiment score. | 7. A system for systematically analyzing an electronic text, comprising: a receiver to receive the electronic text from a plurality of sources; a processor coupled to the receiver to: determine an at least one term of interest to be identified in the electronic text; identify a plurality of locations within the electronic text including the at least one term of interest; create for each location within a plurality of locations a snippet from a text segment around the at least one term of interest at the location within the electronic text; create multiple taxonomies for the at least one term of interest from the snippets, wherein the taxonomies include an at least one category, the at least one category including a sentiment based taxonomy; and determine between categories of a different taxonomies of the multiple taxonomies by determining: co-occurrence between the multiple taxonomies; wherein at least one of the taxonomies is a time based taxonomy that is based on the creation date of the electronic text, the time based taxonomy generated by: crawling sources of electronic text to extract the creation dates; attaching an extracted creation date to a respective snippet to generate a dated snippet; and organizing the dated snippets into chronologically contiguous categories; and a module in electrical communication with the processor, the module configured to determine co-occurrences for a single taxonomy against a term feature space to determine significance of the at least one term of interest; and a module to sort the at least one term of interest by significance, wherein the sentiment based taxonomy is determined by: creating a list of positive, negative and neutral terms indicative of different sentiments, respectively; determining the level of sentiment corresponding to the at least one term generated from a respective snippet based on an assigned value; normalizing the values to generate at least one term having a sentiment score corresponding thereto, the sentiment score including at least one of a positive sentiment score and a negative sentiment score; and sorting snippets of the electronic text based on a calculated sentiment score differential between the at least one positive sentiment score and the at least one negative sentiment score. 12. The system of claim 7 , wherein the electronic text is web based. | 0.915648 |
6,128,612 | 5 | 6 | 5. The data processing system of claim 4, further comprising means, if all items in the postfix queue have been processed, for forming a common table expression to return items represented by the last expression in the second temporary pushdown stack; for removing the last expression from the second temporary pushdown stack; and for forming a final SELECT statement. | 5. The data processing system of claim 4, further comprising means, if all items in the postfix queue have been processed, for forming a common table expression to return items represented by the last expression in the second temporary pushdown stack; for removing the last expression from the second temporary pushdown stack; and for forming a final SELECT statement. 6. The data processing system of claim 5, wherein the means for forming a final SELECT statement includes means for forming a SELECT statement to select all relevant fields using a "JOIN" of ids resulting from the last common table expression and ids found in an original parent table of a relational database. | 0.5 |
8,112,268 | 1 | 4 | 1. A computer-readable medium containing instructions for controlling a computer system to rank documents, by a method comprising: providing a sentence classifier to classify sentences into classifications of sentences; training a document rank classifier by representing each document of training data by the classifications of its sentences as determined by the sentence classifier and a rank of each document; representing a document by the classifications of its sentences as determined by the sentence classifier; and applying the trained document rank classifier to the representation of the document to determine the rank of the document. | 1. A computer-readable medium containing instructions for controlling a computer system to rank documents, by a method comprising: providing a sentence classifier to classify sentences into classifications of sentences; training a document rank classifier by representing each document of training data by the classifications of its sentences as determined by the sentence classifier and a rank of each document; representing a document by the classifications of its sentences as determined by the sentence classifier; and applying the trained document rank classifier to the representation of the document to determine the rank of the document. 4. The computer-readable medium of claim 1 wherein the sentence classifications include declarative, imperative, interrogative, and exclamatory. | 0.873462 |
9,477,446 | 11 | 15 | 11. A non-transitory computer-readable medium for building an integrated system using a formal language, the non-transitory computer-readable medium having computer instructions stored thereon that are executable by a processing device to perform or control performance of steps comprising: designing one or more models for one or more software components to be included in the integrated system, wherein the one or more models describe one or more requirements for the one or more software components; assigning one or more contracts to the one or more models, wherein the one or more contracts are written in the formal language and the one or more contracts include one or more low-level contracts and one or more high-level contracts; integrating the one or more models based on the composition of the one or more contracts to form an integrated model, wherein the integrated model includes each requirement for the one or more software components which is described by the one or more models which form the integrated model; and analyzing the one or more contracts and the integrated model to determine whether the one or more contracts include each requirement described by the integrated model, wherein the one or more low-level contracts are designed relative to the one or more high-level contracts so that analysis of the one or more low-level contracts alone indicates whether an error will be present in the one or more high-level contracts. | 11. A non-transitory computer-readable medium for building an integrated system using a formal language, the non-transitory computer-readable medium having computer instructions stored thereon that are executable by a processing device to perform or control performance of steps comprising: designing one or more models for one or more software components to be included in the integrated system, wherein the one or more models describe one or more requirements for the one or more software components; assigning one or more contracts to the one or more models, wherein the one or more contracts are written in the formal language and the one or more contracts include one or more low-level contracts and one or more high-level contracts; integrating the one or more models based on the composition of the one or more contracts to form an integrated model, wherein the integrated model includes each requirement for the one or more software components which is described by the one or more models which form the integrated model; and analyzing the one or more contracts and the integrated model to determine whether the one or more contracts include each requirement described by the integrated model, wherein the one or more low-level contracts are designed relative to the one or more high-level contracts so that analysis of the one or more low-level contracts alone indicates whether an error will be present in the one or more high-level contracts. 15. The non-transitory computer-readable medium of claim 11 , wherein the integrated system includes an embedded system. | 0.815385 |
8,868,670 | 19 | 20 | 19. The system of claim 12 , wherein selecting the exactly one of the first sentence or the second sentence is further based on: (v) a third number of the first overlapping words; (vi) a fourth number of the second overlapping words. | 19. The system of claim 12 , wherein selecting the exactly one of the first sentence or the second sentence is further based on: (v) a third number of the first overlapping words; (vi) a fourth number of the second overlapping words. 20. The system of claim 19 , wherein selecting the exactly one of the first sentence or the second sentence comprises: computing a first score for the first sentence, the first score equaling the third number divided by the first number; computing a second score for the second sentence, the second score equaling the fourth number divided by the second number; when the first score is higher than the second score, selecting the first sentence as the summary text; and when the second score is higher than the first score, selecting the second sentence as the summary text. | 0.5 |
7,937,401 | 8 | 10 | 8. The method of claim 7 , further comprising generating the procedure utilizing an object-oriented procedural programming language and an object model exposing query language objects to the object-oriented procedural programming language. | 8. The method of claim 7 , further comprising generating the procedure utilizing an object-oriented procedural programming language and an object model exposing query language objects to the object-oriented procedural programming language. 10. The method of claim 8 , further comprising compiling the procedure and storing the compiled procedure to the data store. | 0.624242 |
8,752,011 | 1 | 31 | 1. A method for automatically generating a user interface for a computer program using programming patterns, the method comprising: analyzing application objects of an application computer program to identify programming patterns, wherein each programming pattern is a relationship among signatures of application methods in one of the application objects, and wherein the signatures of the application methods comprise public interfaces of the application methods; automatically generating a user interface for the computer program, wherein automatically generating a user interface includes providing for at least one of a user and a programmer of the computer program to customize mappings between the application objects and user interface elements, wherein the user interface elements include at least one of user interface widgets and speech grammar rules, wherein the identified programming patterns include at least one of an undo pattern, a structure pattern, a graphical pattern, a validation pattern, and a precondition pattern, and wherein the undo pattern identifies, for each application method a pattern-based executed-command-object that can undo/redo the method, wherein the pattern-based executed-command-object comprises an executed-command object that uses at least one of: (a) relationships among the signatures of the application methods in and (b) antonym dictionaries to implement the undo and redo operations, and wherein the executed-command object is an object that provides operations to undo and redo each application method. | 1. A method for automatically generating a user interface for a computer program using programming patterns, the method comprising: analyzing application objects of an application computer program to identify programming patterns, wherein each programming pattern is a relationship among signatures of application methods in one of the application objects, and wherein the signatures of the application methods comprise public interfaces of the application methods; automatically generating a user interface for the computer program, wherein automatically generating a user interface includes providing for at least one of a user and a programmer of the computer program to customize mappings between the application objects and user interface elements, wherein the user interface elements include at least one of user interface widgets and speech grammar rules, wherein the identified programming patterns include at least one of an undo pattern, a structure pattern, a graphical pattern, a validation pattern, and a precondition pattern, and wherein the undo pattern identifies, for each application method a pattern-based executed-command-object that can undo/redo the method, wherein the pattern-based executed-command-object comprises an executed-command object that uses at least one of: (a) relationships among the signatures of the application methods in and (b) antonym dictionaries to implement the undo and redo operations, and wherein the executed-command object is an object that provides operations to undo and redo each application method. 31. The method of claim 1 wherein analyzing the computer program to identify an undo pattern includes analyzing method names to identify names that are antonyms of each other and wherein generating the user interface tool for implementing the undo operation includes, after execution of a method M with an antonym A, providing the ability, via the user interface tool, for the user to execute the antonym A. | 0.705499 |
8,285,048 | 1 | 3 | 1. A method of classifying a character string formed from a known number of hand-written characters, said method comprising the steps of: identifying by a processor character templates having the known number of characters, each character template having a respective predetermined probability of occurrence in a text corpus and representing a respective combination of character types; determining by a processor character probabilities for each hand-written character in the character string, each character probability representing a likelihood of the respective hand-written character being a respective one of a plurality of predetermined characters, each predetermined character having a respective character type; determining by the processor character sequence probabilities corresponding to each of the character templates having the known number of characters, the character sequence probabilities being a function of the predetermined probability of the respective character template and the character probabilities of the hand-written characters in the character string matching the character types of the character template; and classifying by the processor the character string as the sequence of characters having the highest character sequence probability. | 1. A method of classifying a character string formed from a known number of hand-written characters, said method comprising the steps of: identifying by a processor character templates having the known number of characters, each character template having a respective predetermined probability of occurrence in a text corpus and representing a respective combination of character types; determining by a processor character probabilities for each hand-written character in the character string, each character probability representing a likelihood of the respective hand-written character being a respective one of a plurality of predetermined characters, each predetermined character having a respective character type; determining by the processor character sequence probabilities corresponding to each of the character templates having the known number of characters, the character sequence probabilities being a function of the predetermined probability of the respective character template and the character probabilities of the hand-written characters in the character string matching the character types of the character template; and classifying by the processor the character string as the sequence of characters having the highest character sequence probability. 3. The method of claim 1 , wherein the function is of the predetermined probability of the respective character template and the highest character probabilities having character types corresponding to the combination of character types represented by the respective character template. | 0.5 |
9,633,674 | 30 | 31 | 30. The non-transitory computer readable storage medium of claim 23 , further comprising: upon determining that the user interaction indicates an absence of a problem, perform at least one of: avoiding to store the information relating to the request in the repository, and removing the information relating to the request from the repository. | 30. The non-transitory computer readable storage medium of claim 23 , further comprising: upon determining that the user interaction indicates an absence of a problem, perform at least one of: avoiding to store the information relating to the request in the repository, and removing the information relating to the request from the repository. 31. The non-transitory computer readable storage medium of claim 30 , wherein the performance of at least one of: avoiding to store the information relating to the request in the repository, and removing the information relating to the request from the repository comprises: if the information relating to the request is absent in the repository, avoiding to store information relating to the request in the repository; or if the information relating to the request is stored in the repository, removing the information relating to the request from the repository. | 0.5 |
9,201,967 | 5 | 11 | 5. A system, comprising: at least one computing device comprising a processor and a memory; and an application stored in the memory and comprising instructions executable by the processor of the at least one computing device, wherein the application, when executed, causes the at least one computing device to at least: access a catalog that organizes a plurality of items into a categorical hierarchy, wherein each item is expressed in terms of a product description; parse at least a portion of the product descriptions associated with a selected category to generate a plurality of keywords for the selected category; select a subset of the plurality of keywords; generate at least one rule based on the subset, wherein an application of the at least one rule specifies a respective binary result depending upon whether the subset of the plurality of keywords is included in a prospective seller product description; apply the at least one rule to the prospective seller product description to determine that the prospective seller product description expresses an item within the selected category; calculate a percentage of a plurality of product descriptions correctly categorized with the at least one rule; and update the at least one rule based at least in part on the calculated percentage. | 5. A system, comprising: at least one computing device comprising a processor and a memory; and an application stored in the memory and comprising instructions executable by the processor of the at least one computing device, wherein the application, when executed, causes the at least one computing device to at least: access a catalog that organizes a plurality of items into a categorical hierarchy, wherein each item is expressed in terms of a product description; parse at least a portion of the product descriptions associated with a selected category to generate a plurality of keywords for the selected category; select a subset of the plurality of keywords; generate at least one rule based on the subset, wherein an application of the at least one rule specifies a respective binary result depending upon whether the subset of the plurality of keywords is included in a prospective seller product description; apply the at least one rule to the prospective seller product description to determine that the prospective seller product description expresses an item within the selected category; calculate a percentage of a plurality of product descriptions correctly categorized with the at least one rule; and update the at least one rule based at least in part on the calculated percentage. 11. The system of claim 5 , wherein at least one of the plurality of keywords comprises at least one of a negative keyword, a bi-gram, or a tri-gram. | 0.87066 |
8,180,810 | 6 | 10 | 6. A method for schema integration comprising: recasting a first source schema into a first graph of concepts with HasA relationships; recasting a second source schema into a second graph of concepts with HasA relationships; identifying matching concepts in the first graph and the second graph based on correspondences between attributes of the concepts; enumerating the first graph of concepts and the second graph of concepts to output a plurality of integrated schemas that consider choices of concepts that merge and concepts that do not merge; applying enumeration constraints to determine how the concepts merge; and systematically determining alternative integrated schemas and associated mappings, based on identifying possible choices of matching concepts to merge to produce an integrated schema from the plurality of integrated schemas. | 6. A method for schema integration comprising: recasting a first source schema into a first graph of concepts with HasA relationships; recasting a second source schema into a second graph of concepts with HasA relationships; identifying matching concepts in the first graph and the second graph based on correspondences between attributes of the concepts; enumerating the first graph of concepts and the second graph of concepts to output a plurality of integrated schemas that consider choices of concepts that merge and concepts that do not merge; applying enumeration constraints to determine how the concepts merge; and systematically determining alternative integrated schemas and associated mappings, based on identifying possible choices of matching concepts to merge to produce an integrated schema from the plurality of integrated schemas. 10. The method as claimed in claim 6 wherein the systematically determining avoids exploring configurations that output a duplicate alternative integrated schema. | 0.5 |
7,680,783 | 10 | 16 | 10. A search system comprising a computer-readable storage medium storing instructions to be executed by a processor, the instructions, when executed, implementing: an identification strategy associating a parsing grammar in a data entry field with a search algorithm, the parsing grammar comprising parsing grammar rules which split data into a plurality of token names, each token name identifying data in a section of a grammatical statement; a plurality of expression formats, at least one expression format preceding each of the plurality of token names, each expression format representing a number of alphanumeric characters of the identified data of the token name that the expression format precedes; and a punctuation, the punctuation separating each of the plurality of token names; the search algorithm comprising search rules, a search rule producing a query identifying a field in a database to be searched using the data identified by at least one token name in the parsing grammar; a configuration interface displayed on a computer display, the configuration interface receiving a change to the identification strategy; a configuration engine which updates the identification strategy to reflect the change; an application interface displayed on one of the computer display and a second computer display, the application interface receiving search data in the data entry field; a parsing engine to apply the parsing grammar to split the search data by: checking whether the entered data contains the punctuation; checking whether the entered data before the punctuation contains the number of alphanumeric characters required by the expression format for the token name preceding the punctuation; and checking whether the entered data after the punctuation contains the number of alphanumeric characters required by the expression format for the token name following the punctuation; a query generating engine to apply the search algorithm to produce a search query using at least a portion of the search data corresponding to at least one token name; and a search engine to execute the search query in a database to produce and return a results set. | 10. A search system comprising a computer-readable storage medium storing instructions to be executed by a processor, the instructions, when executed, implementing: an identification strategy associating a parsing grammar in a data entry field with a search algorithm, the parsing grammar comprising parsing grammar rules which split data into a plurality of token names, each token name identifying data in a section of a grammatical statement; a plurality of expression formats, at least one expression format preceding each of the plurality of token names, each expression format representing a number of alphanumeric characters of the identified data of the token name that the expression format precedes; and a punctuation, the punctuation separating each of the plurality of token names; the search algorithm comprising search rules, a search rule producing a query identifying a field in a database to be searched using the data identified by at least one token name in the parsing grammar; a configuration interface displayed on a computer display, the configuration interface receiving a change to the identification strategy; a configuration engine which updates the identification strategy to reflect the change; an application interface displayed on one of the computer display and a second computer display, the application interface receiving search data in the data entry field; a parsing engine to apply the parsing grammar to split the search data by: checking whether the entered data contains the punctuation; checking whether the entered data before the punctuation contains the number of alphanumeric characters required by the expression format for the token name preceding the punctuation; and checking whether the entered data after the punctuation contains the number of alphanumeric characters required by the expression format for the token name following the punctuation; a query generating engine to apply the search algorithm to produce a search query using at least a portion of the search data corresponding to at least one token name; and a search engine to execute the search query in a database to produce and return a results set. 16. The system of claim 10 , wherein the configuration interface comprises a first text input field which receives changes to the parsing grammar and a second text input field which receives changes to the search algorithm. | 0.5 |
7,853,597 | 12 | 13 | 12. The computerized system of claim 9 , wherein the product line extractor builds a token tree starting with brand tokens as a tree root. | 12. The computerized system of claim 9 , wherein the product line extractor builds a token tree starting with brand tokens as a tree root. 13. The computerized system of claim 12 , wherein a second level token is added to a root if a confidence factor for the second level token and the root exceeds a threshold confidence factor. | 0.5 |
9,104,660 | 1 | 6 | 1. A method for semantic attribution of a request, said method implemented by a processor of a computer system, said method comprising: said processor receiving source data statements for the request; said processor receiving a selection of a domain for the received source data statements; said processor semantically analyzing the received source data statements, said semantically analyzing comprising matching elements in the received source data statements to respective one or more entries in an ontology associated with the selected domain, wherein the ontology comprises items and relationships that define the selected domain, and wherein each element in the received source data statements is a word or a phrase; after said matching is performed for one matched element of the matched elements, said processor determining whether completeness is indicated for the one matched element; responsive to determining that completeness is indicated for the one matched element, said processor fulfilling completeness for the one matched element; said processor assigning the one or more entries to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries; said processor saving the annotated elements with the respective annotations; and said processor using the annotations to generate a search query for the request. | 1. A method for semantic attribution of a request, said method implemented by a processor of a computer system, said method comprising: said processor receiving source data statements for the request; said processor receiving a selection of a domain for the received source data statements; said processor semantically analyzing the received source data statements, said semantically analyzing comprising matching elements in the received source data statements to respective one or more entries in an ontology associated with the selected domain, wherein the ontology comprises items and relationships that define the selected domain, and wherein each element in the received source data statements is a word or a phrase; after said matching is performed for one matched element of the matched elements, said processor determining whether completeness is indicated for the one matched element; responsive to determining that completeness is indicated for the one matched element, said processor fulfilling completeness for the one matched element; said processor assigning the one or more entries to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries; said processor saving the annotated elements with the respective annotations; and said processor using the annotations to generate a search query for the request. 6. The method of claim 1 , wherein the annotation that annotates one matched element of the matched elements is a pillar which is a main structural element of the ontology. | 0.787129 |
9,424,233 | 1 | 8 | 1. A method of inferring user intent in a search input based on resolving ambiguous portions of the search input, the method comprising: providing access to a set of content items, each of the content items being associated with metadata that describes the corresponding content item, the metadata associated with the content items including a mapping of relationships between entities associated with the content items; receiving search input from a user, the search input being intended by the user to identify at least one desired content item, wherein the search input comprises: a first portion comprising at least one specified entity, and a second portion comprising a reference to at least one unspecified entity related to the at least one desired content item, wherein the at least one unspecified entity of the second portion and the at least one specified entity of the first portion are different; without further user input: inferring a possible meaning for the at least one unspecified entity of the second portion based on the at least one specified entity and the mapping of relationships between entities; based on the inferred possible meaning for the at least one unspecified entity, the at least one specified entity, and the metadata associated with the content items of the set of content items, selecting at least one common content item from the set of content items, wherein the at least one common content item is related to each of the at least one specified entity and the at least one unspecified entity in the mapping of relationships; and presenting the selected at least one common content item to the user in response to the search input received from the user. | 1. A method of inferring user intent in a search input based on resolving ambiguous portions of the search input, the method comprising: providing access to a set of content items, each of the content items being associated with metadata that describes the corresponding content item, the metadata associated with the content items including a mapping of relationships between entities associated with the content items; receiving search input from a user, the search input being intended by the user to identify at least one desired content item, wherein the search input comprises: a first portion comprising at least one specified entity, and a second portion comprising a reference to at least one unspecified entity related to the at least one desired content item, wherein the at least one unspecified entity of the second portion and the at least one specified entity of the first portion are different; without further user input: inferring a possible meaning for the at least one unspecified entity of the second portion based on the at least one specified entity and the mapping of relationships between entities; based on the inferred possible meaning for the at least one unspecified entity, the at least one specified entity, and the metadata associated with the content items of the set of content items, selecting at least one common content item from the set of content items, wherein the at least one common content item is related to each of the at least one specified entity and the at least one unspecified entity in the mapping of relationships; and presenting the selected at least one common content item to the user in response to the search input received from the user. 8. The method of claim 1 , further comprising providing a user preference signature, the user preference signature describing preferences of the user for at least one of (i) particular content items and (ii) metadata associated with the content items, wherein the inferring the possible meaning for the at least one unspecified entity is further based on comparing portions of the search input to the preferences of the user described by the user preference signature. | 0.5 |
9,626,745 | 10 | 11 | 10. A non-transitory program storage device comprising instructions stored thereon to cause one or more processors to: receive three or more images, wherein each image includes a plurality of channel types, and wherein each image has at least one channel of each of the plurality of channel types; select one of the three or more images to serve as a reference image, wherein each of the other images not selected as the reference image is selected to serve as an input image; register each of the input images to the reference image; apply multi-band noise reduction to the reference image to generate a filtered pyramidal representation of each of the reference image's channels, wherein the pyramidal representation of each of the reference image's channels comprises a plurality of levels; apply multi-band noise reduction to each input image to generate a filtered pyramidal representation of each channel of each input image, wherein the pyramidal representation of each channel of each input image comprises a plurality of levels; fuse, on a level-by-level basis, each of the reference image's filtered pyramidal representations with a corresponding filtered pyramidal representation of each input image to generate a fused image channel for each channel of the reference image; and save the fused image channels to a memory. | 10. A non-transitory program storage device comprising instructions stored thereon to cause one or more processors to: receive three or more images, wherein each image includes a plurality of channel types, and wherein each image has at least one channel of each of the plurality of channel types; select one of the three or more images to serve as a reference image, wherein each of the other images not selected as the reference image is selected to serve as an input image; register each of the input images to the reference image; apply multi-band noise reduction to the reference image to generate a filtered pyramidal representation of each of the reference image's channels, wherein the pyramidal representation of each of the reference image's channels comprises a plurality of levels; apply multi-band noise reduction to each input image to generate a filtered pyramidal representation of each channel of each input image, wherein the pyramidal representation of each channel of each input image comprises a plurality of levels; fuse, on a level-by-level basis, each of the reference image's filtered pyramidal representations with a corresponding filtered pyramidal representation of each input image to generate a fused image channel for each channel of the reference image; and save the fused image channels to a memory. 11. The non-transitory program storage device of claim 10 , wherein at least one of the three or more images is under-exposed and at least one of the three or more images is over-exposed. | 0.786041 |
4,187,031 | 2 | 3 | 2. A Korean language typewriter system as claimed in claim 1 in which said keyboard means further has a plurality of additional keys each being for a frequently used combination of alphabet elements of the Korean alphabet, and further means connected to said additional keys for generating an additional binary number signal corresponding to a respective one of said combinations of alphabet elements when the corresponding additional key is actuated; said storage means including means for storing sets of additional hexadecimal numbers each representing a frequently used combination of alphabet elements of the Korean alphabet on a matrix of a predetermined size; said computer means having means for retrieving the stored sets of additional hexadecimal numbers in response to an additional binary number and displaying the combination of alphabet elements corresponding thereto. | 2. A Korean language typewriter system as claimed in claim 1 in which said keyboard means further has a plurality of additional keys each being for a frequently used combination of alphabet elements of the Korean alphabet, and further means connected to said additional keys for generating an additional binary number signal corresponding to a respective one of said combinations of alphabet elements when the corresponding additional key is actuated; said storage means including means for storing sets of additional hexadecimal numbers each representing a frequently used combination of alphabet elements of the Korean alphabet on a matrix of a predetermined size; said computer means having means for retrieving the stored sets of additional hexadecimal numbers in response to an additional binary number and displaying the combination of alphabet elements corresponding thereto. 3. A Korean language typewriter system as claimed in claim 2 in which said computer means further comprises means for prefixing the binary numbers representing an alphabet element with one form of binary element and for prefixing the binary numbers representing the arrangements with the other form of binary element, and for supplying the thus prefixed binary numbers to a transmission means for transmission as a series of signals corresponding to the prefixed binary numbers, whereby the Korean language can be transmitted to a corresponding typewriter and decoded and displayed. | 0.5 |
9,672,819 | 5 | 6 | 5. The non-transitory processor readable medium according to claim 3 , wherein the individual linguistic model data of the cloud server is acquired by analyzing the recognition-related information collected and transmitted through one or more client devices used by the user. | 5. The non-transitory processor readable medium according to claim 3 , wherein the individual linguistic model data of the cloud server is acquired by analyzing the recognition-related information collected and transmitted through one or more client devices used by the user. 6. The non-transitory processor readable medium according to claim 5 , wherein the recognition-related information is collected for a predetermined period of time through one or more client devices used by a user and transmitted. | 0.5 |
5,574,652 | 11 | 20 | 11. An automated machine tool comprising: a machine tool capable of performing a plurality of operations; and a controller for controlling said machine tool, said controller including: a) means for executing a programmed machine cycle for generating output signals to control said machine tool to perform a plurality of operations, said programmed machine cycle comprising a plurality of sequences wherein each of said sequences defines an individual operation to be performed by said machine tool, each of said sequences also being associated with a legend which describes said individual operation of said machine tool defined thereby; b) an input mechanism for selectively controlling the operation of said executing means between a run mode and a command mode, said run mode for automatically operating said machine tool through a complete programmed machine cycle and said command mode for manually stepping one sequence at a time through each of said sequences comprising a programmed machine cycle; c) a visual display operatively connected to said executing means for displaying a plurality of said legends; and d) means for highlighting at least one particular one of said plurality of legends displayed on said visual display wherein, when said run mode is selected, said particular highlighted legend is said legend associated with said sequence currently being performed and, when said command mode is selected, said particular highlighted legend is said legend associated with said next sequence to be performed. | 11. An automated machine tool comprising: a machine tool capable of performing a plurality of operations; and a controller for controlling said machine tool, said controller including: a) means for executing a programmed machine cycle for generating output signals to control said machine tool to perform a plurality of operations, said programmed machine cycle comprising a plurality of sequences wherein each of said sequences defines an individual operation to be performed by said machine tool, each of said sequences also being associated with a legend which describes said individual operation of said machine tool defined thereby; b) an input mechanism for selectively controlling the operation of said executing means between a run mode and a command mode, said run mode for automatically operating said machine tool through a complete programmed machine cycle and said command mode for manually stepping one sequence at a time through each of said sequences comprising a programmed machine cycle; c) a visual display operatively connected to said executing means for displaying a plurality of said legends; and d) means for highlighting at least one particular one of said plurality of legends displayed on said visual display wherein, when said run mode is selected, said particular highlighted legend is said legend associated with said sequence currently being performed and, when said command mode is selected, said particular highlighted legend is said legend associated with said next sequence to be performed. 20. The controller defined in claim 11 wherein said visual display displays a message associated with an error. | 0.849185 |
8,968,068 | 8 | 9 | 8. A gaming device comprising: a playfield that includes a plurality of display positions, wherein each display position is used to display a letter of an alphabet, wherein a letter may be combined with adjacent letters to form a word, wherein the display positions are configured into groups, and wherein at least one word is hidden in the playfield, a microprocessor with a computer-readable medium encoded with a computer program to control the operation of the gaming device, a segment of the computer program to continuously shift the letters at display positions in a group relative to the letters at display positions in another group, wherein a letter at a display position is continuously shifted to an adjacent display position in a group, a segment of said computer program that randomly stops said shifting of letters, a segment of said computer program that determines if a hidden word is uncovered when the shifting of letters is randomly stopped, and a segment of said computer program that determines a payout amount associated with uncovered word. | 8. A gaming device comprising: a playfield that includes a plurality of display positions, wherein each display position is used to display a letter of an alphabet, wherein a letter may be combined with adjacent letters to form a word, wherein the display positions are configured into groups, and wherein at least one word is hidden in the playfield, a microprocessor with a computer-readable medium encoded with a computer program to control the operation of the gaming device, a segment of the computer program to continuously shift the letters at display positions in a group relative to the letters at display positions in another group, wherein a letter at a display position is continuously shifted to an adjacent display position in a group, a segment of said computer program that randomly stops said shifting of letters, a segment of said computer program that determines if a hidden word is uncovered when the shifting of letters is randomly stopped, and a segment of said computer program that determines a payout amount associated with uncovered word. 9. A gaming device as recited in claim 8 , wherein the device is implemented as a bonus game in a primary gaming machine that employs a plurality of rotating reels. | 0.668016 |
10,003,492 | 1 | 10 | 1. A method for managing data related to network elements in a telecommunications network, comprising: receiving, at a server, a document containing data related to one or more network elements in the telecommunications network, the document associated with a corresponding source provider, a location, a receipt timestamp indicating the time and date that the document was received, and a creation timestamp indicating the time and date that the document was created; determining a document class for the document; generating an intermediate, in-memory representation of the document data, the intermediate representation comprising a plurality of key-value pairs, wherein each key-value pair is associated with a network element in the telecommunications network; identifying a parsing template corresponding to the document class and the corresponding source provider of the document, the parsing template comprising a plurality of parsing rules; parsing the intermediate representation according to the plurality of parsing rules to identify relevant values from the intermediate representation; correlating the identified values to a network model according to the plurality of parsing rules, the network model comprising a plurality of network entities that represent types of network elements in the telecommunications network, wherein the network model provides a uniform structure to be applied across a plurality of source providers, wherein each network entity of the network model comprises one or more attributes, and wherein each identified value is correlated to an attribute of a network entity in the network model based on a respective parsing rule of the parsing template; normalizing each identified value according to a format defined by the network model; writing the normalized values to a networking database, the networking database comprising a plurality of different types of data related to network elements in the telecommunications network, wherein the written values are linked to the corresponding associated network elements and correlated network entity attributes. | 1. A method for managing data related to network elements in a telecommunications network, comprising: receiving, at a server, a document containing data related to one or more network elements in the telecommunications network, the document associated with a corresponding source provider, a location, a receipt timestamp indicating the time and date that the document was received, and a creation timestamp indicating the time and date that the document was created; determining a document class for the document; generating an intermediate, in-memory representation of the document data, the intermediate representation comprising a plurality of key-value pairs, wherein each key-value pair is associated with a network element in the telecommunications network; identifying a parsing template corresponding to the document class and the corresponding source provider of the document, the parsing template comprising a plurality of parsing rules; parsing the intermediate representation according to the plurality of parsing rules to identify relevant values from the intermediate representation; correlating the identified values to a network model according to the plurality of parsing rules, the network model comprising a plurality of network entities that represent types of network elements in the telecommunications network, wherein the network model provides a uniform structure to be applied across a plurality of source providers, wherein each network entity of the network model comprises one or more attributes, and wherein each identified value is correlated to an attribute of a network entity in the network model based on a respective parsing rule of the parsing template; normalizing each identified value according to a format defined by the network model; writing the normalized values to a networking database, the networking database comprising a plurality of different types of data related to network elements in the telecommunications network, wherein the written values are linked to the corresponding associated network elements and correlated network entity attributes. 10. The method of claim 1 , wherein the document data relates to network elements in a mobile backhaul network. | 0.899457 |
8,001,562 | 1 | 7 | 1. A scene information extraction apparatus comprising: a first acquisition unit configured to acquire a plurality of comment information items related to video content which defines scenes in a time-sequence manner, each of the plurality of comment information items including a comment, and a start time and an end time of the comment, the comment corresponding to a user who has viewed the video content; a division unit configured to divide the comment into words by morpheme analysis for each of the plurality of comment information items; a second acquisition unit configured to acquire an estimated value of each of the words, the estimated value indicating a degree of importance used at a time that a scene corresponding to a zone of the video content extracted; an addition unit configured to add the estimated value of each of the words for the words during a period of time ranging from the start time of the comment to the end time of the comment that contains a corresponding word included in the words, and to acquire estimated value distributions of the words; and an extraction unit configured to extract a start time and an end time of one scene included in the scenes and to be extracted from the video content, based on a shape of the estimated value distributions. | 1. A scene information extraction apparatus comprising: a first acquisition unit configured to acquire a plurality of comment information items related to video content which defines scenes in a time-sequence manner, each of the plurality of comment information items including a comment, and a start time and an end time of the comment, the comment corresponding to a user who has viewed the video content; a division unit configured to divide the comment into words by morpheme analysis for each of the plurality of comment information items; a second acquisition unit configured to acquire an estimated value of each of the words, the estimated value indicating a degree of importance used at a time that a scene corresponding to a zone of the video content extracted; an addition unit configured to add the estimated value of each of the words for the words during a period of time ranging from the start time of the comment to the end time of the comment that contains a corresponding word included in the words, and to acquire estimated value distributions of the words; and an extraction unit configured to extract a start time and an end time of one scene included in the scenes and to be extracted from the video content, based on a shape of the estimated value distributions. 7. The apparatus according to claim 1 , wherein the second acquisition unit is configured to acquire the estimated value of each of the words, based on a character string length of the comment which contains each of the words, and number of words included in the comment which contains each of the words. | 0.536585 |
8,671,353 | 19 | 27 | 19. A computer-implemented method comprising: receiving a selection of a primary keyword by a customer; causing a display of a hub associated with the primary keyword on a computer display; determining a quantity related to a countable event associated with the primary keyword and each of the secondary keywords, wherein the countable event comprises an order of an item corresponding to the secondary keyword following a selection of the primary keyword by at least one customer; determining a degree of association between the primary keyword and a plurality of secondary keywords based at least in part on the quantity determined for each of the secondary keywords; and causing a display of a plurality of nodes on the computer display, wherein each of the nodes corresponds to one of the plurality of secondary keywords, wherein a characteristic of each of the plurality of nodes is determined based at least in part on the degree of association between the primary keyword and the secondary keyword corresponding to each of the plurality of nodes. | 19. A computer-implemented method comprising: receiving a selection of a primary keyword by a customer; causing a display of a hub associated with the primary keyword on a computer display; determining a quantity related to a countable event associated with the primary keyword and each of the secondary keywords, wherein the countable event comprises an order of an item corresponding to the secondary keyword following a selection of the primary keyword by at least one customer; determining a degree of association between the primary keyword and a plurality of secondary keywords based at least in part on the quantity determined for each of the secondary keywords; and causing a display of a plurality of nodes on the computer display, wherein each of the nodes corresponds to one of the plurality of secondary keywords, wherein a characteristic of each of the plurality of nodes is determined based at least in part on the degree of association between the primary keyword and the secondary keyword corresponding to each of the plurality of nodes. 27. The method according to claim 19 , wherein the degree of association between the primary keyword and the plurality of secondary keywords is determined based at least in part on a time when the primary keyword was selected by the customer. | 0.839735 |
6,167,409 | 21 | 22 | 21. The computer system of claim 20, wherein the data processing component includes means for transforming the selected portion of the requested document according to the structure of the requested document. | 21. The computer system of claim 20, wherein the data processing component includes means for transforming the selected portion of the requested document according to the structure of the requested document. 22. The computer system of claim 21, wherein the means for transforming includes means for applying a declarative specification for the document type of the requested document to the elements in the selected portion of the requested document. | 0.5 |
8,051,071 | 1 | 7 | 1. A method performed by one or more devices, the method comprising: determining, by one or more processors of the one or more devices, an amount or rate that a document moves positions in search result rankings over time, compared to one or more prior positions of the document in the search result rankings; generating, by one or more processors of the one or more devices, a score for the document based on the amount or rate that the document moves in the search result rankings over time, compared to the one or more prior positions of the document in the search result rankings; and ranking, by one or more processors of the one or more devices, the document with regard to at least one other document based on the score. | 1. A method performed by one or more devices, the method comprising: determining, by one or more processors of the one or more devices, an amount or rate that a document moves positions in search result rankings over time, compared to one or more prior positions of the document in the search result rankings; generating, by one or more processors of the one or more devices, a score for the document based on the amount or rate that the document moves in the search result rankings over time, compared to the one or more prior positions of the document in the search result rankings; and ranking, by one or more processors of the one or more devices, the document with regard to at least one other document based on the score. 7. The method of claim 1 , where the score is a first score, the method further comprising: determining a set of search terms relating to a particular topic or news item; determining that the document is associated with the set of search terms; identifying another document that is not associated with the set of search terms; generating a second score for the other document, where the first score exceeds the second score; and ranking the document with regard to at least the other document based on the first and second scores. | 0.5 |
9,164,667 | 1 | 2 | 1. A method performed by at least one electronic device having a processor and a memory for exploring an n-dimensional textual data set using word cloud representations of two-dimensional projections of the data set, comprising: providing a display space with a two dimensional coordinate system; generating a textual data set whose members comprise a set of words, each of which is associated with an n-dimensional vector populated by n numerical values, said vectors defining an n-dimensional data space; storing said textual data set in said memory so as to preserve each word's relationship with its associated vector; calculating a size attribute for each word in said textual data set; creating an initial two-dimensional subspace of the n-dimensional data space and storing said subspace in said memory; calculating the projection of each said n-dimensional vector onto said subspace, and saving said projection to memory; displaying a word cloud by performing steps comprising: placing each word from the textual data set in said display space at coordinates determined by its projection on said subspace; and displaying said word with a font size corresponding to its size attribute; receiving a user's selection of a word displayed in the word cloud via said electronic device's manual data entry means; receiving a user's motion input via said electronic device's manual data entry means; shifting said word cloud by performing steps comprising: selecting a frame rate for animating the movement corresponding to said user's motion input; for each frame, calculating the change in position in the display space corresponding to the portion of said user's motion input that occurred during said frame; replacing said two-dimensional subspace with another two-dimensional subspace in which the projection of the selected word's associated vector causes the selected word to be displayed at the new location dictated by said change in position; projecting each vector on the new subspace and saving each said projection to said memory; placing each word at coordinates in said display space corresponding to its vector's new projection; and repeating for each frame until detecting cessation of motion; upon cessation of motion, repeating the steps comprising displaying a word cloud using each word's associated vector's most recent projection on the most recent subspace. | 1. A method performed by at least one electronic device having a processor and a memory for exploring an n-dimensional textual data set using word cloud representations of two-dimensional projections of the data set, comprising: providing a display space with a two dimensional coordinate system; generating a textual data set whose members comprise a set of words, each of which is associated with an n-dimensional vector populated by n numerical values, said vectors defining an n-dimensional data space; storing said textual data set in said memory so as to preserve each word's relationship with its associated vector; calculating a size attribute for each word in said textual data set; creating an initial two-dimensional subspace of the n-dimensional data space and storing said subspace in said memory; calculating the projection of each said n-dimensional vector onto said subspace, and saving said projection to memory; displaying a word cloud by performing steps comprising: placing each word from the textual data set in said display space at coordinates determined by its projection on said subspace; and displaying said word with a font size corresponding to its size attribute; receiving a user's selection of a word displayed in the word cloud via said electronic device's manual data entry means; receiving a user's motion input via said electronic device's manual data entry means; shifting said word cloud by performing steps comprising: selecting a frame rate for animating the movement corresponding to said user's motion input; for each frame, calculating the change in position in the display space corresponding to the portion of said user's motion input that occurred during said frame; replacing said two-dimensional subspace with another two-dimensional subspace in which the projection of the selected word's associated vector causes the selected word to be displayed at the new location dictated by said change in position; projecting each vector on the new subspace and saving each said projection to said memory; placing each word at coordinates in said display space corresponding to its vector's new projection; and repeating for each frame until detecting cessation of motion; upon cessation of motion, repeating the steps comprising displaying a word cloud using each word's associated vector's most recent projection on the most recent subspace. 2. A method according to claim 1 , wherein the step of generating a textual data set comprises: providing a set of documents; obtaining said words from said documents; creating a matrix containing data concerning said words and documents; and using said matrix to produce said n-dimensional vectors. | 0.648235 |
8,688,456 | 6 | 7 | 6. The method of claim 1 , further comprising: computing an alias comprising a best representative anchor text from a plurality of weighted anchor texts. | 6. The method of claim 1 , further comprising: computing an alias comprising a best representative anchor text from a plurality of weighted anchor texts. 7. The method of claim 6 , wherein the best representative anchor text has a weight associated with a highest ratio of salient words to total words from the plurality of weighted anchor texts. | 0.5 |
9,798,975 | 9 | 14 | 9. A computer program product for operating a production rule engine, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising: loading a production rule ontology into a production rule engine, wherein the production rule ontology provides a description and instances of a production rule, wherein the production rule comprises a condition part and an action part, wherein the condition part matches instances of the production rule to be grouped into a working memory, and wherein the action part updates the instances of the production rule in response to the instances being grouped into the working memory; loading production rules into the production rule engine, wherein the production rule comprises a rule and an action defined by use of the production rule ontology; executing, by one or more processors, the production rules; locating a logical inconsistency between an ontology changed by a respective action defined by use of the production rule ontology and an existing ontology; locating a logical solution to an inconsistent ontology; updating the inconsistent ontology with the located logical solution; embedding an Ontological Web Language (OWL) axiom in a single extended RETE axiom node, wherein the OWL axiom is a class expression, and wherein the single extended RETE axiom node is a stateless RETE subnode that has no local memory associated to it; embedding the OWL axiom into a RETE production rule engine; and defining new language terms based on tight coupling between the RETE production rule engine and the OWL axiom. | 9. A computer program product for operating a production rule engine, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising: loading a production rule ontology into a production rule engine, wherein the production rule ontology provides a description and instances of a production rule, wherein the production rule comprises a condition part and an action part, wherein the condition part matches instances of the production rule to be grouped into a working memory, and wherein the action part updates the instances of the production rule in response to the instances being grouped into the working memory; loading production rules into the production rule engine, wherein the production rule comprises a rule and an action defined by use of the production rule ontology; executing, by one or more processors, the production rules; locating a logical inconsistency between an ontology changed by a respective action defined by use of the production rule ontology and an existing ontology; locating a logical solution to an inconsistent ontology; updating the inconsistent ontology with the located logical solution; embedding an Ontological Web Language (OWL) axiom in a single extended RETE axiom node, wherein the OWL axiom is a class expression, and wherein the single extended RETE axiom node is a stateless RETE subnode that has no local memory associated to it; embedding the OWL axiom into a RETE production rule engine; and defining new language terms based on tight coupling between the RETE production rule engine and the OWL axiom. 14. The computer program product of claim 9 , wherein production rules assertions are executed in order of priority, and wherein logical inconsistencies to the ontology are located in a rule by rule basis. | 0.628623 |
9,348,757 | 12 | 13 | 12. A computer system for facilitating memory access, said computer system comprising: a memory; and a processor in communications with the memory, wherein the computer system is configured to perform a method, said method comprising: providing a first partition within a system configuration, the first partition configured to support an operating system (OS) designed for a first address translation architecture, wherein configuration of the first partition to support the OS designed for the first address translation architecture is indicated in a configuration data structure, and wherein the first partition is not configured, as indicated in the configuration data structure, to support an OS designed for a second address translation architecture; and providing a second partition within the system configuration, the second partition configured to support the OS designed for the second address translation architecture, the second partition not configured to support the OS designed for the first address translation architecture, wherein the first address translation architecture is structurally different from the second address translation architecture, and wherein the first partition is paravirtualized partition in which a guest of the first partition assists in handling address translation faults corresponding to host translations and the second partition is a virtualized partition in which handling of address translation faults corresponding to host translations is independent of assistance from a guest of the second partition. | 12. A computer system for facilitating memory access, said computer system comprising: a memory; and a processor in communications with the memory, wherein the computer system is configured to perform a method, said method comprising: providing a first partition within a system configuration, the first partition configured to support an operating system (OS) designed for a first address translation architecture, wherein configuration of the first partition to support the OS designed for the first address translation architecture is indicated in a configuration data structure, and wherein the first partition is not configured, as indicated in the configuration data structure, to support an OS designed for a second address translation architecture; and providing a second partition within the system configuration, the second partition configured to support the OS designed for the second address translation architecture, the second partition not configured to support the OS designed for the first address translation architecture, wherein the first address translation architecture is structurally different from the second address translation architecture, and wherein the first partition is paravirtualized partition in which a guest of the first partition assists in handling address translation faults corresponding to host translations and the second partition is a virtualized partition in which handling of address translation faults corresponding to host translations is independent of assistance from a guest of the second partition. 13. The computer system of claim 12 , wherein the first partition uses a single level address translation mechanism for translating guest virtual addresses to host physical addresses, and the second partition uses a nested level address translation mechanism for translating guest virtual addresses to host physical addresses. | 0.5 |
8,234,239 | 8 | 10 | 8. A non-transitory computer readable media comprising program code for execution by a programmable processor to perform a method for providing one or more vector terms for use in identifying advertisements, the computer readable media comprising: program code for retrieving, periodically during an instant messaging conversation, one or more terms or phrases used in the instant messaging conversation in which one or more users are participating; program code for generating one or more term vectors comprising one or more vector terms for at least one term or phrase used in the instant messaging conversation with a greatest frequency; program code for identifying one or more advertisements associated with the at least one term or phrase used in the instant messaging conversation with a greatest frequency; and program code for retrieving one or more content items responsive to the query associated with a selected vector term. | 8. A non-transitory computer readable media comprising program code for execution by a programmable processor to perform a method for providing one or more vector terms for use in identifying advertisements, the computer readable media comprising: program code for retrieving, periodically during an instant messaging conversation, one or more terms or phrases used in the instant messaging conversation in which one or more users are participating; program code for generating one or more term vectors comprising one or more vector terms for at least one term or phrase used in the instant messaging conversation with a greatest frequency; program code for identifying one or more advertisements associated with the at least one term or phrase used in the instant messaging conversation with a greatest frequency; and program code for retrieving one or more content items responsive to the query associated with a selected vector term. 10. The computer readable media of claim 8 further comprising program code for selecting a predetermined number of vector terms from a given term vector. | 0.769578 |
9,582,591 | 12 | 16 | 12. A system, comprising: at least one processor; and memory that stores instructions that, when executed by the at least one processor, cause the at least one processor to perform acts comprising: receiving user input that is indicative of a first research document, the first research document is authored by an author and has a publication date, the publication date indicative of a date upon which the first research document was published, wherein a second research document comprises a sentence that includes a citation to the first research document, the second research document has a publication date that is subsequent to the publication date of the first research document; and in response to receipt of the user input, generating a graphical summary of the first research document, the graphical summary comprising portions of sentences included in research documents having publication dates that are subsequent to the publication date of the first research document, the portions of the sentences comprising a portion of the sentence in the second research document that includes the citation to the first research document. | 12. A system, comprising: at least one processor; and memory that stores instructions that, when executed by the at least one processor, cause the at least one processor to perform acts comprising: receiving user input that is indicative of a first research document, the first research document is authored by an author and has a publication date, the publication date indicative of a date upon which the first research document was published, wherein a second research document comprises a sentence that includes a citation to the first research document, the second research document has a publication date that is subsequent to the publication date of the first research document; and in response to receipt of the user input, generating a graphical summary of the first research document, the graphical summary comprising portions of sentences included in research documents having publication dates that are subsequent to the publication date of the first research document, the portions of the sentences comprising a portion of the sentence in the second research document that includes the citation to the first research document. 16. The system of claim 12 , wherein the user input is a selection of a graphical object in a graphical visualization that is representative of the first research document. | 0.732087 |
8,332,787 | 12 | 13 | 12. The apparatus of claim 11 , wherein the structured hardware description language design module is configured to create placement data that defines locations of components in the part of the logic comprising the at least one time sensitive path. | 12. The apparatus of claim 11 , wherein the structured hardware description language design module is configured to create placement data that defines locations of components in the part of the logic comprising the at least one time sensitive path. 13. The apparatus of claim 12 , wherein the structured hardware description language design module is configured to, merge a new hardware description language design with the structured hardware description language design of the part of the logic comprising at least one time sensitive path to create a merged hardware description language design; and synthesize the merged hardware description language design, using the placement data, to create a physical representation of the merged hardware description language design. | 0.5 |
7,509,258 | 25 | 37 | 25. A system adapted to process speech, comprising: an input receiving a speech sample; a processor adapted to: (a) identify a list of candidate words potentially contained in the speech sample, wherein at least some of the candidate words are alternative candidate words corresponding to the same or an overlapping portion of the speech sample, (b) permuting at least some of the candidate words from the identified list of candidate words to create a plurality of potential syntactic structures corresponding to the speech sample, comprising candidate words with word pronunciation boundaries that do not conflict with respective word pronunciation boundaries of other candidate words of a respective potential syntactic structure; and (c) selecting one of the potential syntactic structures as corresponding to the speech sample; and an output presenting information responsive to the selecting. | 25. A system adapted to process speech, comprising: an input receiving a speech sample; a processor adapted to: (a) identify a list of candidate words potentially contained in the speech sample, wherein at least some of the candidate words are alternative candidate words corresponding to the same or an overlapping portion of the speech sample, (b) permuting at least some of the candidate words from the identified list of candidate words to create a plurality of potential syntactic structures corresponding to the speech sample, comprising candidate words with word pronunciation boundaries that do not conflict with respective word pronunciation boundaries of other candidate words of a respective potential syntactic structure; and (c) selecting one of the potential syntactic structures as corresponding to the speech sample; and an output presenting information responsive to the selecting. 37. The system of claim 25 , wherein the speech sample is processed as a series of time-slices to identify candidate phonemes, at least some of the time segments including alternative candidate phonemes. | 0.751225 |
8,229,753 | 19 | 20 | 19. The computer readable storage medium of claim 11 wherein one of the second set of attributes for one of the controls relates to a location of data for audible output. | 19. The computer readable storage medium of claim 11 wherein one of the second set of attributes for one of the controls relates to a location of data for audible output. 20. The computer readable storage medium of claim 19 wherein the data comprises a prerecorded audio data file and the attribute relates to playing the prerecorded audio data file. | 0.5 |
9,350,690 | 2 | 3 | 2. The device of claim 1 , further comprising a data compilation component that aggregates user use context of the message across one or more recipients, and makes available a subset of aggregated information to the recipient or the sender of the message. | 2. The device of claim 1 , further comprising a data compilation component that aggregates user use context of the message across one or more recipients, and makes available a subset of aggregated information to the recipient or the sender of the message. 3. The device of claim 2 , further comprising a grading component that ranks the message as a function of the aggregated information, and provides ranking information of the message to the recipient or the sender of the message. | 0.5 |
9,613,149 | 1 | 5 | 1. A method performed by a computer system having a processor of automatically mapping a pattern related to a location identifier of an object having content in the Web to a semantic type using metadata associated with the object, the method, comprising: collecting the metadata from, one or more of, a plurality of content sources hosted by host servers and the object itself, wherein each of the plurality of content sources includes at least a portion of the object or a reference to the object associated with the location identifier; creating, by a processor, the pattern from the location identifier of the object in the Web, wherein the pattern is not identical to the location identifier and is used to search for other location identifiers of objects in the Web, wherein the metadata corresponds to the semantic type with which the content of the object has a semantic relationship, the metadata having an associated weighting; and storing, by the processor, the pattern in a database embodied in a machine-readable storage medium as being mapped to the semantic type; receiving via a user interface a search query associated with the semantic type; mapping the search query into the pattern stored in the database based on the semantic type; and performing a search for the other location identifiers matching the pattern for locating other objects or other objects including content embodied therein, that have the semantic relationship to the semantic type. | 1. A method performed by a computer system having a processor of automatically mapping a pattern related to a location identifier of an object having content in the Web to a semantic type using metadata associated with the object, the method, comprising: collecting the metadata from, one or more of, a plurality of content sources hosted by host servers and the object itself, wherein each of the plurality of content sources includes at least a portion of the object or a reference to the object associated with the location identifier; creating, by a processor, the pattern from the location identifier of the object in the Web, wherein the pattern is not identical to the location identifier and is used to search for other location identifiers of objects in the Web, wherein the metadata corresponds to the semantic type with which the content of the object has a semantic relationship, the metadata having an associated weighting; and storing, by the processor, the pattern in a database embodied in a machine-readable storage medium as being mapped to the semantic type; receiving via a user interface a search query associated with the semantic type; mapping the search query into the pattern stored in the database based on the semantic type; and performing a search for the other location identifiers matching the pattern for locating other objects or other objects including content embodied therein, that have the semantic relationship to the semantic type. 5. The method of claim 1 , wherein, the metadata is collected from analyzing user behavior. | 0.843103 |
9,263,042 | 13 | 19 | 13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining, by a server for each of multiple words or sub-words, audio data corresponding to multiple users speaking the word or sub-word; training, by the server for each of the multiple words or sub-words, a hotword model for the word or sub-word based on the audio data for the word or sub-word, wherein the hotword model for the word or sub-word is a model that is used to detect an utterance of the word or sub-word in audio input data without transcribing the word or sub-word from input audio data; storing each of the trained hotword models as a pre-computed hotword model; receiving, by the server, a candidate hotword from a computing device; identifying, by the server, one or more of the stored pre-computed hotword models that correspond to the candidate hotword; and providing, by the server, the identified, one or more of the stored pre-computed hotword models to the computing device. | 13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining, by a server for each of multiple words or sub-words, audio data corresponding to multiple users speaking the word or sub-word; training, by the server for each of the multiple words or sub-words, a hotword model for the word or sub-word based on the audio data for the word or sub-word, wherein the hotword model for the word or sub-word is a model that is used to detect an utterance of the word or sub-word in audio input data without transcribing the word or sub-word from input audio data; storing each of the trained hotword models as a pre-computed hotword model; receiving, by the server, a candidate hotword from a computing device; identifying, by the server, one or more of the stored pre-computed hotword models that correspond to the candidate hotword; and providing, by the server, the identified, one or more of the stored pre-computed hotword models to the computing device. 19. The system of claim 13 , wherein training, by the server for each of the multiple words or sub-words, a pre-computed hotword model for the word or sub-word, further comprises: for each word or sub-word of the multiple words or sub-words: obtaining, for each user of the multiple users, a transcription of the audio data of the user speaking the word or sub-word; associating, for each user of the multiple users, the audio data of the user speaking the word or sub-word with the transcription of the audio data of the user speaking the word or sub-word; and generating a particular hotword model corresponding to the word or sub-word based on i) the audio data corresponding to each of the multiple users speaking the word or sub-word and ii) the transcription associated with the audio data corresponding to each of the multiple users speaking the word or sub-word. | 0.5 |
10,152,695 | 1 | 8 | 1. A system comprising: at least one data store configured to maintain profiles of all members, a unstructured data of each of the members, historical data, and a rank model; and at least one server computer that together is configured to: receive from a client device a job posting submitted by a client; receive from a plurality of contractor devices a plurality of proposals submitted by a plurality of contractors regarding the job posting; in response to receiving the plurality of proposals, access the at least one data store to retrieve the unstructured data that is specific to the client and to retrieve the profiles associated with the plurality of contractors who submitted the plurality of proposals; dynamically determine, based on the unstructured data that is specific to the client, a set of parameters that is only pertinent to the client and is to be used by the rank model; for each of the plurality of contractors, determine, based on the rank model using the set of parameters that is only pertinent to the client and based on the profile for a corresponding contractor, a rank score comprising a set of factor scores; and present an ordered listing of the contractors according to the rank scores; and implement a mapping engine configured to: access the at least one data store to retrieve the historical data; and for each of the plurality of contractors, compare the set of factor scores associated with the corresponding contractor to past sets of factor scores that are part of the historical data to determine, based on associated data that are part of the historical data and that are regarding whether respective service providers for the past sets of factor scores had been awarded jobs, a percentage of likelihood of being selected for having the set of factor scores and to, thereby, map the corresponding contractor to one of at least two levels based on the determined percentage of likelihood of being selected. | 1. A system comprising: at least one data store configured to maintain profiles of all members, a unstructured data of each of the members, historical data, and a rank model; and at least one server computer that together is configured to: receive from a client device a job posting submitted by a client; receive from a plurality of contractor devices a plurality of proposals submitted by a plurality of contractors regarding the job posting; in response to receiving the plurality of proposals, access the at least one data store to retrieve the unstructured data that is specific to the client and to retrieve the profiles associated with the plurality of contractors who submitted the plurality of proposals; dynamically determine, based on the unstructured data that is specific to the client, a set of parameters that is only pertinent to the client and is to be used by the rank model; for each of the plurality of contractors, determine, based on the rank model using the set of parameters that is only pertinent to the client and based on the profile for a corresponding contractor, a rank score comprising a set of factor scores; and present an ordered listing of the contractors according to the rank scores; and implement a mapping engine configured to: access the at least one data store to retrieve the historical data; and for each of the plurality of contractors, compare the set of factor scores associated with the corresponding contractor to past sets of factor scores that are part of the historical data to determine, based on associated data that are part of the historical data and that are regarding whether respective service providers for the past sets of factor scores had been awarded jobs, a percentage of likelihood of being selected for having the set of factor scores and to, thereby, map the corresponding contractor to one of at least two levels based on the determined percentage of likelihood of being selected. 8. The system of claim 1 , wherein the ordered listing of the contractors includes the mapping of each contractor. | 0.860294 |
9,195,656 | 9 | 15 | 9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining data indicating a set of linguistic features corresponding to a text; providing (i) data indicating the linguistic features and (ii) data indicating the language of the text as input to a neural network that has been trained to provide output indicating prosody information for multiple languages, the neural network having been trained using speech in multiple languages; receiving, from the neural network, output indicating prosody information for the linguistic features; and generating audio data representing the text using the output of the neural network. | 9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining data indicating a set of linguistic features corresponding to a text; providing (i) data indicating the linguistic features and (ii) data indicating the language of the text as input to a neural network that has been trained to provide output indicating prosody information for multiple languages, the neural network having been trained using speech in multiple languages; receiving, from the neural network, output indicating prosody information for the linguistic features; and generating audio data representing the text using the output of the neural network. 15. The system of claim 9 , wherein generating the audio data representing the text using the output of the neural network comprises selecting one or more recorded speech samples based on the output of the neural network. | 0.915065 |
8,996,555 | 1 | 7 | 1. A computer-implemented method comprising: causing an answering system to receive a user query posed in a natural language to a database; causing the answering system to derive semantics from the user query and create a parse graph, wherein the semantics comprise a first dimension and a second dimension; perform normalization and transformation of the semantics; imposing constraints on the semantics to create artifacts by proposing a related measure connecting the first dimension and the second dimension in a database table; mapping the artifacts into a plurality of structured queries; ranking the plurality of structured queries according to a first scoring function considering a selectivity of the related measure, and a second scoring function considering a complexity of the structured query such that a more complex query structure indicates a higher relevance, a third scoring function comprising a confidence measure based on text retrieval metrics, and a fourth scoring function comprising a popularity of the first dimension, the second dimension, and the related measure; and executing the plurality of structured queries on the database according to the ranking. | 1. A computer-implemented method comprising: causing an answering system to receive a user query posed in a natural language to a database; causing the answering system to derive semantics from the user query and create a parse graph, wherein the semantics comprise a first dimension and a second dimension; perform normalization and transformation of the semantics; imposing constraints on the semantics to create artifacts by proposing a related measure connecting the first dimension and the second dimension in a database table; mapping the artifacts into a plurality of structured queries; ranking the plurality of structured queries according to a first scoring function considering a selectivity of the related measure, and a second scoring function considering a complexity of the structured query such that a more complex query structure indicates a higher relevance, a third scoring function comprising a confidence measure based on text retrieval metrics, and a fourth scoring function comprising a popularity of the first dimension, the second dimension, and the related measure; and executing the plurality of structured queries on the database according to the ranking. 7. A method as in claim 1 wherein each of the plurality of structured queries comprises a data source, a set of dimensions and measures, and a set of filters. | 0.640909 |
8,316,394 | 17 | 18 | 17. The method of claim 1 , further comprising making information about the mosaic page on a first user device available on a second different user device. | 17. The method of claim 1 , further comprising making information about the mosaic page on a first user device available on a second different user device. 18. The method of claim 17 , wherein making the information available comprises storing the information on a portable medium, storing the information at a central location accessible to the first and second user device, or transmitting the information from the first to the second user device via a network connection, or a combination thereof. | 0.5 |
8,918,308 | 1 | 14 | 1. A method implemented in a computer infrastructure, comprising: receiving a search query containing a transliterated word; determining a source language corresponding to the transliterated word, wherein the determining the source language comprises: determining a weighted score for each one of a plurality of candidate languages, and designating the candidate language with the highest weighted score as the source language; converting the transliterated word to a word in the source language; translating the word in the source language to a word in a target language; and performing a search using the word in the target language wherein the weighted score of each one of the plurality of candidate languages is based on: correlating user-entered words against language-specific dictionaries; environmental variables; location-based services; and user profile and/or history. | 1. A method implemented in a computer infrastructure, comprising: receiving a search query containing a transliterated word; determining a source language corresponding to the transliterated word, wherein the determining the source language comprises: determining a weighted score for each one of a plurality of candidate languages, and designating the candidate language with the highest weighted score as the source language; converting the transliterated word to a word in the source language; translating the word in the source language to a word in a target language; and performing a search using the word in the target language wherein the weighted score of each one of the plurality of candidate languages is based on: correlating user-entered words against language-specific dictionaries; environmental variables; location-based services; and user profile and/or history. 14. The method of claim 1 , wherein a service provider at least one of creates, maintains, deploys and supports the computer infrastructure. | 0.872727 |
8,176,032 | 1 | 21 | 1. A computer-implemented method comprising: monitoring search queries associated with a search query category, the search query category associated with at least one search term and associated with a baseline frequency, the baseline frequency reflecting an average number of search queries detected during a time interval associated with the search query category; detecting a change in a search request frequency associated with the search query category with respect to the baseline frequency; determining an event associated with the search query category; identifying one or more data items associated with the event, the one or more items comprising at least one item listing associated with an item for sale; and generating, using at least one processor, a visual representation of a relationship between the one or more data items and the event, the generating including displaying the at least one item listing such that the at least one item listing appears visually related to the event. | 1. A computer-implemented method comprising: monitoring search queries associated with a search query category, the search query category associated with at least one search term and associated with a baseline frequency, the baseline frequency reflecting an average number of search queries detected during a time interval associated with the search query category; detecting a change in a search request frequency associated with the search query category with respect to the baseline frequency; determining an event associated with the search query category; identifying one or more data items associated with the event, the one or more items comprising at least one item listing associated with an item for sale; and generating, using at least one processor, a visual representation of a relationship between the one or more data items and the event, the generating including displaying the at least one item listing such that the at least one item listing appears visually related to the event. 21. The computer-implemented method of claim 1 , wherein the at least one item listing comprises at least one of a music or video listing associated with the item, or a stock listing associated with the item. | 0.780591 |
8,684,839 | 1 | 12 | 1. A gaming system in a casino gaming network, comprising: a gaming controller; a memory; at least one interface configured to communicate with at least one other device in the gaming network; a first gesture input interface device configured to detect movements of the first gesture input interface device associated with one or more persons, wherein the first gesture input interface device is included within a first mobile handheld device in communication with the gaming controller; and a first gesture interpretation component configured to identify selected movements or gestures detected by the first gesture input interface device and to generate gesture interpretation information relating to interpretation of the selected movements or gestures, wherein the gaming system is configured to: detect one or more identification gestures by a first player via the first gesture input interface, wherein the one or more identification gestures are detected by the first gesture input interface device and comprise movement of the first gesture input interface device, determine an identity of the first player based on the detected one or more identification gestures, detect a first gesture by the first player participating in a first game session at the gaming system, wherein the first gesture is detected by the first gesture input interface device, and wherein the first gesture comprises movement of the first gesture input interface device, interpret the first gesture with respect to a first set of criteria; generate gesture interpretation information relating to the interpretation of the first gesture, advance a state of the first game session using at least a portion of the gesture interpretation information, and communicate the advancement of the state of the first game session to the first player via the first mobile handheld device. | 1. A gaming system in a casino gaming network, comprising: a gaming controller; a memory; at least one interface configured to communicate with at least one other device in the gaming network; a first gesture input interface device configured to detect movements of the first gesture input interface device associated with one or more persons, wherein the first gesture input interface device is included within a first mobile handheld device in communication with the gaming controller; and a first gesture interpretation component configured to identify selected movements or gestures detected by the first gesture input interface device and to generate gesture interpretation information relating to interpretation of the selected movements or gestures, wherein the gaming system is configured to: detect one or more identification gestures by a first player via the first gesture input interface, wherein the one or more identification gestures are detected by the first gesture input interface device and comprise movement of the first gesture input interface device, determine an identity of the first player based on the detected one or more identification gestures, detect a first gesture by the first player participating in a first game session at the gaming system, wherein the first gesture is detected by the first gesture input interface device, and wherein the first gesture comprises movement of the first gesture input interface device, interpret the first gesture with respect to a first set of criteria; generate gesture interpretation information relating to the interpretation of the first gesture, advance a state of the first game session using at least a portion of the gesture interpretation information, and communicate the advancement of the state of the first game session to the first player via the first mobile handheld device. 12. The gaming system of claim 1 being further configured to: determine an active game theme of the first game session at the gaming system; and interpret the first gesture based at least in part upon the active game theme of the first game session at the gaming system. | 0.77649 |
4,477,903 | 7 | 8 | 7. A device for the demodulation and decoding of data transferred by means of an error correction method as claimed in claims 1 or 2, characterized in that a non-correctable first number of data words is replaced by substitute data. | 7. A device for the demodulation and decoding of data transferred by means of an error correction method as claimed in claims 1 or 2, characterized in that a non-correctable first number of data words is replaced by substitute data. 8. A decoder for use in a device as claimed in claim 7, characterized in that for the demodulation a group of synchronizing channel bits is ignored, a further group of control bits being ignored for the (possibly correcting) reproduction after demodulation. | 0.5 |
8,725,713 | 1 | 5 | 1. A computer apparatus comprising: at least one processor; a memory coupled to the at least one processor; a database residing in the memory having a record with a beginning position; a query that specifies a sequential string search of the record; a query optimizer that optimizes the query by determining a starting position other than the beginning position of the record to start the string search; and wherein the starting position is determined based on a starting position table containing historical information of previous text string searches. | 1. A computer apparatus comprising: at least one processor; a memory coupled to the at least one processor; a database residing in the memory having a record with a beginning position; a query that specifies a sequential string search of the record; a query optimizer that optimizes the query by determining a starting position other than the beginning position of the record to start the string search; and wherein the starting position is determined based on a starting position table containing historical information of previous text string searches. 5. The computer apparatus of claim 1 wherein the query optimizer determines the starting position for the search based on the position where previous queries found the string in a predetermined number of the records that match the query. | 0.5 |
7,917,841 | 21 | 27 | 21. A non-transitory computer readable storage medium having stored thereon computer-executable instructions for viewing information associated with data in a spreadsheet, which, when executed by a processor, perform a method the comprising: providing a document including data and information associated with the data; parsing the document to retrieve the associated information; code for processing the associated information to break the associated information down into at least one sentence; categorizing the at least one sentence based on a likelihood that the at least one sentence corresponds to at least one category in a taxonomy corresponding to the data resulting in at least one categorized sentence; assigning an association strength to the at least one categorized sentence, the association strength indicating the likelihood that the at least on categorized sentence corresponds to the at least one category in the taxonomy; filtering the at least one categorized sentence based on the association strength; matching one or more of the at least one categorized sentence with the at least one category in the taxonomy, based on the filtering, resulting in an at least one categorized sentence matched with the at least one category in the taxonomy; and outputting only the at least one categorized sentence matched with the at least one category in the taxonomy to the spreadsheet. | 21. A non-transitory computer readable storage medium having stored thereon computer-executable instructions for viewing information associated with data in a spreadsheet, which, when executed by a processor, perform a method the comprising: providing a document including data and information associated with the data; parsing the document to retrieve the associated information; code for processing the associated information to break the associated information down into at least one sentence; categorizing the at least one sentence based on a likelihood that the at least one sentence corresponds to at least one category in a taxonomy corresponding to the data resulting in at least one categorized sentence; assigning an association strength to the at least one categorized sentence, the association strength indicating the likelihood that the at least on categorized sentence corresponds to the at least one category in the taxonomy; filtering the at least one categorized sentence based on the association strength; matching one or more of the at least one categorized sentence with the at least one category in the taxonomy, based on the filtering, resulting in an at least one categorized sentence matched with the at least one category in the taxonomy; and outputting only the at least one categorized sentence matched with the at least one category in the taxonomy to the spreadsheet. 27. The non-transitory computer readable storage medium of claim 21 , wherein the filtering comprises a “matches over n %” type filter in which only matches with association strengths above a predefined value (n) are output. | 0.5 |
9,256,590 | 1 | 9 | 1. A method of generating a spreadsheet function, comprising: receiving an electronic spreadsheet document; displaying a first content item in the electronic spreadsheet document; receiving a selection on the first content item, followed by a movement of a representation of the first content item to a formula bar associated with the electronic spreadsheet document; displaying a cell reference in the formula bar, the cell reference being a cell reference corresponding to a location of the first content item in the electronic spreadsheet document; and automatically displaying one or more spreadsheet function syntax components in the formula bar in association with the cell reference for building a spreadsheet function for operation on the first content item. | 1. A method of generating a spreadsheet function, comprising: receiving an electronic spreadsheet document; displaying a first content item in the electronic spreadsheet document; receiving a selection on the first content item, followed by a movement of a representation of the first content item to a formula bar associated with the electronic spreadsheet document; displaying a cell reference in the formula bar, the cell reference being a cell reference corresponding to a location of the first content item in the electronic spreadsheet document; and automatically displaying one or more spreadsheet function syntax components in the formula bar in association with the cell reference for building a spreadsheet function for operation on the first content item. 9. The method of claim 1 , wherein displaying a first content item in the electronic spreadsheet document includes displaying a first collection of content items, and wherein receiving the selection on the first content item followed by a movement of a representation of the first content item to a formula bar includes receiving a selection on the first collection of content items followed by a movement of a representation of the first collection of content items to the formula bar. | 0.5 |
8,706,734 | 11 | 12 | 11. A non-transitory computer readable medium storing computer readable instructions which, upon execution by a computer system, provide operation relating to electronic resource annotation comprising: receiving, for each of a plurality of categories of a resource, a category tag list of tags often applied to resources in that category; receiving, from a user terminal, one or more tags the user attributes to that resource; calculating on the basis of said one or more tags received from said user terminal and said category tag lists, a degree of membership of the resource to each of said plurality of categories; selecting two or more candidate categories to which the resource has the highest degree of membership; and proposing further tags in the category tag lists of said selected candidate categories to said user terminal, the proposed further tags including tags from a first of the two or more selected candidate categories and at least one tag from a second of the two or more selected candidate categories, the resource having a higher degree of membership with respect to the first selected candidate category than to the second selected candidate category, and the proposed further tags including a number of tags from the first selected candidate category which is higher than a number of the at least one tag from the second selected candidate category. | 11. A non-transitory computer readable medium storing computer readable instructions which, upon execution by a computer system, provide operation relating to electronic resource annotation comprising: receiving, for each of a plurality of categories of a resource, a category tag list of tags often applied to resources in that category; receiving, from a user terminal, one or more tags the user attributes to that resource; calculating on the basis of said one or more tags received from said user terminal and said category tag lists, a degree of membership of the resource to each of said plurality of categories; selecting two or more candidate categories to which the resource has the highest degree of membership; and proposing further tags in the category tag lists of said selected candidate categories to said user terminal, the proposed further tags including tags from a first of the two or more selected candidate categories and at least one tag from a second of the two or more selected candidate categories, the resource having a higher degree of membership with respect to the first selected candidate category than to the second selected candidate category, and the proposed further tags including a number of tags from the first selected candidate category which is higher than a number of the at least one tag from the second selected candidate category. 12. The method according to claim 11 wherein the tags from the first selected candidate category in the proposed further tags are the most frequently used tags in the first selected candidate category and the at least one tag from the second selected candidate category in the proposed further tags is the most frequently used tag in the second selected candidate category. | 0.5 |
8,892,549 | 19 | 20 | 19. The program product of claim 14 , where determining the topic score for the topic with respect to the document includes determining the topic score based on features of occurrence of the topic in the document. | 19. The program product of claim 14 , where determining the topic score for the topic with respect to the document includes determining the topic score based on features of occurrence of the topic in the document. 20. The program product of claim 19 , where features of an occurrence include one or more of: a location within the document of the occurrence; and typographical properties of the occurrence. | 0.5 |
10,165,291 | 1 | 11 | 1. A method of decoding an encoded video bitstream, said method comprising the steps of: receiving said encoded video bitstream comprising frame header information and macroblock information, said frame header information defining a sequence of frames and each frame being composed of macroblocks represented by said macroblock information; parsing said encoded video bitstream using a first parsing unit and a second parsing unit, each parsing unit independently deriving a full set of parsing state information from said encoded video bitstream on which subsequent parsing of said encoded video bitstream at least partially depends and which identifies data dependencies of frames in said encoded video bitstream, and identifying macroblock information for decoding, and said parsing step includes parsing all of said frame header information in both said first parsing unit and in said second parsing unit such that each parsing unit maintains said full set of said parsing state information for said encoded video bitstream; and allocating each frame of macroblock information to one of said first parsing unit and said second parsing unit, wherein said first parsing unit and said second parsing unit each parse said macroblock information, skipping macroblock information allocated to the other parsing unit, the full set parsing state information derived by each parsing unit identifying data dependencies of at least one frame allocated to the other parsing unit. | 1. A method of decoding an encoded video bitstream, said method comprising the steps of: receiving said encoded video bitstream comprising frame header information and macroblock information, said frame header information defining a sequence of frames and each frame being composed of macroblocks represented by said macroblock information; parsing said encoded video bitstream using a first parsing unit and a second parsing unit, each parsing unit independently deriving a full set of parsing state information from said encoded video bitstream on which subsequent parsing of said encoded video bitstream at least partially depends and which identifies data dependencies of frames in said encoded video bitstream, and identifying macroblock information for decoding, and said parsing step includes parsing all of said frame header information in both said first parsing unit and in said second parsing unit such that each parsing unit maintains said full set of said parsing state information for said encoded video bitstream; and allocating each frame of macroblock information to one of said first parsing unit and said second parsing unit, wherein said first parsing unit and said second parsing unit each parse said macroblock information, skipping macroblock information allocated to the other parsing unit, the full set parsing state information derived by each parsing unit identifying data dependencies of at least one frame allocated to the other parsing unit. 11. The method of decoding an encoded video bitstream as claimed in claim 1 , further comprising allocating a next frame of macroblock information to a first available parsing unit, said first available parsing unit being either said first parsing unit or said second parsing unit. | 0.793988 |
7,757,191 | 1 | 8 | 1. A computer-implemented method for race logic analysis on an integrated circuit (IC) design, to aid IC chip designers to detect and correct errors in their circuits and hence produce reliable IC products, the race logic analysis method comprising—using a processor to perform one or more of the following steps (a) detecting concurrent invocation of HDL-defined system functions/tasks that may cause one or more static or global signals/registers in the IC to be concurrently assigned or concurrently assigned and referenced, and render indeterminate values for those signals/registers; (b) detecting concurrently execution of “un-related” process blocks in the IC design that may cause one or more signals/registers to be concurrently assigned with different values, and hence render indeterminate values for those signals/registers; (c) detecting concurrently execution of “un-related” process blocks in the IC design that may cause one or more signals/registers to be concurrently assigned and being referenced by different process blocks, and render indeterminate values being read by driven process blocks; (d) detecting, dynamically via an event-driven logic simulation, circular functions/tasks invocation that may cause operation of the IC design to hang (deadlock); (e) detecting user-defined functions/tasks that invoke themselves recursively without termination, and hence render the IC design operation to hang (deadlock); (f) detecting concurrent invocation of HDL-defined functions/tasks that are built-in to HDL-defined inter-process communication (IPC) objects by “un-related” processes, that may render execution order of said “un-related” processes indeterminate, and/or that may process data that are of indeterminate values. | 1. A computer-implemented method for race logic analysis on an integrated circuit (IC) design, to aid IC chip designers to detect and correct errors in their circuits and hence produce reliable IC products, the race logic analysis method comprising—using a processor to perform one or more of the following steps (a) detecting concurrent invocation of HDL-defined system functions/tasks that may cause one or more static or global signals/registers in the IC to be concurrently assigned or concurrently assigned and referenced, and render indeterminate values for those signals/registers; (b) detecting concurrently execution of “un-related” process blocks in the IC design that may cause one or more signals/registers to be concurrently assigned with different values, and hence render indeterminate values for those signals/registers; (c) detecting concurrently execution of “un-related” process blocks in the IC design that may cause one or more signals/registers to be concurrently assigned and being referenced by different process blocks, and render indeterminate values being read by driven process blocks; (d) detecting, dynamically via an event-driven logic simulation, circular functions/tasks invocation that may cause operation of the IC design to hang (deadlock); (e) detecting user-defined functions/tasks that invoke themselves recursively without termination, and hence render the IC design operation to hang (deadlock); (f) detecting concurrent invocation of HDL-defined functions/tasks that are built-in to HDL-defined inter-process communication (IPC) objects by “un-related” processes, that may render execution order of said “un-related” processes indeterminate, and/or that may process data that are of indeterminate values. 8. The method of claim 1 , wherein during step (d), the user-defined functions/tasks are capable of invoking other user-defined functions/tasks that directly or indirectly invoke the original functions/tasks, which render circular feedback loops and cause IC designs to be deadlock when in a field operation, and wherein these user-defined functions/tasks that are capable of invoking other user-defined functions/tasks are identified and analyzed for potentially circular invocation in a static analysis. | 0.753659 |
7,693,738 | 1 | 22 | 1. A method of using a computer system to gather information about an organizational process or system, comprising: obtaining information about an organization to be assessed, wherein the information comprises information regarding assessors; the computer system preparing at least one question regarding the organizational process or system by analyzing the obtained information about the organization; the computer system displaying on a display device a first user adjustable icon and a second user adjustable icon and at least one question, the first user adjustable icon being adjustable within a first allowed range; the second user adjustable icon being adjustable within a second allowed range; and wherein the at least one question being adapted to prompt the assessor to input the assessor's perceptions of the organizational process or system; the computer system receiving a first quantitative input from a user, the first input corresponding to movement of the first user adjustable icon; the computer system determining a second allowed input range for a second user adjustable icon based on the first input, wherein the bottom of the determined second allowed input range for the second user adjustable icon is the value of the first quantitative input; the computer system displaying the second user adjustable icon such that the full width of the second user adjustable icon corresponds to the determined second allowed input range; and the computer system receiving a second quantitative input from the user, the second input corresponding to movement of the second user adjustable icon. | 1. A method of using a computer system to gather information about an organizational process or system, comprising: obtaining information about an organization to be assessed, wherein the information comprises information regarding assessors; the computer system preparing at least one question regarding the organizational process or system by analyzing the obtained information about the organization; the computer system displaying on a display device a first user adjustable icon and a second user adjustable icon and at least one question, the first user adjustable icon being adjustable within a first allowed range; the second user adjustable icon being adjustable within a second allowed range; and wherein the at least one question being adapted to prompt the assessor to input the assessor's perceptions of the organizational process or system; the computer system receiving a first quantitative input from a user, the first input corresponding to movement of the first user adjustable icon; the computer system determining a second allowed input range for a second user adjustable icon based on the first input, wherein the bottom of the determined second allowed input range for the second user adjustable icon is the value of the first quantitative input; the computer system displaying the second user adjustable icon such that the full width of the second user adjustable icon corresponds to the determined second allowed input range; and the computer system receiving a second quantitative input from the user, the second input corresponding to movement of the second user adjustable icon. 22. The method of claim 1 , further comprising receiving first and second inputs from a plurality of assessors, and determining the standard deviation of the first input, and the standard deviation of the second input, from the inputs received from the assessors, and then using a standard deviation to evaluate at least a portion of the organizational process or system. | 0.5 |
9,892,414 | 5 | 7 | 5. The computer-implemented method of claim 1 , wherein generating the data corresponding to the API request comprises: selecting a template from a plurality of available templates using a template selection model; rendering the template by replacing variables with data for the variables. | 5. The computer-implemented method of claim 1 , wherein generating the data corresponding to the API request comprises: selecting a template from a plurality of available templates using a template selection model; rendering the template by replacing variables with data for the variables. 7. The computer-implemented method of claim 5 , wherein the data for the variables is generated by performing named entity recognition on the first message received from the customer. | 0.5 |
6,101,461 | 24 | 25 | 24. A command inputting method used when inputting characters using software for Kana (Japanese character)-to-Chinese character conversion, comprising the steps of: receiving a string comprising a plurality of characters through a keyboard; determining by looking up the string in command information comprising a character string and a command correlated to said character string whether the string matches a character string in said command information; determining by referring to command execution restricting information which restricts conditions for execution of each command are satisfied or not when it is determined that the string matches said character string in said command information; executing the corresponding command when it is determined that the conditions for execution are satisfied; and replacing the string with at least one corresponding Chinese character when it is not determined that the character string is a command. | 24. A command inputting method used when inputting characters using software for Kana (Japanese character)-to-Chinese character conversion, comprising the steps of: receiving a string comprising a plurality of characters through a keyboard; determining by looking up the string in command information comprising a character string and a command correlated to said character string whether the string matches a character string in said command information; determining by referring to command execution restricting information which restricts conditions for execution of each command are satisfied or not when it is determined that the string matches said character string in said command information; executing the corresponding command when it is determined that the conditions for execution are satisfied; and replacing the string with at least one corresponding Chinese character when it is not determined that the character string is a command. 25. A computer-readable medium in which a program causing a computer to execute the method of claim 24 is recorded. | 0.5 |
10,157,229 | 12 | 14 | 12. A method for building a search service, the method comprising: receiving a request to build a search service application for a first object selected from a plurality of objects, wherein each of the plurality of objects is associated with a plurality of attributes; retrieve and present for selection the plurality of attributes associated with the first object; receiving a selection of an end-user input field corresponding to a first attribute selected from the plurality of attributes associated with the first object and a selection of a search result output field corresponding to a second attribute selected from plurality of attributes associated with the first object; building, by a computer device, the search service application for first object of the plurality of objects, the search service application being built based on at least the received selection of the end-user input field corresponding to the first attribute selected from the plurality of attributes associated with the first object and the received selection of the search result output field corresponding to the second attribute selected from the plurality of attributes associated with the first object, wherein the first attribute corresponding to the end-user input field is explicitly selected as a searchable attribute by a business expert user and the second attribute corresponding to the search result output field is explicitly selected as a displayable search result attribute by the business expert user, and the search service application being associated with a backend data store system that supports a storage structure configured to store information relating to the first object in a data record; and deploying the built search service application, the deploying including instantiating the built search service application for the backend data store and configuring, by the computer device, a search engine associated with the backend data store system to structurally modify a structure of at least one search index based on of the first attribute corresponding to the received selection of an end-user input field and the second attribute corresponding to the received selection of the search result output field, wherein the structurally modifying the structure of the at least one search index includes identifying, from a search model representing the built search service application, the first attribute and the second attribute, and configuring the search engine to expose the identified first attribute and identified second attribute in the at least one search index. | 12. A method for building a search service, the method comprising: receiving a request to build a search service application for a first object selected from a plurality of objects, wherein each of the plurality of objects is associated with a plurality of attributes; retrieve and present for selection the plurality of attributes associated with the first object; receiving a selection of an end-user input field corresponding to a first attribute selected from the plurality of attributes associated with the first object and a selection of a search result output field corresponding to a second attribute selected from plurality of attributes associated with the first object; building, by a computer device, the search service application for first object of the plurality of objects, the search service application being built based on at least the received selection of the end-user input field corresponding to the first attribute selected from the plurality of attributes associated with the first object and the received selection of the search result output field corresponding to the second attribute selected from the plurality of attributes associated with the first object, wherein the first attribute corresponding to the end-user input field is explicitly selected as a searchable attribute by a business expert user and the second attribute corresponding to the search result output field is explicitly selected as a displayable search result attribute by the business expert user, and the search service application being associated with a backend data store system that supports a storage structure configured to store information relating to the first object in a data record; and deploying the built search service application, the deploying including instantiating the built search service application for the backend data store and configuring, by the computer device, a search engine associated with the backend data store system to structurally modify a structure of at least one search index based on of the first attribute corresponding to the received selection of an end-user input field and the second attribute corresponding to the received selection of the search result output field, wherein the structurally modifying the structure of the at least one search index includes identifying, from a search model representing the built search service application, the first attribute and the second attribute, and configuring the search engine to expose the identified first attribute and identified second attribute in the at least one search index. 14. The method of claim 12 wherein the search service application is built further based on at least one of a search result filtering field corresponding to a third attribute selected from the plurality of attributes associated with the first object and a facets field corresponding to a fourth attribute of the plurality of attributes associated with the first object, the method further comprising configuring, by the computer device, the search engine to, at least one of: generate and update at least one search index based on the third attribute corresponding to at least one of the search result filtering field and the fourth attribute corresponding to at least one of the facets field. | 0.551166 |
8,676,730 | 10 | 13 | 10. An apparatus operable to provide at least one sentiment classifier based on a plurality of features, the apparatus comprising: a feature extraction component, implemented by at least one processing device, operable to extract the plurality of features from training data, wherein the training data comprises a plurality of units, the feature extraction component comprising: a part-of-speech (PoS) sub-component operable to label at least one element of each unit of the training data according to a plurality of PoS tags to provide PoS features; a dictionary sub-component operable to: check at least one element of each unit of the training data according to a plurality of dictionaries to provide dictionary features; and a negation/inversion sub-component operable to detect a plurality of negation/inversion elements in the training data to provide a plurality of negation/inversion features based on a negation dictionary and an inversion dictionary of the plurality of dictionaries, and operable to label at least one element after each of the plurality of negation/inversion features to provide negated/inverted elements features based on at least one of a propagation window or punctuation in the training data; a feature value determination component, implemented by the at least one processing device and operatively connected to the feature extraction component, operable to determine a value for each feature of the plurality of features based on a frequency at which each feature occurs in the training data; a class labeling component, implemented by the at least one processing device, operable to label each unit of the training data according to a plurality of sentiment classes to provide labeled training data; and a sentiment classifier generation component, implemented by the at least one processing device and operatively connected to the feature value determination component and the class labeling component, operable to provide the at least one sentiment classifier based on the value of each feature of the plurality of features and the labeled training data using a supervised classification technique. | 10. An apparatus operable to provide at least one sentiment classifier based on a plurality of features, the apparatus comprising: a feature extraction component, implemented by at least one processing device, operable to extract the plurality of features from training data, wherein the training data comprises a plurality of units, the feature extraction component comprising: a part-of-speech (PoS) sub-component operable to label at least one element of each unit of the training data according to a plurality of PoS tags to provide PoS features; a dictionary sub-component operable to: check at least one element of each unit of the training data according to a plurality of dictionaries to provide dictionary features; and a negation/inversion sub-component operable to detect a plurality of negation/inversion elements in the training data to provide a plurality of negation/inversion features based on a negation dictionary and an inversion dictionary of the plurality of dictionaries, and operable to label at least one element after each of the plurality of negation/inversion features to provide negated/inverted elements features based on at least one of a propagation window or punctuation in the training data; a feature value determination component, implemented by the at least one processing device and operatively connected to the feature extraction component, operable to determine a value for each feature of the plurality of features based on a frequency at which each feature occurs in the training data; a class labeling component, implemented by the at least one processing device, operable to label each unit of the training data according to a plurality of sentiment classes to provide labeled training data; and a sentiment classifier generation component, implemented by the at least one processing device and operatively connected to the feature value determination component and the class labeling component, operable to provide the at least one sentiment classifier based on the value of each feature of the plurality of features and the labeled training data using a supervised classification technique. 13. The apparatus of claim 10 , wherein the class labeling component is further operable to: apply an existing sentiment classifier to each unit of the training data to provide a sentiment score for each unit of the training data; and label each unit of the training data with one of the plurality of sentiment classes based on the sentiment score. | 0.751783 |
9,336,496 | 1 | 8 | 1. A computer-implemented method for generating a reference set via clustering, comprising the steps of: obtaining a collection of unclassified documents; grouping the unclassified documents into clusters; selecting n-documents from each cluster, comprising: building a hierarchical tree of the clusters; and traversing the hierarchical tree to identify the n-documents, wherein one of the n-documents from each cluster is located closest to a center of that cluster; combining the selected n-documents as reference set candidates assigning a classification code to each of the reference set candidates; and grouping two or more of the reference set candidates as a reference set of classified documents, wherein the steps are performed by a suitably programmed computer. | 1. A computer-implemented method for generating a reference set via clustering, comprising the steps of: obtaining a collection of unclassified documents; grouping the unclassified documents into clusters; selecting n-documents from each cluster, comprising: building a hierarchical tree of the clusters; and traversing the hierarchical tree to identify the n-documents, wherein one of the n-documents from each cluster is located closest to a center of that cluster; combining the selected n-documents as reference set candidates assigning a classification code to each of the reference set candidates; and grouping two or more of the reference set candidates as a reference set of classified documents, wherein the steps are performed by a suitably programmed computer. 8. A method according to claim 1 , further comprising: identifying features of the unclassified documents; grouping the features into clusters; identifying n-features from each cluster as reference set candidate features; assigning a classification code to each of the reference set candidate features; and grouping at least a portion of the documents associated with the classified reference set candidate features as a further reference set. | 0.5 |
9,633,674 | 14 | 16 | 14. The electronic device of claim 13 , wherein detecting the user interaction comprises detecting an additional speech input, and determining whether the user interaction is indicative of a problem comprises determining that the additional speech input indicates dissatisfaction with the at least one action. | 14. The electronic device of claim 13 , wherein detecting the user interaction comprises detecting an additional speech input, and determining whether the user interaction is indicative of a problem comprises determining that the additional speech input indicates dissatisfaction with the at least one action. 16. The electronic device of claim 14 , wherein determining whether the additional speech input indicates dissatisfaction includes determining a volume of the additional speech input. | 0.623457 |
9,268,818 | 6 | 11 | 6. The method of claim 1 , further comprising: responsive to receiving the selection of at least one of the plurality of content components of the recommended content applicable to the recommendation made by the user, the social network application sending to a server, in communication with the user device over a network, data identifying the at least one content component of the recommended content selected by the user; and receiving at the social network application, from the server, an annotation for display in the social network application, the annotation indicating the at least one content component of the recommended content to which the recommendation of the user applies. | 6. The method of claim 1 , further comprising: responsive to receiving the selection of at least one of the plurality of content components of the recommended content applicable to the recommendation made by the user, the social network application sending to a server, in communication with the user device over a network, data identifying the at least one content component of the recommended content selected by the user; and receiving at the social network application, from the server, an annotation for display in the social network application, the annotation indicating the at least one content component of the recommended content to which the recommendation of the user applies. 11. The method of claim 6 , wherein the data identifying the at least one content component of the recommended content selected by the user is sent by the social network application to the server as encrypted data. | 0.5 |
7,680,853 | 5 | 6 | 5. The method of claim 1 wherein using the query term to retrieve a document identifier and a position identifier comprises comparing a term confidence level to word scores associated with occurrences of the query term in the index and retrieving document identifiers and position identifiers that are associated with word scores that exceed the term confidence level, wherein the word scores are based on probabilities of phonetic units given feature vectors formed from the audio signal. | 5. The method of claim 1 wherein using the query term to retrieve a document identifier and a position identifier comprises comparing a term confidence level to word scores associated with occurrences of the query term in the index and retrieving document identifiers and position identifiers that are associated with word scores that exceed the term confidence level, wherein the word scores are based on probabilities of phonetic units given feature vectors formed from the audio signal. 6. The method of claim 5 further comprising: determining that the query term comprises a combination of two query words; and increasing the word scores retrieved from the index for occurrences of the query term before comparing the word scores to the term confidence level. | 0.594955 |
9,009,192 | 1 | 4 | 1. A method implemented by a data processing apparatus, the method comprising: identifying multiple candidate entities that are associated with a first web resource, each candidate entity being a word or a phrase; obtaining a first entity graph representing relationships between entities associated with resources in a collection of resources, wherein the first entity graph includes multiple nodes, each node representing a different entity associated with a respective resource in the collection of resources, each entity being a word or a phrase, wherein the first entity graph includes edges connecting pairs of nodes, and wherein each of the edges represents that two nodes connected by an edge represent two entities that are frequently associated with a same resource in the collection of resources; filtering the first entity graph to remove nodes that do not represent any of the candidate entities associated with the first web resource; generating, from the filtered first entity graph, a second entity graph for the first resource, including removing nodes from the filtered first entity graph that are not connected by an edge to at least one other node in the filtered first entity graph; identifying candidate entities that are represented by respective nodes in the second entity graph as being central entities for the first resource; generating respective search queries for each of the identified central entities; obtaining search results responsive to the search queries from a search engine; selecting a web resource referenced by a particular search result of the obtained search results as relevant additional content for the first web resource; and associating the relevant additional content with the first web resource for presentation to a user requesting content from the first web resource. | 1. A method implemented by a data processing apparatus, the method comprising: identifying multiple candidate entities that are associated with a first web resource, each candidate entity being a word or a phrase; obtaining a first entity graph representing relationships between entities associated with resources in a collection of resources, wherein the first entity graph includes multiple nodes, each node representing a different entity associated with a respective resource in the collection of resources, each entity being a word or a phrase, wherein the first entity graph includes edges connecting pairs of nodes, and wherein each of the edges represents that two nodes connected by an edge represent two entities that are frequently associated with a same resource in the collection of resources; filtering the first entity graph to remove nodes that do not represent any of the candidate entities associated with the first web resource; generating, from the filtered first entity graph, a second entity graph for the first resource, including removing nodes from the filtered first entity graph that are not connected by an edge to at least one other node in the filtered first entity graph; identifying candidate entities that are represented by respective nodes in the second entity graph as being central entities for the first resource; generating respective search queries for each of the identified central entities; obtaining search results responsive to the search queries from a search engine; selecting a web resource referenced by a particular search result of the obtained search results as relevant additional content for the first web resource; and associating the relevant additional content with the first web resource for presentation to a user requesting content from the first web resource. 4. The method of claim 1 , wherein each edge in the first entity graph and the second entity graph is weighted, and wherein a weight of an edge between a particular pair of nodes is based on a measure of relatedness of the pair of entities represented by the nodes. | 0.807692 |
10,142,708 | 6 | 8 | 6. The method of claim 2 , further comprising: identifying, by the at least one processor-based component, at least one candidate for the user to share with based at least in part on the narrative path graph specific to the user and the respective narrative. | 6. The method of claim 2 , further comprising: identifying, by the at least one processor-based component, at least one candidate for the user to share with based at least in part on the narrative path graph specific to the user and the respective narrative. 8. The method of claim 6 wherein identifying at least one candidate for the user to share with based at least in part on the narrative path graph for the user and the respective narrative includes comparing the narrative path graph specific to the user and the respective narrative to respective narrative path graphs specific to a plurality of other users and the respective narrative. | 0.657801 |
7,574,347 | 1 | 2 | 1. A method of parsing text in a computing device to form a logical representation of the text, the logical representation having tokens representing other tokens and words of the text, the method comprising: forming tokens from the text; selecting a token; a processor identifying an integer that represents the selected token, wherein identifying an integer comprises identifying an integer that is an offset into a pointer array of cells, the offset identifying a cell comprising a pointer that points to an identifier array of cells, each cell in the identifier array providing a token identifier for a token that is activated by the selected token according to a parsing rule for the token where the selected token is a first child node in the parsing rule; a processor utilizing the integer to identify: at least one token that is activated by the selected token; and a parsing rule that licenses the activation of the token by the selected token to form an activated token where the selected token is a first child node in the parsing rule; a processor adding at least one activated token to a chart; and a processor using the activated token to form the logical representation of the text. | 1. A method of parsing text in a computing device to form a logical representation of the text, the logical representation having tokens representing other tokens and words of the text, the method comprising: forming tokens from the text; selecting a token; a processor identifying an integer that represents the selected token, wherein identifying an integer comprises identifying an integer that is an offset into a pointer array of cells, the offset identifying a cell comprising a pointer that points to an identifier array of cells, each cell in the identifier array providing a token identifier for a token that is activated by the selected token according to a parsing rule for the token where the selected token is a first child node in the parsing rule; a processor utilizing the integer to identify: at least one token that is activated by the selected token; and a parsing rule that licenses the activation of the token by the selected token to form an activated token where the selected token is a first child node in the parsing rule; a processor adding at least one activated token to a chart; and a processor using the activated token to form the logical representation of the text. 2. The method of claim 1 wherein the token identifiers are integers. | 0.5 |
7,779,397 | 18 | 19 | 18. The computer-implemented system of claim 17 , wherein using the second interface component to strongly type the untyped datum includes compiling source code that refers to the untyped datum. | 18. The computer-implemented system of claim 17 , wherein using the second interface component to strongly type the untyped datum includes compiling source code that refers to the untyped datum. 19. The computer-implemented system of claim 18 , wherein compiling source code includes erasing a type associated with the second interface component. | 0.5 |
9,825,890 | 1 | 14 | 1. A method comprising: determining one or more events performed on a first data content object of a file, the one or more events being performed by a first user on a first client device using a data-content-object processing application, the file being stored in a data store, the first data content object being a defined portion less than all of the file; storing one or more event indications about the one or more events in a history buffer, each of the one or more event indications including event metadata indicating the one or more events performed by the first user on the first data content object; retrieving a notification threshold condition associated with a second user, wherein the notification threshold condition is based on a notification frequency determined by the second user, the notification threshold condition defining first criteria for determining which of the one or more event indications are relevant to the second user and second criteria for determining based on at least one of the one or more event indications being relevant to the second user whether to generate and send a notification to the second user, the first criteria defining that a particular event indication is relevant to the second user based on, at least in part, whether the second user has collaboratively worked with another user that has commented on the first data content object of the file, the second criteria defining whether to generate and send the notification to the second user based on, at least in part, second user preferences configurable by the second user and defining threshold quality of change to the first data content object before the generating and sending of the notification; using the first criteria to determine which of the one or more event indications are relevant to the second user; using the second criteria to determine whether the at least one of the one or more event indications being relevant to the second user satisfies the threshold quality of change to the first data content object; and if the second criteria is satisfied, generating and sending the notification for the second user. | 1. A method comprising: determining one or more events performed on a first data content object of a file, the one or more events being performed by a first user on a first client device using a data-content-object processing application, the file being stored in a data store, the first data content object being a defined portion less than all of the file; storing one or more event indications about the one or more events in a history buffer, each of the one or more event indications including event metadata indicating the one or more events performed by the first user on the first data content object; retrieving a notification threshold condition associated with a second user, wherein the notification threshold condition is based on a notification frequency determined by the second user, the notification threshold condition defining first criteria for determining which of the one or more event indications are relevant to the second user and second criteria for determining based on at least one of the one or more event indications being relevant to the second user whether to generate and send a notification to the second user, the first criteria defining that a particular event indication is relevant to the second user based on, at least in part, whether the second user has collaboratively worked with another user that has commented on the first data content object of the file, the second criteria defining whether to generate and send the notification to the second user based on, at least in part, second user preferences configurable by the second user and defining threshold quality of change to the first data content object before the generating and sending of the notification; using the first criteria to determine which of the one or more event indications are relevant to the second user; using the second criteria to determine whether the at least one of the one or more event indications being relevant to the second user satisfies the threshold quality of change to the first data content object; and if the second criteria is satisfied, generating and sending the notification for the second user. 14. The method of claim 1 , wherein the second user sets the notification threshold condition. | 0.75 |
8,849,807 | 1 | 3 | 1. A system for ranking websites comprising: a first computer database comprising machine-readable memory having website indexing records, each website indexing record comprising an indexed website ID and website indexing information; a second computer database comprising machine-readable memory having total activity records, each total activity record comprising an activity website ID and a total activity weight; a third computer database comprising machine-readable memory having activity records, each activity record comprising: an affiliated website ID, a website promoter ID associated with the affiliated website ID, the website promoter ID identifying a human website promoter, a website activity ID, the website activity ID identifying a website activity, the website activity being performed by the website promoter, and an activity weight for the website activity; a tracking system comprising a tracking system network connection and one or more tracking system processors, the one or more tracking system processors having computer-executable instructions for: tracking the website activities through the tracking system network connection, assembling tracked activity records, and transmitting the tracked activity records through the tracking system network connection; a search engine computer network having a search engine network connection and one or more search engine processors, the one or more search engine processors having computer-executable instructions for: receiving a search query through the search engine network connection into the one or more search engine processors, the search query comprising search criteria; transmitting a request for the website indexing records from the one or more search engine processors to the first computer database; receiving the website indexing records from the first computer database into the one or more search engine processors; calculating a relevance score for each indexed website ID by the one or more search engine processors, the relevance score being based on the search criteria and the website indexing information of each website indexing record; transmitting a request for the total activity records from the one or more search engine processors to the second computer database; receiving the total activity records from the second computer database into the one or more search engine processors; matching the website indexing records with the total activity records by comparing the indexed website IDs to the activity website IDs by the one or more search engine processors; calculating a total weight for each indexed website ID by the one or more search engine processors, the total weight being based on the relevance score of the indexed website ID and the total activity weight in the matching total activity record; assembling a list of the indexed website IDs ranked by the total weight of each indexed website ID by the one or more search engine processors; transmitting a request for the activity records from the one or more search engine processors to the third computer database; receiving the requested activity records into the one or more search engine processors from the third computer database; and for each requested activity record received: transmitting a request for a total activity record from the one or more search engine processors to the second computer database, the request comprising the affiliated website ID of the requested activity record; receiving the requested total activity record from the second computer database into the one or more search engine processors, wherein the activity website ID of the requested total activity record is identical to the affiliated website ID of the requested activity record; calculating a new total activity weight from the sum of the activity weight of the requested activity record and the total activity weight of the requested total activity record by the one or more search engine processors; and transmitting the new total activity weight from the one or more search engine processors to the second computer database. | 1. A system for ranking websites comprising: a first computer database comprising machine-readable memory having website indexing records, each website indexing record comprising an indexed website ID and website indexing information; a second computer database comprising machine-readable memory having total activity records, each total activity record comprising an activity website ID and a total activity weight; a third computer database comprising machine-readable memory having activity records, each activity record comprising: an affiliated website ID, a website promoter ID associated with the affiliated website ID, the website promoter ID identifying a human website promoter, a website activity ID, the website activity ID identifying a website activity, the website activity being performed by the website promoter, and an activity weight for the website activity; a tracking system comprising a tracking system network connection and one or more tracking system processors, the one or more tracking system processors having computer-executable instructions for: tracking the website activities through the tracking system network connection, assembling tracked activity records, and transmitting the tracked activity records through the tracking system network connection; a search engine computer network having a search engine network connection and one or more search engine processors, the one or more search engine processors having computer-executable instructions for: receiving a search query through the search engine network connection into the one or more search engine processors, the search query comprising search criteria; transmitting a request for the website indexing records from the one or more search engine processors to the first computer database; receiving the website indexing records from the first computer database into the one or more search engine processors; calculating a relevance score for each indexed website ID by the one or more search engine processors, the relevance score being based on the search criteria and the website indexing information of each website indexing record; transmitting a request for the total activity records from the one or more search engine processors to the second computer database; receiving the total activity records from the second computer database into the one or more search engine processors; matching the website indexing records with the total activity records by comparing the indexed website IDs to the activity website IDs by the one or more search engine processors; calculating a total weight for each indexed website ID by the one or more search engine processors, the total weight being based on the relevance score of the indexed website ID and the total activity weight in the matching total activity record; assembling a list of the indexed website IDs ranked by the total weight of each indexed website ID by the one or more search engine processors; transmitting a request for the activity records from the one or more search engine processors to the third computer database; receiving the requested activity records into the one or more search engine processors from the third computer database; and for each requested activity record received: transmitting a request for a total activity record from the one or more search engine processors to the second computer database, the request comprising the affiliated website ID of the requested activity record; receiving the requested total activity record from the second computer database into the one or more search engine processors, wherein the activity website ID of the requested total activity record is identical to the affiliated website ID of the requested activity record; calculating a new total activity weight from the sum of the activity weight of the requested activity record and the total activity weight of the requested total activity record by the one or more search engine processors; and transmitting the new total activity weight from the one or more search engine processors to the second computer database. 3. The system of claim 1 , wherein the website activity of each activity record is selected from the group consisting of: the website promoter logging into a tracked website; the website promoter opening a tracked email; the website promoter clicking on a tracked email hyperlink in the tracked email; the website promoter clicking on a tracked website hyperlink on the webpage content transmitted by the tracked website; the website promoter uploading personal information to the tracked website; the website promoter submitting a tracked search query to the tracked website; the website promoter uploading a review of an affiliated website to the tracked website; the website promoter publishing a tracked promoter hyperlink on a promoted webpage, the tracked promoter hyperlink being enabled to transmit a tracked request for webpage content to the tracked website; the website promoter making a tracked relationship with another person through a tracked online social networking platform; the website promoter removing the tracked relationship; the website promoter sending a tracked message through the tracked online social networking platform; the website promoter registering a domain name on a tracked domain name registry; the website promoter creating a tracked account with the tracked website; and the website promoter uploading tracked content to the tracked website. | 0.5 |
7,893,850 | 1 | 5 | 1. A method of disambiguating an input into a handheld electronic device having an input device, an output device, and a memory having stored therein a plurality of language objects, the input device including a first input member and a plurality of second input members, each of at least some of the second input members having a plurality of characters assigned thereto, one of the second input members being a <NEXT> second input member and including a particular visual appearance, the <NEXT> second input member being adapted to provide a selection input, the method comprising: detecting an ambiguous input; generating a prefix object corresponding with the ambiguous input; identifying a language object corresponding with the prefix object; outputting a default output comprising the prefix object and a variant output; and outputting a visual indicator representative of the particular visual appearance of the <NEXT> second input member as an indication that alternative variant outputs are available. | 1. A method of disambiguating an input into a handheld electronic device having an input device, an output device, and a memory having stored therein a plurality of language objects, the input device including a first input member and a plurality of second input members, each of at least some of the second input members having a plurality of characters assigned thereto, one of the second input members being a <NEXT> second input member and including a particular visual appearance, the <NEXT> second input member being adapted to provide a selection input, the method comprising: detecting an ambiguous input; generating a prefix object corresponding with the ambiguous input; identifying a language object corresponding with the prefix object; outputting a default output comprising the prefix object and a variant output; and outputting a visual indicator representative of the particular visual appearance of the <NEXT> second input member as an indication that alternative variant outputs are available. 5. The method of claim 1 , further comprising providing a rotatable thumbwheel, and detecting a rotational input of the thumbwheel and an actuation of the <NEXT> second input member as being substantially identical to one another. | 0.5 |
9,128,723 | 17 | 18 | 17. The computer readable medium of claim 16 , wherein the at least one modification to the DOM elements comprises a line number where the at least one modification is made. | 17. The computer readable medium of claim 16 , wherein the at least one modification to the DOM elements comprises a line number where the at least one modification is made. 18. The computer readable medium of claim 17 , wherein modifications made to the DOM elements within a function are stored as changes made at the line number where the function call was invoked. | 0.5 |
8,913,187 | 10 | 16 | 10. A method to detect garbled closed captioning data, comprising: detecting closed captioning data in a video data stream; identifying and extracting individual words from the closed captioning data; determining a word boundary in the closed captioning data using a delimiter; storing a count of the total number of words in the closed captioning data in a memory based on the determined word boundary; storing a count of the total number of words having a desired word length or range of word lengths in the closed captioning data in the memory based on the determined word boundary; determining a percentage of words having the desired length or range of lengths in the closed captioning data as a ratio of the count of the number of words in the closed captioning data having the desired length or range of lengths to the count of the total number of words in the closed captioning data; and providing an alert when the determined percentage exceeds a predetermined threshold. | 10. A method to detect garbled closed captioning data, comprising: detecting closed captioning data in a video data stream; identifying and extracting individual words from the closed captioning data; determining a word boundary in the closed captioning data using a delimiter; storing a count of the total number of words in the closed captioning data in a memory based on the determined word boundary; storing a count of the total number of words having a desired word length or range of word lengths in the closed captioning data in the memory based on the determined word boundary; determining a percentage of words having the desired length or range of lengths in the closed captioning data as a ratio of the count of the number of words in the closed captioning data having the desired length or range of lengths to the count of the total number of words in the closed captioning data; and providing an alert when the determined percentage exceeds a predetermined threshold. 16. The method recited in claim 10 , wherein the desired word length or range of word lengths is greater or equal to 10 characters. | 0.704955 |
9,767,188 | 6 | 7 | 6. The method of claim 1 , further comprising: receiving an input from the user device, the input identifying one of the first and second candidates; and performing an action using the identified candidate. | 6. The method of claim 1 , further comprising: receiving an input from the user device, the input identifying one of the first and second candidates; and performing an action using the identified candidate. 7. The method of claim 6 , wherein the action comprises performing a search of an online database for content that corresponds to the identified candidate. | 0.614428 |
8,904,348 | 3 | 5 | 3. The method of claim 1 , further comprising creating a plurality of custom processes executed for at least one statement. | 3. The method of claim 1 , further comprising creating a plurality of custom processes executed for at least one statement. 5. The method of claim 3 , wherein executing the plurality of statements further comprises executing the custom processes for the at least one statement. | 0.5 |
9,977,802 | 14 | 18 | 14. A database system comprising: one or more processors; and one or more memories in communication with the one or more processors, the one or more memories storing computer-executable instructions to perform operations comprising: receiving a request to access a large string value, the request comprising a value ID or a value string; searching a value block vector, the value block vector associated with a dictionary page for a dictionary block of a dictionary comprising multiple dictionary blocks, for a value block corresponding to the value ID, or a value ID corresponding to the value string, the value block comprising a first portion of the requested large string value and one or more physical or logical pointers to one or more large string blocks containing a remainder of the large string value; loading the first portion of the large string value from the value block, and loading the remainder of the large string value by dereferencing the one or more physical or logical pointers to load from at least corresponding referenced large string blocks the remainder of the large string value, providing the large string value; storing the loaded large string value in memory; creating a pointer to the stored large string value; storing the pointer to the large string value; and returning a pointer that can be dereferenced to access the stored large string value in response to the request. | 14. A database system comprising: one or more processors; and one or more memories in communication with the one or more processors, the one or more memories storing computer-executable instructions to perform operations comprising: receiving a request to access a large string value, the request comprising a value ID or a value string; searching a value block vector, the value block vector associated with a dictionary page for a dictionary block of a dictionary comprising multiple dictionary blocks, for a value block corresponding to the value ID, or a value ID corresponding to the value string, the value block comprising a first portion of the requested large string value and one or more physical or logical pointers to one or more large string blocks containing a remainder of the large string value; loading the first portion of the large string value from the value block, and loading the remainder of the large string value by dereferencing the one or more physical or logical pointers to load from at least corresponding referenced large string blocks the remainder of the large string value, providing the large string value; storing the loaded large string value in memory; creating a pointer to the stored large string value; storing the pointer to the large string value; and returning a pointer that can be dereferenced to access the stored large string value in response to the request. 18. The database system of claim 14 , the operations further comprising: loading one or more intermediate dictionary blocks, each of the one or more intermediate dictionary blocks containing one or more logical pointers to one or more value blocks of one or more of the multiple dictionary blocks for normal string values and/or one or more logical pointers to one or more large string dictionary blocks for large string values. | 0.542735 |
9,286,292 | 15 | 16 | 15. A computer system for identifying and translating jargon, the computer system comprising: one or more computer processors; one or more computer-readable storage medium; program instructions stored on the computer-readable storage medium for execution by at least one of the one or more processors, the program instructions comprising: program instructions to retrieve a profile information of a first participant of a multi-party communication, wherein the profile information of the first participant i) includes demographic information related to the first participant, and ii) indicates a location of the first participant; program instructions to identify an original jargon submitted by a second participant included in the multi-party communication based, at least in part, on the profile information of the first participant; program instructions to predict whether the first participant will understand the original jargon based, at least in part, on the demographic information related to the first participant and the location of the first participant; program instructions to respond to a prediction that the first participant will not understand the original jargon by generating a translated jargon by translating the original jargon based, at least in part, on the profile information of the first participant, wherein the translated jargon can be understood by the first participant of the multi-party communication; and program instructions to send the translated jargon to the first participant of the multi-party communication. | 15. A computer system for identifying and translating jargon, the computer system comprising: one or more computer processors; one or more computer-readable storage medium; program instructions stored on the computer-readable storage medium for execution by at least one of the one or more processors, the program instructions comprising: program instructions to retrieve a profile information of a first participant of a multi-party communication, wherein the profile information of the first participant i) includes demographic information related to the first participant, and ii) indicates a location of the first participant; program instructions to identify an original jargon submitted by a second participant included in the multi-party communication based, at least in part, on the profile information of the first participant; program instructions to predict whether the first participant will understand the original jargon based, at least in part, on the demographic information related to the first participant and the location of the first participant; program instructions to respond to a prediction that the first participant will not understand the original jargon by generating a translated jargon by translating the original jargon based, at least in part, on the profile information of the first participant, wherein the translated jargon can be understood by the first participant of the multi-party communication; and program instructions to send the translated jargon to the first participant of the multi-party communication. 16. The computer system of claim 15 , the program instructions further comprising: program instructions to predict whether the participant of the multi-party communication will understand the original jargon based, at least in part, on i) the profile information of the first participant and a profile information of a second participant of the multi-party communication, wherein the profile information of the second participant includes a location of the second participant and a primary language used for communication by the second participant, and ii) at least one of: a translation of the original jargon, a definition of the original jargon, a result of a text analysis including the original jargon, and a search result for original jargon. | 0.505945 |
7,606,785 | 1 | 5 | 1. A machine implemented method, comprising: receiving a set of rules, specifying actions to be taken in response to finding specific types of input data and a format of an output t-box; receiving a first set of input information, in a format satisfying the rules; wherein the input information has sufficient structure to enable rules to be applied to the input information to determine individual fields therefrom; generating from the first set of input information and the set of rules a t-box comprising categories and relationships about categories, and an a-box comprising assertions of individual instances of the categories of the t-box, wherein the a-box is generated by applying the set of rules to the first set of input information, and wherein the t-box and the a-box are generated concurrently such that the a-box is generated while the t-box is being generated; generating a Web Ontology Language (“OWL”) database using the a-box and the t-box; and generating a knowledge base based on OWL statements of the OWL database, wherein the method is performed by a computer executing program instructions. | 1. A machine implemented method, comprising: receiving a set of rules, specifying actions to be taken in response to finding specific types of input data and a format of an output t-box; receiving a first set of input information, in a format satisfying the rules; wherein the input information has sufficient structure to enable rules to be applied to the input information to determine individual fields therefrom; generating from the first set of input information and the set of rules a t-box comprising categories and relationships about categories, and an a-box comprising assertions of individual instances of the categories of the t-box, wherein the a-box is generated by applying the set of rules to the first set of input information, and wherein the t-box and the a-box are generated concurrently such that the a-box is generated while the t-box is being generated; generating a Web Ontology Language (“OWL”) database using the a-box and the t-box; and generating a knowledge base based on OWL statements of the OWL database, wherein the method is performed by a computer executing program instructions. 5. The method of claim 1 , wherein the first set of input information comprises statements in a markup language. | 0.916293 |
4,727,547 | 1 | 4 | 1. A method for transforming a first sequence of words, comprising digital data words and correction words and having a first ordering of said data words and correction words, comprising the steps of: forming blocks out of said first sequence, each block consisting of a plurality of said data words and a plurality of said correction words in said first ordering; selecting data words and correction words from said first sequence and combining said data words and correction words in a way to form a second sequence with a second ordering of data words and correction words; selecting out of the second sequence of words a first group and a second group each composed of data words and correction words in such a way that said first group and said second group (share) have one common word (with one of said blocks of words having the first ordering) and said common word also belongs to one of said blocks composed of words having said first ordering; submitting simultaneously the data words of the first group and of the second group to a checking operation; evaluating the result of the checking operation and deciding if erroneous data words of the first group and of the second group can be corrected; and correcting said second sequence of words using said correction words, when indicated by said evaluation. | 1. A method for transforming a first sequence of words, comprising digital data words and correction words and having a first ordering of said data words and correction words, comprising the steps of: forming blocks out of said first sequence, each block consisting of a plurality of said data words and a plurality of said correction words in said first ordering; selecting data words and correction words from said first sequence and combining said data words and correction words in a way to form a second sequence with a second ordering of data words and correction words; selecting out of the second sequence of words a first group and a second group each composed of data words and correction words in such a way that said first group and said second group (share) have one common word (with one of said blocks of words having the first ordering) and said common word also belongs to one of said blocks composed of words having said first ordering; submitting simultaneously the data words of the first group and of the second group to a checking operation; evaluating the result of the checking operation and deciding if erroneous data words of the first group and of the second group can be corrected; and correcting said second sequence of words using said correction words, when indicated by said evaluation. 4. Method according to claim 1, comprising the steps of: adding a block error detection code word to the blocks of said first sequence prior to transforming said first sequence; for transforming said first sequence, first checking said blocks of said first sequence with respect to said block error detection code by generating again a code word and comparing it with the existing code word; adjoining a block flag to each block of the first sequence composed of data words and correction words according to the results of said checking with respect to the block error detection code, said block flag marking erroneous and error free blocks; and deriving word flags from said block flags for the data words and correction words of said blocks, said word flags being set for a group of word preceeding said group of data words and correction words already under checking and evaluation operations. | 0.503326 |
9,965,812 | 12 | 13 | 12. The method of claim 1 , further comprising: providing a suggestion that the entity profile be modified based on the overrepresented common token determined to be descriptive of the common entity. | 12. The method of claim 1 , further comprising: providing a suggestion that the entity profile be modified based on the overrepresented common token determined to be descriptive of the common entity. 13. The method of claim 12 , wherein: the providing of the suggestion includes communicating the suggestion to an author of the entity profile. | 0.5 |
8,112,544 | 6 | 8 | 6. A system for formatting content for display on a mobile wireless client device that is based on a form that is used to display content, the form being associated with an action that is executable by an application, wherein the form is stored remotely from the mobile wireless client device, the system comprising: a server comprising one or more processors configured to: receive from the mobile wireless client device via a wireless medium a selection of an action made by a user on an interface of the mobile wireless client device; generate content that is displayed using a form by executing the action remotely from the mobile wireless client device, wherein the form includes a user-customized mobile design element; format the content according to a user-customized mobile design element for inclusion in the form, wherein the user-customized mobile design element is associated with the mobile wireless client device and has been customized by the user of the mobile wireless client device; transmit the content formatted according to the mobile design element to the wireless client device via the wireless medium; and store the mobile design element remotely from the mobile wireless client device for future access by the server. | 6. A system for formatting content for display on a mobile wireless client device that is based on a form that is used to display content, the form being associated with an action that is executable by an application, wherein the form is stored remotely from the mobile wireless client device, the system comprising: a server comprising one or more processors configured to: receive from the mobile wireless client device via a wireless medium a selection of an action made by a user on an interface of the mobile wireless client device; generate content that is displayed using a form by executing the action remotely from the mobile wireless client device, wherein the form includes a user-customized mobile design element; format the content according to a user-customized mobile design element for inclusion in the form, wherein the user-customized mobile design element is associated with the mobile wireless client device and has been customized by the user of the mobile wireless client device; transmit the content formatted according to the mobile design element to the wireless client device via the wireless medium; and store the mobile design element remotely from the mobile wireless client device for future access by the server. 8. The system of claim 6 , wherein the customization of the mobile design element by the user impacts one or both of the type of information included in the content and/or the visual layout of the content. | 0.677673 |
8,423,366 | 1 | 17 | 1. A method comprising: receiving, by a system, a voicemail associated with a user; transcribing, by the system, the voicemail into text that includes a group of words; storing, by the system, an association between a portion of each respective word from the group of words and a corresponding portion of the voicemail, wherein the corresponding portion of the voicemail is the portion of the voicemail from which the portion of the respective word was transcribed; generating, by the system, a voiceprint from the voicemail; comparing, by the system, the voiceprint to voiceprints generated from previously received voicemails; identifying, by the system, based at least in part on the comparison and a portion of the voiceprints generated from the previously received voicemails, at least one matching voiceprint; selecting, by the system, based at least in part on the at least one matching voiceprint, a speech synthesis voice associated with the user; and determining, by the system, a modification to the speech synthesis voice associated with the user based at least in part on the association between the portion of each respective word from the group of words and the corresponding portion of the voicemail. | 1. A method comprising: receiving, by a system, a voicemail associated with a user; transcribing, by the system, the voicemail into text that includes a group of words; storing, by the system, an association between a portion of each respective word from the group of words and a corresponding portion of the voicemail, wherein the corresponding portion of the voicemail is the portion of the voicemail from which the portion of the respective word was transcribed; generating, by the system, a voiceprint from the voicemail; comparing, by the system, the voiceprint to voiceprints generated from previously received voicemails; identifying, by the system, based at least in part on the comparison and a portion of the voiceprints generated from the previously received voicemails, at least one matching voiceprint; selecting, by the system, based at least in part on the at least one matching voiceprint, a speech synthesis voice associated with the user; and determining, by the system, a modification to the speech synthesis voice associated with the user based at least in part on the association between the portion of each respective word from the group of words and the corresponding portion of the voicemail. 17. The method of claim 1 , wherein the voicemail associated with the user comprises an audio sample embedded in a video message associated with the user. | 0.938889 |
7,536,673 | 30 | 31 | 30. The method of claim 27 , further comprising determining whether a portion of the script should be sent for processing. | 30. The method of claim 27 , further comprising determining whether a portion of the script should be sent for processing. 31. The method of claim 30 , wherein determining whether a portion of a script should be sent for processing comprises determining whether a portion of the script is associated with a specific processing engine. | 0.511574 |
9,495,350 | 1 | 9 | 1. A method comprising: associating speakers with respective segments of an audio speech file to yield associated speaker segments; generating, via a processor using automatic speech recognition of audio in the audio speech file, expertise vectors for one or more of the speakers, the expertise vectors comprising scores based on: (i) number of times the speakers have spoken about a topic in the audio speech file by searching the associated speaker segments for a term associated with the topic, and (ii) at least one of word classes, usages, styles, or behaviors of the speakers; and ranking the speakers as experts based on the expertise vectors; presenting, by the processor, the ranking of the speakers as experts based on the expertise vectors; tagging the associated speaker segments having the term with keyword tags; and matching a respective segment from the associated speaker segments with a speaker, the respective segment having a keyword tag. | 1. A method comprising: associating speakers with respective segments of an audio speech file to yield associated speaker segments; generating, via a processor using automatic speech recognition of audio in the audio speech file, expertise vectors for one or more of the speakers, the expertise vectors comprising scores based on: (i) number of times the speakers have spoken about a topic in the audio speech file by searching the associated speaker segments for a term associated with the topic, and (ii) at least one of word classes, usages, styles, or behaviors of the speakers; and ranking the speakers as experts based on the expertise vectors; presenting, by the processor, the ranking of the speakers as experts based on the expertise vectors; tagging the associated speaker segments having the term with keyword tags; and matching a respective segment from the associated speaker segments with a speaker, the respective segment having a keyword tag. 9. The method of claim 1 , further comprising tagging a segment from the associated speaker segments with a keyword tag based on a probability that the segment from the associated speaker segments contains the term. | 0.781947 |
9,237,291 | 23 | 24 | 23. The computer readable medium of claim 22 , wherein, in a social volume visualization, selected contents of each linked social network profile of a social contact and/or inbound messages and/or outbound messages from or to a linked social media contact and/or current activity of the social media contact is presented in a displayed object on the television screen, the displayed object comprising at least one tile. | 23. The computer readable medium of claim 22 , wherein, in a social volume visualization, selected contents of each linked social network profile of a social contact and/or inbound messages and/or outbound messages from or to a linked social media contact and/or current activity of the social media contact is presented in a displayed object on the television screen, the displayed object comprising at least one tile. 24. The computer readable medium of claim 23 , wherein a size of the at least one tile is related to one or more of a relative degree of importance of the linked social contact to the user, a type of relationship of user to the linked social contact, a degree of influence of the linked social contact to the user, a geographic proximity of the linked social contact to the user, a degree to which the currently provided media content is of interest both to the user and linked social contact, an assigned ranking of the linked social contact by the user, a type of social network type linking the user with the linked social contact, a current activity of the linked social contact, a current online or offline status of the linked social contact, and a social network grouping type or category to which both the user and linked social contact belong. | 0.5 |
8,364,488 | 1 | 9 | 1. A computer implemented method comprising: providing by a computer, a user interface that displays a plurality of representations of characters, the characters each including the representation as a graphic image of an entity corresponding to the character and at least one associated voice model, the voice model characterized by a set of attributes; receiving a user selection of one of the representations from the plurality of representations to associate with one or more portions of a sequence of words in an electronic document that is rendered on a user display device; associating by the computer the selected character corresponding to the representation with the selected one or more portions of the sequence of words; and modifying by the computer the at least one voice model associated with the selected character, with modifying applying data received from the user through the user interface to change one or more attributes of the set of attributes of the voice model. | 1. A computer implemented method comprising: providing by a computer, a user interface that displays a plurality of representations of characters, the characters each including the representation as a graphic image of an entity corresponding to the character and at least one associated voice model, the voice model characterized by a set of attributes; receiving a user selection of one of the representations from the plurality of representations to associate with one or more portions of a sequence of words in an electronic document that is rendered on a user display device; associating by the computer the selected character corresponding to the representation with the selected one or more portions of the sequence of words; and modifying by the computer the at least one voice model associated with the selected character, with modifying applying data received from the user through the user interface to change one or more attributes of the set of attributes of the voice model. 9. The method of claim 1 , wherein modifying the voice model comprises modifying a pitch of the voice model as one of the attributes in the set of attributes associated with the voice model. | 0.627451 |
8,612,232 | 15 | 19 | 15. A computer-readable storage medium having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: partitioning, via a processor, a speech recognizer output into independent clauses; identifying, independent of domain, a dialog act for each of the independent clauses; identifying, dependent on domain, an object within each of the independent clauses; and recursively generating, for each independent clause in the independent clauses, a semantic representation using the dialog act and the object of each independent clause. | 15. A computer-readable storage medium having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: partitioning, via a processor, a speech recognizer output into independent clauses; identifying, independent of domain, a dialog act for each of the independent clauses; identifying, dependent on domain, an object within each of the independent clauses; and recursively generating, for each independent clause in the independent clauses, a semantic representation using the dialog act and the object of each independent clause. 19. The computer-readable storage medium of claim 15 , wherein identifying the object comprises using a domain specific classifier. | 0.817549 |
10,025,977 | 3 | 10 | 3. The method of identifying according to claim 1 , wherein said document is a game ticket or an identity document. | 3. The method of identifying according to claim 1 , wherein said document is a game ticket or an identity document. 10. A non-transitory computer-readable medium comprising code instructions for executing a method of identification as claimed in claim 3 , when said code instructions are executed by a processor. | 0.533333 |
7,580,836 | 8 | 9 | 8. A method comprising: (a) recognizing utterances of a speaker through converting the utterances into a recognized string, the utterances being received by a speaker input and converted to digital signals; (b) comparing the recognized string with a reference string to determine errors; (c) calculating estimated weights for sections of the utterances; (d) marking the errors in the utterances and providing corresponding estimated weights to form adaptation enrollment data; and (e) using the adaptation enrollment data to convert a speaker independent model to a speaker dependent model; wherein calculating the estimated weights comprises computing an average likelihood difference per frame and then computing a weight value by averaging the average likelihood difference over all error words. | 8. A method comprising: (a) recognizing utterances of a speaker through converting the utterances into a recognized string, the utterances being received by a speaker input and converted to digital signals; (b) comparing the recognized string with a reference string to determine errors; (c) calculating estimated weights for sections of the utterances; (d) marking the errors in the utterances and providing corresponding estimated weights to form adaptation enrollment data; and (e) using the adaptation enrollment data to convert a speaker independent model to a speaker dependent model; wherein calculating the estimated weights comprises computing an average likelihood difference per frame and then computing a weight value by averaging the average likelihood difference over all error words. 9. The method of claim 8 , wherein the utterances are converted into the recognized string through applying the speaker independent model. | 0.79403 |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.