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9,998,412 | 22 | 24 | 22. The computer-readable storage medium of claim 21 , wherein the program instructs the microprocessor to: enable, via the user interface, a third message configuration to be used when replying to an electronic message received from both a source internal to a particular organization and an electronic message received from a source external to the particular organization. | 22. The computer-readable storage medium of claim 21 , wherein the program instructs the microprocessor to: enable, via the user interface, a third message configuration to be used when replying to an electronic message received from both a source internal to a particular organization and an electronic message received from a source external to the particular organization. 24. The computer-readable storage medium of claim 22 , wherein a class of a user is indicated by associated information stored in an address book. | 0.956182 |
8,738,403 | 24 | 26 | 24. The apparatus of claim 16 , wherein the updating comprises generating natural language text corresponding to the first fact, and adding the generated text to a textual representation of the free-form narration. | 24. The apparatus of claim 16 , wherein the updating comprises generating natural language text corresponding to the first fact, and adding the generated text to a textual representation of the free-form narration. 26. The apparatus of claim 24 , wherein the updating further comprises adding the generated text to a location, in the textual representation of the free-form narration, specified by the user. | 0.932961 |
9,606,630 | 18 | 19 | 18. The system of claim 14 , wherein the gesture vocabulary includes a string of characters that represent a state of kinematic linkages of the body. | 18. The system of claim 14 , wherein the gesture vocabulary includes a string of characters that represent a state of kinematic linkages of the body. 19. The system of claim 18 , wherein the kinematic linkage is at least one first appendage of the body. | 0.927157 |
8,306,909 | 1 | 2 | 1. An apparatus for determining a collections treatment type, said apparatus comprising: a scoring analyzer operable to select a score band based on a credit score associated with a debtor, wherein said scoring analyzer is further operable to determine a collections score based on raw credit data and a first scoring expression of a plurality of different scoring expressions, wherein said first scoring expression is associated with said score band, wherein said first scoring expression utilizes a first variable, and wherein a second scoring expression associated with a second score band utilizes a second variable; and a treatment analyzer operable to determine said collections treatment type based on said collections score. | 1. An apparatus for determining a collections treatment type, said apparatus comprising: a scoring analyzer operable to select a score band based on a credit score associated with a debtor, wherein said scoring analyzer is further operable to determine a collections score based on raw credit data and a first scoring expression of a plurality of different scoring expressions, wherein said first scoring expression is associated with said score band, wherein said first scoring expression utilizes a first variable, and wherein a second scoring expression associated with a second score band utilizes a second variable; and a treatment analyzer operable to determine said collections treatment type based on said collections score. 2. The apparatus of claim 1 further comprising: a treatment generator operable to initiate a treatment action based on said collections treatment type, wherein said treatment action is associated with said debtor. | 0.705801 |
8,140,556 | 8 | 9 | 8. The method of claim 1 wherein generating the one or more queries in the second language comprises: parsing the first query to identify a set of terms in the first query; associating a tag with each term in the set of terms; generating one or more representations based upon the set of terms and tags associated with the terms in the set of terms; and generating the one or more queries in the second language based upon the one or more representations. | 8. The method of claim 1 wherein generating the one or more queries in the second language comprises: parsing the first query to identify a set of terms in the first query; associating a tag with each term in the set of terms; generating one or more representations based upon the set of terms and tags associated with the terms in the set of terms; and generating the one or more queries in the second language based upon the one or more representations. 9. The method of claim 8 wherein the one or more representations are in XML format. | 0.978475 |
9,812,205 | 11 | 12 | 11. The content addressable memory cell apparatus of claim 7 , wherein a search operation is performed by turning off the first and the second transistors and placing a search value on at least two of the plurality of the search lines. | 11. The content addressable memory cell apparatus of claim 7 , wherein a search operation is performed by turning off the first and the second transistors and placing a search value on at least two of the plurality of the search lines. 12. The content addressable memory cell apparatus of claim 11 , wherein a match between the search value and a stored value is determined by a high resistance between at least two of the plurality of matchlines. | 0.925177 |
8,504,537 | 8 | 10 | 8. A document registration system comprising: a manager agent including: a registration module to register documents, and a master signature database to maintain signatures of registered documents; a match agent including: at least one object capture module to intercept packets being transmitted over a network and reassemble the packets into an intercepted document, a signature generator to generate a set of signatures associated with the intercepted document, a search engine to compare the set of signatures associated with the intercepted document with signatures stored in a local signature database of the distributed match agent that are associated with registered documents, and a notification module to determine whether to send a notification to the manager agent of registration system based on the result of the comparison. | 8. A document registration system comprising: a manager agent including: a registration module to register documents, and a master signature database to maintain signatures of registered documents; a match agent including: at least one object capture module to intercept packets being transmitted over a network and reassemble the packets into an intercepted document, a signature generator to generate a set of signatures associated with the intercepted document, a search engine to compare the set of signatures associated with the intercepted document with signatures stored in a local signature database of the distributed match agent that are associated with registered documents, and a notification module to determine whether to send a notification to the manager agent of registration system based on the result of the comparison. 10. The document registration system of claim 8 , wherein the notification indicates content of a registered document in the intercepted document. | 0.650718 |
8,380,741 | 1 | 3 | 1. A text mining apparatus for performing text mining using, as targets, a plurality of text data pieces including a text data piece generated by computer processing, confidence being set for each of the text data pieces, the text mining apparatus comprising: a processor, an inherent portion extraction unit that, for each of the text data pieces, extracts an inherent portion of the text data piece relative to another of the text data pieces using the processor; an inherent confidence setting unit that, for each inherent portion of each of the text data pieces relative to another of the text data pieces, sets inherent confidence that indicates confidence of the inherent portion, using the confidence that has been set for each of the text data pieces; and a mining processing unit that performs text mining on each inherent portion of each of the text data pieces relative to another of the text data pieces, using the inherent confidence, wherein a numerical value less than or equal to one is set as the confidence for each of the text data pieces, and in a case of setting the inherent confidence for each inherent portion of one of the text data pieces relative to another of the text data pieces, the inherent confidence setting unit sets the inherent confidence by multiplying the confidence that has been set for the one text data piece by a value obtained by subtracting the confidence that has been set for the other text data piece from one. | 1. A text mining apparatus for performing text mining using, as targets, a plurality of text data pieces including a text data piece generated by computer processing, confidence being set for each of the text data pieces, the text mining apparatus comprising: a processor, an inherent portion extraction unit that, for each of the text data pieces, extracts an inherent portion of the text data piece relative to another of the text data pieces using the processor; an inherent confidence setting unit that, for each inherent portion of each of the text data pieces relative to another of the text data pieces, sets inherent confidence that indicates confidence of the inherent portion, using the confidence that has been set for each of the text data pieces; and a mining processing unit that performs text mining on each inherent portion of each of the text data pieces relative to another of the text data pieces, using the inherent confidence, wherein a numerical value less than or equal to one is set as the confidence for each of the text data pieces, and in a case of setting the inherent confidence for each inherent portion of one of the text data pieces relative to another of the text data pieces, the inherent confidence setting unit sets the inherent confidence by multiplying the confidence that has been set for the one text data piece by a value obtained by subtracting the confidence that has been set for the other text data piece from one. 3. The text mining apparatus according to claim 1 , wherein, for each word constituting each of the text data pieces, the inherent portion extraction unit calculates the degree to which the word corresponds to an inherent portion of the text data piece relative to another of the text data pieces, using the confidence that has been set for each of the text data pieces, and extracts an inherent portion of the text data piece relative to the other text data piece based on the calculated degree. | 0.514677 |
8,942,986 | 1 | 8 | 1. A method for operating an intelligent automated assistant, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: storing a plurality of predefined domains each representing a respective area of service offered by the intelligent automated assistant, wherein each of the predefined domains comprises a respective plurality of concepts and one or more relations relating the respective plurality of concepts, wherein each predefined domain is associated with at least one task flow specifying steps for performing a respective task in the predefined domain, and wherein each of the predefined domains is associated with a respective plurality of words relevant to the predefined domain; obtaining a text string derived from a user request, the text string including at least one or more words derived from a speech input received from a user; from the plurality of predefined domains, identifying a relevant domain for the user request based at least on respective degrees of match between the text string derived from the user request and the respective plurality of words associated with each predefined domain; and executing a task in accordance with steps specified in a task flow associated with the relevant domain, and in accordance with one or more task parameters derived from the user request. | 1. A method for operating an intelligent automated assistant, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: storing a plurality of predefined domains each representing a respective area of service offered by the intelligent automated assistant, wherein each of the predefined domains comprises a respective plurality of concepts and one or more relations relating the respective plurality of concepts, wherein each predefined domain is associated with at least one task flow specifying steps for performing a respective task in the predefined domain, and wherein each of the predefined domains is associated with a respective plurality of words relevant to the predefined domain; obtaining a text string derived from a user request, the text string including at least one or more words derived from a speech input received from a user; from the plurality of predefined domains, identifying a relevant domain for the user request based at least on respective degrees of match between the text string derived from the user request and the respective plurality of words associated with each predefined domain; and executing a task in accordance with steps specified in a task flow associated with the relevant domain, and in accordance with one or more task parameters derived from the user request. 8. The method of claim 1 , wherein the user request further includes context information associated with the speech input received from the user, and one or more of the task parameters are derived based on the context information. | 0.847682 |
7,672,852 | 1 | 7 | 1. A computer-implemented method for executing, by a processor of a computing device, a prompt statement, the prompt statement having a NAME variable associated therewith, the method comprising: determining that the prompt statement specifies a resource string, wherein the resource string includes a personal information manager variable, and wherein the personal information manager variable is a KEY variable; identifying a grammar variable that corresponds to the KEY variable; concatenating the grammar variable to the NAME variable; identifying, by the processor, a resource string for the prompt statement that corresponds to the NAME variable; retrieving a media file that corresponds to the identified resource string; and rendering the retrieved media file that corresponds to the resource string in response to the prompt statement and rendering, in a speech-to-text format, the personal information manager variable, said rendering occurring in an order specified by the resource string. | 1. A computer-implemented method for executing, by a processor of a computing device, a prompt statement, the prompt statement having a NAME variable associated therewith, the method comprising: determining that the prompt statement specifies a resource string, wherein the resource string includes a personal information manager variable, and wherein the personal information manager variable is a KEY variable; identifying a grammar variable that corresponds to the KEY variable; concatenating the grammar variable to the NAME variable; identifying, by the processor, a resource string for the prompt statement that corresponds to the NAME variable; retrieving a media file that corresponds to the identified resource string; and rendering the retrieved media file that corresponds to the resource string in response to the prompt statement and rendering, in a speech-to-text format, the personal information manager variable, said rendering occurring in an order specified by the resource string. 7. The computer-implemented method of claim 1 , wherein the resource string is grammatically correct for the language of the text. | 0.700461 |
8,645,389 | 1 | 3 | 1. A method for adaptive information recommendation, the method comprising: storing user-specific information in memory, the user-specific information concerning user activity with a plurality of documents; and executing instructions stored in memory, wherein execution of the instructions by a processor: clusters an interest set of documents associated with the user activity into one or more clusters, wherein clustering an interest set of documents comprises: assembling the interest set of documents, pre-processing words of the interest set of documents, and grouping documents from the interest set of documents into the clusters utilizing a clustering algorithm that maximizes a cluster score of the clusters, wherein the cluster score is an average similarity score between the documents in the cluster, identifies a keyword for a cluster of the one or more clusters, the keyword identified based on natural language input by a user and representing the theme of the documents in the cluster, identifies a set of eligible documents within the cluster of the one or more clusters, each identified document containing either the keyword or the natural language input by the user representing the theme of the documents, filters the set of eligible documents in the cluster to meet an application criterion, the application criterion based on the user-specific information stored in memory and a user-defined limit on document age, wherein filtering documents does not require user interaction, and adaptively constructs a recommended set of documents for the cluster from the filtered set of eligible documents based on relevance to the keyword or the natural language input wherein constructing the recommended set of document includes: calculating a relevance score of each document in the filtered set of eligible documents, wherein the relevance score is based on a number of times the keyword or the natural language input by the user representing the theme appears in each document in the filtered set of eligible documents, selecting documents of the filtered set of eligible documents with high relevance scores, and applying a selection criterion measuring popularity of the document in the filtered set of eligible documents. | 1. A method for adaptive information recommendation, the method comprising: storing user-specific information in memory, the user-specific information concerning user activity with a plurality of documents; and executing instructions stored in memory, wherein execution of the instructions by a processor: clusters an interest set of documents associated with the user activity into one or more clusters, wherein clustering an interest set of documents comprises: assembling the interest set of documents, pre-processing words of the interest set of documents, and grouping documents from the interest set of documents into the clusters utilizing a clustering algorithm that maximizes a cluster score of the clusters, wherein the cluster score is an average similarity score between the documents in the cluster, identifies a keyword for a cluster of the one or more clusters, the keyword identified based on natural language input by a user and representing the theme of the documents in the cluster, identifies a set of eligible documents within the cluster of the one or more clusters, each identified document containing either the keyword or the natural language input by the user representing the theme of the documents, filters the set of eligible documents in the cluster to meet an application criterion, the application criterion based on the user-specific information stored in memory and a user-defined limit on document age, wherein filtering documents does not require user interaction, and adaptively constructs a recommended set of documents for the cluster from the filtered set of eligible documents based on relevance to the keyword or the natural language input wherein constructing the recommended set of document includes: calculating a relevance score of each document in the filtered set of eligible documents, wherein the relevance score is based on a number of times the keyword or the natural language input by the user representing the theme appears in each document in the filtered set of eligible documents, selecting documents of the filtered set of eligible documents with high relevance scores, and applying a selection criterion measuring popularity of the document in the filtered set of eligible documents. 3. The method of claim 1 , wherein identifying a keyword for the one or more clusters includes calculating a plurality of keyword scores corresponding to the one or more clusters and selecting the keyword that maximizes the keyword score of the cluster, wherein calculating a keyword score is based on a frequency of a keyword in the interest set and a frequency of the keyword in the cluster. | 0.596509 |
9,824,188 | 16 | 17 | 16. The method as recited in claim 13 , wherein the response includes information about a comparison between a metric of the user and a metric for another user. | 16. The method as recited in claim 13 , wherein the response includes information about a comparison between a metric of the user and a metric for another user. 17. The method as recited in claim 16 , wherein the metric of the user is obtained from at least one of an electronic medical record of the user, input provided by the user, a result of a test administered to the user, or data from the medical device. | 0.942458 |
7,788,253 | 17 | 18 | 17. A system for building a search index, comprising: hardware logic capable of performing operations, the operations comprising: while building the search index and using the search index to respond to one or more search requests and performing synchronous anchor text processing: maintaining an anchor information store, wherein each entry of the anchor information store identifies a referring document, a target document, and anchor text associated with a link from the referring document to the target document; maintaining a rebuild agenda, wherein each entry of the rebuild agenda identifies a target document that has an entry in the search index and whose anchor text is to be updated in the search index with asynchronous processing because there is at least one new or updated link pointing to the target document; receiving a document for processing; for each outgoing link in the document that points to a target document, adding an entry to the anchor information store that identifies the received document, the target document, and anchor text; and adding an entry to the rebuild agenda for the target document; and for each link pointing from a referring document to the document, locating one or more entries in the anchor information store for which the received document to be processed is identified as the target document; retrieving anchor text from each of the identified entries; and storing the retrieved anchor text in an entry of the search index for the received document; and performing asynchronous anchor text processing to incrementally update current entries in the search index for each document identified in each entry in the rebuild agenda in parallel with the building of the search index and in parallel with using the search index to respond to one or more search requests by: selecting a first target document in the rebuild agenda; using the anchor information store to find anchor text for the first target document by identifying one or more entries in the anchor information store for which the first target document is identified as the target document in the anchor information store; retrieving anchor text from each of the identified entries; and updating the anchor text in the entry of the search index for the first target document. | 17. A system for building a search index, comprising: hardware logic capable of performing operations, the operations comprising: while building the search index and using the search index to respond to one or more search requests and performing synchronous anchor text processing: maintaining an anchor information store, wherein each entry of the anchor information store identifies a referring document, a target document, and anchor text associated with a link from the referring document to the target document; maintaining a rebuild agenda, wherein each entry of the rebuild agenda identifies a target document that has an entry in the search index and whose anchor text is to be updated in the search index with asynchronous processing because there is at least one new or updated link pointing to the target document; receiving a document for processing; for each outgoing link in the document that points to a target document, adding an entry to the anchor information store that identifies the received document, the target document, and anchor text; and adding an entry to the rebuild agenda for the target document; and for each link pointing from a referring document to the document, locating one or more entries in the anchor information store for which the received document to be processed is identified as the target document; retrieving anchor text from each of the identified entries; and storing the retrieved anchor text in an entry of the search index for the received document; and performing asynchronous anchor text processing to incrementally update current entries in the search index for each document identified in each entry in the rebuild agenda in parallel with the building of the search index and in parallel with using the search index to respond to one or more search requests by: selecting a first target document in the rebuild agenda; using the anchor information store to find anchor text for the first target document by identifying one or more entries in the anchor information store for which the first target document is identified as the target document in the anchor information store; retrieving anchor text from each of the identified entries; and updating the anchor text in the entry of the search index for the first target document. 18. The system of claim 17 , wherein the received document in the entry added to the anchor information store for the outgoing link is a referring document. | 0.892414 |
9,754,187 | 1 | 6 | 1. A method comprising: acquiring an electronic image of a document with a fixed structure, wherein the fixed structure comprises field names and field values corresponding to the field names, and wherein the field names and the field values are located at set locations in the document; recognizing key words in the electronic image of the document, wherein the key words comprise the field names and the field values; matching one or more templates from a plurality of templates with the document, wherein the one or more templates comprise reference objects that specify areas in the electronic image of the document where permitted field values corresponding to field names are to be extracted, and wherein matching the one or more templates comprises matching the field names and the permitted field values from the one or more templates with the identified field names and the field values from the recognized key words; selecting, by a processor device, a template from the one or more templates based on a quality of a match between the field names and the permitted field values from the template with the identified field names and the field values from the recognized key words; and extracting the field values from the electronic image of the document using the selected template. | 1. A method comprising: acquiring an electronic image of a document with a fixed structure, wherein the fixed structure comprises field names and field values corresponding to the field names, and wherein the field names and the field values are located at set locations in the document; recognizing key words in the electronic image of the document, wherein the key words comprise the field names and the field values; matching one or more templates from a plurality of templates with the document, wherein the one or more templates comprise reference objects that specify areas in the electronic image of the document where permitted field values corresponding to field names are to be extracted, and wherein matching the one or more templates comprises matching the field names and the permitted field values from the one or more templates with the identified field names and the field values from the recognized key words; selecting, by a processor device, a template from the one or more templates based on a quality of a match between the field names and the permitted field values from the template with the identified field names and the field values from the recognized key words; and extracting the field values from the electronic image of the document using the selected template. 6. The method of claim 1 , further comprising applying at least one filter to the electronic image of the document. | 0.911674 |
9,026,904 | 1 | 2 | 1. A method of managing cascading style sheet rules, comprising: identifying, by a web application on a server, a markup page of content items; designating, by the web application, a plurality of super-themes by: defining a first markup element that associates a first container that contains a first content item of the markup page and a first cascading style sheet rule, with a first cascading style sheet class; designating the first markup element by a first super-theme; defining a second markup element that associates a second container that contains a second content item of the markup page and a second cascading style sheet rule, with a second cascading style sheet class different from the first cascading style sheet class; and designating the second markup element by a second super-theme; loading a common cascading style sheet for the markup page; automatically modifying, by a processor, the common cascading style sheet to use the first super-theme as a parent selector for selecting the first cascading style sheet rule from the first container, which is applied to the first content item, wherein: the first super-theme causes the first cascading style sheet rule to apply only to the first content item, such that the first cascading style sheet rule does not override other cascading style sheet rules; and automatically modifying, by the processor, the common cascading style sheet to use the second super-theme as a parent selector for selecting the second cascading style sheet rule from the second set of cascading style sheet rules, which is applied to the second content item, wherein: the second super-theme causes the second cascading style sheet rule to apply only to the second content item, such that the second cascading style sheet rule does not override other cascading style sheet rules. | 1. A method of managing cascading style sheet rules, comprising: identifying, by a web application on a server, a markup page of content items; designating, by the web application, a plurality of super-themes by: defining a first markup element that associates a first container that contains a first content item of the markup page and a first cascading style sheet rule, with a first cascading style sheet class; designating the first markup element by a first super-theme; defining a second markup element that associates a second container that contains a second content item of the markup page and a second cascading style sheet rule, with a second cascading style sheet class different from the first cascading style sheet class; and designating the second markup element by a second super-theme; loading a common cascading style sheet for the markup page; automatically modifying, by a processor, the common cascading style sheet to use the first super-theme as a parent selector for selecting the first cascading style sheet rule from the first container, which is applied to the first content item, wherein: the first super-theme causes the first cascading style sheet rule to apply only to the first content item, such that the first cascading style sheet rule does not override other cascading style sheet rules; and automatically modifying, by the processor, the common cascading style sheet to use the second super-theme as a parent selector for selecting the second cascading style sheet rule from the second set of cascading style sheet rules, which is applied to the second content item, wherein: the second super-theme causes the second cascading style sheet rule to apply only to the second content item, such that the second cascading style sheet rule does not override other cascading style sheet rules. 2. The method of claim 1 , wherein: defining a first markup, comprises: rendering inline, a content item by enclosing the content item in the first markup element that is given a cascading style sheet class specific to the content item, designating the first super theme. | 0.765165 |
8,290,778 | 1 | 11 | 1. Computerized apparatus comprising: a wireless interface; data processing apparatus; a touch-screen input and display device; a speech recognition apparatus in data communication with the data processing apparatus; and a storage apparatus in data communication with the data processing apparatus, said storage apparatus comprising at least one computer program, said at least one program being configured to: receive a digitized speech input via the speech recognition apparatus, the input relating to an organization or entity which a user wishes to locate; based at least in part on the input, cause identification of a location associated with the organization or entity; and provide a graphical or visual representation of the location on the touch screen input and display device in order to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity. | 1. Computerized apparatus comprising: a wireless interface; data processing apparatus; a touch-screen input and display device; a speech recognition apparatus in data communication with the data processing apparatus; and a storage apparatus in data communication with the data processing apparatus, said storage apparatus comprising at least one computer program, said at least one program being configured to: receive a digitized speech input via the speech recognition apparatus, the input relating to an organization or entity which a user wishes to locate; based at least in part on the input, cause identification of a location associated with the organization or entity; and provide a graphical or visual representation of the location on the touch screen input and display device in order to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity. 11. The apparatus of claim 1 , wherein the at least one computer program is further configured to receive and utilize inputs in an iterative or hierarchical fashion to progress through a menu structure comprising multiple possible matching destinations or locations or entities. | 0.813172 |
10,158,733 | 8 | 12 | 8. A computer program product for tracking usage of applications on a mobile device, the computer program product comprising a computer-readable storage medium containing computer program code for: storing, in the rules dictionary, a rule for each application of a plurality of applications that are executable on a mobile device, where each rule is used identifying network traffic associated with the associated application, and wherein each rule comprises an identifier for the application and a regular expression that is configured to identify network traffic associated with the application; installing a new mobile application on the mobile device; executing the new application on the mobile device to cause the new application to create network traffic; inspecting the network traffic caused by the new application; creating a regular expression that matches the network traffic created by the new application; and while the shutter button is displayed at the second location, detecting a second touch input to the shutter button; and storing in the rules dictionary a new rule that comprises the regular expression created for the new application and an identifier for the new application. | 8. A computer program product for tracking usage of applications on a mobile device, the computer program product comprising a computer-readable storage medium containing computer program code for: storing, in the rules dictionary, a rule for each application of a plurality of applications that are executable on a mobile device, where each rule is used identifying network traffic associated with the associated application, and wherein each rule comprises an identifier for the application and a regular expression that is configured to identify network traffic associated with the application; installing a new mobile application on the mobile device; executing the new application on the mobile device to cause the new application to create network traffic; inspecting the network traffic caused by the new application; creating a regular expression that matches the network traffic created by the new application; and while the shutter button is displayed at the second location, detecting a second touch input to the shutter button; and storing in the rules dictionary a new rule that comprises the regular expression created for the new application and an identifier for the new application. 12. The computer program product of claim 8 , wherein the regular expression is a sequence of characters that define a search pattern associated with the traffic created by an executing mobile application. | 0.791667 |
9,286,278 | 17 | 18 | 17. A system for editing text, the system comprising: a processor; and a display screen, the system configured to perform a method comprising: in response to an instruction to apply editing to at least one sentence within a document that is displayed on a display screen, changing, by the processor, a first word or phrase in the at least one sentence for a second word or phrase while maintaining semantic content of the first word or phrase and such that the at least one sentence falls within a predetermined range, wherein the changing the first word or phrase comprises one of: in response to the second word or phrase having more characters or words than the first word or phrase, changing a third word or phrase within the at least one sentence including the second word or phrase for a fourth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and in response the second word or phrase having fewer characters or words than the first word or phrase, changing a fifth word or phrase within the at least one sentence including the second word or phrase for a sixth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and displaying, by the processor, the at least one sentence including the second word or phrase, and one of the fourth word or phrase and the sixth word or phrase, on the display screen. | 17. A system for editing text, the system comprising: a processor; and a display screen, the system configured to perform a method comprising: in response to an instruction to apply editing to at least one sentence within a document that is displayed on a display screen, changing, by the processor, a first word or phrase in the at least one sentence for a second word or phrase while maintaining semantic content of the first word or phrase and such that the at least one sentence falls within a predetermined range, wherein the changing the first word or phrase comprises one of: in response to the second word or phrase having more characters or words than the first word or phrase, changing a third word or phrase within the at least one sentence including the second word or phrase for a fourth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and in response the second word or phrase having fewer characters or words than the first word or phrase, changing a fifth word or phrase within the at least one sentence including the second word or phrase for a sixth word or phrase, such that the at least one sentence including the second word or phrase falls within the predetermined range; and displaying, by the processor, the at least one sentence including the second word or phrase, and one of the fourth word or phrase and the sixth word or phrase, on the display screen. 18. The system according to claim 17 , wherein displaying the at least one sentence including the second word or phrase on the display screen comprises displaying at least one of the second word or phrase, the fourth word or phrase, and the sixth word or phrase to a user; the method further comprising: in response to at least one of the second word or phrase, the fourth word or phrase and the sixth word or phrase being selected by the user, displaying on the display screen a conversion list indicating at least one conversion candidate that maintains the semantic content of the selected word or phrase; and in response to a conversion candidate on the conversion list being selected by the user, replacing the selected word or phrase with the conversion candidate selected by the user. | 0.710044 |
9,881,616 | 1 | 4 | 1. A method for improving speech recognition by a speech recognition system, comprising: receiving, from each of a plurality of microphones of a device, a microphone output signal, at least one of the microphone signals comprising a voice sample; authenticating, by a voice biometrics engine of the device, a speaker based on the voice sample comprising: providing to the voice biometrics engine, the received microphone output signals, and determining, by the voice biometrics engine, a voice model matching the voice sample, the voice model corresponding to an authenticated speaker, the voice model being one of a plurality of stored voice models; providing, by the voice biometrics engine to the directional sound capturing system, an indication of a microphone associated with the matching voice sample; providing, to a directional sound capturing system of the device, the received microphone output signals; identifying an area from which the microphone output signal comprising the matching voice sample is received; filtering, by the directional sound capturing system, subsequent received subsequent microphone output signals based on the identified area, the subsequent microphone output signals comprising subsequent voice samples; providing at least one filtered subsequent microphone output signals to the speech recognition system for processing; and at predefined intervals, performing the authenticating, by the voice biometrics engine, the authenticated speaker based on at least one filtered subsequent microphone output signal. | 1. A method for improving speech recognition by a speech recognition system, comprising: receiving, from each of a plurality of microphones of a device, a microphone output signal, at least one of the microphone signals comprising a voice sample; authenticating, by a voice biometrics engine of the device, a speaker based on the voice sample comprising: providing to the voice biometrics engine, the received microphone output signals, and determining, by the voice biometrics engine, a voice model matching the voice sample, the voice model corresponding to an authenticated speaker, the voice model being one of a plurality of stored voice models; providing, by the voice biometrics engine to the directional sound capturing system, an indication of a microphone associated with the matching voice sample; providing, to a directional sound capturing system of the device, the received microphone output signals; identifying an area from which the microphone output signal comprising the matching voice sample is received; filtering, by the directional sound capturing system, subsequent received subsequent microphone output signals based on the identified area, the subsequent microphone output signals comprising subsequent voice samples; providing at least one filtered subsequent microphone output signals to the speech recognition system for processing; and at predefined intervals, performing the authenticating, by the voice biometrics engine, the authenticated speaker based on at least one filtered subsequent microphone output signal. 4. The method according to claim 1 , wherein said method comprises separating ambient noise from speech, based on the voice model, to produce the at least one filtered subsequent microphone output signals. | 0.839844 |
7,945,575 | 1 | 4 | 1. A computer-implemented method of transforming queries based upon an entity/relationship schema into multi-dimensional expression queries, the method comprising: matching, by operation of one or more computer processors, an object referenced in a report specification based on an entity/relationship schema to a corresponding object in the entity/relationship schema, the corresponding object adorned with associated multi-dimensional metadata; adding the associated multi-dimensional metadata to the object referenced in the report specification; translating the report specification into a multi-dimensional expression query; directly retrieving all data required to populate a report output of the report specification; and converting, by operation of the one or more computer processors, results of the multi-dimensional expression query into a result set matching semantics of the report specification, wherein converting results of the multi-dimensional expression query comprises: converting the results of the multi-dimensional expression query into rows of data; and producing headers for inclusion into the rows of data. | 1. A computer-implemented method of transforming queries based upon an entity/relationship schema into multi-dimensional expression queries, the method comprising: matching, by operation of one or more computer processors, an object referenced in a report specification based on an entity/relationship schema to a corresponding object in the entity/relationship schema, the corresponding object adorned with associated multi-dimensional metadata; adding the associated multi-dimensional metadata to the object referenced in the report specification; translating the report specification into a multi-dimensional expression query; directly retrieving all data required to populate a report output of the report specification; and converting, by operation of the one or more computer processors, results of the multi-dimensional expression query into a result set matching semantics of the report specification, wherein converting results of the multi-dimensional expression query comprises: converting the results of the multi-dimensional expression query into rows of data; and producing headers for inclusion into the rows of data. 4. The computer-implemented method of claim 1 , wherein data in the report specification is stored in an OLAP format. | 0.789568 |
7,519,957 | 2 | 12 | 2. The method according to claim 1 and also comprising generating at least one disjunctive partition for each variable of said model. | 2. The method according to claim 1 and also comprising generating at least one disjunctive partition for each variable of said model. 12. The method according to claim 2 and also comprising computing reachability from said disjunctive partitions. | 0.846575 |
7,996,768 | 6 | 7 | 6. An apparatus to filter text for an operation, the apparatus comprising: a rule selector to pick at least one text attribute of both a first section and a third section of a document, wherein further the first and third sections comprise text of a first person, wherein further the first and third sections are separated by a second section of text added by a second person; a text comparator communicably coupled with the rule selector to compare text of the three sections to the at least one text attribute and filter the first and third sections from the second section via the at least one text attribute, wherein the at least one text attribute comprises one of a text font, a text color, a text style, a text size, and a text author; and an operation module communicably coupled with the text comparator to perform the operation on the text of the first and third sections, wherein the operation comprises a spelling checker operation for checking spelling of text of the first and third sections of text, wherein performance of the operation is invoked prior to filtering the first and third sections, the filtering of the first and third sections is performed in response to invoking performance of the operation, and wherein the spelling check operation is performed in response to the filtering of the first and third sections. | 6. An apparatus to filter text for an operation, the apparatus comprising: a rule selector to pick at least one text attribute of both a first section and a third section of a document, wherein further the first and third sections comprise text of a first person, wherein further the first and third sections are separated by a second section of text added by a second person; a text comparator communicably coupled with the rule selector to compare text of the three sections to the at least one text attribute and filter the first and third sections from the second section via the at least one text attribute, wherein the at least one text attribute comprises one of a text font, a text color, a text style, a text size, and a text author; and an operation module communicably coupled with the text comparator to perform the operation on the text of the first and third sections, wherein the operation comprises a spelling checker operation for checking spelling of text of the first and third sections of text, wherein performance of the operation is invoked prior to filtering the first and third sections, the filtering of the first and third sections is performed in response to invoking performance of the operation, and wherein the spelling check operation is performed in response to the filtering of the first and third sections. 7. The apparatus of claim 6 , wherein the at least one text attribute is used to filter text of an e-mail reply document. | 0.683246 |
9,183,256 | 6 | 7 | 6. A method as in claim 1 additionally comprising: generating an auxiliary table for storing histogram data. | 6. A method as in claim 1 additionally comprising: generating an auxiliary table for storing histogram data. 7. A method as in claim 6 wherein the auxiliary table is invisible to the SQL query that contains the join operation, but is otherwise visible to subsequent SQL queries. | 0.926072 |
7,644,014 | 10 | 14 | 10. A method, comprising: one or more computers performing: receiving one or more input documents in a markup language, wherein the input documents comprise a purchasing request, wherein each input document comprises one or more tag names specifying purchasing parameters for the purchasing request; parsing each of the one or more input document to identify each of the one or more tag names; generating one or more data objects each corresponding to a respective tag name; identifying one or more purchasing parameters related to one or more of the identified tag names; and generating one or more output documents in the markup language specifying a purchasing order to a supplier corresponding to the purchasing request specified in the one or more input documents, wherein the one or more output documents comprise: one or more tag names corresponding to the one or more identified purchasing parameters, and one or more data attributes each corresponding to one of the one or more tag names corresponding to the one or more identified purchasing parameters. | 10. A method, comprising: one or more computers performing: receiving one or more input documents in a markup language, wherein the input documents comprise a purchasing request, wherein each input document comprises one or more tag names specifying purchasing parameters for the purchasing request; parsing each of the one or more input document to identify each of the one or more tag names; generating one or more data objects each corresponding to a respective tag name; identifying one or more purchasing parameters related to one or more of the identified tag names; and generating one or more output documents in the markup language specifying a purchasing order to a supplier corresponding to the purchasing request specified in the one or more input documents, wherein the one or more output documents comprise: one or more tag names corresponding to the one or more identified purchasing parameters, and one or more data attributes each corresponding to one of the one or more tag names corresponding to the one or more identified purchasing parameters. 14. The method of claim 10 , wherein the markup language is eXtensible Markup Language (XML). | 0.926424 |
8,004,539 | 1 | 7 | 1. A method, comprising: receiving, by a graphical editing tool of a computer, a command associated with a graphical editing operation directed to performing a transformation to a graphical object, wherein the transformation is associated with changing a value of a first parameter of the graphical object; displaying, by the graphical editing tool, a transformation object associated with the transformation, wherein the transformation object comprises a second parameter comprising a value associated with the transformation, and wherein the value of the first parameter of the graphical object is related to the value of the second parameter; receiving, by the graphical editing tool, an indication to convert the transformation object into a new parameter of the graphical object; converting, by the graphical editing tool, the transformation object into the new parameter of the graphical object; retaining, by the graphical editing tool, the converted transformation object during operations on other objects; and determining a function that defines the value of the first parameter based upon the value of the second parameter; wherein the new parameter comprises a derived parameter formed from expressions and/or functions that relate the derived parameter to one or more other parameters of the graphical object. | 1. A method, comprising: receiving, by a graphical editing tool of a computer, a command associated with a graphical editing operation directed to performing a transformation to a graphical object, wherein the transformation is associated with changing a value of a first parameter of the graphical object; displaying, by the graphical editing tool, a transformation object associated with the transformation, wherein the transformation object comprises a second parameter comprising a value associated with the transformation, and wherein the value of the first parameter of the graphical object is related to the value of the second parameter; receiving, by the graphical editing tool, an indication to convert the transformation object into a new parameter of the graphical object; converting, by the graphical editing tool, the transformation object into the new parameter of the graphical object; retaining, by the graphical editing tool, the converted transformation object during operations on other objects; and determining a function that defines the value of the first parameter based upon the value of the second parameter; wherein the new parameter comprises a derived parameter formed from expressions and/or functions that relate the derived parameter to one or more other parameters of the graphical object. 7. The method of claim 1 , further comprising: determining the value of the second parameter. | 0.958995 |
9,378,203 | 17 | 22 | 17. At least one non-transitory computer readable storage medium storing processor-executable instructions that when executed by at least one processor, cause the at least one processor to perform a method for providing information selected from a large set of digital content to at least one user, the method comprising: receiving user context information associated with the at least one user; identifying or generating a first concept in a semantic network, the first concept representing at least a portion of the user context information, wherein, after performance of the identifying or generating, the semantic network comprises a first node representing the first concept; synthesizing a second concept, semantically relevant to the first concept, and augmenting the semantic network with a second node representing the second concept, the second node being different from the first node, the synthesizing comprising: identifying in the semantic network a third concept that, together with the first concept or a parent or sibling concept of the first concept, co-defines a fourth concept in the semantic network, and combining the first concept and the third concept to synthesize the second concept; and providing information to the at least one user, wherein the information is selected by using the first concept and the synthesized second concept semantically relevant to the first concept, wherein the first and second concepts in the semantic network are represented by at least one data structure storing data associated with the first and second nodes. | 17. At least one non-transitory computer readable storage medium storing processor-executable instructions that when executed by at least one processor, cause the at least one processor to perform a method for providing information selected from a large set of digital content to at least one user, the method comprising: receiving user context information associated with the at least one user; identifying or generating a first concept in a semantic network, the first concept representing at least a portion of the user context information, wherein, after performance of the identifying or generating, the semantic network comprises a first node representing the first concept; synthesizing a second concept, semantically relevant to the first concept, and augmenting the semantic network with a second node representing the second concept, the second node being different from the first node, the synthesizing comprising: identifying in the semantic network a third concept that, together with the first concept or a parent or sibling concept of the first concept, co-defines a fourth concept in the semantic network, and combining the first concept and the third concept to synthesize the second concept; and providing information to the at least one user, wherein the information is selected by using the first concept and the synthesized second concept semantically relevant to the first concept, wherein the first and second concepts in the semantic network are represented by at least one data structure storing data associated with the first and second nodes. 22. The at least one non-transitory computer readable storage medium of claim 17 , wherein the semantic network is user-specific. | 0.887238 |
9,729,381 | 3 | 30 | 3. A non-transitory computer-readable medium having stored thereon processor-executable instructions, which instructions, when executed by the processor, cause the processor to perform steps comprising: receiving geographical location information for an entity; receiving a proprietary name for the entity; geocoding the geographical location information into a hierarchical address by first transforming the geographical location information into latitude/longitude coordinates, next transforming the latitude/longitude coordinates to reference grid coordinates, wherein a reference grid for the geographical location is selected, at least in part, according to the entity's proximity to a regional centroid of a candidate reference grid or a governmental jurisdiction, and determining the hierarchical address based on the location of the latitude/longitude coordinates of the geographical location of the entity within the reference grid. | 3. A non-transitory computer-readable medium having stored thereon processor-executable instructions, which instructions, when executed by the processor, cause the processor to perform steps comprising: receiving geographical location information for an entity; receiving a proprietary name for the entity; geocoding the geographical location information into a hierarchical address by first transforming the geographical location information into latitude/longitude coordinates, next transforming the latitude/longitude coordinates to reference grid coordinates, wherein a reference grid for the geographical location is selected, at least in part, according to the entity's proximity to a regional centroid of a candidate reference grid or a governmental jurisdiction, and determining the hierarchical address based on the location of the latitude/longitude coordinates of the geographical location of the entity within the reference grid. 30. The non-transitory computer-readable medium of claim 3 , wherein the proprietary name and the hierarchical address serve as alternate keys for accessing a record in a Unified Geographic Database (UGD) and dynamic location-related data for the entity is stored in the record. | 0.636126 |
8,412,747 | 14 | 15 | 14. A system comprising: one or more processors to: obtain, from one or more queries, a plurality of words associated with a particular web page; determine, for each of one or more links between one or more words of the plurality of words and a concept, a probability that text, generated based on the concept, will include a respective one of the one or more words; determine, based on the probability for each of the one or more links, that the concept is related to the particular web page; store as particular information: information identifying the probability for each of the one or more links, and information indicating that the concept is related to the particular web page; and predict a probability of the concept being related to one or more other web pages, based on the particular information. | 14. A system comprising: one or more processors to: obtain, from one or more queries, a plurality of words associated with a particular web page; determine, for each of one or more links between one or more words of the plurality of words and a concept, a probability that text, generated based on the concept, will include a respective one of the one or more words; determine, based on the probability for each of the one or more links, that the concept is related to the particular web page; store as particular information: information identifying the probability for each of the one or more links, and information indicating that the concept is related to the particular web page; and predict a probability of the concept being related to one or more other web pages, based on the particular information. 15. The system of claim 14 , where the one or more processors are further to: use the particular information to predict a concept associated with a document that is different than a web page. | 0.911819 |
8,135,800 | 23 | 24 | 23. The computer-implemented method as set forth in claim 13 , further comprising: for each selected user, normalizing a contribution of points of the selected user to the target user's profile. | 23. The computer-implemented method as set forth in claim 13 , further comprising: for each selected user, normalizing a contribution of points of the selected user to the target user's profile. 24. The computer-implemented method as set forth in claim 23 , wherein normalizing includes accessing data stored in a points allocation profile. | 0.965882 |
10,068,129 | 9 | 11 | 9. A non-transitory computer readable storage medium comprising instructions that, when executed by at least one processor, cause a computer system to: determine a probability that a first unknown person instance in an image is each of a plurality of known person instances from images in an image gallery; identify a plurality of context cues between one or more of the first unknown person instance and one or more known person instances of the plurality of known person instances or between known person instances of the plurality of known person instances; determine a context weight for each combination of the first unknown person instance and each known person instance from the plurality of known person instances using a conditional random field algorithm based on the identified plurality of context cues; calculate a contextual probability based on the determined probabilities and the determined context weights; and identify the first unknown person instance as a known person instance from the plurality of known person instances with a highest contextual probability. | 9. A non-transitory computer readable storage medium comprising instructions that, when executed by at least one processor, cause a computer system to: determine a probability that a first unknown person instance in an image is each of a plurality of known person instances from images in an image gallery; identify a plurality of context cues between one or more of the first unknown person instance and one or more known person instances of the plurality of known person instances or between known person instances of the plurality of known person instances; determine a context weight for each combination of the first unknown person instance and each known person instance from the plurality of known person instances using a conditional random field algorithm based on the identified plurality of context cues; calculate a contextual probability based on the determined probabilities and the determined context weights; and identify the first unknown person instance as a known person instance from the plurality of known person instances with a highest contextual probability. 11. The non-transitory computer readable storage medium as recited in claim 9 , wherein the instructions, when executed by the at least one processor, cause the computer system to determine the context weight for each combination by: determining that a first known person instance from the one or more known person instances and a second known person instance from the one or more known person instances appear together in the images of the image gallery; and boosting a probability that the first known person instance and the second known person instance will appear together in additional images added to the image gallery. | 0.718525 |
8,095,912 | 2 | 4 | 2. A method for generating a set of strings for testing operation of a context-free language compiler for a context-free language, the method comprising acts of: (g) generating a terminal string based, at least in part, on a grammar description for the context-free language comprising a set of production rules, each production rules comprising a replacement string for a non-terminal symbol, the terminal string comprising one or more instances of at least one terminal symbol; (h) generating a test string by replacing, with a value, one or more instances of a terminal symbol in the terminal string; (i) generating an invalid terminal string based on at least one valid production rule from the set of production rules and at least one invalid production rule from a set of invalid production rules, wherein each invalid production rule comprises an invalid replacement string for a non- terminal symbol, the invalid replacement string is guaranteed to be invalid for the context-free language; (j) generating an invalid test string by replacing, with a value, one or more instances of a terminal symbol in the invalid terminal string; (k) applying the invalid test string to the context-free language compiler so that the context-free language compiler produces a response based upon the invalid test string; and (l) determining whether the response matches an expected response for application of the invalid test string. | 2. A method for generating a set of strings for testing operation of a context-free language compiler for a context-free language, the method comprising acts of: (g) generating a terminal string based, at least in part, on a grammar description for the context-free language comprising a set of production rules, each production rules comprising a replacement string for a non-terminal symbol, the terminal string comprising one or more instances of at least one terminal symbol; (h) generating a test string by replacing, with a value, one or more instances of a terminal symbol in the terminal string; (i) generating an invalid terminal string based on at least one valid production rule from the set of production rules and at least one invalid production rule from a set of invalid production rules, wherein each invalid production rule comprises an invalid replacement string for a non- terminal symbol, the invalid replacement string is guaranteed to be invalid for the context-free language; (j) generating an invalid test string by replacing, with a value, one or more instances of a terminal symbol in the invalid terminal string; (k) applying the invalid test string to the context-free language compiler so that the context-free language compiler produces a response based upon the invalid test string; and (l) determining whether the response matches an expected response for application of the invalid test string. 4. The method of claim 2 , wherein the grammar description comprises flags for influencing the generation of the value of act (h). | 0.603659 |
7,991,613 | 6 | 7 | 6. The method of claim 5 , wherein the indexing is selectively performed such that at least a portion of the additional information is not indexed. | 6. The method of claim 5 , wherein the indexing is selectively performed such that at least a portion of the additional information is not indexed. 7. The method of claim 6 , wherein at least some of the additional information that is not indexed is integrated with the information as an HTML tag. | 0.943216 |
8,032,509 | 1 | 19 | 1. A computer system comprising: (a) at least one processor; (b) at least one memory, wherein the at least one memory includes a relation store and a data set information store; and (c) computer program instructions stored in the memory and configured to be executed by the processor to provide a requested data set, including: (i) instructions for receiving a first query language statement referencing a plurality of data sets; (ii) instructions for storing information in the data set information store regarding the data sets referenced in the first query language statement, including temporal information regarding the data sets referenced in the first query language statement; (iii) instructions for composing a first plurality of algebraic relations referencing the data sets specified in the first query language statement, wherein each of the algebraic relations in the first plurality of algebraic relations comprises a respective first expression including a symbolic representation of at least a first respective data set, a respective second expression including a symbolic representation of at least a second respective data set, and a relational operator symbolically defining a mathematical relationship between the respective first expression and the respective second expression; (iv) instructions for storing the first plurality of algebraic relations in the relation store; (v) instructions for receiving a second query language statement referencing a second plurality of data sets; (vi) instructions for composing a second plurality of algebraic relations referencing the data sets specified in the second query language statement; (vii) instructions for storing the second plurality of algebraic relations in the relation store; (viii) instructions for providing the requested data set in response to the second query language statement using at least one algebraic relation from the first plurality of algebraic relations and at least one algebraic relation from the second plurality of algebraic relations; and (ix) instructions for removing at least some of the first plurality of algebraic relations from the relation store based, at least in part, on the temporal information regarding the data sets referenced in the first query language statement. | 1. A computer system comprising: (a) at least one processor; (b) at least one memory, wherein the at least one memory includes a relation store and a data set information store; and (c) computer program instructions stored in the memory and configured to be executed by the processor to provide a requested data set, including: (i) instructions for receiving a first query language statement referencing a plurality of data sets; (ii) instructions for storing information in the data set information store regarding the data sets referenced in the first query language statement, including temporal information regarding the data sets referenced in the first query language statement; (iii) instructions for composing a first plurality of algebraic relations referencing the data sets specified in the first query language statement, wherein each of the algebraic relations in the first plurality of algebraic relations comprises a respective first expression including a symbolic representation of at least a first respective data set, a respective second expression including a symbolic representation of at least a second respective data set, and a relational operator symbolically defining a mathematical relationship between the respective first expression and the respective second expression; (iv) instructions for storing the first plurality of algebraic relations in the relation store; (v) instructions for receiving a second query language statement referencing a second plurality of data sets; (vi) instructions for composing a second plurality of algebraic relations referencing the data sets specified in the second query language statement; (vii) instructions for storing the second plurality of algebraic relations in the relation store; (viii) instructions for providing the requested data set in response to the second query language statement using at least one algebraic relation from the first plurality of algebraic relations and at least one algebraic relation from the second plurality of algebraic relations; and (ix) instructions for removing at least some of the first plurality of algebraic relations from the relation store based, at least in part, on the temporal information regarding the data sets referenced in the first query language statement. 19. The computer system of claim 1 , wherein the second query language statement requests the requested data set to be provided and the requested data set is different from each of the data sets referenced in the first query language statement. | 0.7109 |
7,487,072 | 1 | 2 | 1. A method of storing and searching multimedia data, the method comprising: receiving a multimedia data signal having content that progresses based on a timing; converting the multimedia data signal into a searchable format; identifying a set of features in the searchable format and outputting the set of features as content index data; determining a set of confidence values for the set of features in the searchable format that estimates the accuracy of the set of features in the searchable format as a function of the timing of the multimedia data signal and outputting the confidence values as confidence index data; linking the content index data and the confidence index data with the multimedia data signal as a function of the timing of the multimedia data signal; storing the content index data and the confidence index data into a database that is indexed based on the set of features and the confidence values; receiving, from a requestor, a query that specifies a set of temporal parameters and content parameters; parsing the query into a set of sub-queries; selecting respective search engines for each of the sub-queries, wherein the set of the sub-queries comprises at least two sub-queries, wherein the at least two sub-queries are transmitted to at least two different search engines based on confidence index data among the stored confidence index data which corresponds to the specified set of at least the content parameters; receiving, in response to the transmitted at least two sub-queries, results from the at least two different search engines; and transmitting the received results to the requestor, wherein the converting the multimedia data signal into the searchable format comprises: receiving at least one of the set of confidence values for a previous portion of the multimedia data signal; and adjusting the conversion of a current portion of the multimedia data signal based on the received at least one set of confidence values, wherein the adjusting the conversion of the current portion of the multimedia data signal comprises: comparing the at least one set of confidence values to a threshold; and adjusting the conversion of the current portion of the multimedia data signal based on the comparison of the at least one set of confidence values to the threshold. | 1. A method of storing and searching multimedia data, the method comprising: receiving a multimedia data signal having content that progresses based on a timing; converting the multimedia data signal into a searchable format; identifying a set of features in the searchable format and outputting the set of features as content index data; determining a set of confidence values for the set of features in the searchable format that estimates the accuracy of the set of features in the searchable format as a function of the timing of the multimedia data signal and outputting the confidence values as confidence index data; linking the content index data and the confidence index data with the multimedia data signal as a function of the timing of the multimedia data signal; storing the content index data and the confidence index data into a database that is indexed based on the set of features and the confidence values; receiving, from a requestor, a query that specifies a set of temporal parameters and content parameters; parsing the query into a set of sub-queries; selecting respective search engines for each of the sub-queries, wherein the set of the sub-queries comprises at least two sub-queries, wherein the at least two sub-queries are transmitted to at least two different search engines based on confidence index data among the stored confidence index data which corresponds to the specified set of at least the content parameters; receiving, in response to the transmitted at least two sub-queries, results from the at least two different search engines; and transmitting the received results to the requestor, wherein the converting the multimedia data signal into the searchable format comprises: receiving at least one of the set of confidence values for a previous portion of the multimedia data signal; and adjusting the conversion of a current portion of the multimedia data signal based on the received at least one set of confidence values, wherein the adjusting the conversion of the current portion of the multimedia data signal comprises: comparing the at least one set of confidence values to a threshold; and adjusting the conversion of the current portion of the multimedia data signal based on the comparison of the at least one set of confidence values to the threshold. 2. The method of claim 1 , wherein converting the multimedia data signal comprises: identifying an event in the multimedia data signal; and selectively converting the multimedia data signal based on the event. | 0.689911 |
9,542,502 | 7 | 12 | 7. A data processing system comprising: a processor; and an accessible memory, the data processing system particularly configured to receive a document having fragments with attribute/value pairs; receive logical expressions that define relationships between fragments of the document; analyze the logical expressions to identify fragment names and attributes; create an index based on the analysis that includes names of the fragments to be candidates for selection into subdocuments; extract, from the document, all fragments named in the index; create, in the index, an entry for each attribute/value pair; create a plurality of subdocuments corresponding to the document, which includes finding top-level fragments in the index, finding second-level fragments related to each top-level fragment, and finding third-level fragments related to each second-level fragment; and store the subdocuments, including the respective related fragments. | 7. A data processing system comprising: a processor; and an accessible memory, the data processing system particularly configured to receive a document having fragments with attribute/value pairs; receive logical expressions that define relationships between fragments of the document; analyze the logical expressions to identify fragment names and attributes; create an index based on the analysis that includes names of the fragments to be candidates for selection into subdocuments; extract, from the document, all fragments named in the index; create, in the index, an entry for each attribute/value pair; create a plurality of subdocuments corresponding to the document, which includes finding top-level fragments in the index, finding second-level fragments related to each top-level fragment, and finding third-level fragments related to each second-level fragment; and store the subdocuments, including the respective related fragments. 12. The data processing system of claim 7 , wherein the logical expressions are Xpath expressions. | 0.785088 |
9,323,485 | 1 | 5 | 1. A verifiable document security system comprising: a validation center for generating a security architecture for a secured document and transmitting print instructions for printing the security architecture on a document in a form of a check payable to a recipient, the validation center communicating with an issuer and the recipient to receive and validate transaction information, wherein the recipient receives the secured document after printing; wherein the security architecture comprises a plurality of security elements comprising indicia printed with a print media and in a print configuration; wherein the print media is selected from the group consisting of a transparent magnetizable fluid, an ultraviolet (UV) excitable fluid, an infrared (IR) fluid, an x-ray excitable fluid, a gamma ray excitable fluid, an electron beam (EB) excitable fluid, an alternative energy excitable fluid, and a fluorescent fluid, further wherein at least one of the security elements is printed with the transparent magnetizable fluid; wherein the print configuration is selected from the group consisting of at least two sizes, a non-linear configuration, a curved configuration and an angled configuration; and a printing means comprising an ink suite, which comprises the print media, wherein the printing means is capable of receiving print instructions and capable of printing the security architecture on the document. | 1. A verifiable document security system comprising: a validation center for generating a security architecture for a secured document and transmitting print instructions for printing the security architecture on a document in a form of a check payable to a recipient, the validation center communicating with an issuer and the recipient to receive and validate transaction information, wherein the recipient receives the secured document after printing; wherein the security architecture comprises a plurality of security elements comprising indicia printed with a print media and in a print configuration; wherein the print media is selected from the group consisting of a transparent magnetizable fluid, an ultraviolet (UV) excitable fluid, an infrared (IR) fluid, an x-ray excitable fluid, a gamma ray excitable fluid, an electron beam (EB) excitable fluid, an alternative energy excitable fluid, and a fluorescent fluid, further wherein at least one of the security elements is printed with the transparent magnetizable fluid; wherein the print configuration is selected from the group consisting of at least two sizes, a non-linear configuration, a curved configuration and an angled configuration; and a printing means comprising an ink suite, which comprises the print media, wherein the printing means is capable of receiving print instructions and capable of printing the security architecture on the document. 5. The verifiable document security system according to claim 1 , wherein the validation center provides feedback and cyclic verification between issuer and recipient before, during, and after printing of the secure document; wherein, the issuer is notified in a case of unauthentic print, wherein the issuer has an option of real time interference to halt final processing of the secure document, wherein the issuer has an option to flag secure data and inform a primary authority of unauthentic data. | 0.500994 |
9,098,836 | 10 | 13 | 10. The method of claim 1 , comprising generating at least some of the intention metadata for the attachment. | 10. The method of claim 1 , comprising generating at least some of the intention metadata for the attachment. 13. The method of claim 10 , generating at least some of the intention metadata for the attachment comprising using sender generated intention metadata. | 0.933157 |
7,844,502 | 24 | 25 | 24. The automated shopping method of claim 19 , wherein the management system used in tracking allocates a pre-determined time to complete at least one step of the multiple steps using a timer. | 24. The automated shopping method of claim 19 , wherein the management system used in tracking allocates a pre-determined time to complete at least one step of the multiple steps using a timer. 25. The automated shopping method of claim 24 , wherein the management system used in tracking sends an alarm if a predetermined time period has lapsed without requisite action. | 0.967283 |
4,214,125 | 51 | 52 | 51. A system for synthesizing signals from compressed information signals having the form of an inverse transformation of a partially symmetric phase adjusted transform of the original signals, said compressed information signals being devoid of selected portions corresponding to a fraction of the partially symmetric portions of said phase adjusted transform, and instruction signals identifying the selected portions, said system comprising: means for reproducing said compressed information signals; means coupled to said reproducing means for expanding the reproduced signals to supply said fractional portions in accordance with said instruction signals; and means for converting the expanded reproduced signals to audible form. | 51. A system for synthesizing signals from compressed information signals having the form of an inverse transformation of a partially symmetric phase adjusted transform of the original signals, said compressed information signals being devoid of selected portions corresponding to a fraction of the partially symmetric portions of said phase adjusted transform, and instruction signals identifying the selected portions, said system comprising: means for reproducing said compressed information signals; means coupled to said reproducing means for expanding the reproduced signals to supply said fractional portions in accordance with said instruction signals; and means for converting the expanded reproduced signals to audible form. 52. The combination of claim 51 further including memory means for storing said compressed signals and wherein said reproducing means includes means for reading said compressed signals from said memory means. | 0.979588 |
7,610,237 | 6 | 8 | 6. The method of claim 1 , further comprising: receiving a user request to view the user data associated with the annotation record; and providing the user data associated with the annotation record. | 6. The method of claim 1 , further comprising: receiving a user request to view the user data associated with the annotation record; and providing the user data associated with the annotation record. 8. The method of claim 6 , wherein providing the user data comprises displaying the user data via the second graphical interface. | 0.964286 |
6,045,277 | 12 | 15 | 12. A tape printing apparatus, comprising: selection means for selecting a print format from a plurality of print formats, each print format corresponding to instructions stored in a memory; character input means for inputting at least one character string containing a plurality of characters; storage means for storing the character string; printing means for printing the stored character string on a tape defining a longitudinal direction according to the instructions for the print format; and control means for equally spacing the characters of the character string along a predetermined print length and printing the characters, the control means comprising arranging means for, when the print format defines a horizontal writing index tab print format, arranging a vertical direction of each character of the stored character string in agreement with a transverse direction transverse to a longitudinal direction of the tape and arranging said each of the characters in the longitudinal direction of the tape, the character string is printed from a head thereof in a line and from a rear thereof in another line. | 12. A tape printing apparatus, comprising: selection means for selecting a print format from a plurality of print formats, each print format corresponding to instructions stored in a memory; character input means for inputting at least one character string containing a plurality of characters; storage means for storing the character string; printing means for printing the stored character string on a tape defining a longitudinal direction according to the instructions for the print format; and control means for equally spacing the characters of the character string along a predetermined print length and printing the characters, the control means comprising arranging means for, when the print format defines a horizontal writing index tab print format, arranging a vertical direction of each character of the stored character string in agreement with a transverse direction transverse to a longitudinal direction of the tape and arranging said each of the characters in the longitudinal direction of the tape, the character string is printed from a head thereof in a line and from a rear thereof in another line. 15. A tape printing apparatus according to claim 12, wherein the control means sets a variety of different print lengths other than the predetermined print length. | 0.971964 |
7,877,403 | 7 | 8 | 7. The storage medium of claim 1 further comprising instructions that upon execution cause the processor to display two or more learned rules from the plurality of learned rules. | 7. The storage medium of claim 1 further comprising instructions that upon execution cause the processor to display two or more learned rules from the plurality of learned rules. 8. The storage medium of claim 7 further comprising instructions that upon execution cause the processor to select at least one of the two or more learned rules. | 0.932296 |
7,949,106 | 1 | 4 | 1. A method comprising: receiving a signal at an interactive voice response system during a call that involves said interactive voice response system and a telecommunications terminal, wherein said signal is associated with a content stream that is delivered to said telecommunications terminal during said call, and wherein said interactive voice response system executes an application that is for prompting for and receiving one or more caller inputs unrelated to said content stream; and in response to said signal performing, concurrently with the execution of said application, an action at said interactive voice response system that is related to said content stream. | 1. A method comprising: receiving a signal at an interactive voice response system during a call that involves said interactive voice response system and a telecommunications terminal, wherein said signal is associated with a content stream that is delivered to said telecommunications terminal during said call, and wherein said interactive voice response system executes an application that is for prompting for and receiving one or more caller inputs unrelated to said content stream; and in response to said signal performing, concurrently with the execution of said application, an action at said interactive voice response system that is related to said content stream. 4. The method of claim 1 wherein the performing of said action is in a separate thread of said application. | 0.761161 |
8,676,800 | 17 | 18 | 17. A method defined by claim 15 wherein the conceptual representation includes an interpretive portion, wherein the interpretive portion represents an operation on one or more aggregate data items, and wherein the operation on the one or more aggregate data items includes determining one or more of the following: (a) the number of data items comprising the one or more aggregate data items; (b) if the one or more aggregate data items is empty; (c) if the one or more aggregate data items includes a specific data item; (d) any other set operation. | 17. A method defined by claim 15 wherein the conceptual representation includes an interpretive portion, wherein the interpretive portion represents an operation on one or more aggregate data items, and wherein the operation on the one or more aggregate data items includes determining one or more of the following: (a) the number of data items comprising the one or more aggregate data items; (b) if the one or more aggregate data items is empty; (c) if the one or more aggregate data items includes a specific data item; (d) any other set operation. 18. A method defined by claim 17 , wherein the step of generating information includes generating information from the interpretive portion. | 0.956656 |
5,426,700 | 10 | 13 | 10. A method as described as claim 1 wherein said document further incorporates a second encrypted decryption key GE encrypted with a group encryption key GE for an encryption/decryption key pair GE,GD, and wherein documents in at least a a second particular class incorporate a third encrypted decryption key GE, and further comprising the step of: a) providing verifying means for receiving said enabling information and for decrypting said encrypted information E, said verifying means further comprising memory means for storing a decryption key; and wherein, b) said enabling information comprises information defining a group decryption key GD for said key pair GE, GD, said decryption key GD enabling decryption of encrypted decryption keys on all documents comprised in said selected group; and c) said verifying means further comprises means responsive to said enabling information for storing said decryption key GD in said memory means. | 10. A method as described as claim 1 wherein said document further incorporates a second encrypted decryption key GE encrypted with a group encryption key GE for an encryption/decryption key pair GE,GD, and wherein documents in at least a a second particular class incorporate a third encrypted decryption key GE, and further comprising the step of: a) providing verifying means for receiving said enabling information and for decrypting said encrypted information E, said verifying means further comprising memory means for storing a decryption key; and wherein, b) said enabling information comprises information defining a group decryption key GD for said key pair GE, GD, said decryption key GD enabling decryption of encrypted decryption keys on all documents comprised in said selected group; and c) said verifying means further comprises means responsive to said enabling information for storing said decryption key GD in said memory means. 13. A method as described in claim 10 comprising the further step of: a) transmitting request information to a data center, said request information including encrypted information identifying said verifying means and a request for enabling information defining said group decryption key GD, wherein said data center decrypts said encrypted identifying information and responds to transmit said requested enabling information to said verifying means. | 0.829287 |
8,127,220 | 11 | 14 | 11. A computer-implemented method, comprising: receiving a search query; providing a list of search results in response to the search query; receiving selection of one of the search results in the list of search results; identifying links in a document corresponding to the selected search result; determining a score for one of the links based on a degree of match between the search query and a content of a linked document pointed to by the one of the links; modifying the document based on the determined score for the one of the links; and providing the modified document. | 11. A computer-implemented method, comprising: receiving a search query; providing a list of search results in response to the search query; receiving selection of one of the search results in the list of search results; identifying links in a document corresponding to the selected search result; determining a score for one of the links based on a degree of match between the search query and a content of a linked document pointed to by the one of the links; modifying the document based on the determined score for the one of the links; and providing the modified document. 14. The method of claim 11 , wherein modifying the document includes: changing at least one visual characteristic of the one of the links within the document based on the determined score. | 0.948857 |
8,631,037 | 7 | 10 | 7. The system of claim 5 further comprising a communication system configured to communicate electronically with the equipment. | 7. The system of claim 5 further comprising a communication system configured to communicate electronically with the equipment. 10. The system of claim 7 wherein the information delivery engine is configured to cause at least one of the user queries to be answered by the user through the user interface and at least one of the user queries to be answered by the equipment through communication with the equipment through the communication system. | 0.884504 |
10,120,933 | 1 | 13 | 1. A method of language processing that represents both sematic and orientation content within a text, the method being performed by circuitry included in a computing device, the method comprising: receiving, by the circuitry, ordered data elements representing respective words in a text, the ordered data elements including a first data element including one or more words and a second data element, which is sequential with the first data element and include another one or more words; generating, based on a plurality of semantic classes corresponding respectively to blades of a graded vector space representing clusters of semantic meaning, a first subspace formed within the graded vector space by the first data element, a second subspace within the graded vector space by the second data element, a first set of data elements corresponding to one or more first semantic classes that include the first data element, and a second set of data elements corresponding to one or more second semantic classes that include the second data element; encoding by the circuitry, when the one or more first semantic classes is non-degenerate with the one or more second semantic classes, the first data element with respect to the second data element such that an encoded subspace formed by encoding the first data element with respect to the second data element is oriented with respect to an order of the first data element with respect to the second data element, the encoding being performed by computing one of a left contraction and a right contraction of the first set of data elements with respect to the second set of data elements; computing by the circuitry, respective components of a weight distribution of the first data element with respect to the second data element, the components of the weight distribution being computed using respective ordered pairs for each of the one or more first semantic classes with respect to each of the one or more second semantic classes; and determining a dominant semantic class of an ordered sequence of the first data element and the second data element, the dominant semantic class representing an oriented semantic context of an ordered sequence of the first and second data elements, and the dominant semantic class being determined as a semantic class corresponding to a component having a maximum magnitude of the weight distribution, wherein the left contraction is one of a Clifford Algebra left contraction and a Geometric Algebra left contraction, and the right contraction is one of a Clifford Algebra right contraction and a Geometric Algebra right contraction. | 1. A method of language processing that represents both sematic and orientation content within a text, the method being performed by circuitry included in a computing device, the method comprising: receiving, by the circuitry, ordered data elements representing respective words in a text, the ordered data elements including a first data element including one or more words and a second data element, which is sequential with the first data element and include another one or more words; generating, based on a plurality of semantic classes corresponding respectively to blades of a graded vector space representing clusters of semantic meaning, a first subspace formed within the graded vector space by the first data element, a second subspace within the graded vector space by the second data element, a first set of data elements corresponding to one or more first semantic classes that include the first data element, and a second set of data elements corresponding to one or more second semantic classes that include the second data element; encoding by the circuitry, when the one or more first semantic classes is non-degenerate with the one or more second semantic classes, the first data element with respect to the second data element such that an encoded subspace formed by encoding the first data element with respect to the second data element is oriented with respect to an order of the first data element with respect to the second data element, the encoding being performed by computing one of a left contraction and a right contraction of the first set of data elements with respect to the second set of data elements; computing by the circuitry, respective components of a weight distribution of the first data element with respect to the second data element, the components of the weight distribution being computed using respective ordered pairs for each of the one or more first semantic classes with respect to each of the one or more second semantic classes; and determining a dominant semantic class of an ordered sequence of the first data element and the second data element, the dominant semantic class representing an oriented semantic context of an ordered sequence of the first and second data elements, and the dominant semantic class being determined as a semantic class corresponding to a component having a maximum magnitude of the weight distribution, wherein the left contraction is one of a Clifford Algebra left contraction and a Geometric Algebra left contraction, and the right contraction is one of a Clifford Algebra right contraction and a Geometric Algebra right contraction. 13. The method of claim 1 , wherein each type of semantic class of the plurality of semantic classes is assigned a unique metric, the unique metric being utilized in the computation of one of the left contraction and a right contraction operations as a measure within one of the respective blades. | 0.667785 |
9,211,891 | 1 | 11 | 1. A method of facilitating a user driving a vehicle, the method involving a device having a processor and comprising: executing on the processor instructions configured to: at a first time point associated with a first instance of a driving context, monitor a vehicle control input of the vehicle by the user to identify a user driving behavior of the user in the driving context; identify at least one alternative driving behavior providing an advantage over the user driving behavior of the user for operating the vehicle in the driving context; identify a suggestion location that is associated with at least one alternate driving behavior; and at a second time point that is associated with a second instance of the driving context and at the suggestion location, present to the user a driving suggestion of the alternative driving behavior in the driving context. | 1. A method of facilitating a user driving a vehicle, the method involving a device having a processor and comprising: executing on the processor instructions configured to: at a first time point associated with a first instance of a driving context, monitor a vehicle control input of the vehicle by the user to identify a user driving behavior of the user in the driving context; identify at least one alternative driving behavior providing an advantage over the user driving behavior of the user for operating the vehicle in the driving context; identify a suggestion location that is associated with at least one alternate driving behavior; and at a second time point that is associated with a second instance of the driving context and at the suggestion location, present to the user a driving suggestion of the alternative driving behavior in the driving context. 11. The method of claim 1 , presenting the driving suggestion to the user comprising: presenting to the user the driving suggestion and an explanation of the advantage of the alternative driving behavior over the user driving behavior of the user. | 0.809414 |
8,892,495 | 1 | 17 | 1. A programmable environmental controller, comprising: an local area network interface port configured to communicate digital data through a local area network; at least one climate sensor configured to sense environmental climate conditions; at least one movement sensor configured to detect a movement of an individual in a vicinity of the at least one movement sensor; and at least one automated processor configured to receive the sensed environmental climate conditions and the detected movement, to jointly classify a temporal pattern of the sensed environmental climate conditions and the detected movement, and to communicate at least one signal in dependence on the jointly classified pattern, the at least one signal being adapted to at least control an environmental control system. | 1. A programmable environmental controller, comprising: an local area network interface port configured to communicate digital data through a local area network; at least one climate sensor configured to sense environmental climate conditions; at least one movement sensor configured to detect a movement of an individual in a vicinity of the at least one movement sensor; and at least one automated processor configured to receive the sensed environmental climate conditions and the detected movement, to jointly classify a temporal pattern of the sensed environmental climate conditions and the detected movement, and to communicate at least one signal in dependence on the jointly classified pattern, the at least one signal being adapted to at least control an environmental control system. 17. The programmable environmental controller according to claim 1 , wherein the at least one automated processor is further configured to model an efficiency of the environmental control system in dependence on the at least one control signal, and to produce the at least one signal in a manner adapted to optimize the modeled efficiency. | 0.814348 |
7,983,490 | 9 | 11 | 9. A computer-implemented method for labeling Gaussian probability density functions representative of the underlying population densities in an input-data-set, as belonging to one of two classes, either a class-of-interest or a class-other; and a method for classifying a pattern from said input-data-set into one of two classes, either a said class-of-interest or a said class-other, comprising the steps of: receiving a training set of class-of-interest patterns, a set of unlabeled patterns from said input-data-set, and an estimate of the a priori probability of said class-of-interest in said input-data-set, said input-data-set being at least one of an image, video or speech data set; receiving a plurality of said Gaussian probability density functions, representative of said underlying population densities in said input-data-set; executing a training stage utilizing said estimate of the a priori probability of said class-of-interest, said training set of class-of-interest patterns, and said patterns from said input-data-set, said training stage including a step of least squares estimation of the probabilities that said Gaussian probability density functions belong to said class-of-interest, utilizing using a linear combination of weighted said Gaussian density functions; labeling each said Gaussian probability density function as belonging to said class-of-interest or to said class-other, based on a predetermined conditional test of the value of said probability that said Gaussian probability density function belong to said class-of-interest; classifying said pattern from said input-data-set as being said class-of-interest or said class-other using an adaptive Bayes decision rule; and wherein said Gaussian probability density functions, representative of the underlying said population densities in said input-data-set, are labeled with minimum error as belonging to said class-of-interest or class-other using a said predetermined decision rule and said pattern from said input-data-set is classified with minimum error using said adaptive Bayes decision rule, with both classifiers trained without any a priori knowledge of said class-other. | 9. A computer-implemented method for labeling Gaussian probability density functions representative of the underlying population densities in an input-data-set, as belonging to one of two classes, either a class-of-interest or a class-other; and a method for classifying a pattern from said input-data-set into one of two classes, either a said class-of-interest or a said class-other, comprising the steps of: receiving a training set of class-of-interest patterns, a set of unlabeled patterns from said input-data-set, and an estimate of the a priori probability of said class-of-interest in said input-data-set, said input-data-set being at least one of an image, video or speech data set; receiving a plurality of said Gaussian probability density functions, representative of said underlying population densities in said input-data-set; executing a training stage utilizing said estimate of the a priori probability of said class-of-interest, said training set of class-of-interest patterns, and said patterns from said input-data-set, said training stage including a step of least squares estimation of the probabilities that said Gaussian probability density functions belong to said class-of-interest, utilizing using a linear combination of weighted said Gaussian density functions; labeling each said Gaussian probability density function as belonging to said class-of-interest or to said class-other, based on a predetermined conditional test of the value of said probability that said Gaussian probability density function belong to said class-of-interest; classifying said pattern from said input-data-set as being said class-of-interest or said class-other using an adaptive Bayes decision rule; and wherein said Gaussian probability density functions, representative of the underlying said population densities in said input-data-set, are labeled with minimum error as belonging to said class-of-interest or class-other using a said predetermined decision rule and said pattern from said input-data-set is classified with minimum error using said adaptive Bayes decision rule, with both classifiers trained without any a priori knowledge of said class-other. 11. The method of claim 9 wherein said step of executing the training stage includes a step of providing a plurality of said weights for each said Gaussian probability density function. | 0.859636 |
8,441,454 | 33 | 35 | 33. The system of claim 1 further comprising: means for dynamically changing character set member locations or sub-regions within the auto-correcting keyboard region. | 33. The system of claim 1 further comprising: means for dynamically changing character set member locations or sub-regions within the auto-correcting keyboard region. 35. The system of claim 33 , wherein said means for dynamically changing assigns more sub-region area to a character set member based on the frequency of said character set member at a given position in said strings of said plurality of objects in memory. | 0.949081 |
4,841,441 | 15 | 23 | 15. A method of constructing a data model of an organizational structure for a user, utilising a digital or analogue computer system comprising: (a) storing in a main memory of a computer system a source series of questions which are presentable in conversational language concerning the entities represented in the organizational structure and operation thereof, the attributes of those entities, the relationship between those entities, (b) storing in the memory in coded form a series of answers in conversational language which are provided by the user to the series of questions which answers in coded form constitute data for the model, (c) comparing the coded form of answers with coded data in the main memory, (d) analysing the comparisons and compiling a data model for the user from the comparisons in the data. | 15. A method of constructing a data model of an organizational structure for a user, utilising a digital or analogue computer system comprising: (a) storing in a main memory of a computer system a source series of questions which are presentable in conversational language concerning the entities represented in the organizational structure and operation thereof, the attributes of those entities, the relationship between those entities, (b) storing in the memory in coded form a series of answers in conversational language which are provided by the user to the series of questions which answers in coded form constitute data for the model, (c) comparing the coded form of answers with coded data in the main memory, (d) analysing the comparisons and compiling a data model for the user from the comparisons in the data. 23. A method as claimed in claim 15 wherein for a model of a procedure in the organization, the entities concerned in that procedure are identified by reference to codes stored in the memory, the relationships between these entities are compared with standard types of relationship stored in the memory and a suitable procedure is displayed for the user's inspection of choice. | 0.657273 |
7,703,028 | 6 | 10 | 6. A computer-implemented method, said computer including a processor and having a graphical display that includes at least one object that is associated with data, said method comprising: splitting said graphical display into a left area forming a left rectangle, a center area forming a center rectangle, and a right area forming a right rectangle; displaying a star schema in said graphical display by displaying dimension objects including dimension tables that include attribute data in said left area, a facts object including a facts table that includes measurement data in said center area, and additional dimension objects including dimension tables that include attribute data in said right area and by displaying connecting lines across said rectangles in the graphical display to illustrate associations between said facts object and said dimension objects, wherein said objects in each area are manipulated independently of said other objects in said each area and said objects in each other area; accepting input that reduces said at least one object in one area, wherein said at least one object is one of said dimension objects and facts objects; and in response to reducing said at least one object in said one area; reducing said display of said one area that includes said reduced at least one object; realigning vertically and horizontally other objects within said reduced area relative to said reduced at least one object in said reduced area; moving said display of said each other area including at least one object that is not included in said reduced area in response to reduction of the display of said reduced area on the graphical device, thereby enabling efficient analysis of said data associated with said at least one object that is included in said reduced area; and realigning said objects in said each other area with the realigned other objects within said reduced area, wherein positions of said objects in said each other area are adjusted in at least one of a horizontal direction and a vertical direction to accommodate alignment of said other objects within said each other area. | 6. A computer-implemented method, said computer including a processor and having a graphical display that includes at least one object that is associated with data, said method comprising: splitting said graphical display into a left area forming a left rectangle, a center area forming a center rectangle, and a right area forming a right rectangle; displaying a star schema in said graphical display by displaying dimension objects including dimension tables that include attribute data in said left area, a facts object including a facts table that includes measurement data in said center area, and additional dimension objects including dimension tables that include attribute data in said right area and by displaying connecting lines across said rectangles in the graphical display to illustrate associations between said facts object and said dimension objects, wherein said objects in each area are manipulated independently of said other objects in said each area and said objects in each other area; accepting input that reduces said at least one object in one area, wherein said at least one object is one of said dimension objects and facts objects; and in response to reducing said at least one object in said one area; reducing said display of said one area that includes said reduced at least one object; realigning vertically and horizontally other objects within said reduced area relative to said reduced at least one object in said reduced area; moving said display of said each other area including at least one object that is not included in said reduced area in response to reduction of the display of said reduced area on the graphical device, thereby enabling efficient analysis of said data associated with said at least one object that is included in said reduced area; and realigning said objects in said each other area with the realigned other objects within said reduced area, wherein positions of said objects in said each other area are adjusted in at least one of a horizontal direction and a vertical direction to accommodate alignment of said other objects within said each other area. 10. The computer-implemented method of claim 6 further comprising including at least one additional object that is associated with said data within said at least one object thereby enabling efficient analysis in a recursive manner of said data associated with said at least one additional object. | 0.783942 |
8,019,756 | 13 | 14 | 13. A method for calculating the importance of at least one of a plurality of electronic documents, based on (i) a plurality of electronic documents, (ii) information on referencing relation between each pair of the electronic documents, (iii) an important phrase, and (iv) a response coefficient determining phrase, (i) through (iv) being stored in a storage device, the method comprising: (a) calculating importance unique to one electronic document of a given electronic document among the plurality of electronic documents, on the basis of the degree of similarity between the important phrase and a phrase included in the given electronic document; (b) identifying at least one of other electronic documents which references the given electronic document, on the basis of the reference information; (c) calculating a response coefficient against the given electronic document, on the basis of at least one of the degrees of similarities between a phrase included in the other electronic documents and the response coefficient determining phrase; (d) calculating total importance of the given electronic document, on the basis of the importance unique to one electronic document of the given electronic document, the response coefficient, and total importance of the other electronic documents; and (e) calculating a total importance of each of the electronic documents in an electronic document group in which the given electronic document and the other electronic documents are directly and indirectly linked to each other on the basis of the reference information through relations of referencing and being referenced, by performing (a) through (d) on each pair of electronic documents having a mutual relation of directly referencing and being referenced in the electronic document group. | 13. A method for calculating the importance of at least one of a plurality of electronic documents, based on (i) a plurality of electronic documents, (ii) information on referencing relation between each pair of the electronic documents, (iii) an important phrase, and (iv) a response coefficient determining phrase, (i) through (iv) being stored in a storage device, the method comprising: (a) calculating importance unique to one electronic document of a given electronic document among the plurality of electronic documents, on the basis of the degree of similarity between the important phrase and a phrase included in the given electronic document; (b) identifying at least one of other electronic documents which references the given electronic document, on the basis of the reference information; (c) calculating a response coefficient against the given electronic document, on the basis of at least one of the degrees of similarities between a phrase included in the other electronic documents and the response coefficient determining phrase; (d) calculating total importance of the given electronic document, on the basis of the importance unique to one electronic document of the given electronic document, the response coefficient, and total importance of the other electronic documents; and (e) calculating a total importance of each of the electronic documents in an electronic document group in which the given electronic document and the other electronic documents are directly and indirectly linked to each other on the basis of the reference information through relations of referencing and being referenced, by performing (a) through (d) on each pair of electronic documents having a mutual relation of directly referencing and being referenced in the electronic document group. 14. The method of claim 13 , including sequentially applying the equation c i =s i +a×r ij ×c j to pairs of the plurality of the electronic documents. | 0.921301 |
9,387,014 | 33 | 34 | 33. A method for decompressing a spinal canal, comprising: moving a posterior element of a vertebra that is separated from a first portion of a lateral mass of the vertebra away from the first portion of the lateral mass to expand a spinal canal disposed between the posterior element and the first portion of the lateral mass; implanting a first bone anchor into the first portion of the lateral mass, the bone anchor including a head having opposed arms; coupling a first end of a first connecting plate to the first bone anchor by contacting the head to an opening formed in the first end; and coupling a second end of the first connecting plate to the posterior element to maintain the posterior element in a fixed position with respect to the first portion of the lateral mass, wherein coupling a first end of a first connecting plate to the first bone anchor comprises positioning a first locking member within an opening formed in the first end of the first connecting plate such that a distal portion of the first locking member engages opposed inner walls of the opposed arms to maintain a location of the first connecting plate with respect to the first bone anchor. | 33. A method for decompressing a spinal canal, comprising: moving a posterior element of a vertebra that is separated from a first portion of a lateral mass of the vertebra away from the first portion of the lateral mass to expand a spinal canal disposed between the posterior element and the first portion of the lateral mass; implanting a first bone anchor into the first portion of the lateral mass, the bone anchor including a head having opposed arms; coupling a first end of a first connecting plate to the first bone anchor by contacting the head to an opening formed in the first end; and coupling a second end of the first connecting plate to the posterior element to maintain the posterior element in a fixed position with respect to the first portion of the lateral mass, wherein coupling a first end of a first connecting plate to the first bone anchor comprises positioning a first locking member within an opening formed in the first end of the first connecting plate such that a distal portion of the first locking member engages opposed inner walls of the opposed arms to maintain a location of the first connecting plate with respect to the first bone anchor. 34. The method of claim 33 , further comprising dissecting the posterior element from the first portion of the lateral mass of the vertebra. | 0.9125 |
9,418,155 | 14 | 16 | 14. A computerized system comprising: one or more processors; and a non-transitory computer storage media storing computer-useable instructions that, when used by the one or more processors, cause the one or more processors to: receive a search query from a user input via an interconnected computing network of the computing system; identify an ambiguous term in the search query by utilizing lists of categories from semi-structured data containing the ambiguous term; infer categories of the ambiguous term via extraction on the semi-structured data; for each of the categories inferred for the ambiguous term, compute an amount of network traffic, wherein computing includes calculating a number of webpage views representing each category and a dwell time for each of the webpage views; compute a total amount of network traffic to all of the webpages representing the categories inferred; determine a probability for each category of the ambiguous term based on the amount of network traffic computed for each of the categories and the total amount of network traffic computed for all categories inferred of the ambiguous entity; identify a most probable category of the ambiguous term, wherein the most probable category has a highest probability compared to remaining categories of the ambiguous term; and return search results representing the most probable category of the ambiguous term to a user via a graphical user interface of the computing system based on the probability calculated for each category of the ambiguous term from the amount of network traffic computed for each of the categories and the total amount of network traffic computed for all categories inferred of the ambiguous entity. | 14. A computerized system comprising: one or more processors; and a non-transitory computer storage media storing computer-useable instructions that, when used by the one or more processors, cause the one or more processors to: receive a search query from a user input via an interconnected computing network of the computing system; identify an ambiguous term in the search query by utilizing lists of categories from semi-structured data containing the ambiguous term; infer categories of the ambiguous term via extraction on the semi-structured data; for each of the categories inferred for the ambiguous term, compute an amount of network traffic, wherein computing includes calculating a number of webpage views representing each category and a dwell time for each of the webpage views; compute a total amount of network traffic to all of the webpages representing the categories inferred; determine a probability for each category of the ambiguous term based on the amount of network traffic computed for each of the categories and the total amount of network traffic computed for all categories inferred of the ambiguous entity; identify a most probable category of the ambiguous term, wherein the most probable category has a highest probability compared to remaining categories of the ambiguous term; and return search results representing the most probable category of the ambiguous term to a user via a graphical user interface of the computing system based on the probability calculated for each category of the ambiguous term from the amount of network traffic computed for each of the categories and the total amount of network traffic computed for all categories inferred of the ambiguous entity. 16. The system of claim 14 , wherein the search results returned comprise content for all categories having a probability above a minimum probability threshold level. | 0.67451 |
5,539,529 | 19 | 23 | 19. A selective call receiver, comprising: a receiver for receiving information in a first format comprising a bitmap image; a segmenter, coupled to the receiver, for segmenting the bitmap image into a text region and a non text region; a subtracter, coupled to the segmenter, for subtracting the non text region from the bitmap image; an identifier, coupled to the subtracter, for identifying text lines within the text region of the bitmap image; a formatter, coupled to the identifier, for reformatting the text lines of the bitmap image to a second format, the formatter further comprises means for wrapping which reformats the text lines to the second format having a number of black pixels greater than a threshold energy measure; and a display, coupled to the formatter, for displaying the text lines being formatted. | 19. A selective call receiver, comprising: a receiver for receiving information in a first format comprising a bitmap image; a segmenter, coupled to the receiver, for segmenting the bitmap image into a text region and a non text region; a subtracter, coupled to the segmenter, for subtracting the non text region from the bitmap image; an identifier, coupled to the subtracter, for identifying text lines within the text region of the bitmap image; a formatter, coupled to the identifier, for reformatting the text lines of the bitmap image to a second format, the formatter further comprises means for wrapping which reformats the text lines to the second format having a number of black pixels greater than a threshold energy measure; and a display, coupled to the formatter, for displaying the text lines being formatted. 23. The selective call receiver according to claim 19 wherein the reformatter further comprising: means for designating an input pointer and an output pointer; means, coupled to the means for designating, for establishing a threshold energy measure; a counter, coupled to the means for establishing, for counting black pixels in the text lines; and a comparator, coupled to the counter, for comparing the black pixels with the threshold energy measure. | 0.773092 |
7,613,719 | 5 | 7 | 5. The method of claim 1 and further comprising: changing the table based on a further command received. | 5. The method of claim 1 and further comprising: changing the table based on a further command received. 7. The method of claim 5 wherein the further command is sorting a portion of the table. | 0.969917 |
8,745,094 | 1 | 7 | 1. A method for distributed tokenization of sensitive strings of characters in a local server, the method comprising: receiving at the local server from a central server one or more token lookup tables having a plurality of tokens, each token comprising at least one character; receiving a sensitive string of characters at the local server; selecting a substring of the sensitive string of characters; replacing the selected substring of the sensitive string of characters with a first token from the received token lookup tables to form an intermediate tokenized string of characters; selecting a substring of the intermediate tokenized string of characters, the selected substring of the intermediate tokenized string of characters including at least one character replaced by the first token; and replacing the selected substring of the intermediate tokenized string of characters with a second token from the received token lookup tables to form a final tokenized string of characters, the second token being different from the first token. | 1. A method for distributed tokenization of sensitive strings of characters in a local server, the method comprising: receiving at the local server from a central server one or more token lookup tables having a plurality of tokens, each token comprising at least one character; receiving a sensitive string of characters at the local server; selecting a substring of the sensitive string of characters; replacing the selected substring of the sensitive string of characters with a first token from the received token lookup tables to form an intermediate tokenized string of characters; selecting a substring of the intermediate tokenized string of characters, the selected substring of the intermediate tokenized string of characters including at least one character replaced by the first token; and replacing the selected substring of the intermediate tokenized string of characters with a second token from the received token lookup tables to form a final tokenized string of characters, the second token being different from the first token. 7. The method of claim 1 , wherein at least one of the selected substring of the sensitive string of characters and the selected substring of the intermediate tokenized string of characters comprises only numerical characters, and wherein at least one of the first and second tokens comprises alphanumerical characters. | 0.714669 |
7,788,402 | 7 | 17 | 7. A processor-implemented method for generating a circuit for converting a first network packet into a second network packet, the processor-implemented method comprising: inputting a textual language specification that includes a plurality of modification actions, each modification action being one of an insertion action for inserting a data segment into the first network packet and a removal action for removing a data segment from the first network packet; concurrently scanning through a first plurality of data units in a first sequence of data words in the first network packet and a second plurality of data units in a second sequence of data words in the second network packet, each data word in the first and second network packets including a same number of the data units, wherein the scanning through the first plurality of data units in the first sequence of data words is suspended throughout each insertion action of the modification actions, and the scanning through the second plurality of data units in the second sequence of data words is suspended throughout each removal action of the modification actions; generating a respective one of a plurality of states of a state machine of the circuit for each pairing, which is encountered during the concurrently scanning, of a first data word from the first sequence and a second data word from the second sequence, the respective state for selecting the data units of the second data word from the data segment of each insertion action of the at least one modification action and the data units of both the first data word and a prior data word to the first data word in the first sequence; generating a look-ahead stage, an operation stage coupled to the look-ahead stage, an insert/remove stage that includes the state machine and is coupled to the operation stage, and an interleave stage that is coupled to the insert/remove stage; and outputting a specification of the state machine, the look-ahead stage, the operation stage, the insert/remove stage, and the interleave stage in a hardware description language. | 7. A processor-implemented method for generating a circuit for converting a first network packet into a second network packet, the processor-implemented method comprising: inputting a textual language specification that includes a plurality of modification actions, each modification action being one of an insertion action for inserting a data segment into the first network packet and a removal action for removing a data segment from the first network packet; concurrently scanning through a first plurality of data units in a first sequence of data words in the first network packet and a second plurality of data units in a second sequence of data words in the second network packet, each data word in the first and second network packets including a same number of the data units, wherein the scanning through the first plurality of data units in the first sequence of data words is suspended throughout each insertion action of the modification actions, and the scanning through the second plurality of data units in the second sequence of data words is suspended throughout each removal action of the modification actions; generating a respective one of a plurality of states of a state machine of the circuit for each pairing, which is encountered during the concurrently scanning, of a first data word from the first sequence and a second data word from the second sequence, the respective state for selecting the data units of the second data word from the data segment of each insertion action of the at least one modification action and the data units of both the first data word and a prior data word to the first data word in the first sequence; generating a look-ahead stage, an operation stage coupled to the look-ahead stage, an insert/remove stage that includes the state machine and is coupled to the operation stage, and an interleave stage that is coupled to the insert/remove stage; and outputting a specification of the state machine, the look-ahead stage, the operation stage, the insert/remove stage, and the interleave stage in a hardware description language. 17. The processor-implemented method of claim 7 , further comprising tracking each guard condition of the modification actions during the concurrently scanning through the first plurality of data units in the first sequence of data words and the second plurality of data units in the second sequence of data words, the tracking of the guard condition including determining the guard condition cannot enable the modification action that includes the guard condition in response to the guard condition of another modification action already being one of enabled and disabled. | 0.500871 |
8,683,220 | 8 | 11 | 8. Logic encoded in one or more non-transitory media that includes code for execution and when executed by one or more processors is operable to perform operations comprising: detecting database activity by a database activity monitor (DAM) that is collocated with a database server for which it performs monitoring, wherein the database activity includes an attempt to execute a statement in a script, and wherein the statement includes a plurality of instructions for executing the database activity; validating a signature by parsing the statement to determine whether the statement includes the signature, wherein an association is generated between the signature and the statement in order to distinguish authorized database activity from unauthorized database activity, and wherein different rules are defined for handling the authorized database activity and the unauthorized database activity; and evaluating the statement as a signed statement if the signature is valid, wherein the signed statement is indicative of a planned, preapproved database activity that has been authorized. | 8. Logic encoded in one or more non-transitory media that includes code for execution and when executed by one or more processors is operable to perform operations comprising: detecting database activity by a database activity monitor (DAM) that is collocated with a database server for which it performs monitoring, wherein the database activity includes an attempt to execute a statement in a script, and wherein the statement includes a plurality of instructions for executing the database activity; validating a signature by parsing the statement to determine whether the statement includes the signature, wherein an association is generated between the signature and the statement in order to distinguish authorized database activity from unauthorized database activity, and wherein different rules are defined for handling the authorized database activity and the unauthorized database activity; and evaluating the statement as a signed statement if the signature is valid, wherein the signed statement is indicative of a planned, preapproved database activity that has been authorized. 11. The encoded logic of claim 8 , wherein the signature is embedded in a comment portion of the statement. | 0.844928 |
8,416,454 | 1 | 8 | 1. A computer implemented method of producing personalized documents comprising: inputting handwritten alphanumeric characters; using the computer to map the inputted characters into at least one set of text characters, wherein the mapping is done by converting the inputted alphanumeric characters into mathematical functions approximating a shape of each inputted alphanumeric character; entering a textural document into the computer; transcribing the textural document into a set of text characters corresponding to the inputted alphanumeric characters; and printing the transcribed textural document. | 1. A computer implemented method of producing personalized documents comprising: inputting handwritten alphanumeric characters; using the computer to map the inputted characters into at least one set of text characters, wherein the mapping is done by converting the inputted alphanumeric characters into mathematical functions approximating a shape of each inputted alphanumeric character; entering a textural document into the computer; transcribing the textural document into a set of text characters corresponding to the inputted alphanumeric characters; and printing the transcribed textural document. 8. The method of claim 1 , wherein the mathematical function is selected from the group consisting of a Taylor Series and a McLauren Series or a piecewise continuous Taylor Series and a piecewise continuous McLauren Series. | 0.566148 |
9,152,716 | 1 | 4 | 1. A method comprising, by a crawler application running on a computing device connected to a network, the method comprising: crawling through a distributed collection of data sets available on the network, at least one data set of the distributed collection being published by an entity distinct and under separate control from the crawler, to generate a search structure indexing a plurality of searchable data items found within the distributed collection of data sets, the search structure establishing a correspondence between each searchable data item and particular data sets that contain that searchable data item; generating an authenticated search structure, the authenticated search structure including the search structure and a set of item witnesses using an authentication primitive associated with a set of security parameters, each item witness associated with a particular searchable data item and serving to cryptographically verify which data sets of the distributed collection of data sets correspond to that searchable data item as indicated by the search structure; building a digest of the distributed collection of data sets using the authenticated search structure; signing the digest to produce a digest signature; sending the authenticated search structure and the digest to a search server; and publishing the digest signature and the set of security parameters for access by client devices to allow client devices to authenticate results of searches for particular searchable data items performed by the search server over the distributed collection of data sets; wherein: the crawler application is a web crawler; the data sets are hyperlinked web pages; the searchable data items are searchable terms that appear within the distributed collection of hyperlinked web pages; the item witnesses are term witnesses, each term witness serving to cryptographically verify that a particular sub-collection of the distributed collection of hyperlinked web pages all contain a searchable term associated with that term witness; building the digest of the distributed collection of data sets includes building a Merkle hash tree over the set of term witnesses, the Merkle hash tree having a root node; signing the digest to produce the digest signature includes signing the root node of the Merkle hash tree; the set of security parameters includes: a prime integer order, p; a generator element, g; a first cyclic multiplicative group, G, of order, p, G being generated by g; a second cyclic multiplicative group, G′, of order, p; and a non-degenerate bilinear pairing, e, e mapping G×G→G′; generating the term witnesses includes, using a secret key, s, sεZ p *, for each searchable term, calculating the associated term witness by raising g to the power of a product of multiplicands, each multiplicand being an injective function of s and an identifier of a hyperlinked web page corresponding to that searchable term, for each hyperlinked web page corresponding to that searchable term; the particular hyperlinked web pages that contain each searchable term define a term set for that searchable term, that term set having n elements, t i , for i=1 through i=n; calculating the associated term witness for each searchable term by raising g to the power of the product of multiplicands includes raising g to the power of Π i=1 i=n (s+t i ); the method further comprises, by the web crawler: for all integers, x, from 1 to a maximum size, m, of the term set for any searchable term, computing a set of generator powers, {g^(s x )}, the set of generator powers having m elements; and publishing the set of generator powers for access by client devices; and the method further comprises, by the search server: receiving a conjunctive term web search request from a client device, the conjunctive term web search request including a plurality of search terms; in response to receiving the request, generating a set of search results by performing a set intersection operation between the term sets for each search term of the conjunctive term web search request; for each search term: generating a Merkle proof for the term witness associated with that search term, the Merkle proof including sibling node values along a path within the Merkle hash tree from a leaf corresponding to that term witness to the root node; and generating a subset witness for that search term with reference to a complementary term set associated with that search term, the complementary term set associated with that search term having p elements, t′ j , for j=1 through j=p, such that that complementary term set is the relative complement of the set of search results in the term set defined by that search term, the subset witness equal to g raised to the power of ∏ j = 1 j = p ( s + t j ′ ) , the subset witness being calculated by expanding a mathematical representation of ∏ j = 1 j = p ( s + t j ′ ) , into a set of polynomial terms of powers of s, calculating a value of g raised to the power of each polynomial term of the set of polynomial terms of powers of s with reference to the set of generator powers, and multiplying the calculated values together; generating, using an extended Euclidian algorithm, a set of completeness witnesses, each completeness witness of the set of completeness witnesses having a greatest common divisor of 1 with the subset witnesses for all of the search terms; and sending the set of search results, the term witness associated with each search term, the Merkle proof for each search term, the subset witness for each search term, and the set of completeness witnesses to the client device in response to the received conjunctive term web search request. | 1. A method comprising, by a crawler application running on a computing device connected to a network, the method comprising: crawling through a distributed collection of data sets available on the network, at least one data set of the distributed collection being published by an entity distinct and under separate control from the crawler, to generate a search structure indexing a plurality of searchable data items found within the distributed collection of data sets, the search structure establishing a correspondence between each searchable data item and particular data sets that contain that searchable data item; generating an authenticated search structure, the authenticated search structure including the search structure and a set of item witnesses using an authentication primitive associated with a set of security parameters, each item witness associated with a particular searchable data item and serving to cryptographically verify which data sets of the distributed collection of data sets correspond to that searchable data item as indicated by the search structure; building a digest of the distributed collection of data sets using the authenticated search structure; signing the digest to produce a digest signature; sending the authenticated search structure and the digest to a search server; and publishing the digest signature and the set of security parameters for access by client devices to allow client devices to authenticate results of searches for particular searchable data items performed by the search server over the distributed collection of data sets; wherein: the crawler application is a web crawler; the data sets are hyperlinked web pages; the searchable data items are searchable terms that appear within the distributed collection of hyperlinked web pages; the item witnesses are term witnesses, each term witness serving to cryptographically verify that a particular sub-collection of the distributed collection of hyperlinked web pages all contain a searchable term associated with that term witness; building the digest of the distributed collection of data sets includes building a Merkle hash tree over the set of term witnesses, the Merkle hash tree having a root node; signing the digest to produce the digest signature includes signing the root node of the Merkle hash tree; the set of security parameters includes: a prime integer order, p; a generator element, g; a first cyclic multiplicative group, G, of order, p, G being generated by g; a second cyclic multiplicative group, G′, of order, p; and a non-degenerate bilinear pairing, e, e mapping G×G→G′; generating the term witnesses includes, using a secret key, s, sεZ p *, for each searchable term, calculating the associated term witness by raising g to the power of a product of multiplicands, each multiplicand being an injective function of s and an identifier of a hyperlinked web page corresponding to that searchable term, for each hyperlinked web page corresponding to that searchable term; the particular hyperlinked web pages that contain each searchable term define a term set for that searchable term, that term set having n elements, t i , for i=1 through i=n; calculating the associated term witness for each searchable term by raising g to the power of the product of multiplicands includes raising g to the power of Π i=1 i=n (s+t i ); the method further comprises, by the web crawler: for all integers, x, from 1 to a maximum size, m, of the term set for any searchable term, computing a set of generator powers, {g^(s x )}, the set of generator powers having m elements; and publishing the set of generator powers for access by client devices; and the method further comprises, by the search server: receiving a conjunctive term web search request from a client device, the conjunctive term web search request including a plurality of search terms; in response to receiving the request, generating a set of search results by performing a set intersection operation between the term sets for each search term of the conjunctive term web search request; for each search term: generating a Merkle proof for the term witness associated with that search term, the Merkle proof including sibling node values along a path within the Merkle hash tree from a leaf corresponding to that term witness to the root node; and generating a subset witness for that search term with reference to a complementary term set associated with that search term, the complementary term set associated with that search term having p elements, t′ j , for j=1 through j=p, such that that complementary term set is the relative complement of the set of search results in the term set defined by that search term, the subset witness equal to g raised to the power of ∏ j = 1 j = p ( s + t j ′ ) , the subset witness being calculated by expanding a mathematical representation of ∏ j = 1 j = p ( s + t j ′ ) , into a set of polynomial terms of powers of s, calculating a value of g raised to the power of each polynomial term of the set of polynomial terms of powers of s with reference to the set of generator powers, and multiplying the calculated values together; generating, using an extended Euclidian algorithm, a set of completeness witnesses, each completeness witness of the set of completeness witnesses having a greatest common divisor of 1 with the subset witnesses for all of the search terms; and sending the set of search results, the term witness associated with each search term, the Merkle proof for each search term, the subset witness for each search term, and the set of completeness witnesses to the client device in response to the received conjunctive term web search request. 4. The method of claim 1 , wherein the method further comprises, by the client device: (a) sending the conjunctive term web search request to the search server; (b) receiving the set of search results, the term witness associated with each search term, the Merkle proof for each search term, the subset witness for each search term, and the set of completeness witnesses from the search server in response to the received conjunctive term web search request; (c) verifying, for each search term, that its associated term witness and Merkle proof are consistent with the published tree signature; (d) verifying, with reference to the published set of security parameters and the published set of generator powers, for each search term, with reference to the term witness associated with that search term and the subset witness for that search term, that the set of search results is a subset of the term set for that term; (e) verifying, with reference to the published set of security parameters, the subset witness for all of the search terms, and the completeness witness for all of the search terms, that an intersection of the complementary term sets for all of the search terms is null; and (f) in response to verifying (c), (d), and (e), validating that the set of search results is complete and correct. | 0.605422 |
8,972,390 | 1 | 10 | 1. A method of identifying web pages of a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a list of inquiries based on the plurality of web pages; providing, by the system server, the list of inquiries to at least one first author of the first file; receiving from the at least one first author at least one response to the list of inquiries; selecting a subset of the plurality of web pages based on the at least one response; storing information related to the selected subset of the plurality of web pages for access if the first file is selected; generating, by the system server, a second list of inquiries based on the plurality of web pages; providing, by the system server, the second list of inquiries to at least one second author of the plurality of web pages; receiving from the at least one second author of the plurality of web pages at least one second response to the second list of inquiries; re-selecting the subset of the plurality of web pages based on the at least one response and the at least one second response; and storing information related to the re-selected subset of the plurality of web pages for access if the first file is selected; providing, by the system server, the re-selected subset of the plurality of web pages or the selected subset of the plurality of web pages to a user that selects the first file; and identifying the at least one second author or the at least one first author to the user. | 1. A method of identifying web pages of a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a list of inquiries based on the plurality of web pages; providing, by the system server, the list of inquiries to at least one first author of the first file; receiving from the at least one first author at least one response to the list of inquiries; selecting a subset of the plurality of web pages based on the at least one response; storing information related to the selected subset of the plurality of web pages for access if the first file is selected; generating, by the system server, a second list of inquiries based on the plurality of web pages; providing, by the system server, the second list of inquiries to at least one second author of the plurality of web pages; receiving from the at least one second author of the plurality of web pages at least one second response to the second list of inquiries; re-selecting the subset of the plurality of web pages based on the at least one response and the at least one second response; and storing information related to the re-selected subset of the plurality of web pages for access if the first file is selected; providing, by the system server, the re-selected subset of the plurality of web pages or the selected subset of the plurality of web pages to a user that selects the first file; and identifying the at least one second author or the at least one first author to the user. 10. The method of claim 1 , wherein the list of inquiries includes a relationship tag between at least one of the plurality of web pages and the first file. | 0.831533 |
9,819,633 | 1 | 4 | 1. A method of categorizing messages, comprising: receiving, by a first server from a second server maintaining a plurality of social media messages, a message, the first server configured to categorize the message under a first category or a second category; removing, by the first server, from the message, one or more words that match a predetermined set of stop words; replacing, by the first server, one or more character strings included in the message that are associated with stem words with the corresponding stem word; determining a frequency of each of the words included in the modified message; determining, using a probabilistic engine executing on the first server, a relevancy score of the modified message indicating a level of relevance between the message and the first category based on the determined frequency of each of the words, the probabilistic engine using training data including a first list of messages including a predetermined number of messages previously categorized under the first category and a second list of messages previously categorized under the second category, the second list of messages including the same predetermined number of messages as the first list of messages, the messages in the first list of messages or the messages in the second list of messages including one or more of the stem words; and responsive to determining that the relevancy score satisfies a threshold, categorizing the message under the first category. | 1. A method of categorizing messages, comprising: receiving, by a first server from a second server maintaining a plurality of social media messages, a message, the first server configured to categorize the message under a first category or a second category; removing, by the first server, from the message, one or more words that match a predetermined set of stop words; replacing, by the first server, one or more character strings included in the message that are associated with stem words with the corresponding stem word; determining a frequency of each of the words included in the modified message; determining, using a probabilistic engine executing on the first server, a relevancy score of the modified message indicating a level of relevance between the message and the first category based on the determined frequency of each of the words, the probabilistic engine using training data including a first list of messages including a predetermined number of messages previously categorized under the first category and a second list of messages previously categorized under the second category, the second list of messages including the same predetermined number of messages as the first list of messages, the messages in the first list of messages or the messages in the second list of messages including one or more of the stem words; and responsive to determining that the relevancy score satisfies a threshold, categorizing the message under the first category. 4. The method of claim 1 , wherein each message included in the first list of messages are selected responsive to determining that the message is relevant to one or more keywords. | 0.898295 |
8,271,631 | 1 | 3 | 1. A system for dynamically assigning people to activity-centric communication groups, comprising: a memory; and a processor, operatively coupled to the memory, the processor executing computer executable instructions to effect the following: a communication group manager that routes communications to members of groups and that receives context data associated with a communicating party, the context data indicating one or more activities with which the communicating party is associated; and a communication group establisher that dynamically establishes a group of communicating parties based, at least in part, on the context data when the context data indicates that a set of communicating parties meeting dynamic assignment criteria exceeds a configurable threshold, the group relating to an activity and comprising communicating parties, each of which is indicated by the context data to be associated with the activity, wherein the communication group manager routes communications to communicating parties of the dynamically established group, and wherein the dynamic assignment criteria comprises at least communication with the communicating party occurring within a specified period of time. | 1. A system for dynamically assigning people to activity-centric communication groups, comprising: a memory; and a processor, operatively coupled to the memory, the processor executing computer executable instructions to effect the following: a communication group manager that routes communications to members of groups and that receives context data associated with a communicating party, the context data indicating one or more activities with which the communicating party is associated; and a communication group establisher that dynamically establishes a group of communicating parties based, at least in part, on the context data when the context data indicates that a set of communicating parties meeting dynamic assignment criteria exceeds a configurable threshold, the group relating to an activity and comprising communicating parties, each of which is indicated by the context data to be associated with the activity, wherein the communication group manager routes communications to communicating parties of the dynamically established group, and wherein the dynamic assignment criteria comprises at least communication with the communicating party occurring within a specified period of time. 3. The system of claim 1 , further comprising a communication group modifier that dynamically modifies the group of communicating parties based, at least in part, on the context data, wherein the dynamic modification of the group is the result of satisfying dynamic assignment criteria. | 0.501742 |
8,718,623 | 1 | 2 | 1. A computing system for retrieving user activity data from a mobile device, the system comprising: a component configured to store user activity data on the mobile device, wherein the user activity data represents a record of multiple user interactions with an application or service of the mobile device; a component configured to receive from a user of the mobile device an indication to initiate transfer of the stored user activity data to a remote entity; a component configured to generate a usage code representing the stored user activity data, wherein the usage code contains an identifier that specifies a format of the usage code; a component configured to, in response to the received indication to initiate transfer, populate a communication message with the generated usage code; and a component configured to transmit the populated communication message from the mobile device to the remote entity via a mobile device communication protocol. | 1. A computing system for retrieving user activity data from a mobile device, the system comprising: a component configured to store user activity data on the mobile device, wherein the user activity data represents a record of multiple user interactions with an application or service of the mobile device; a component configured to receive from a user of the mobile device an indication to initiate transfer of the stored user activity data to a remote entity; a component configured to generate a usage code representing the stored user activity data, wherein the usage code contains an identifier that specifies a format of the usage code; a component configured to, in response to the received indication to initiate transfer, populate a communication message with the generated usage code; and a component configured to transmit the populated communication message from the mobile device to the remote entity via a mobile device communication protocol. 2. The system of claim 1 wherein the user activity data comprises data that can be analyzed to assess usability of the mobile device or of the application or service of the mobile device. | 0.821224 |
8,423,952 | 2 | 3 | 2. The method according to claim 1 , wherein each process goal is formed by at least a process object and a state of said model element. | 2. The method according to claim 1 , wherein each process goal is formed by at least a process object and a state of said model element. 3. The method according to claim 2 , wherein each decoupled process goal comprises a structure having an identifier for the decoupled process goal, a process object, a state of said process object, and a set of constraints indicating a precondition with reference to said process object and said state. | 0.922643 |
8,209,162 | 1 | 7 | 1. A method of translation, comprising: uploading a source text portion to be translated to a back end processor that identifies a subset of translation knowledge specifically associated with the uploaded source text portion and downloading the subset; and running a translation engine on a processor other than the back end processor to generate a translation of the source text portion as a function of the subset, wherein uploading the source text portion to the back end processor, which identifies the subset of translation knowledge specifically associated with the source text portion, is carried out prior to any attempt to translate the source text portion on the processor other than the back end processor, and wherein the back end processor splits the source text portion into minimal independent translation segments, and wherein the back end processor identifies, for each minimal independent translation segment of the minimal independent translation segments, a corresponding knowledge segment, and wherein the back end processor assembles the identified knowledge segments corresponding to respective ones of the minimal independent translation segments to form the subset of translation knowledge. | 1. A method of translation, comprising: uploading a source text portion to be translated to a back end processor that identifies a subset of translation knowledge specifically associated with the uploaded source text portion and downloading the subset; and running a translation engine on a processor other than the back end processor to generate a translation of the source text portion as a function of the subset, wherein uploading the source text portion to the back end processor, which identifies the subset of translation knowledge specifically associated with the source text portion, is carried out prior to any attempt to translate the source text portion on the processor other than the back end processor, and wherein the back end processor splits the source text portion into minimal independent translation segments, and wherein the back end processor identifies, for each minimal independent translation segment of the minimal independent translation segments, a corresponding knowledge segment, and wherein the back end processor assembles the identified knowledge segments corresponding to respective ones of the minimal independent translation segments to form the subset of translation knowledge. 7. The method of claim 1 further comprising: dividing a source text into multiple source text portions and providing the multiple source text portions to the back end processor. | 0.85151 |
9,501,592 | 1 | 2 | 1. A computer implemented method for implementing analog behavioral modeling and IP (intellectual property) integration using a Hardware Description Language, comprising: determining or identifying, with a nettype and resolution function management module at least partially stored in memory and configured to include or function in conjunction with at least one processor or at least one processor core, a set of built-in nettypes including at least one wire-real nettype in a SystemVerilog modeling environment; defining a discipline with a domain type of a domain as a native capability of the SystemVerilog modeling environment at least by binding one or more attributes of the domain; characterizing at least one real-valued net of one or more real-valued nets with the discipline associated with the at least one real-valued net and one or more characteristics of the discipline; determining or identifying a plurality of resolution functions for the set of built-in nettypes natively in the SystemVerilog modeling-environment, the plurality of resolution functions including at least one built-in resolution function and at least one modified resolution function modified from a built-in resolution function; porting an analog or a mixed-signal portion including at least the at least one real-valued net of the one or more real-valued nets and information about the domain and the discipline into an electronic design in the SystemVerilog modeling environment by using at least native real modeling capabilities of the SystemVerilog modeling environment without recreating details of the analog or mixed-signal portion; and reducing computational resource utilization at least by elaborating the electronic design into an elaborated electronic design and by performing multiple verification or simulation tasks, at a simulation or verification module residing on one computing node and receiving the electronic design from a separate computing node, for the elaborated electronic design with the set of native real modeling capabilities of the SystemVerilog modeling environment. | 1. A computer implemented method for implementing analog behavioral modeling and IP (intellectual property) integration using a Hardware Description Language, comprising: determining or identifying, with a nettype and resolution function management module at least partially stored in memory and configured to include or function in conjunction with at least one processor or at least one processor core, a set of built-in nettypes including at least one wire-real nettype in a SystemVerilog modeling environment; defining a discipline with a domain type of a domain as a native capability of the SystemVerilog modeling environment at least by binding one or more attributes of the domain; characterizing at least one real-valued net of one or more real-valued nets with the discipline associated with the at least one real-valued net and one or more characteristics of the discipline; determining or identifying a plurality of resolution functions for the set of built-in nettypes natively in the SystemVerilog modeling-environment, the plurality of resolution functions including at least one built-in resolution function and at least one modified resolution function modified from a built-in resolution function; porting an analog or a mixed-signal portion including at least the at least one real-valued net of the one or more real-valued nets and information about the domain and the discipline into an electronic design in the SystemVerilog modeling environment by using at least native real modeling capabilities of the SystemVerilog modeling environment without recreating details of the analog or mixed-signal portion; and reducing computational resource utilization at least by elaborating the electronic design into an elaborated electronic design and by performing multiple verification or simulation tasks, at a simulation or verification module residing on one computing node and receiving the electronic design from a separate computing node, for the elaborated electronic design with the set of native real modeling capabilities of the SystemVerilog modeling environment. 2. The computer implemented method of claim 1 , the process further comprising: determining a mapping between the plurality of resolution functions and the set of built-in nettypes; resolving multiple real-valued drivers that drive a receiver in the SystemVerilog modeling-environment based at least in part upon the mapping; creating or defining a wreal to be a discrete signal having four states natively in the SystemVerilog modeling environment, wherein the wreal is used to model an analog signal in the SystemVerilog modeling environment; and associating a resolution function of the plurality of resolution functions with the wreal. | 0.758321 |
9,769,107 | 21 | 29 | 21. At least one non-transitory storage device storing instructions operable to cause one or more computing devices to perform operations comprising: receiving, from a first user device, activity information on an activity performed by a user of the first user device; receiving, from the first user device, a location where the first user device has stayed for at least a threshold amount of time; determining a type of the activity; creating a social group based on the location and the type of the activity, including determining a theme of the social group based on the type of the activity; determining that a first condition that a second user device is located at the location or will visit the location is satisfied; determining that a second condition that the second user device seeks information related to the location or related to the theme of the social group is satisfied; and in response to determining that the first and second conditions are satisfied, providing a recommendation to join the social group to the second user device. | 21. At least one non-transitory storage device storing instructions operable to cause one or more computing devices to perform operations comprising: receiving, from a first user device, activity information on an activity performed by a user of the first user device; receiving, from the first user device, a location where the first user device has stayed for at least a threshold amount of time; determining a type of the activity; creating a social group based on the location and the type of the activity, including determining a theme of the social group based on the type of the activity; determining that a first condition that a second user device is located at the location or will visit the location is satisfied; determining that a second condition that the second user device seeks information related to the location or related to the theme of the social group is satisfied; and in response to determining that the first and second conditions are satisfied, providing a recommendation to join the social group to the second user device. 29. The non-transitory storage device of claim 21 , the operations comprising providing a count of user devices that are located at the location and that have joined the social group as a membership count to be associated with the recommendation. | 0.805994 |
8,738,381 | 1 | 14 | 1. A prosody generation apparatus that receives phonological information and linguistic information so as to generate prosody, the prosody generation apparatus being operable to refer to (a) a representative prosodic pattern storage unit for accumulating beforehand representative prosodic patterns of portions of speech data, the portions including prosody changing points; (b) a selection rule storage unit that stores a selection rule predetermined according to attributes concerning phonology or attributes concerning linguistic information of the portions of the speech data including the prosody changing points; and (c) a transformation rule storage unit that stores a transformation rule predetermined according to attributes concerning the phonology or the linguistic information of the portions of the speech data including the prosody changing points; the prosody generation apparatus comprising a computer processing unit and a memory storing a program that are configured to implement: a prosody changing point setting unit that sets a prosody changing point according to at least any one of the received phonological information and the linguistic information; a pattern selection unit that selects a representative prosodic pattern from the representative prosodic pattern storage unit according to the selection rule, based on the received phonological information and the linguistic information; and a prosody generation unit that transforms the representative prosodic pattern selected by the pattern selection unit according to the transformation rule and interpolates the transformed prosodic pattern for a portion between the prosodic patterns corresponding to the prosody changing points, wherein assuming that a difference in pitch between adjacent moras or adjacent syllables of the speech data is ΔP, the prosody changing point is a point where the ΔP and an immediately following ΔP are different in sign. | 1. A prosody generation apparatus that receives phonological information and linguistic information so as to generate prosody, the prosody generation apparatus being operable to refer to (a) a representative prosodic pattern storage unit for accumulating beforehand representative prosodic patterns of portions of speech data, the portions including prosody changing points; (b) a selection rule storage unit that stores a selection rule predetermined according to attributes concerning phonology or attributes concerning linguistic information of the portions of the speech data including the prosody changing points; and (c) a transformation rule storage unit that stores a transformation rule predetermined according to attributes concerning the phonology or the linguistic information of the portions of the speech data including the prosody changing points; the prosody generation apparatus comprising a computer processing unit and a memory storing a program that are configured to implement: a prosody changing point setting unit that sets a prosody changing point according to at least any one of the received phonological information and the linguistic information; a pattern selection unit that selects a representative prosodic pattern from the representative prosodic pattern storage unit according to the selection rule, based on the received phonological information and the linguistic information; and a prosody generation unit that transforms the representative prosodic pattern selected by the pattern selection unit according to the transformation rule and interpolates the transformed prosodic pattern for a portion between the prosodic patterns corresponding to the prosody changing points, wherein assuming that a difference in pitch between adjacent moras or adjacent syllables of the speech data is ΔP, the prosody changing point is a point where the ΔP and an immediately following ΔP are different in sign. 14. The prosody generation apparatus according to claim 1 , wherein the transformation is a parallel shifting along a power axis of a power pattern. | 0.947961 |
9,704,128 | 1 | 3 | 1. A computer-implemented method for synthesizing and analyzing user input in a collaborative work session, the method comprising: monitoring a plurality of inputs submitted by a group of users in the collaborative work session, wherein at least some of the plurality of inputs include natural language content; algorithmically analyzing the natural language content in real time in order to parse a plurality of ideas from the plurality of inputs; algorithmically identifying similarities among the plurality of ideas; clustering the plurality of ideas into a set of clusters based on the similarities; and presenting the clusters to the group of users during the collaborative work session, wherein the algorithmically analyzing, the algorithmically identifying, and the clustering are each performed at least in part using a processor, and wherein at least one user of the group of users is a synthetic participant that is independent from a moderator for the collaborative work session. | 1. A computer-implemented method for synthesizing and analyzing user input in a collaborative work session, the method comprising: monitoring a plurality of inputs submitted by a group of users in the collaborative work session, wherein at least some of the plurality of inputs include natural language content; algorithmically analyzing the natural language content in real time in order to parse a plurality of ideas from the plurality of inputs; algorithmically identifying similarities among the plurality of ideas; clustering the plurality of ideas into a set of clusters based on the similarities; and presenting the clusters to the group of users during the collaborative work session, wherein the algorithmically analyzing, the algorithmically identifying, and the clustering are each performed at least in part using a processor, and wherein at least one user of the group of users is a synthetic participant that is independent from a moderator for the collaborative work session. 3. The computer-implemented method of claim 1 , wherein the algorithmically analyzing and the algorithmically identifying are performed by the moderator who is a synthetic, non-human moderator. | 0.524631 |
9,269,028 | 14 | 19 | 14. A string similarity assessment system, comprising: a memory storing instructions that, when executed, are configured to: receive a plurality of input strings comprising characters from a character set; generate hashtables for each respective input string using a hash function that assigns the characters as keys and character positions in the strings as values; determine a character similarity index for at least two of the input strings relative to each other by comparing a similarity of the values for each key in the their respective hashtables; determining a total disordering index based representative of an alignment of the at least two input strings by determining differences between a plurality of index values for each individual key in their respective hashtables and determining the total disordering index based on the differences; and determining a string similarity metric based on at least one character similarity index and the total disordering index; and one or more processors configured to execute the instructions. | 14. A string similarity assessment system, comprising: a memory storing instructions that, when executed, are configured to: receive a plurality of input strings comprising characters from a character set; generate hashtables for each respective input string using a hash function that assigns the characters as keys and character positions in the strings as values; determine a character similarity index for at least two of the input strings relative to each other by comparing a similarity of the values for each key in the their respective hashtables; determining a total disordering index based representative of an alignment of the at least two input strings by determining differences between a plurality of index values for each individual key in their respective hashtables and determining the total disordering index based on the differences; and determining a string similarity metric based on at least one character similarity index and the total disordering index; and one or more processors configured to execute the instructions. 19. The system of claim 14 , wherein the string similarity metric is determined by the following equation: 1 - ( m 2 2 + 1 - o m 2 2 + 1 * m - s AB m ) where m is a length of the longer string of the at least two strings, where o is the total disordering index, and wherein s AB is a greater of the character similarity indices for at least two of the input strings. | 0.619919 |
8,645,418 | 10 | 14 | 10. An apparatus for word mining and evaluating, comprising: one or more processors; a memory; and one or more program units stored in the memory and to be executed by the one or more processors, the one or more program units comprising; a DF calculating unit, configured to calculate a DF of a word in mass categorized data; a single-aspect evaluating unit, configured to evaluate the word in multiple single-aspects according to the DF of the word; a multiple-aspect evaluating unit, configured to evaluate the word in a multiple-aspect according to the multiple single-aspect evaluations to obtain an importance weight of the word, wherein the multiple-aspect evaluating unit comprises: a level dividing module, configured to configure levels according to DFs of candidate words, wherein the levels comprises a SuperHigh level, a MidHigh level, a MidLow level and a SuperLow level; and a multiple-aspect evaluating module, configured to evaluate the word in the multiple-aspect according to the level of the word to obtain an importance weight of the word in the level, to determine, for each candidate word in the SuperHigh level, the MidHigh level or the MidLow level, the importance weight of the candidate word according to: an absolute value of a difference between an average inverse document frequency (AVAIDF) and an inverse document frequency (IDF) of the candidate word, a linear combination of mutual information (MI), expect cross entropy (ECE) and entropy (ENT) of the candidate word, a combination of logarithmic normalized chi-square and information gain (IG) of the candidate word, and logarithmic normalized selective preference (SELPRE) of the candidate word; determine, for each candidate word in the SuperLow level, the importance weight of the candidate word according to, an absolute value of a difference between an average inverse document frequency (AVAIDF) and an inverse document frequency (IDF) of the candidate word, a linear combination of mutual information (MI), expect cross entropy (ECE) and entropy (ENT) of the candidate word, and a combination of logarithmic normalized chi-square and information gain (iq) of the candidate word. | 10. An apparatus for word mining and evaluating, comprising: one or more processors; a memory; and one or more program units stored in the memory and to be executed by the one or more processors, the one or more program units comprising; a DF calculating unit, configured to calculate a DF of a word in mass categorized data; a single-aspect evaluating unit, configured to evaluate the word in multiple single-aspects according to the DF of the word; a multiple-aspect evaluating unit, configured to evaluate the word in a multiple-aspect according to the multiple single-aspect evaluations to obtain an importance weight of the word, wherein the multiple-aspect evaluating unit comprises: a level dividing module, configured to configure levels according to DFs of candidate words, wherein the levels comprises a SuperHigh level, a MidHigh level, a MidLow level and a SuperLow level; and a multiple-aspect evaluating module, configured to evaluate the word in the multiple-aspect according to the level of the word to obtain an importance weight of the word in the level, to determine, for each candidate word in the SuperHigh level, the MidHigh level or the MidLow level, the importance weight of the candidate word according to: an absolute value of a difference between an average inverse document frequency (AVAIDF) and an inverse document frequency (IDF) of the candidate word, a linear combination of mutual information (MI), expect cross entropy (ECE) and entropy (ENT) of the candidate word, a combination of logarithmic normalized chi-square and information gain (IG) of the candidate word, and logarithmic normalized selective preference (SELPRE) of the candidate word; determine, for each candidate word in the SuperLow level, the importance weight of the candidate word according to, an absolute value of a difference between an average inverse document frequency (AVAIDF) and an inverse document frequency (IDF) of the candidate word, a linear combination of mutual information (MI), expect cross entropy (ECE) and entropy (ENT) of the candidate word, and a combination of logarithmic normalized chi-square and information gain (iq) of the candidate word. 14. The apparatus of claim 10 , wherein the level dividing module comprises: a level rang dividing module, configured to configure levels according to the DFs of the words in all the categorized data; and a word classifying module, configured to classify the word to a corresponding level according to the DF of the word in all the categorized data. | 0.86303 |
8,407,169 | 72 | 73 | 72. The system according to claim 67 wherein said backward directed reasoning function further comprises: searching for a backward rule to match a first known consequent fact against a rule consequent part node; said backward rule comprising a first set of consequent part nodes, a first set of antecedent part nodes and a first set of context nodes; matching said backward rule consequent part node to said first known consequent fact; then determining a new set of antecedent facts based upon antecedent nodes of an antecedent rule part. | 72. The system according to claim 67 wherein said backward directed reasoning function further comprises: searching for a backward rule to match a first known consequent fact against a rule consequent part node; said backward rule comprising a first set of consequent part nodes, a first set of antecedent part nodes and a first set of context nodes; matching said backward rule consequent part node to said first known consequent fact; then determining a new set of antecedent facts based upon antecedent nodes of an antecedent rule part. 73. The system according to claim 72 wherein said antecedent rule part comprises a disjunction comprising a first set of disjunctive antecedent nodes. | 0.916667 |
8,700,414 | 1 | 19 | 1. In a computer system wherein messages are transferred between participants, at least some of which are human users of the computer system using the computer system in furtherance of work projects, and wherein a workflow system handles task-based operations in a structured environment, the computer system further comprising at least one monitored operations system that generates alerts to notify participants of events within the at least one monitored operations system, a computer implemented method of handling alerts in a structured manner comprising: transmitting by the computer system, to a determined participant, a message comprising a first alert that a particular first event occurred, wherein the first event is determinable from at least one of the state of the computer system, the computer system's data or external data available to the computer system, wherein an alert rule indicates that the determined participant is to be alerted with the message when the particular first event occurs; initiating a logging of event resolution responses by the determined participant in response to the first event to form an event resolution log; storing, by the computer system, the event resolution log for use in informing a future determined participant, via the workflow system, as to a possible event resolution process when the future determined participant encounters a second alert of a second event wherein the second alert is similar to the first alert, the second event is similar to the first event or both, the possible event resolution process depending, at least in part, on the event resolution log for the first event; ending the event resolution log when the determined participant signals to the computer system a resolution of the first event; generating by the computer system a workflow process template from the event resolution log, the workflow process template comprising at least one workflow item; and storing by the computer system the workflow process template in the workflow system in association with a category identifier associated with the first event. | 1. In a computer system wherein messages are transferred between participants, at least some of which are human users of the computer system using the computer system in furtherance of work projects, and wherein a workflow system handles task-based operations in a structured environment, the computer system further comprising at least one monitored operations system that generates alerts to notify participants of events within the at least one monitored operations system, a computer implemented method of handling alerts in a structured manner comprising: transmitting by the computer system, to a determined participant, a message comprising a first alert that a particular first event occurred, wherein the first event is determinable from at least one of the state of the computer system, the computer system's data or external data available to the computer system, wherein an alert rule indicates that the determined participant is to be alerted with the message when the particular first event occurs; initiating a logging of event resolution responses by the determined participant in response to the first event to form an event resolution log; storing, by the computer system, the event resolution log for use in informing a future determined participant, via the workflow system, as to a possible event resolution process when the future determined participant encounters a second alert of a second event wherein the second alert is similar to the first alert, the second event is similar to the first event or both, the possible event resolution process depending, at least in part, on the event resolution log for the first event; ending the event resolution log when the determined participant signals to the computer system a resolution of the first event; generating by the computer system a workflow process template from the event resolution log, the workflow process template comprising at least one workflow item; and storing by the computer system the workflow process template in the workflow system in association with a category identifier associated with the first event. 19. The method of claim 1 , further comprising: recording, by the computer system, objects and transactions that were involved when recording steps that a user took to respond to the message. | 0.875974 |
10,108,702 | 9 | 12 | 9. The system of claim 8 , wherein the processor executes the program instructions stored on the computer-readable storage medium via the computer readable memory and thereby further: generates a response to the second spoken query that satisfies: the initial topic, in response to determining that the second spoken query is directed to the initial topic; the new topic, in response to determining that the second spoken query is directed to the new topic and is independent of the initial topic; and the initial topic and the new topic, in response to determining that the second spoken query is directed to the new topic within a context of the initial topic. | 9. The system of claim 8 , wherein the processor executes the program instructions stored on the computer-readable storage medium via the computer readable memory and thereby further: generates a response to the second spoken query that satisfies: the initial topic, in response to determining that the second spoken query is directed to the initial topic; the new topic, in response to determining that the second spoken query is directed to the new topic and is independent of the initial topic; and the initial topic and the new topic, in response to determining that the second spoken query is directed to the new topic within a context of the initial topic. 12. The system of claim 9 , wherein the processor executes the program instructions stored on the computer-readable storage medium via the computer readable memory and thereby determines that the second spoken query is directed to the new topic in response to determining that a gaze orientation of the user during the second spoken query is different from an initial gaze orientation during the first spoken query. | 0.899904 |
8,606,815 | 1 | 6 | 1. A computer-implemented method for systematically analyzing an electronic text, comprising: receiving by a computer the electronic text from a plurality of sources; determining an at least one term of interest to be identified in the electronic text; determining an at least one term of interest to be identified in the electronic text; identifying by the computer a plurality of locations within the electronic text including the at least one term of interest; for each location within a plurality of locations, creating by the computer a snippet from a text segment around the at least one term of interest at the location within the electronic text; creating by the computer 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 determining by the computer associations between categories of a different taxonomies of the multiple taxonomies by determining: co-occurrences between the multiple taxonomies; and significance of co-occurrences between the multiple taxonomies, wherein the determining the co-occurrences further comprises: determining co-occurrences between a category of a single taxonomy and the at least one term of interest to determine significance of the at least one term of interest; and sorting the at least one term of interest by significance; and 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, 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. | 1. A computer-implemented method for systematically analyzing an electronic text, comprising: receiving by a computer the electronic text from a plurality of sources; determining an at least one term of interest to be identified in the electronic text; determining an at least one term of interest to be identified in the electronic text; identifying by the computer a plurality of locations within the electronic text including the at least one term of interest; for each location within a plurality of locations, creating by the computer a snippet from a text segment around the at least one term of interest at the location within the electronic text; creating by the computer 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 determining by the computer associations between categories of a different taxonomies of the multiple taxonomies by determining: co-occurrences between the multiple taxonomies; and significance of co-occurrences between the multiple taxonomies, wherein the determining the co-occurrences further comprises: determining co-occurrences between a category of a single taxonomy and the at least one term of interest to determine significance of the at least one term of interest; and sorting the at least one term of interest by significance; and 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, 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. 6. The computer-implemented method of claim 1 , wherein the electronic text is web based. | 0.862229 |
9,734,123 | 18 | 19 | 18. A calculation device comprising: a plurality of entry keys configured to allow a user to enter mathematical expressions, the plurality of entry keys including a fraction entry key to allow a user to enter a fraction having a numerator and a denominator; a display configured to display the mathematical expressions and an editing cursor; a hardware processor, wherein the hardware processor: enables entry and editing of mathematical expressions by the user, determines, when the fraction entry key is pressed, whether to place a position of the editing cursor into the numerator or denominator of the fraction, wherein said determination is based at least in part on one or both of a prior mathematical expression entry and a position of the editing cursor, and configures the display to output the fraction with the editing cursor in the position thus determined. | 18. A calculation device comprising: a plurality of entry keys configured to allow a user to enter mathematical expressions, the plurality of entry keys including a fraction entry key to allow a user to enter a fraction having a numerator and a denominator; a display configured to display the mathematical expressions and an editing cursor; a hardware processor, wherein the hardware processor: enables entry and editing of mathematical expressions by the user, determines, when the fraction entry key is pressed, whether to place a position of the editing cursor into the numerator or denominator of the fraction, wherein said determination is based at least in part on one or both of a prior mathematical expression entry and a position of the editing cursor, and configures the display to output the fraction with the editing cursor in the position thus determined. 19. The calculation device of claim 18 , where when the fraction entry key is pressed and the hardware processor determines to place the position of the editing cursor into the denominator of the fraction, all or part of a previously entered expression is placed into the numerator of the fraction. | 0.667411 |
8,832,541 | 6 | 7 | 6. The method of claim 5 , wherein placement of the textual description embedded within the document is proximate to the at least one visually orientated object. | 6. The method of claim 5 , wherein placement of the textual description embedded within the document is proximate to the at least one visually orientated object. 7. The method of claim 6 , wherein a font size, typographic character attribute, paragraph attribute, page attribute, or any combination thereof, of the textual description is adjusted to minimize an impact to the aesthetics of the document. | 0.882439 |
8,799,799 | 1 | 3 | 1. A computer system comprising: an electronic data structure configured to store a plurality of features or objects as vector data, wherein each of the features or objects is associated with metadata, and each of the features or objects represents at least one of a road, a terrain, a lake, a river, a vegetation, a utility, a street light, a railroad, a hotel, a motel, a school, a hospital, a building or other structure, a region, a transportation object, an entity, an event, or a document; a non-transitory computer readable medium storing software modules including computer executable instructions; and one or more hardware processors in communication with the electronic data structure and the non-transitory computer readable medium, and configured to execute a user interface module of the software modules in order to: display an interactive map on an electronic display of the computer system; include on the interactive map one or more features or objects, wherein the features or objects are selectable by a user of the computer system, and wherein the features or objects are accessed from the electronic data structure; in response to a first input from the user selecting a plurality of the included features or objects: access, from the electronic data structure, metadata associated with respective selected features or objects; determine one or more metadata categories associated with at least one of the accessed metadata; and for each of the determined metadata categories: generate one or more histograms including metadata values or value ranges associated with respective selected features or objects, each of the histograms including a visual indicator indicating a quantity of the respective selected plurality of features or objects included on the interactive map having the respective metadata value or value range; and display the one or more histograms on the electronic display; in response to a second input from the user selecting a second one or more features or objects from the one or more histograms: update the interactive map to display the second one or more features or objects on the display; and highlight the second one or more features or objects on the interactive map; and in response to a third input from the user selecting a drill-down group of features or objects from the one or more histograms, drill-down on the selected drill-down group of features or objects by: accessing metadata associated with respective features or objects of the selected drill-down group; determining one or more drill-down metadata categories associated with at least one of the accessed metadata associated with each of the features or objects of the selected drill-down group; and for each of the determined drill-down metadata categories: generating one or more drill-down histograms including drill-down metadata values or value ranges associated with respective features or objects of the selected drill-down group, each of the drill-down histograms including a visual indicator indicating a quantity of the respective features or objects of the selected drill-down group having the respective drill-down metadata value or value range; and displaying on the interactive map the one or more drill-down histograms. | 1. A computer system comprising: an electronic data structure configured to store a plurality of features or objects as vector data, wherein each of the features or objects is associated with metadata, and each of the features or objects represents at least one of a road, a terrain, a lake, a river, a vegetation, a utility, a street light, a railroad, a hotel, a motel, a school, a hospital, a building or other structure, a region, a transportation object, an entity, an event, or a document; a non-transitory computer readable medium storing software modules including computer executable instructions; and one or more hardware processors in communication with the electronic data structure and the non-transitory computer readable medium, and configured to execute a user interface module of the software modules in order to: display an interactive map on an electronic display of the computer system; include on the interactive map one or more features or objects, wherein the features or objects are selectable by a user of the computer system, and wherein the features or objects are accessed from the electronic data structure; in response to a first input from the user selecting a plurality of the included features or objects: access, from the electronic data structure, metadata associated with respective selected features or objects; determine one or more metadata categories associated with at least one of the accessed metadata; and for each of the determined metadata categories: generate one or more histograms including metadata values or value ranges associated with respective selected features or objects, each of the histograms including a visual indicator indicating a quantity of the respective selected plurality of features or objects included on the interactive map having the respective metadata value or value range; and display the one or more histograms on the electronic display; in response to a second input from the user selecting a second one or more features or objects from the one or more histograms: update the interactive map to display the second one or more features or objects on the display; and highlight the second one or more features or objects on the interactive map; and in response to a third input from the user selecting a drill-down group of features or objects from the one or more histograms, drill-down on the selected drill-down group of features or objects by: accessing metadata associated with respective features or objects of the selected drill-down group; determining one or more drill-down metadata categories associated with at least one of the accessed metadata associated with each of the features or objects of the selected drill-down group; and for each of the determined drill-down metadata categories: generating one or more drill-down histograms including drill-down metadata values or value ranges associated with respective features or objects of the selected drill-down group, each of the drill-down histograms including a visual indicator indicating a quantity of the respective features or objects of the selected drill-down group having the respective drill-down metadata value or value range; and displaying on the interactive map the one or more drill-down histograms. 3. The computer system of claim 1 , wherein the features or objects are selectable by the user using a mouse and/or a touch interface. | 0.862986 |
9,756,149 | 1 | 3 | 1. A non-transitory computer-readable medium having instructions stored thereon that, when executed on a computing device having a machine-specific instruction set, cause the computing device to perform operations comprising: receiving, by the computing device and from a computing system that is remotely located from the computing device, first portable code, the first portable code being a portable version of a first program, wherein the computing device includes multiple sets of application environment components and each set of application environment components includes: (i) a respective translator component for translating portable code into the machine-specific instruction set of the computing device, and (ii) a respective sandboxing component for executing translated programs that have been translated into the machine-specific instruction set of the computing device by one of the translator components, the respective sandboxing component using software-based fault isolation; selecting, based on a set of selection criteria and from among the multiple sets of application environment components, a particular set of application environment components; translating the first portable code into the machine-specific instruction set of the computing device using the respective translator component of the particular set of application environment components to generate a machine-specific version of the first program; and executing the machine-specific version of the first program on the computing device using the respective sandboxing component of the particular set of application environment components. | 1. A non-transitory computer-readable medium having instructions stored thereon that, when executed on a computing device having a machine-specific instruction set, cause the computing device to perform operations comprising: receiving, by the computing device and from a computing system that is remotely located from the computing device, first portable code, the first portable code being a portable version of a first program, wherein the computing device includes multiple sets of application environment components and each set of application environment components includes: (i) a respective translator component for translating portable code into the machine-specific instruction set of the computing device, and (ii) a respective sandboxing component for executing translated programs that have been translated into the machine-specific instruction set of the computing device by one of the translator components, the respective sandboxing component using software-based fault isolation; selecting, based on a set of selection criteria and from among the multiple sets of application environment components, a particular set of application environment components; translating the first portable code into the machine-specific instruction set of the computing device using the respective translator component of the particular set of application environment components to generate a machine-specific version of the first program; and executing the machine-specific version of the first program on the computing device using the respective sandboxing component of the particular set of application environment components. 3. The computer-readable medium of claim 1 , wherein the first portable code comprises bitcode having a neutral, non-machine specific format. | 0.870879 |
8,300,941 | 1 | 2 | 1. A method of determining a regular grid pattern from a surface coded pattern that comprises the regular grid pattern interleaved with a further data carrying pattern wherein the surface coded pattern is subject to perspective distortion, the method comprising: extracting a set of straight line hypotheses from the surface coded pattern by identifying a plurality of surface pattern points that are co-linear to one another, identifying sets of the plurality of surface pattern points that are co-linear to one another, deleting sets of the plurality of surface pattern points that have a cross-ratio value outside a predetermined range, and fitting a line hypothesis to sets of the plurality of surface pattern points that have a cross-ratio value within the predetermined range; clustering the straight line hypotheses by orientation; for each cluster, extracting a set of line pencil hypotheses; generating a set of regular grid hypotheses from pairs of the line pencil hypotheses; and determining, by a processor, a regular grid hypothesis closest to a true regular grid. | 1. A method of determining a regular grid pattern from a surface coded pattern that comprises the regular grid pattern interleaved with a further data carrying pattern wherein the surface coded pattern is subject to perspective distortion, the method comprising: extracting a set of straight line hypotheses from the surface coded pattern by identifying a plurality of surface pattern points that are co-linear to one another, identifying sets of the plurality of surface pattern points that are co-linear to one another, deleting sets of the plurality of surface pattern points that have a cross-ratio value outside a predetermined range, and fitting a line hypothesis to sets of the plurality of surface pattern points that have a cross-ratio value within the predetermined range; clustering the straight line hypotheses by orientation; for each cluster, extracting a set of line pencil hypotheses; generating a set of regular grid hypotheses from pairs of the line pencil hypotheses; and determining, by a processor, a regular grid hypothesis closest to a true regular grid. 2. The method of claim 1 , wherein extracting the set of straight line hypotheses comprises: identifying triples of the surface pattern points in which the surface pattern points are co-linear to one another; identifying sets of the triples that are co-linear to one another; deleting those sets of co-linear triples that have a cross-ratio value outside the range of 0.225 to 0.275; and fitting a line hypothesis to each of the remaining sets of co-linear triples. | 0.704949 |
7,895,275 | 1 | 10 | 1. A computer-implemented method of reviewing and distributing digital content comprising: identifying a plurality of authors of digital content via a registration process wherein the plurality of authors agree to review digital content in exchange for review of their own digital content; receiving a submission from one of the plurality of authors including metadata for digital content to be reviewed where the metadata includes a target quality level for the digital content; and effecting review of the digital content by at least one group of reviewers selected from others of the plurality of authors based on the metadata for the digital content and reviewer credentials for the others of the plurality of authors, wherein effecting review of the digital content includes selecting a group of reviewers from the others of the plurality of authors based on the target quality level and the reviewer credentials of the others of the plurality of authors and feedback is provided to the one of the plurality of authors based on the review. | 1. A computer-implemented method of reviewing and distributing digital content comprising: identifying a plurality of authors of digital content via a registration process wherein the plurality of authors agree to review digital content in exchange for review of their own digital content; receiving a submission from one of the plurality of authors including metadata for digital content to be reviewed where the metadata includes a target quality level for the digital content; and effecting review of the digital content by at least one group of reviewers selected from others of the plurality of authors based on the metadata for the digital content and reviewer credentials for the others of the plurality of authors, wherein effecting review of the digital content includes selecting a group of reviewers from the others of the plurality of authors based on the target quality level and the reviewer credentials of the others of the plurality of authors and feedback is provided to the one of the plurality of authors based on the review. 10. The computer-implemented method of claim 1 wherein the submission further comprises the digital content, and effecting review of the digital content further comprises transferring the digital content to user devices associated with the at least one group of reviewers. | 0.856842 |
6,141,641 | 3 | 4 | 3. The method of claim 2 wherein identifying a plurality of deep senones comprises: identifying a pair of parameters to be merged corresponding to the plurality of deep senones. | 3. The method of claim 2 wherein identifying a plurality of deep senones comprises: identifying a pair of parameters to be merged corresponding to the plurality of deep senones. 4. The method of claim 3 wherein each of the deep senones is represented by a single discrete output distribution and wherein identifying a pair of parameters to be merged comprises: identifying a pair of output distributions to be merged based on an amount of reduction in likelihood of generating a dataset aligned with the pair of output distributions which results from merging the pair of output distributions. | 0.847874 |
9,069,847 | 22 | 23 | 22. The article of claim 19 wherein the initially processing comprises generating a list of the features present in the initial documents, and wherein the subsequently processing includes adding new features to the list which occur in the subsequent documents but do not occur in the initial documents. | 22. The article of claim 19 wherein the initially processing comprises generating a list of the features present in the initial documents, and wherein the subsequently processing includes adding new features to the list which occur in the subsequent documents but do not occur in the initial documents. 23. The article of claim 22 further comprising, after the initially identifying, identifying one of the initial documents as being aged, and further comprising removing one of the features which is present in the one of the initial documents from the list of the features as a result of the identifying the one of the initial documents as being aged. | 0.860335 |
8,412,511 | 1 | 6 | 1. A system for providing a translation of a set of one or more terms or phrases from a source language to more than one target language, the system comprising: (a) a memory adapted to store one or more translations of said set of one or more terms or phrases in said more than one target language; and (b) a processor in communication with said memory and adapted to execute a translation module, wherein said translation module is adapted for execution by said processor to: (1) obtain said one or more translations in said more than one target language for individual terms or phrases of said set of one or more terms or phrases provided by one or more users, wherein said one or more users enter said one or more translations into one or more computer systems, that are in communication with said processor; (2) store said one or more translations for said individual terms or phrases in said memory; (3) store a first particular target language and a second particular target language identified by a user; and (4) in response to receiving a user's request for a preferred translation of each term or phrase in said set of one or more terms or phrases: (i) retrieve said user's first particular target language and said user's second particular target language; (ii) identify said preferred translation for each individual term or phrase of said set of one or more terms or phrases, wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said first particular target language; (iii) in response to a translation not being provided for an individual term or phrase of said set of one or more terms or phrases for said user's first target language, identify said preferred translation for said individual term or phrase wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said second target language; and (iv) cause display said identified preferred translation to said user. | 1. A system for providing a translation of a set of one or more terms or phrases from a source language to more than one target language, the system comprising: (a) a memory adapted to store one or more translations of said set of one or more terms or phrases in said more than one target language; and (b) a processor in communication with said memory and adapted to execute a translation module, wherein said translation module is adapted for execution by said processor to: (1) obtain said one or more translations in said more than one target language for individual terms or phrases of said set of one or more terms or phrases provided by one or more users, wherein said one or more users enter said one or more translations into one or more computer systems, that are in communication with said processor; (2) store said one or more translations for said individual terms or phrases in said memory; (3) store a first particular target language and a second particular target language identified by a user; and (4) in response to receiving a user's request for a preferred translation of each term or phrase in said set of one or more terms or phrases: (i) retrieve said user's first particular target language and said user's second particular target language; (ii) identify said preferred translation for each individual term or phrase of said set of one or more terms or phrases, wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said first particular target language; (iii) in response to a translation not being provided for an individual term or phrase of said set of one or more terms or phrases for said user's first target language, identify said preferred translation for said individual term or phrase wherein said preferred translation for each said individual term or phrase is a translation of said one or more translations most frequently provided by said one or more users for each said individual term or phrase in said second target language; and (iv) cause display said identified preferred translation to said user. 6. The system of claim 1 , wherein said translation module is adapted for execution by said processor to: display a list of target languages to said user; and store said user's selected first and second particular target languages selected by said user from said list of target languages. | 0.665116 |
8,219,566 | 1 | 11 | 1. A system for determining valid citation patterns in text within an electronic document, the system comprising: a processor; and a memory coupled to the processor, the memory storing instructions to direct the processor to perform operations comprising: accessing, from the memory, a citation pattern comprising a set of citation components that define a predetermined pattern, each citation component being associated with a set of citation component criteria, comparing text in the electronic document with the citation components of the predetermined pattern, and determining valid citation patterns by identifying text that corresponds to the set of citation components of the predetermined pattern. | 1. A system for determining valid citation patterns in text within an electronic document, the system comprising: a processor; and a memory coupled to the processor, the memory storing instructions to direct the processor to perform operations comprising: accessing, from the memory, a citation pattern comprising a set of citation components that define a predetermined pattern, each citation component being associated with a set of citation component criteria, comparing text in the electronic document with the citation components of the predetermined pattern, and determining valid citation patterns by identifying text that corresponds to the set of citation components of the predetermined pattern. 11. The system of claim 1 , wherein the operations further comprise: inserting an annotation into the electronic document corresponding to text determined not to correspond to a valid citation pattern, wherein the text includes one or more identified citation components. | 0.733268 |
9,606,967 | 9 | 11 | 9. The method of claim 1 , further comprising further comprising embedding said mark in a new font having a unique name. | 9. The method of claim 1 , further comprising further comprising embedding said mark in a new font having a unique name. 11. The method of claim 9 , further comprising providing said new font at a remote site. | 0.95501 |
9,237,211 | 1 | 20 | 1. An energy harvesting communication device configured with signal booster apparatus, comprising: at least a communication apparatus; at least an antenna apparatus communicatively coupled to the communication apparatus and in association with at least an input output (IO) device; at least a microprocessor configured with a software for controlling communications via the communication apparatus and for processing data associated with said IO device; said at least an antenna apparatus in communication with said at least a microprocessor; and at least a sensor apparatus embedded in silicon substrate and embedded in a microfiber material to provide at least one of a communication medium, communication clarity, a detection platform, detection selectivity, and detection sensitivity. | 1. An energy harvesting communication device configured with signal booster apparatus, comprising: at least a communication apparatus; at least an antenna apparatus communicatively coupled to the communication apparatus and in association with at least an input output (IO) device; at least a microprocessor configured with a software for controlling communications via the communication apparatus and for processing data associated with said IO device; said at least an antenna apparatus in communication with said at least a microprocessor; and at least a sensor apparatus embedded in silicon substrate and embedded in a microfiber material to provide at least one of a communication medium, communication clarity, a detection platform, detection selectivity, and detection sensitivity. 20. The energy harvesting communication device of claim 1 , wherein said detection platform further comprises at least one of: a solar panel for converting light photons to a photo generating electrical energy, optical elements; a light shield film; an ultraviolet curing resin; a transparent support substrate; a plate; an electric power generating system; an energy management apparatus; a heating module, a cooling module; a method for manufacturing an electronic wafer module; a photovoltaic array; a solar module; a solar cell; a mono-crystalline silicon wafer; a fuel cell, metal-ceramic membranes, film composite metal-ceramic materials, thin film; polymer; an amplified signal transmitter; an amplified signal receiver; a power generator engine; nanotechnology; photovoltaic module; an energy harvester; a nano-rectifier. | 0.71629 |
8,024,183 | 1 | 5 | 1. A method for audio classification, comprising: maximizing a discriminative criterion over a plurality of speakers to obtain a best transform for audio class modeling under a target channel condition state; and transforming, based on said best transform, features of a speaker utterance in a source channel condition state with a processor to match the target channel condition state and as a result provide a channel matched transformed utterance. | 1. A method for audio classification, comprising: maximizing a discriminative criterion over a plurality of speakers to obtain a best transform for audio class modeling under a target channel condition state; and transforming, based on said best transform, features of a speaker utterance in a source channel condition state with a processor to match the target channel condition state and as a result provide a channel matched transformed utterance. 5. The method as recited in claim 1 , wherein the system undergoes many input conditions and further comprises applying a best transform for each input condition. | 0.859619 |
8,831,957 | 2 | 3 | 2. The method of claim 1 , wherein receiving data corresponding to the utterance comprises receiving data corresponding to the utterance from a client device, and wherein obtaining location indicia for an area within a building where the utterance was spoken comprises receiving location indicia for the area within the building where the utterance was spoken from the client device. | 2. The method of claim 1 , wherein receiving data corresponding to the utterance comprises receiving data corresponding to the utterance from a client device, and wherein obtaining location indicia for an area within a building where the utterance was spoken comprises receiving location indicia for the area within the building where the utterance was spoken from the client device. 3. The method of claim 2 , wherein the location indicia comprises location data based on short-range wireless radio transmissions received at the client device. | 0.932717 |
4,485,468 | 1 | 2 | 1. A control word source for supplying control words defining nonsubrate and subrate data communication paths through a time division switching system comprising subrate memory means having a plurality of locations for storing subrate data path-definition words, nonsubrate and reference memory means for storing nonsubrate data path-definition words and storage reference words, circuit means responsive to storage reference words read from said nonsubrate and reference memory means for defining said subrate memory means locations to effect a reading of said subrate data path-definition words and logic means responsive to nonsubrate data path-definition words read from said nonsubrate and reference memory means for supplying control words defining nonsubrate data communication paths through said time division switching system and responsive to subrate data path-definition words read from said subrate memory means locations for supplying control words defining subrate data communication paths through said time division switching system. | 1. A control word source for supplying control words defining nonsubrate and subrate data communication paths through a time division switching system comprising subrate memory means having a plurality of locations for storing subrate data path-definition words, nonsubrate and reference memory means for storing nonsubrate data path-definition words and storage reference words, circuit means responsive to storage reference words read from said nonsubrate and reference memory means for defining said subrate memory means locations to effect a reading of said subrate data path-definition words and logic means responsive to nonsubrate data path-definition words read from said nonsubrate and reference memory means for supplying control words defining nonsubrate data communication paths through said time division switching system and responsive to subrate data path-definition words read from said subrate memory means locations for supplying control words defining subrate data communication paths through said time division switching system. 2. A control word source of claim 1 wherein said circuit means comprises means for generating timing pulses and location generator means responsive to a receipt of said timing pulses and said read storage reference words for generating location signals defining said subrate memory means locations. | 0.838919 |
9,811,938 | 8 | 13 | 8. An apparatus for generating an animated data visualization, the apparatus comprising: a query module to submit a data query on a data structure; a sample size calculation module, implemented using at least one hardware device of one or more hardware devices, to obtain a time measurement for performing the data query and adjust a sample size of the data query based on the time measurement and a frame refresh rate, wherein the sample size is a size of a subset of data obtained in a sample and the time measurement is an amount of time between the submission of the query and obtaining a query result, wherein the adjustment decreases the sample size if the obtained time measurement multiplied by the multiplication factor equals or exceeds an inverse of the frame refresh rate, and wherein the multiplication factor is not equal to zero or one; and a frame generation module, implemented using at least one hardware device of the one or more hardware devices, to generate the animated data visualization based on one or more results of the data query. | 8. An apparatus for generating an animated data visualization, the apparatus comprising: a query module to submit a data query on a data structure; a sample size calculation module, implemented using at least one hardware device of one or more hardware devices, to obtain a time measurement for performing the data query and adjust a sample size of the data query based on the time measurement and a frame refresh rate, wherein the sample size is a size of a subset of data obtained in a sample and the time measurement is an amount of time between the submission of the query and obtaining a query result, wherein the adjustment decreases the sample size if the obtained time measurement multiplied by the multiplication factor equals or exceeds an inverse of the frame refresh rate, and wherein the multiplication factor is not equal to zero or one; and a frame generation module, implemented using at least one hardware device of the one or more hardware devices, to generate the animated data visualization based on one or more results of the data query. 13. The apparatus of claim 8 , wherein the time measurement is provided as an output of the query. | 0.718391 |
7,957,968 | 1 | 10 | 1. A computer based method for automatically generating a hierarchical grammar associated with a plurality of tasks comprising the steps of: creating a sub-grammar for each of the plurality of tasks, wherein creating a sub-grammar for a task comprises: receiving data representing the task based from responses received from a distributed database; automatically tagging the data into parts of speech to form tagged data using a processor executing instructions included in a memory coupled to the processor; identifying filler words and core words from said tagged data by applying rules to differentiate between filler words and core words using the processor executing instructions included in the memory coupled to the processor; automatically modeling sentence structure based upon said tagged data using a set of modeling rules retrieved from the memory coupled to the processor; automatically identifying synonyms of said core words; and automatically creating a sub-grammar using the modeled sentence structure, the tagged data, the identified synonyms, and the identified core words; and creating a high-level grammar by combining filler words identified in the creation of the sub-grammars. | 1. A computer based method for automatically generating a hierarchical grammar associated with a plurality of tasks comprising the steps of: creating a sub-grammar for each of the plurality of tasks, wherein creating a sub-grammar for a task comprises: receiving data representing the task based from responses received from a distributed database; automatically tagging the data into parts of speech to form tagged data using a processor executing instructions included in a memory coupled to the processor; identifying filler words and core words from said tagged data by applying rules to differentiate between filler words and core words using the processor executing instructions included in the memory coupled to the processor; automatically modeling sentence structure based upon said tagged data using a set of modeling rules retrieved from the memory coupled to the processor; automatically identifying synonyms of said core words; and automatically creating a sub-grammar using the modeled sentence structure, the tagged data, the identified synonyms, and the identified core words; and creating a high-level grammar by combining filler words identified in the creation of the sub-grammars. 10. The method of claim 1 , further comprising the step of identifying synonyms of the identified filler words. | 0.566406 |
8,402,430 | 13 | 17 | 13. A non-transitory computer readable medium that stores a modeling profile defining a semantic extension to a modeling language, wherein the modeling profile stored on the computer readable medium comprises: a plurality of tagged profile constructs that assign new properties to standard model elements associated with the modeling language, wherein the new properties that the plurality of tagged profile constructs assign to the standard model elements associated with the modeling language define a semantic extension to the modeling language; a plurality of stereotyped profile constructs that add supplemental values or constraints to the standard model elements associated with the modeling language, wherein the supplemental values or constraints that the plurality of stereotyped profile constructs add to the standard model elements associated with the modeling language further define the semantic extension to the modeling language; and a plurality of mapping algorithms that map the plurality of tagged profile constructs and the plurality of stereotyped profile constructs to an object-oriented constructs construct in an object-oriented programming language having semantic features that support inferencing over rules without an instantiated inference engine, wherein the semantic extension defined in the modeling profile provides the modeling language with the semantic features that support inferencing over rules in the object-oriented programming language. | 13. A non-transitory computer readable medium that stores a modeling profile defining a semantic extension to a modeling language, wherein the modeling profile stored on the computer readable medium comprises: a plurality of tagged profile constructs that assign new properties to standard model elements associated with the modeling language, wherein the new properties that the plurality of tagged profile constructs assign to the standard model elements associated with the modeling language define a semantic extension to the modeling language; a plurality of stereotyped profile constructs that add supplemental values or constraints to the standard model elements associated with the modeling language, wherein the supplemental values or constraints that the plurality of stereotyped profile constructs add to the standard model elements associated with the modeling language further define the semantic extension to the modeling language; and a plurality of mapping algorithms that map the plurality of tagged profile constructs and the plurality of stereotyped profile constructs to an object-oriented constructs construct in an object-oriented programming language having semantic features that support inferencing over rules without an instantiated inference engine, wherein the semantic extension defined in the modeling profile provides the modeling language with the semantic features that support inferencing over rules in the object-oriented programming language. 17. The computer readable medium of claim 13 , wherein the plurality of stereotyped profile constructs include a domain interface member profile construct that defines an action to execute in response to the standard model elements associated with the modeling language satisfying a condition, and wherein the plurality of tagged profile constructs include an action profile construct that defines the action and a condition profile construct that defines the condition. | 0.577338 |
9,247,013 | 9 | 12 | 9. A computer system for automating repetitive operations using a social media access interface, comprising: a computer processor to execute a set of program code instructions; and a memory to hold the program code instructions, in which the program code instructions comprises program code to perform, initiating a recording session to record user steps within an interactive session, wherein the user steps being recorded are associated with a post retrieved, from within the interactive session, from a social media site using the social media access interface; saving the recording session; and initiating a batch processor to replay at least a portion of the saved recording session. | 9. A computer system for automating repetitive operations using a social media access interface, comprising: a computer processor to execute a set of program code instructions; and a memory to hold the program code instructions, in which the program code instructions comprises program code to perform, initiating a recording session to record user steps within an interactive session, wherein the user steps being recorded are associated with a post retrieved, from within the interactive session, from a social media site using the social media access interface; saving the recording session; and initiating a batch processor to replay at least a portion of the saved recording session. 12. The computer system of claim 9 , further comprising program code for processing the retrieved post by performing at least one of, extracting an author of the retrieved post, extracting a sentiment of the retrieved post, extracting a category of the retrieved post. | 0.597598 |
9,177,046 | 8 | 14 | 8. A system, comprising: a data processing apparatus; and a memory coupled to the data processing apparatus having instructions stored thereon which, when executed by the data processing apparatus cause the data processing apparatus to perform operations comprising: obtaining a trained image relevance model that generates relevance measures of images to a query; and re-training the image relevance model, the re-training comprising: generating an aggregation of near duplicate images among a set of training images; associating image selection data of the aggregated near duplicate images with the aggregation of the near duplicate images, the image selection data corresponding to user interactions with the near duplicate images when the near duplicate images were presented as search results; and generating a re-trained image relevance model based on content feature values of each image in the aggregation of near duplicate images and the image selection data associated with the aggregation of near duplicate images. | 8. A system, comprising: a data processing apparatus; and a memory coupled to the data processing apparatus having instructions stored thereon which, when executed by the data processing apparatus cause the data processing apparatus to perform operations comprising: obtaining a trained image relevance model that generates relevance measures of images to a query; and re-training the image relevance model, the re-training comprising: generating an aggregation of near duplicate images among a set of training images; associating image selection data of the aggregated near duplicate images with the aggregation of the near duplicate images, the image selection data corresponding to user interactions with the near duplicate images when the near duplicate images were presented as search results; and generating a re-trained image relevance model based on content feature values of each image in the aggregation of near duplicate images and the image selection data associated with the aggregation of near duplicate images. 14. The system of claim 8 , wherein generating a re-trained image relevance model based on content feature values of the aggregation of near duplicate images and the image selection data associated with the aggregation of near duplicate images comprises generating the re-trained image relevance model based on content features of a single representation of the aggregation of near duplicate images and a single selection value based on the image selection data of the aggregation of near duplicate images. | 0.501969 |
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