patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
1
|
|---|---|---|---|---|---|
8,503,715 | 1 | 4 | 1. A method implemented by one or more computing devices, the method comprising: identifying values representing individual text characters in a string of one or more text characters to determine which human writing system is associated with the individual text characters; comparing the values to a table that associates subsets of values with individual human writing systems; determining that the values representing the individual text characters are within a particular subset of values in the table that correspond to a particular said human writing system; and designating that the particular said human writing system is associated with the string based on the values associated with the individual text characters being within the particular subset of values that corresponds with the particular said human writing system. | 1. A method implemented by one or more computing devices, the method comprising: identifying values representing individual text characters in a string of one or more text characters to determine which human writing system is associated with the individual text characters; comparing the values to a table that associates subsets of values with individual human writing systems; determining that the values representing the individual text characters are within a particular subset of values in the table that correspond to a particular said human writing system; and designating that the particular said human writing system is associated with the string based on the values associated with the individual text characters being within the particular subset of values that corresponds with the particular said human writing system. 4. The method of claim 1 , further comprising indicating a service available to perform a function with the one or more text characters based on the particular said human writing system. | 0.771499 |
10,095,486 | 21 | 41 | 21. A software application development tool for assembling applications in which a check-in terminal communicates with two or more airline systems and services, the software application development tool stored on non-transitory computer readable media and comprising computer readable program code comprising: a common code base, wherein the common code base is incompatible with the two or more airline systems and services; data and messages used by the application described using a declarative data description language; a library of system components including: a) a terminal abstraction layer that allows interactions between the check-in terminal and the application to control the check-in terminal; and b) an airline systems and services abstraction layer that allows interactions between the two or more airline systems and services and the application, wherein the two or more airline systems and services comprise check-in systems; a graphical (GUI) tool to model the workflow of the application, the workflow including screens and services described declaratively by a declarative data description language; and an assembler for assembling the application using the graphical tool, declarative rules, and customizations of the system components selected from the library. | 21. A software application development tool for assembling applications in which a check-in terminal communicates with two or more airline systems and services, the software application development tool stored on non-transitory computer readable media and comprising computer readable program code comprising: a common code base, wherein the common code base is incompatible with the two or more airline systems and services; data and messages used by the application described using a declarative data description language; a library of system components including: a) a terminal abstraction layer that allows interactions between the check-in terminal and the application to control the check-in terminal; and b) an airline systems and services abstraction layer that allows interactions between the two or more airline systems and services and the application, wherein the two or more airline systems and services comprise check-in systems; a graphical (GUI) tool to model the workflow of the application, the workflow including screens and services described declaratively by a declarative data description language; and an assembler for assembling the application using the graphical tool, declarative rules, and customizations of the system components selected from the library. 41. A software application development tool according to claim 21 , wherein the application is a ticketing client. | 0.784906 |
8,224,805 | 16 | 17 | 16. A system for generating a context hierarchy, the system comprising: a memory; a frequent itemset tree generator generating frequent itemset trees for continuously generated transactions; a context tree generator detecting ones of the frequent itemsets of the new frequent itemset trees as a single context when a difference in support is a predetermined value or less and generating the context tree having a hierarchical structure based on the detected contexts, after vertically projecting the frequent itemset trees into a plurality of boundaries and assigning indexes to basic itemsets of each boundary to generate new first transactions and new frequent itemset trees; and a context hierarchy generator determining that there are no selectable contexts in the contexts of the new context trees and if not, ending the generation of the context hierarchy and if so, selecting the appropriately contexts to assign the new name to each context and after generating the subsequent layer having the context hierarchy, and repeatedly performing the process from a process generating new second transactions for a subsequent layer as the new name, after generating a lowermost layer having a context hierarchy by assigning a new name to only contexts selected in the context trees and generating new second transactions for a subsequent layer as a new name and generating new context trees. | 16. A system for generating a context hierarchy, the system comprising: a memory; a frequent itemset tree generator generating frequent itemset trees for continuously generated transactions; a context tree generator detecting ones of the frequent itemsets of the new frequent itemset trees as a single context when a difference in support is a predetermined value or less and generating the context tree having a hierarchical structure based on the detected contexts, after vertically projecting the frequent itemset trees into a plurality of boundaries and assigning indexes to basic itemsets of each boundary to generate new first transactions and new frequent itemset trees; and a context hierarchy generator determining that there are no selectable contexts in the contexts of the new context trees and if not, ending the generation of the context hierarchy and if so, selecting the appropriately contexts to assign the new name to each context and after generating the subsequent layer having the context hierarchy, and repeatedly performing the process from a process generating new second transactions for a subsequent layer as the new name, after generating a lowermost layer having a context hierarchy by assigning a new name to only contexts selected in the context trees and generating new second transactions for a subsequent layer as a new name and generating new context trees. 17. The system of claim 16 , wherein when generating new second transactions and new context trees, the context hierarchy generator performs context detection that includes a process that performs third frequent itemset mining on second transactions after generating the second transactions to generate new context trees. | 0.725171 |
9,946,751 | 13 | 15 | 13. A non-transitory computer-readable medium containing program code executable by a processor in a computer configurable to cause the computer to improve a query in a multi-tenant database system that is to be performed in the context of a tenant-specific filter on a tenant identifier, the program code including instructions to: receiving at a network interface of a server an original query, wherein the original query is associated with data within a database as identified by the tenant identifier, and wherein the database includes at least a first index and a second index, further wherein the database stores data for multiple tenants that are unrelated organizations and have different database schemas, the data corresponding to each tenant having tenant-specific characteristics; retrieving, using a processor of the server, metadata associated with the data, wherein at least a portion of the data is stored in a common table within the database system; determining, using the processor, a tenant-selective query syntax by analyzing at least metadata generated from tenant-specific characteristics; analyzing, using the processor, metadata generated from information about the organization to which the original query corresponds; and generating, using the processor, an improved query using the query syntax, wherein the improved query is based at least in part upon the original query and a result of a join between a first number of rows associated with the first index and a second number of rows associated with the second index and the analysis of the metadata. | 13. A non-transitory computer-readable medium containing program code executable by a processor in a computer configurable to cause the computer to improve a query in a multi-tenant database system that is to be performed in the context of a tenant-specific filter on a tenant identifier, the program code including instructions to: receiving at a network interface of a server an original query, wherein the original query is associated with data within a database as identified by the tenant identifier, and wherein the database includes at least a first index and a second index, further wherein the database stores data for multiple tenants that are unrelated organizations and have different database schemas, the data corresponding to each tenant having tenant-specific characteristics; retrieving, using a processor of the server, metadata associated with the data, wherein at least a portion of the data is stored in a common table within the database system; determining, using the processor, a tenant-selective query syntax by analyzing at least metadata generated from tenant-specific characteristics; analyzing, using the processor, metadata generated from information about the organization to which the original query corresponds; and generating, using the processor, an improved query using the query syntax, wherein the improved query is based at least in part upon the original query and a result of a join between a first number of rows associated with the first index and a second number of rows associated with the second index and the analysis of the metadata. 15. The computer-readable medium of claim 13 , wherein the program code includes further instructions to: calculating selectivity for one or more columns of data accessible by the tenant; and wherein determining, using a processor of the server, comprises analyzing the selectivity of the one or more columns of data accessible by the tenant. | 0.785982 |
9,602,447 | 3 | 4 | 3. The method of claim 2 , further comprising receiving from the browser component of the client network node of the user a uniform resource identifier of the document. | 3. The method of claim 2 , further comprising receiving from the browser component of the client network node of the user a uniform resource identifier of the document. 4. The method of claim 3 , further comprising: based on the uniform resource identifier of the document, automatically ascertaining content items of one or more particular content types that are associated with the document; and transmitting, to the client network node of the user, instructions for presenting user-selectable graphical representations of the ascertained content items in the graphical user interface. | 0.87341 |
8,745,055 | 10 | 13 | 10. A computer implemented method of clustering documents, the method comprising: generating document vectors for each of a plurality of documents of a corpus, wherein each document vector comprises a plurality of terms from the corresponding document and a frequency score for each term; generating a plurality of reference vectors based on the document vectors, wherein each reference vector comprises a plurality of terms from the document vectors and a frequency score for each term, wherein the frequency score for each term in each reference vector comprises a random or pseudo-random value; comparing the document vectors to each of the reference vectors to generate similarity values for each of the document vectors; sorting the document vectors based on the similarity values for the document vectors to form a sorted list; and forming clusters of documents based on the similarity values between adjacent document vectors in the sorted list. | 10. A computer implemented method of clustering documents, the method comprising: generating document vectors for each of a plurality of documents of a corpus, wherein each document vector comprises a plurality of terms from the corresponding document and a frequency score for each term; generating a plurality of reference vectors based on the document vectors, wherein each reference vector comprises a plurality of terms from the document vectors and a frequency score for each term, wherein the frequency score for each term in each reference vector comprises a random or pseudo-random value; comparing the document vectors to each of the reference vectors to generate similarity values for each of the document vectors; sorting the document vectors based on the similarity values for the document vectors to form a sorted list; and forming clusters of documents based on the similarity values between adjacent document vectors in the sorted list. 13. The method of claim 10 , wherein the terms include one or more of words, phrases, and groups of words or phrases. | 0.905032 |
6,088,707 | 48 | 49 | 48. The method of claim 46, wherein the keyword search criteria includes a list of keywords. | 48. The method of claim 46, wherein the keyword search criteria includes a list of keywords. 49. The method of claim 48, wherein the list of keywords includes at least one of text and a delimiter selected from the group consisting of a format delimiter, a tag, a style delimiter, a type delimiter, a token, an object definition, and combinations thereof. | 0.935492 |
9,836,305 | 15 | 16 | 15. The computer-implemented method of claim 1 , the method further comprising: obtaining, by the computing system, at least one second document, wherein the second document includes the data that is referenced by the script; determining, by the computing system, a binary representation of the second document; determining; by the computing system, an interlaced binary structure based at least in part on the binary representation of the document and the binary representation of the second document; and processing, by the computing system, the parallelized code with respect to the document and the second document based at least in part on the interlaced binary representation. | 15. The computer-implemented method of claim 1 , the method further comprising: obtaining, by the computing system, at least one second document, wherein the second document includes the data that is referenced by the script; determining, by the computing system, a binary representation of the second document; determining; by the computing system, an interlaced binary structure based at least in part on the binary representation of the document and the binary representation of the second document; and processing, by the computing system, the parallelized code with respect to the document and the second document based at least in part on the interlaced binary representation. 16. The computer-implemented method of claim 15 , the method further comprising: allocating, by the computing system, memory for the document prior to executing the parallelized code; allocating, by the computing system, memory for the second document prior to executing the parallelized code, wherein the memory allocated for the document and the memory allocated for the second document is coalesced. | 0.832779 |
8,914,320 | 1 | 7 | 1. A computer-based method for generation of a graph representation of a rule set, the method comprising: setting a first rule list equal to the rule set; and performing a recursive process on the first rule list, wherein the recursive process comprises: setting a second rule list equal to the first rule list; when the second rule list includes more than one rule, for each rule in the second rule list: selecting the rule for processing; determining at least one verification set for said selected rule, wherein said at least one verification set is composed of individual offsets or data fields that define said selected rule, and data ranges for each individual offset or data field; creating a third rule list for the at least one verification set, wherein the third rule list represents a subgraph that is a portion of the graph representation; updating the individual offsets or data fields of the at least one verification set; adding the at least one verification set to the second rule list; and performing the recursive process on the third rule set to generate a new subgraph. | 1. A computer-based method for generation of a graph representation of a rule set, the method comprising: setting a first rule list equal to the rule set; and performing a recursive process on the first rule list, wherein the recursive process comprises: setting a second rule list equal to the first rule list; when the second rule list includes more than one rule, for each rule in the second rule list: selecting the rule for processing; determining at least one verification set for said selected rule, wherein said at least one verification set is composed of individual offsets or data fields that define said selected rule, and data ranges for each individual offset or data field; creating a third rule list for the at least one verification set, wherein the third rule list represents a subgraph that is a portion of the graph representation; updating the individual offsets or data fields of the at least one verification set; adding the at least one verification set to the second rule list; and performing the recursive process on the third rule set to generate a new subgraph. 7. The method of claim 1 , comprising multiple verification sets, wherein each of said multiple verification sets is unique and does not overlap with any other verification set. | 0.502809 |
9,633,007 | 1 | 14 | 1. A method for aspect categorization comprising: receiving an input text sequence; providing for identifying aspect terms in the input text sequence; providing for identifying sentiment phrases in the input text sequence; for an identified aspect term: providing for identifying sentiment dependencies in which the aspect term is in a syntactic dependency with one of the identified sentiment phrases, and from a dependency graph of the input text sequence, the dependency graph comprising a sequence of nodes, providing for identifying pseudo-dependencies in which a node representing the aspect term precedes or follows a node representing a semantic anchor in the dependency graph without an intervening other aspect term; extracting features from at least one of identified sentiment dependencies and identified pseudo-dependencies; with a classifier trained to output at least one of category labels and polarity labels for aspect terms, classifying the identified aspect term based on the extracted features; and outputting information based on the classification. | 1. A method for aspect categorization comprising: receiving an input text sequence; providing for identifying aspect terms in the input text sequence; providing for identifying sentiment phrases in the input text sequence; for an identified aspect term: providing for identifying sentiment dependencies in which the aspect term is in a syntactic dependency with one of the identified sentiment phrases, and from a dependency graph of the input text sequence, the dependency graph comprising a sequence of nodes, providing for identifying pseudo-dependencies in which a node representing the aspect term precedes or follows a node representing a semantic anchor in the dependency graph without an intervening other aspect term; extracting features from at least one of identified sentiment dependencies and identified pseudo-dependencies; with a classifier trained to output at least one of category labels and polarity labels for aspect terms, classifying the identified aspect term based on the extracted features; and outputting information based on the classification. 14. The method of claim 1 , further comprising training a first classifier for predicting category labels for aspect terms and a second classifier for predicting polarity labels for aspect terms based on features extracted from training samples labeled with category and polarity information. | 0.571848 |
9,984,155 | 5 | 6 | 5. The method of claim 1 , wherein providing items in the first sub-set of items for display comprises sending a user interface document, the user interface document comprising instructions to display the items of the first sub-set of items as the discussion stream. | 5. The method of claim 1 , wherein providing items in the first sub-set of items for display comprises sending a user interface document, the user interface document comprising instructions to display the items of the first sub-set of items as the discussion stream. 6. The method of claim 5 , wherein the user interface document comprises a web page. | 0.982594 |
7,774,746 | 34 | 38 | 34. A method of generating code, comprising: receiving a specification of one or more translation patterns; and using the one or more translation patterns to generate using a processor at least a portion of a first code associated with a first translator, wherein the first code is generated at least in part by using a query compiler to generate a portion of the first code which portion is configured to obtain from a source content in a source format a data value to be used in determining one or more elements of a target object model that the first translator is configured at least in part to create; using at least one of the one or more translation patterns to generate at least a portion of a second code associated with a second translator; and connecting together the first translator and the second translator to form at least a portion of a converter. | 34. A method of generating code, comprising: receiving a specification of one or more translation patterns; and using the one or more translation patterns to generate using a processor at least a portion of a first code associated with a first translator, wherein the first code is generated at least in part by using a query compiler to generate a portion of the first code which portion is configured to obtain from a source content in a source format a data value to be used in determining one or more elements of a target object model that the first translator is configured at least in part to create; using at least one of the one or more translation patterns to generate at least a portion of a second code associated with a second translator; and connecting together the first translator and the second translator to form at least a portion of a converter. 38. A method as recited in claim 34 , wherein the query compiler is generated based at least in part on one or more of the following: a schema, a coding standard, a query language, and an Application Programming Interface. | 0.702413 |
8,977,248 | 1 | 9 | 1. A system, comprising: at least one computing device comprising hardware; non-transitory memory coupled to the at least one computing device that stores instructions that when executed by the at least one computing device cause, at least in part, the system to implement: a speech-to-text recognizer configured to translate into text some or all of a voice communication, including a plurality of spoken words, from a first user; a message generator configured to generate a text message from a selected portion of the translated text based at least in part on: an identification of one or more words in the translated text that correspond to respective one or more words in a vocabulary of uncommon words that are uncommon in voice communications; and a network interface configured to transmit the text message from the translated text to a social networking for posting on a social networking web page; wherein the social networking web page is configured to share first user information posted on the social networking web page with others. | 1. A system, comprising: at least one computing device comprising hardware; non-transitory memory coupled to the at least one computing device that stores instructions that when executed by the at least one computing device cause, at least in part, the system to implement: a speech-to-text recognizer configured to translate into text some or all of a voice communication, including a plurality of spoken words, from a first user; a message generator configured to generate a text message from a selected portion of the translated text based at least in part on: an identification of one or more words in the translated text that correspond to respective one or more words in a vocabulary of uncommon words that are uncommon in voice communications; and a network interface configured to transmit the text message from the translated text to a social networking for posting on a social networking web page; wherein the social networking web page is configured to share first user information posted on the social networking web page with others. 9. The system as defined in claim 1 , wherein the system is configured to size the selected portion of the translated text to be transmittable via a single SMS message at least in part by: conversion of a word and/or phrase into an abbreviation; conversion of a word and/or phrase using non-standard spelling; conversion of a cardinal and/or ordinal numbers to a digit representation; or conversion of a spoken address into a representation suitable for being used as an email address. | 0.501029 |
7,647,415 | 34 | 40 | 34. A computer-accessible storage medium comprising program instructions, wherein the program instructions are configured to implement: a Web services stack communicating with another Web services stack according to a markup language protocol, wherein the markup language protocol is based on XML (eXtensible Markup Language); and the Web services stack dynamically switching to communicating with the other Web services stack according to a binary encoding protocol wherein communication according to the binary encoding protocol comprises mapping from an XML schema to a binary encoding schema and generating a binary encoding from the binary encoding schema; wherein the Web services stack supports the markup language protocol and the binary encoding protocol with a single API (application programming interface). | 34. A computer-accessible storage medium comprising program instructions, wherein the program instructions are configured to implement: a Web services stack communicating with another Web services stack according to a markup language protocol, wherein the markup language protocol is based on XML (eXtensible Markup Language); and the Web services stack dynamically switching to communicating with the other Web services stack according to a binary encoding protocol wherein communication according to the binary encoding protocol comprises mapping from an XML schema to a binary encoding schema and generating a binary encoding from the binary encoding schema; wherein the Web services stack supports the markup language protocol and the binary encoding protocol with a single API (application programming interface). 40. The computer-accessible storage medium as recited in claim 34 , wherein the binary encoding protocol uses Packed Encoding Rules (PER) encoding. | 0.897203 |
7,921,415 | 23 | 25 | 23. A computer-readable medium having stored thereon instructions for execution by a computing device, the instructions, which when executed, cause a method to be performed at the computing device, the method comprising: loading from a voice server, an interpreter program written in a language natively supported by a voice browser on the computing device, in response to a statement in a document being parsed; the interpreter program being designed to interpret a second program language that is not natively supported by the voice browser on the computing device; loading from the voice server, a second program written in the second program language at the voice browser; executing, at the voice browser, the second program using the interpreter program; wherein the second language is an XML-based language. | 23. A computer-readable medium having stored thereon instructions for execution by a computing device, the instructions, which when executed, cause a method to be performed at the computing device, the method comprising: loading from a voice server, an interpreter program written in a language natively supported by a voice browser on the computing device, in response to a statement in a document being parsed; the interpreter program being designed to interpret a second program language that is not natively supported by the voice browser on the computing device; loading from the voice server, a second program written in the second program language at the voice browser; executing, at the voice browser, the second program using the interpreter program; wherein the second language is an XML-based language. 25. The method of claim 23 , wherein the computing device includes an HTML browser. | 0.505952 |
8,676,722 | 1 | 39 | 1. A computer implemented method for generating a semantic network, the method comprising: representing an information domain as a data set, the data set being defined by data entities and one or more relationships between the data entities; receiving a text query from a human user; and synthesizing, or facilitating the synthesizing of, by one or more computer processors, a semantic network in response to the text query, the synthesizing comprising: translating the text query from the human user into an active concept; including the active concept as a node in the semantic network; deriving relationships between the active concept and selected data entities from the information domain; and populating the semantic network at least in part with the selected data entities from the information domain and the derived relationships between the selected data entities and the active concept. | 1. A computer implemented method for generating a semantic network, the method comprising: representing an information domain as a data set, the data set being defined by data entities and one or more relationships between the data entities; receiving a text query from a human user; and synthesizing, or facilitating the synthesizing of, by one or more computer processors, a semantic network in response to the text query, the synthesizing comprising: translating the text query from the human user into an active concept; including the active concept as a node in the semantic network; deriving relationships between the active concept and selected data entities from the information domain; and populating the semantic network at least in part with the selected data entities from the information domain and the derived relationships between the selected data entities and the active concept. 39. The computer implemented method of claim 1 , wherein the data entities comprise media or content. | 0.885747 |
7,546,381 | 15 | 16 | 15. The computer-readable storage medium of claim 10 , wherein the root server is selected from a group of root servers associated with a range of generalized representations of international domain names. | 15. The computer-readable storage medium of claim 10 , wherein the root server is selected from a group of root servers associated with a range of generalized representations of international domain names. 16. The computer-readable storage medium of claim 15 , where the group of root servers is associated with a range of UNICODE representations of international domain names. | 0.904894 |
8,417,710 | 1 | 4 | 1. A method for managing queries using semantic analysis, the method comprising: receiving, with a processor, a public relations query from a user, wherein the public relations query comprises query of expressed sentiments about at least one person, entity, or action taken thereby; identifying, with a processor, a set of relevant topics and subjects associated with the query; identifying, based on the set of topics and subjects, a set of information sources that are identified as relevant information sources for the user and that comprise data associated with the set of topics and subjects; identifying a set of data from the set of information sources that satisfies the query; determining, with a processor, for each data element in the set of data, a number of web pages that a) point to a web page comprising the each data element, and b) are in the set of information sources that are identified as relevant information sources for the user; assigning a weight to the each data element based on the determined number of web pages, where a higher number of web pages results in a higher weight being assigned than a lower number of web pages; identifying a set of data elements within the set of data that comprises a set of weights above a given threshold; and generating a response to the query using the set of data elements that has been identified. | 1. A method for managing queries using semantic analysis, the method comprising: receiving, with a processor, a public relations query from a user, wherein the public relations query comprises query of expressed sentiments about at least one person, entity, or action taken thereby; identifying, with a processor, a set of relevant topics and subjects associated with the query; identifying, based on the set of topics and subjects, a set of information sources that are identified as relevant information sources for the user and that comprise data associated with the set of topics and subjects; identifying a set of data from the set of information sources that satisfies the query; determining, with a processor, for each data element in the set of data, a number of web pages that a) point to a web page comprising the each data element, and b) are in the set of information sources that are identified as relevant information sources for the user; assigning a weight to the each data element based on the determined number of web pages, where a higher number of web pages results in a higher weight being assigned than a lower number of web pages; identifying a set of data elements within the set of data that comprises a set of weights above a given threshold; and generating a response to the query using the set of data elements that has been identified. 4. The method of claim 1 , wherein the set of information sources comprises a set of proprietary information sources and a set of public information sources. | 0.836798 |
6,166,739 | 18 | 34 | 18. An apparatus for navigating a group of information in a computer system, comprising: means for identifying said group of information associated with a selected data item; means for converting certain pieces of said group information into generated data items; means for associating unilateral and multilateral display relationships with said generated data items, each unilateral display relationship representing a direct relationship between two of said generated data items, and said multilateral relationships also representing an indirect relationship with other generated data items; means for associating unilateral and multilateral display relationships with said generated data items and said selected data item, each unilateral display relationship representing a direct relationship between said selected data item and one of said generated data items, and said multilateral relationships also representing an indirect relationship between said selected data item and said generated data items; and means for forming a display associated with said selected data item, including said generated data items, wherein said display distinguishes between said selected data item and said generated data items. | 18. An apparatus for navigating a group of information in a computer system, comprising: means for identifying said group of information associated with a selected data item; means for converting certain pieces of said group information into generated data items; means for associating unilateral and multilateral display relationships with said generated data items, each unilateral display relationship representing a direct relationship between two of said generated data items, and said multilateral relationships also representing an indirect relationship with other generated data items; means for associating unilateral and multilateral display relationships with said generated data items and said selected data item, each unilateral display relationship representing a direct relationship between said selected data item and one of said generated data items, and said multilateral relationships also representing an indirect relationship between said selected data item and said generated data items; and means for forming a display associated with said selected data item, including said generated data items, wherein said display distinguishes between said selected data item and said generated data items. 34. The apparatus claimed in claim 18, wherein said linked items comprise a web site. | 0.854949 |
7,523,261 | 15 | 16 | 15. The method as claimed in claim 13 , wherein the information describing the association comprises the virtual addresses, and each virtual address refers to a memory location at which one of the machine words is stored. | 15. The method as claimed in claim 13 , wherein the information describing the association comprises the virtual addresses, and each virtual address refers to a memory location at which one of the machine words is stored. 16. The method as claimed in claim 15 , wherein the describing information comprises a first virtual address and a second virtual address, the first virtual address refers to a first memory location for storing a first machine word, the second virtual address refers to a second memory location for storing a second machine word, and during the alteration of the association the first virtual address refers to the second memory location. | 0.892383 |
9,426,071 | 1 | 3 | 1. A method comprising: intercepting a first packet from a network link at a node coupled to the network link, the node including persistent storage devices organized as a plurality of volumes having a hierarchical file system; computing a first hash value based on a network flow of the first packet; recording the first packet in a packet capture (PCAP) format as a first PCAP record including the first hash value and first flow metadata appended to the first PCAP record; copying the first PCAP record to a first metadata repository stored as a first file on a first volume of the hierarchical file system of the node, wherein the first metadata repository stores a plurality of second PCAP records having second hash values and second flow metadata; and concurrently searching and retrieving one or more of the second PCAP records of the first metadata repository while copying the first packet to a data repository stored as a second file of a second volume of the hierarchical file system of the node to realize a substantially high sustained packet transfer rate of the network link. | 1. A method comprising: intercepting a first packet from a network link at a node coupled to the network link, the node including persistent storage devices organized as a plurality of volumes having a hierarchical file system; computing a first hash value based on a network flow of the first packet; recording the first packet in a packet capture (PCAP) format as a first PCAP record including the first hash value and first flow metadata appended to the first PCAP record; copying the first PCAP record to a first metadata repository stored as a first file on a first volume of the hierarchical file system of the node, wherein the first metadata repository stores a plurality of second PCAP records having second hash values and second flow metadata; and concurrently searching and retrieving one or more of the second PCAP records of the first metadata repository while copying the first packet to a data repository stored as a second file of a second volume of the hierarchical file system of the node to realize a substantially high sustained packet transfer rate of the network link. 3. The method of claim 1 wherein concurrently searching and retrieving comprises: issuing an expression as a query to the node; searching the second flow metadata of the second PCAP records stored in the first metadata repository to match the expression; in response to a match, using a second hash value retrieved from a matching second PCAP record to scan a second metadata repository to find a second entry matching the second hash value; and in response to finding a matching second entry, retrieving a second packet from the data repository. | 0.66129 |
6,112,304 | 7 | 8 | 7. The method of claim 2, wherein the providing step includes providing a user denizen which reproduces itself. | 7. The method of claim 2, wherein the providing step includes providing a user denizen which reproduces itself. 8. The method of claim 7, wherein the providing step includes providing a user denizen which detects an error in itself and attempts to rebuild itself. | 0.929898 |
8,484,199 | 6 | 7 | 6. The method of claim 1 wherein, when the first or second geographic feature comprises a road, the respective rank score is generated based on at least one of a total length of the road, a width of the road, a number of lanes of the road, a type of paving of the road, a capacity of the road, or a degree of networking of the road. | 6. The method of claim 1 wherein, when the first or second geographic feature comprises a road, the respective rank score is generated based on at least one of a total length of the road, a width of the road, a number of lanes of the road, a type of paving of the road, a capacity of the road, or a degree of networking of the road. 7. The method of claim 6 wherein the degree of networking comprises at least one of a number of intersections with other roads, a degree of access to general public, complexity of intersections with other roads, or prominence of intersections with other roads. | 0.925158 |
10,079,800 | 1 | 2 | 1. A method comprising: receiving a Domain Name System (DNS) query from a client; determining, based on predetermined class criteria, that the client is associated with an equivalency class; and resolving the DNS query using client subnet data associated with the equivalency class. | 1. A method comprising: receiving a Domain Name System (DNS) query from a client; determining, based on predetermined class criteria, that the client is associated with an equivalency class; and resolving the DNS query using client subnet data associated with the equivalency class. 2. The method of claim 1 , wherein resolving the DNS query includes: searching a cache associated with the equivalence class for an answer corresponding to the DNS query; and upon locating the answer, serving the answer to the client. | 0.832378 |
8,996,648 | 1 | 3 | 1. An apparatus, comprising: a processor; a custom feed system executing on the processor to customize a social networking feed for a social networking system, the custom feed system comprising: a message reception component operative to receive a message from a client device; a message analysis component operative to determine a message type of the message based on a syntax of the message, wherein the message type is associated with a specific message display style comprising at least one of a presentation parameter and formatting parameter, the syntax of the message comprising a custom syntax for the message type; and a message display component operative to display the message according to the message display style associated with the message type of the message. | 1. An apparatus, comprising: a processor; a custom feed system executing on the processor to customize a social networking feed for a social networking system, the custom feed system comprising: a message reception component operative to receive a message from a client device; a message analysis component operative to determine a message type of the message based on a syntax of the message, wherein the message type is associated with a specific message display style comprising at least one of a presentation parameter and formatting parameter, the syntax of the message comprising a custom syntax for the message type; and a message display component operative to display the message according to the message display style associated with the message type of the message. 3. The system of claim 1 , the message display style to specify an image. | 0.742958 |
8,898,557 | 30 | 38 | 30. A computer-implemented method, comprising: detecting, at a server including one or more processors, whether document editor software is currently executing at a computing device that is logged into an account associated with a user; detecting, at the server, whether a handheld mobile computing device is logged into the account associated with the user; in response to detecting that (i) the document editor software is currently executing at the computing device and (ii) both the computing device and the handheld mobile computing device are logged into the account: transmitting, from the server to the computing device, a first command that causes the document editing software to include a selectable command in one of its menus, the selectable command being configured to cause the handheld mobile computing device to obtain an image of a document currently being edited in the document editor software; receiving, at the server, an indication that the user selected the selectable command at the computing device; in response to receiving the indication, transmitting, from the server, a second command to the handheld mobile computing device, the second command causing the handheld mobile computing device to: (i) obtain the image of the document from at least one of the server and the computing device, and (ii) in response to obtaining the image of the document, automatically displaying the image of the document at a touch display of the handheld mobile computing device; receive, at the server, annotation information indicative of handwritten annotations made by the user to the image of the document via the touch display of the handwritten mobile computing device, the handwritten annotations having been made by the user in a locked editing mode of the handheld mobile computing device in which the rendering of the document was not modifiable and the handwritten annotations were overlaid to the rendering of the document in one or more layers; and at least one of: storing, at the server, the annotation information; transmitting, from the server to the computing device, the annotation information for at least one of (i) display at the computing device and (ii) storage at the computing device; and transmitting, from the server to a paper printer (i) directly or (ii) via the computing device, the annotation information and the image of the document, wherein receiving the annotation information and the image of the document causes the paper printer to print the annotation information and the image of the document on paper. | 30. A computer-implemented method, comprising: detecting, at a server including one or more processors, whether document editor software is currently executing at a computing device that is logged into an account associated with a user; detecting, at the server, whether a handheld mobile computing device is logged into the account associated with the user; in response to detecting that (i) the document editor software is currently executing at the computing device and (ii) both the computing device and the handheld mobile computing device are logged into the account: transmitting, from the server to the computing device, a first command that causes the document editing software to include a selectable command in one of its menus, the selectable command being configured to cause the handheld mobile computing device to obtain an image of a document currently being edited in the document editor software; receiving, at the server, an indication that the user selected the selectable command at the computing device; in response to receiving the indication, transmitting, from the server, a second command to the handheld mobile computing device, the second command causing the handheld mobile computing device to: (i) obtain the image of the document from at least one of the server and the computing device, and (ii) in response to obtaining the image of the document, automatically displaying the image of the document at a touch display of the handheld mobile computing device; receive, at the server, annotation information indicative of handwritten annotations made by the user to the image of the document via the touch display of the handwritten mobile computing device, the handwritten annotations having been made by the user in a locked editing mode of the handheld mobile computing device in which the rendering of the document was not modifiable and the handwritten annotations were overlaid to the rendering of the document in one or more layers; and at least one of: storing, at the server, the annotation information; transmitting, from the server to the computing device, the annotation information for at least one of (i) display at the computing device and (ii) storage at the computing device; and transmitting, from the server to a paper printer (i) directly or (ii) via the computing device, the annotation information and the image of the document, wherein receiving the annotation information and the image of the document causes the paper printer to print the annotation information and the image of the document on paper. 38. The computer-implemented method of claim 30 , wherein the handwritten annotations are made by the user via the touch display of the handheld mobile computing device using at least one of a finger and a stylus. | 0.538961 |
10,042,603 | 10 | 14 | 10. A method for providing a context-aware service of a user device, the method comprising: operating the user device in a rule configuration mode, a user interface for configuring a rule being displayed during the rule configuration mode; receiving, by an input unit of the user device, a first user input according to a guidance provided by the user device if the user device is operating in the rule configuration mode, the first user input being at least one of a natural language-based speech input or a natural language-based text input; in response to receiving the first user input, parsing the received first user input to extract and identifying a condition, an action, and a command, wherein the action is a function executable by one or more applications of the user device; configuring a rule with the condition and the action based on the parsed first user input; mapping the command to the rule in response to the configuring of the rule; storing the rule and the mapped command at the user device; switching the user device to a second mode different from the rule configuration mode; receiving, by the input unit, a second user input, wherein the second user input is one of a natural language-based text input or a natural language based speech input; and in response to receiving the second user input: determining whether the second user input corresponds to the command; activating, if the second user input corresponds to the command while the user device is in the second mode, the rule to detect, by a sensor of the user device, an event at the user device, which corresponds to the condition of the rule; and executing, if the detected event corresponds to the condition of the rule while the user device is in the second mode, the action corresponding to the condition. | 10. A method for providing a context-aware service of a user device, the method comprising: operating the user device in a rule configuration mode, a user interface for configuring a rule being displayed during the rule configuration mode; receiving, by an input unit of the user device, a first user input according to a guidance provided by the user device if the user device is operating in the rule configuration mode, the first user input being at least one of a natural language-based speech input or a natural language-based text input; in response to receiving the first user input, parsing the received first user input to extract and identifying a condition, an action, and a command, wherein the action is a function executable by one or more applications of the user device; configuring a rule with the condition and the action based on the parsed first user input; mapping the command to the rule in response to the configuring of the rule; storing the rule and the mapped command at the user device; switching the user device to a second mode different from the rule configuration mode; receiving, by the input unit, a second user input, wherein the second user input is one of a natural language-based text input or a natural language based speech input; and in response to receiving the second user input: determining whether the second user input corresponds to the command; activating, if the second user input corresponds to the command while the user device is in the second mode, the rule to detect, by a sensor of the user device, an event at the user device, which corresponds to the condition of the rule; and executing, if the detected event corresponds to the condition of the rule while the user device is in the second mode, the action corresponding to the condition. 14. The method of claim 10 , wherein the activating of the rule further comprises: releasing, when a rule release condition is satisfied in a state in which the rule is activated, the activated rule, and providing feedback associated with release information, the feedback including information notifying of the release of the rule. | 0.624434 |
6,088,675 | 16 | 17 | 16. An article of manufacture having computer-readable program means for representing SGML documents auditorially embodied thereon, the SGML document including text and at least one SGML tag, the article of manufacture comprising: (a) computer-readable program means (214) for assigning a unique sound to an SGML tag encountered in a document; (b) computer-readable program means (218) for producing the assigned sound whenever the SGML tag associated with the sound is encountered; and (c) computer-readable program means (220) for producing speech representing text encountered in the SGML document. | 16. An article of manufacture having computer-readable program means for representing SGML documents auditorially embodied thereon, the SGML document including text and at least one SGML tag, the article of manufacture comprising: (a) computer-readable program means (214) for assigning a unique sound to an SGML tag encountered in a document; (b) computer-readable program means (218) for producing the assigned sound whenever the SGML tag associated with the sound is encountered; and (c) computer-readable program means (220) for producing speech representing text encountered in the SGML document. 17. The article of claim 16 further comprising: (d) computer-readable program means for accepting input indicating selection of a particular SGML tag; and (e) computer-readable program means for auditorially displaying a new SGML document identified by the selected tag. | 0.501845 |
9,292,568 | 1 | 2 | 1. A method of query optimization, comprising: comparing a complexity measure of a client query received from a client application to a predetermined threshold, wherein the predetermined threshold is determined based on query execution data collected from a previous query; generating an optimized query by automatically modifying the client query without user input to reduce the complexity measure of the client query if the complexity measure of the client query exceeds the predetermined threshold; submitting the optimized query to a server application on a server; selecting a post-processing routine to be applied to a result set of the optimized query; applying the post-processing routine to the result set of the optimized query to generate a filtered result set; and forwarding the filtered result set to the client application. | 1. A method of query optimization, comprising: comparing a complexity measure of a client query received from a client application to a predetermined threshold, wherein the predetermined threshold is determined based on query execution data collected from a previous query; generating an optimized query by automatically modifying the client query without user input to reduce the complexity measure of the client query if the complexity measure of the client query exceeds the predetermined threshold; submitting the optimized query to a server application on a server; selecting a post-processing routine to be applied to a result set of the optimized query; applying the post-processing routine to the result set of the optimized query to generate a filtered result set; and forwarding the filtered result set to the client application. 2. The method of claim 1 , wherein the complexity measure of the client query is calculated using at least one of a type of operators in the client query, a number of operators in the client query, and a number of sub-queries. | 0.897738 |
10,157,226 | 8 | 9 | 8. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive a knowledge graph that is generated based on training data and an ontology for the training data, the training data including information associated with a subject of the ontology, and the ontology including: classes, and properties; convert the knowledge graph into knowledge graph embeddings, the knowledge graph embeddings including points in a k-dimensional metric space; receive additional ontology information; identify a new entity, in the additional ontology information, that is not present in the knowledge graph embeddings; generate revised knowledge graph embeddings that include an embedding for the new entity based on: a first average quantity of entities that are related to the knowledge graph and the new entity, and a second average quantity of entities that are related to the new entity and are not related to the knowledge graph; receive a query for information associated with the knowledge graph; generate candidate responses to the query based on the knowledge graph; score the candidate responses based on the revised knowledge graph embeddings; and identify a particular candidate response, of the candidate responses, based on scores for the candidate responses. | 8. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive a knowledge graph that is generated based on training data and an ontology for the training data, the training data including information associated with a subject of the ontology, and the ontology including: classes, and properties; convert the knowledge graph into knowledge graph embeddings, the knowledge graph embeddings including points in a k-dimensional metric space; receive additional ontology information; identify a new entity, in the additional ontology information, that is not present in the knowledge graph embeddings; generate revised knowledge graph embeddings that include an embedding for the new entity based on: a first average quantity of entities that are related to the knowledge graph and the new entity, and a second average quantity of entities that are related to the new entity and are not related to the knowledge graph; receive a query for information associated with the knowledge graph; generate candidate responses to the query based on the knowledge graph; score the candidate responses based on the revised knowledge graph embeddings; and identify a particular candidate response, of the candidate responses, based on scores for the candidate responses. 9. The non-transitory computer-readable medium of claim 8 , where the knowledge graph is generated based on a schema matching technique that determines semantic correspondences between the training data and the ontology. | 0.819079 |
9,876,814 | 1 | 6 | 1. A method comprising: at a computing device, classifying each one of first domain names as either a likely domain generation algorithm (DGA) domain name or a likely non-DGA domain name, based on one or more features of the first domain names, the classifying producing a first pool of likely DGA domain names; determining statistics regarding requests for the likely DGA domain names in the first pool to identify a second pool of likely DGA domain names out of the first pool, wherein, for each of the likely DGA domain names in the second pool, the statistics of the requests indicate a spike over a period of time, wherein a number of the likely DGA domain names in the second pool is less than a number of the likely DGA domain names in the first pool; identifying additional domain names that share an infrastructure with the likely DGA domain names in the second pool; and mitigating a security vulnerability related to one or more of the likely DGA domain names in the second pool and the additional domain names. | 1. A method comprising: at a computing device, classifying each one of first domain names as either a likely domain generation algorithm (DGA) domain name or a likely non-DGA domain name, based on one or more features of the first domain names, the classifying producing a first pool of likely DGA domain names; determining statistics regarding requests for the likely DGA domain names in the first pool to identify a second pool of likely DGA domain names out of the first pool, wherein, for each of the likely DGA domain names in the second pool, the statistics of the requests indicate a spike over a period of time, wherein a number of the likely DGA domain names in the second pool is less than a number of the likely DGA domain names in the first pool; identifying additional domain names that share an infrastructure with the likely DGA domain names in the second pool; and mitigating a security vulnerability related to one or more of the likely DGA domain names in the second pool and the additional domain names. 6. The method of claim 1 , wherein the identifying of additional domain names that use the infrastructure comprises identifying additional domain names that use a domain name server also used by one of the likely DGA domain names in the second pool. | 0.861667 |
9,818,398 | 6 | 7 | 6. The method of claim 4 , wherein determining whether the two or more results comprise an indication of a potential error that may cause the meaning of the first recognition result to differ from a meaning of the speech input comprises determining whether the first recognition result includes a first member of a set of words or phrases, each member of the set comprising a word or phrase and being associated with at least one other member of the set, and determining whether the second recognition result includes at least one other member associated with the first member of the set. | 6. The method of claim 4 , wherein determining whether the two or more results comprise an indication of a potential error that may cause the meaning of the first recognition result to differ from a meaning of the speech input comprises determining whether the first recognition result includes a first member of a set of words or phrases, each member of the set comprising a word or phrase and being associated with at least one other member of the set, and determining whether the second recognition result includes at least one other member associated with the first member of the set. 7. The method of claim 6 , wherein: the first member of the set of words or phrases is associated with a second member of the set with which the first member is acoustically confusable and that, when substituted for the first member in a recognition result, changes a medical meaning of the recognition result; and the determining whether the second recognition result includes the at least one other member associated with the first member of the set comprises determining whether the second recognition result includes the second member of the set. | 0.682448 |
8,396,709 | 1 | 17 | 1. A computer-implemented method, comprising: accessing audio data that includes encoded speech; accessing information that indicates a docking context of a client device, the docking context being associated with the audio data; identifying a plurality of language models; identifying multiple sets of weighting values for the plurality of language models, the multiple sets of weighting values comprising at least a first set of multiple weighting values that correspond to multiple language models of the plurality of language models, the first set of multiple weighting values being associated with a first key phrase, wherein the first set of multiple weighting values is used to bias selection of a language model when a user utters the first key phrase, and a second set of multiple weighting values that correspond to multiple language models of the plurality of language models, the second set of multiple weighting values being associated with a second key phrase, the second set of multiple weighting values being different from the first set of multiple weighting values, and the second key phrase being different from the first key phrase; determining that the docking context indicates docking of the client device with a docking station of a first type; based on determining that the docking context indicates docking of the client device with the docking station of the first type, selecting, from among the multiple sets of weighting values, the first set of multiple weighting values associated with the first key phrase; selecting at least a first language model of the plurality of language models using the first set of multiple weighting values associated with the first key phrase; and performing speech recognition on the audio data using the first language model to identify a transcription for a portion of the audio data. | 1. A computer-implemented method, comprising: accessing audio data that includes encoded speech; accessing information that indicates a docking context of a client device, the docking context being associated with the audio data; identifying a plurality of language models; identifying multiple sets of weighting values for the plurality of language models, the multiple sets of weighting values comprising at least a first set of multiple weighting values that correspond to multiple language models of the plurality of language models, the first set of multiple weighting values being associated with a first key phrase, wherein the first set of multiple weighting values is used to bias selection of a language model when a user utters the first key phrase, and a second set of multiple weighting values that correspond to multiple language models of the plurality of language models, the second set of multiple weighting values being associated with a second key phrase, the second set of multiple weighting values being different from the first set of multiple weighting values, and the second key phrase being different from the first key phrase; determining that the docking context indicates docking of the client device with a docking station of a first type; based on determining that the docking context indicates docking of the client device with the docking station of the first type, selecting, from among the multiple sets of weighting values, the first set of multiple weighting values associated with the first key phrase; selecting at least a first language model of the plurality of language models using the first set of multiple weighting values associated with the first key phrase; and performing speech recognition on the audio data using the first language model to identify a transcription for a portion of the audio data. 17. The computer-implemented method of claim 1 , further comprising: accessing second audio data that includes encoded speech; determining that the encoded speech included in the second audio data includes the first key phrase; based on determining that the encoded speech included in the second audio data includes the first key phrase, selecting, from among the multiple sets of weighting values, the first set of multiple weighting values associated with the first key phrase; selecting at least a first language model of the plurality of language models using the first set of multiple weighting values associated with the first key phrase; and performing speech recognition on the second audio data using the first language model to identify a transcription for a portion of the second audio data. | 0.72942 |
6,110,226 | 11 | 12 | 11. The method of claim 10, comprising the further step of performing optimizations on the machine-instruction-level code representation to produce an optimized machine-instruction-level code representation. | 11. The method of claim 10, comprising the further step of performing optimizations on the machine-instruction-level code representation to produce an optimized machine-instruction-level code representation. 12. The method of claim 11, comprising the further step of producing assembly code from the optimized machine-instruction-level code representation. | 0.913247 |
9,092,636 | 17 | 18 | 17. The method of claim 16 , wherein each of the plurality of registered entities included in the GED is generated by: generating a hash-value for a first entity that an organization protects from unauthorized disclosure; and associating the hash-value with metadata related to the first entity. | 17. The method of claim 16 , wherein each of the plurality of registered entities included in the GED is generated by: generating a hash-value for a first entity that an organization protects from unauthorized disclosure; and associating the hash-value with metadata related to the first entity. 18. The method of claim 17 , wherein the metadata related to the first entity includes one or more of: an entity type associated with the first entity; a location of the first entity within a particular document; or an origin information of a particular document. | 0.941058 |
10,089,292 | 12 | 16 | 12. In a computer network environment, a method for facilitating field content suggestions by associating forms with contexts using a training model, the method comprising: defining a plurality of form contexts, wherein the form contexts comprise a unique purpose, a circumstance, or a perspective of a representative form, and wherein each of the form contexts is defined by assigning to it a plurality of representative form features and by assigning a weighting to each of the representative form features, wherein the representative form features comprise non-text field characteristics, field labels, and other field-specific text characteristics; creating a training model for associating forms with respective form contexts, the training model trained using a collection of training forms; applying, by a processor of a computing device, the training model to a form to determine which of the plurality of form contexts to assign to a portion of the form wherein the training model identifies form features found in the portion of the form, correlates the identified form features to the representative form features of each of the form contexts, and assigns to the portion of the form the form context having a highest degree of correlation, and wherein the portion of the form comprises a plurality of fillable fields of the form; and identifying, by the processor and from the form context of the form, a field content suggestion for a fillable field within the form, the field content suggestion indicating content items selectable by a user to complete the fillable field. | 12. In a computer network environment, a method for facilitating field content suggestions by associating forms with contexts using a training model, the method comprising: defining a plurality of form contexts, wherein the form contexts comprise a unique purpose, a circumstance, or a perspective of a representative form, and wherein each of the form contexts is defined by assigning to it a plurality of representative form features and by assigning a weighting to each of the representative form features, wherein the representative form features comprise non-text field characteristics, field labels, and other field-specific text characteristics; creating a training model for associating forms with respective form contexts, the training model trained using a collection of training forms; applying, by a processor of a computing device, the training model to a form to determine which of the plurality of form contexts to assign to a portion of the form wherein the training model identifies form features found in the portion of the form, correlates the identified form features to the representative form features of each of the form contexts, and assigns to the portion of the form the form context having a highest degree of correlation, and wherein the portion of the form comprises a plurality of fillable fields of the form; and identifying, by the processor and from the form context of the form, a field content suggestion for a fillable field within the form, the field content suggestion indicating content items selectable by a user to complete the fillable field. 16. The method of claim 12 further comprising tagging the form with the identified form context. | 0.930029 |
8,135,727 | 13 | 16 | 13. The system of claim 12 , further comprising: receiving an activation of the increase interactive indicator, wherein the activation causes an additional selectable search parameter to be displayed. | 13. The system of claim 12 , further comprising: receiving an activation of the increase interactive indicator, wherein the activation causes an additional selectable search parameter to be displayed. 16. The system of claim 13 , wherein at least one selectable search parameter includes a metadata search attribute. | 0.949694 |
9,720,941 | 16 | 20 | 16. A computer-readable non-transitory storage medium storing instructions, wherein the instructions include instructions which, when executed by one or more processors, cause the one or more processors to perform steps of: from a workload set, automatically selecting a plurality of database query language statements for automatic tuning, wherein the workload set comprises multiple database query language statements and performance data for the multiple database query language statements; automatically tuning the plurality of database query language statements until one or more time periods for said tuning the plurality of database query language statements are reached or exceeded, thereby generating a plurality of tuning recommendations for a subset of database query language statements of said plurality of database query language statements, each tuning recommendation of said plurality of tuning recommendations being a tuning recommendation for a database query language statement of said subset of database query language statements; automatically testing the plurality of tuning recommendations against a database, wherein testing the plurality of tuning recommendations comprises, for one or more tuning recommendations of said plurality of tuning recommendations, automatically executing a particular database query language statement from said subset of database query language statements with said one or more tuning recommendations enabled thereby automatically generating an execution plan for the particular database query language statement based on said one or more tuning recommendations enabled for testing and automatically testing said execution plan against one or more other alternative execution plans for the particular database query language statement generated based on enabling, for testing, one or more other tuning recommendations from the plurality of tuning recommendations; based at least in part on automatically testing the plurality of tuning recommendations against the database, automatically implementing at least one tuning recommendation of said plurality of tuning recommendations and not implementing at least another tuning recommendation of said plurality of tuning recommendations. | 16. A computer-readable non-transitory storage medium storing instructions, wherein the instructions include instructions which, when executed by one or more processors, cause the one or more processors to perform steps of: from a workload set, automatically selecting a plurality of database query language statements for automatic tuning, wherein the workload set comprises multiple database query language statements and performance data for the multiple database query language statements; automatically tuning the plurality of database query language statements until one or more time periods for said tuning the plurality of database query language statements are reached or exceeded, thereby generating a plurality of tuning recommendations for a subset of database query language statements of said plurality of database query language statements, each tuning recommendation of said plurality of tuning recommendations being a tuning recommendation for a database query language statement of said subset of database query language statements; automatically testing the plurality of tuning recommendations against a database, wherein testing the plurality of tuning recommendations comprises, for one or more tuning recommendations of said plurality of tuning recommendations, automatically executing a particular database query language statement from said subset of database query language statements with said one or more tuning recommendations enabled thereby automatically generating an execution plan for the particular database query language statement based on said one or more tuning recommendations enabled for testing and automatically testing said execution plan against one or more other alternative execution plans for the particular database query language statement generated based on enabling, for testing, one or more other tuning recommendations from the plurality of tuning recommendations; based at least in part on automatically testing the plurality of tuning recommendations against the database, automatically implementing at least one tuning recommendation of said plurality of tuning recommendations and not implementing at least another tuning recommendation of said plurality of tuning recommendations. 20. The computer-readable non-transitory storage medium of claim 16 , wherein the testing said plurality of tuning recommendations further comprises measuring an execution time period for executing the particular database query language statement with said one or more tuning recommendations enabled. | 0.756888 |
7,937,348 | 23 | 24 | 23. A computer implemented method of correlating user profiles to software applications comprising the steps of: reading a first learning objective from a user profile from a storage medium; reading a second learning objective from a software application; determining a relevance of the first learning objective to the second learning objective; and adapting the software application in accordance with the determined relevance and updating the user profile in accordance with the determined relevance. | 23. A computer implemented method of correlating user profiles to software applications comprising the steps of: reading a first learning objective from a user profile from a storage medium; reading a second learning objective from a software application; determining a relevance of the first learning objective to the second learning objective; and adapting the software application in accordance with the determined relevance and updating the user profile in accordance with the determined relevance. 24. The computer implemented method of claim 23 , wherein said step of adapting the software application comprises applying a weighting factor to at least one of existing experience data in the user profile related to the learning objective of the software application and performance data related to the subsequent use of the software application. | 0.74928 |
8,027,977 | 4 | 5 | 4. The method of claim 1 wherein training includes minimizing an expected number of errors for the ensemble of document similarity classification models for the set of training samples. | 4. The method of claim 1 wherein training includes minimizing an expected number of errors for the ensemble of document similarity classification models for the set of training samples. 5. The method of claim 4 wherein minimizing an expected number of errors for the ensemble of document similarity classification models comprises: forming a set of individual class loss functions where each class is modeled by document model; obtaining the training set using a set of target document word vectors, a set of training document word vectors and a document similarity matrix; initially setting values of target document models of the ensemble; and while a stopping criteria has not been met, iterate where each training iteration includes for each document: computing a set of related documents; for each related document. assume a word vector for the document belongs to a related class; and for each document model in ensemble compute new model parameters; and update individual document models. | 0.698809 |
7,533,102 | 3 | 4 | 3. A method as claimed in claim 1 wherein populating the schema tree comprises: selecting a first node from the plurality of nodes in the walk through the language-specific metamodel, in accordance with a breadth-first selection algorithm; examining the respective schema element of the first node to determine a type of the elements, the type of the elements determined being a determined element type; and applying the predefined mapped relationship to the first node in accordance with the determined element type to generate the respective schema element. | 3. A method as claimed in claim 1 wherein populating the schema tree comprises: selecting a first node from the plurality of nodes in the walk through the language-specific metamodel, in accordance with a breadth-first selection algorithm; examining the respective schema element of the first node to determine a type of the elements, the type of the elements determined being a determined element type; and applying the predefined mapped relationship to the first node in accordance with the determined element type to generate the respective schema element. 4. A method as claimed in claim 3 wherein applying the predefined mapped relationship comprises: generating the respective schema element by creating a first object of a type determined by the predefined mapped relationship, the type of the object determined being a determined object type; specifying a first name for the first object; and setting all required attributes of the first object according to the determined object type. | 0.822976 |
8,185,865 | 1 | 12 | 1. A method for generating a biased layout for making an integrated circuit, comprising: (a) identifying a nominal layout defined by one or more cells, each cell having one or more transistors having transistor gate features with a nominal gate length; (b) identifying an annotated layout, the annotated layout itself provides information for identifying gate-length biasing of one or more of the transistor gate features in one or more cells of the nominal layout; and (c) producing a biased layout by modifying the nominal layout using the information provided by the annotated layout, such that the biasing modifies a gate length of those transistor gate features identified by the information of the annotated layout, the method implemented by a processor executing a program. | 1. A method for generating a biased layout for making an integrated circuit, comprising: (a) identifying a nominal layout defined by one or more cells, each cell having one or more transistors having transistor gate features with a nominal gate length; (b) identifying an annotated layout, the annotated layout itself provides information for identifying gate-length biasing of one or more of the transistor gate features in one or more cells of the nominal layout; and (c) producing a biased layout by modifying the nominal layout using the information provided by the annotated layout, such that the biasing modifies a gate length of those transistor gate features identified by the information of the annotated layout, the method implemented by a processor executing a program. 12. The method of claim 1 , wherein the information in the annotated layout further defines or identifies a shape or size parameters for biasing particular ones of the transistors. | 0.606987 |
8,135,589 | 11 | 12 | 11. The computer program product of claim 9 wherein the operations further comprise: receiving additional data associated with a first new model service request, wherein the additional data comprises a text representation of a word or phrase to be modeled, a user identifier identifying a speaker, and a specification of a type of model to be generated; determining, from the specification of the type of model, that a particular type of model is to be generated; and generating the speech recognition model as a model of the particular type. | 11. The computer program product of claim 9 wherein the operations further comprise: receiving additional data associated with a first new model service request, wherein the additional data comprises a text representation of a word or phrase to be modeled, a user identifier identifying a speaker, and a specification of a type of model to be generated; determining, from the specification of the type of model, that a particular type of model is to be generated; and generating the speech recognition model as a model of the particular type. 12. The computer program product of claim 11 wherein the operations further comprise: determining that the particular type of model is a speaker-independent type of model or a speaker-dependent type of model; generating a speaker-independent speech recognition model using the training database if it is determined that the particular type of model is a speaker-independent type of model; and generating a speaker-dependent speech recognition model using the received additional data if it is determined that the particular type of model is a speaker-dependent type of model. | 0.769447 |
9,715,877 | 1 | 4 | 1. A method for searching navigation system data including phonetic data and text data, the method comprising: storing the phonetic data and the text data in a storage device accessible from within a mobile platform, the phonetic data including a set of point-of-interest names in phonetic form, and the text data including at least a portion of the same set of point-of-interest names in text form; receiving a spoken utterance from a user; querying the phonetic data of the navigation system data with the spoken utterance to find a corresponding match; if a corresponding word-for-word match is not found via the querying of the phonetic data, processing the spoken utterance to produce a dictation text substantially corresponding to the spoken utterance, wherein the dictation text is tuned for speech that is typical of navigation destination entry types; and querying the text data of the navigation system data with the dictation text using an approximate string matching criteria and producing a results list associated therewith. | 1. A method for searching navigation system data including phonetic data and text data, the method comprising: storing the phonetic data and the text data in a storage device accessible from within a mobile platform, the phonetic data including a set of point-of-interest names in phonetic form, and the text data including at least a portion of the same set of point-of-interest names in text form; receiving a spoken utterance from a user; querying the phonetic data of the navigation system data with the spoken utterance to find a corresponding match; if a corresponding word-for-word match is not found via the querying of the phonetic data, processing the spoken utterance to produce a dictation text substantially corresponding to the spoken utterance, wherein the dictation text is tuned for speech that is typical of navigation destination entry types; and querying the text data of the navigation system data with the dictation text using an approximate string matching criteria and producing a results list associated therewith. 4. The method of claim 1 , further including providing the results list to the user for selection of a desired result. | 0.792254 |
8,934,278 | 7 | 19 | 7. A hybrid ternary content addressable memory (TCAM), comprising: a first TCAM stage configured to compare a first portion of a search word to a first portion of a stored word; and a second TCAM stage configured to compare a second portion of the search word to a second portion of the stored word when the first portion of the search word matches the first portion of the stored word, the first portion of the search word being different than the second portion of the search word, and the first TCAM stage being configured as a first type TCAM and the second TCAM stage being configured as a second type TCAM, the first type TCAM being different than the second type TCAM. | 7. A hybrid ternary content addressable memory (TCAM), comprising: a first TCAM stage configured to compare a first portion of a search word to a first portion of a stored word; and a second TCAM stage configured to compare a second portion of the search word to a second portion of the stored word when the first portion of the search word matches the first portion of the stored word, the first portion of the search word being different than the second portion of the search word, and the first TCAM stage being configured as a first type TCAM and the second TCAM stage being configured as a second type TCAM, the first type TCAM being different than the second type TCAM. 19. The TCAM of claim 7 , wherein the search word consists of N values, the first portion of the search word consists of M values, and the second portion of the search word consists of N-M values. | 0.951292 |
8,625,451 | 1 | 3 | 1. A method for non-intrusive mean opinion score estimation based on packet loss pattern, the method comprising: receiving a packet data stream; measuring the packet loss for the received data stream; calculating a probability of packet loss based on the measured packet loss; and calculating an estimated mean opinion score based on the calculated probability of packet loss using a function that maps probabilities of packet loss to measured mean opinion scores, wherein the function was derived by generating a plurality of probabilities of packet loss, and, for each generated probability of packet loss: generating, from a reference data stream, a degraded data stream suffering packet loss according to the generated probability, measuring a mean opinion score for the degraded data stream using an intrusive algorithm that operates on the contents of the data packets of the degraded data stream, and determining an association between the generated probability of packet loss and the calculated mean opinion score. | 1. A method for non-intrusive mean opinion score estimation based on packet loss pattern, the method comprising: receiving a packet data stream; measuring the packet loss for the received data stream; calculating a probability of packet loss based on the measured packet loss; and calculating an estimated mean opinion score based on the calculated probability of packet loss using a function that maps probabilities of packet loss to measured mean opinion scores, wherein the function was derived by generating a plurality of probabilities of packet loss, and, for each generated probability of packet loss: generating, from a reference data stream, a degraded data stream suffering packet loss according to the generated probability, measuring a mean opinion score for the degraded data stream using an intrusive algorithm that operates on the contents of the data packets of the degraded data stream, and determining an association between the generated probability of packet loss and the calculated mean opinion score. 3. The method of claim 1 wherein calculating an estimated mean opinion score based on the calculated probability of packet loss comprises calculating an estimated mean opinion score by using a mathematical function that uses the calculated probability of packet loss as input and that outputs the estimated mean opinion score. | 0.563003 |
7,561,780 | 37 | 42 | 37. An optical disc player for reproducing text subtitle streams recorded on an optical disc, the optical disc player comprising: an audio decoder configured to decode audio streams recorded on the optical disc into audio data; a video decoder configured to decode video streams recorded on the optical disc into video image data; a text subtitle decoder configured to decode a text subtitle stream recorded on the optical disc into text subtitle image data; and an image superimposition unit configured to superimpose the decoded text subtitle image data with the decoded video image data, wherein the text subtitle decoder comprises: a text subtitle processor configured to parse the text subtitle stream into composition information, rendering information, and text data for at least one region, the text data including one or more text strings for each region; a text renderer configured to render the text strings into graphic data for each region according to the rendering information; and a presentation controller configured to compose the rendered graphic data according to the composition information. | 37. An optical disc player for reproducing text subtitle streams recorded on an optical disc, the optical disc player comprising: an audio decoder configured to decode audio streams recorded on the optical disc into audio data; a video decoder configured to decode video streams recorded on the optical disc into video image data; a text subtitle decoder configured to decode a text subtitle stream recorded on the optical disc into text subtitle image data; and an image superimposition unit configured to superimpose the decoded text subtitle image data with the decoded video image data, wherein the text subtitle decoder comprises: a text subtitle processor configured to parse the text subtitle stream into composition information, rendering information, and text data for at least one region, the text data including one or more text strings for each region; a text renderer configured to render the text strings into graphic data for each region according to the rendering information; and a presentation controller configured to compose the rendered graphic data according to the composition information. 42. The optical disc player of claim 37 , wherein the text subtitle processor is configured to parse the text subtitle stream into the composition information including at least one of presentation time information, palette update information, and a region position for each region. | 0.828676 |
9,152,315 | 11 | 12 | 11. A mobile device supporting an Electronic Book (e-book) function, the mobile device comprising: a display unit for displaying e-book content, and highlighting guide items and text selected from the e-book content according to the guide items, wherein the guide items guide a user to select the text in the e-book content; a storage unit for storing the guide items and setting information, wherein the setting information is related to a mode for displaying a block that designates the text according to the guide items and a mode for estimating candidate locations according to anchor interactions and a controller for estimating the candidate locations to designate a block, based on the anchor interactions applied to the e-book content, displaying a first plurality of candidate anchors at corresponding candidate locations between first text items of the e-book content based on a first location where a first anchor interaction is input, determining a first candidate anchor from the first plurality of candidate anchors to be a first definite anchor when the first candidate anchor is selected, removing remaining candidate anchors of the first plurality of candidate anchors, except the first candidate anchor for a start location of a block, displaying a second plurality of candidate anchors at corresponding candidate locations between second text items of the e-book content based on a second location where a second anchor interaction is input, determining a second candidate anchor from the second plurality of candidate anchors to be a second definite anchor when the second candidate anchor is selected, removing remaining candidate anchors of the second plurality of candidate anchors, except the second candidate anchor for an end location of the block, and forming the block enclosing the text between the first definite anchor and the second definite anchor, wherein the first and second anchor interactions are input at locations corresponding to a start location of corresponding text or a location close to the start location. | 11. A mobile device supporting an Electronic Book (e-book) function, the mobile device comprising: a display unit for displaying e-book content, and highlighting guide items and text selected from the e-book content according to the guide items, wherein the guide items guide a user to select the text in the e-book content; a storage unit for storing the guide items and setting information, wherein the setting information is related to a mode for displaying a block that designates the text according to the guide items and a mode for estimating candidate locations according to anchor interactions and a controller for estimating the candidate locations to designate a block, based on the anchor interactions applied to the e-book content, displaying a first plurality of candidate anchors at corresponding candidate locations between first text items of the e-book content based on a first location where a first anchor interaction is input, determining a first candidate anchor from the first plurality of candidate anchors to be a first definite anchor when the first candidate anchor is selected, removing remaining candidate anchors of the first plurality of candidate anchors, except the first candidate anchor for a start location of a block, displaying a second plurality of candidate anchors at corresponding candidate locations between second text items of the e-book content based on a second location where a second anchor interaction is input, determining a second candidate anchor from the second plurality of candidate anchors to be a second definite anchor when the second candidate anchor is selected, removing remaining candidate anchors of the second plurality of candidate anchors, except the second candidate anchor for an end location of the block, and forming the block enclosing the text between the first definite anchor and the second definite anchor, wherein the first and second anchor interactions are input at locations corresponding to a start location of corresponding text or a location close to the start location. 12. The mobile device of claim 11 , wherein the controller estimates a start point candidate location as the start location of the block, based on the first location where the first anchor interaction is input; provides one of the first plurality of candidate anchors for guiding a start location of the block to a corresponding start point candidate location; determines the one of the first plurality of candidate anchors as the first definite anchor for the block start; estimates an end point candidate location as the end location of the block, based on the second location where the second anchor interaction is input after determining the first definite anchor; provides one of the second plurality of candidate anchors for guiding an end location of the block to a corresponding end point candidate location; and determines the one of the plurality of candidate anchors as the second definite anchor for the block end. | 0.500539 |
7,797,622 | 19 | 21 | 19. A system for detection of page numbers comprising: memory which stores instructions for: (a) identifying a plurality of text fragments associated with a plurality of pages of a document, from the identified text fragments; (b) identifying at least one sequence, each identified sequence comprising a plurality of terms, each term derived from a text fragment selected from the plurality text fragments, the terms of a sequence complying with at least one predefined numbering scheme which defines a form and an incremental state of the terms in a sequence that enforces an increase of the page number over a sequence of pages; (c) the at least one predefined numbering scheme excluding terms from a sequence which do not comply with an incremental state in which terms on each two consecutive pages vary by a constant value, the identifying of the at least one sequence comprising, for each page of a plurality of pages of the document in sequence: (d) identifying text fragments which comprise a term that complies with the form of the predefined numbering scheme; (e) for each of the identified fragments, determining if the term of the identified fragment complies with an incremental state accepted by an existing sequence and if so, adding the term to that sequence, the existing sequence comprising at least one term derived from a text fragment of a previous page of the document; and (f) for each of the terms which do not comply with an incremental state accepted by an existing sequence, considering the term as a potential start of a new sequence; (g) computing a subset of the identified sequences which cover at least some of the pages of the document, wherein the computing subset of the identified sequences comprises: for each of the identified sequences, defining the identified sequence as a series of nodes, each node representing a state of the sequence for a page of a plurality of consecutive pages, each node comprising a term or a hole, wherein a hole identifies the page as lacking a term of the sequence; selecting a subset of identified sequences based on assigned scores of nodes of the subset of identified sequences which cover at best the entire document, the assigned score of each node of the selected sequences being a function of at least one of: whether the node comprises a hole or a term, a number of terms in the sequence, and a coverage of the sequence; and (h) construing terms of the subset of sequences as page numbers of pages of the document; and a processor which executes the instructions. | 19. A system for detection of page numbers comprising: memory which stores instructions for: (a) identifying a plurality of text fragments associated with a plurality of pages of a document, from the identified text fragments; (b) identifying at least one sequence, each identified sequence comprising a plurality of terms, each term derived from a text fragment selected from the plurality text fragments, the terms of a sequence complying with at least one predefined numbering scheme which defines a form and an incremental state of the terms in a sequence that enforces an increase of the page number over a sequence of pages; (c) the at least one predefined numbering scheme excluding terms from a sequence which do not comply with an incremental state in which terms on each two consecutive pages vary by a constant value, the identifying of the at least one sequence comprising, for each page of a plurality of pages of the document in sequence: (d) identifying text fragments which comprise a term that complies with the form of the predefined numbering scheme; (e) for each of the identified fragments, determining if the term of the identified fragment complies with an incremental state accepted by an existing sequence and if so, adding the term to that sequence, the existing sequence comprising at least one term derived from a text fragment of a previous page of the document; and (f) for each of the terms which do not comply with an incremental state accepted by an existing sequence, considering the term as a potential start of a new sequence; (g) computing a subset of the identified sequences which cover at least some of the pages of the document, wherein the computing subset of the identified sequences comprises: for each of the identified sequences, defining the identified sequence as a series of nodes, each node representing a state of the sequence for a page of a plurality of consecutive pages, each node comprising a term or a hole, wherein a hole identifies the page as lacking a term of the sequence; selecting a subset of identified sequences based on assigned scores of nodes of the subset of identified sequences which cover at best the entire document, the assigned score of each node of the selected sequences being a function of at least one of: whether the node comprises a hole or a term, a number of terms in the sequence, and a coverage of the sequence; and (h) construing terms of the subset of sequences as page numbers of pages of the document; and a processor which executes the instructions. 21. The system of claim 19 , wherein the processor annotates the documents with page numbers comprising terms of the subset of sequences. | 0.91351 |
8,155,399 | 8 | 9 | 8. A method, comprising: acquiring image data for an image of a person; and aligning a template to the image data by maximizing a strong classifier score, wherein the strong classifier score is based on a plurality of weak classifiers defined by positive and negative training images; wherein the positive training images are obtained by warping image data according to ground truth shape parameters, and the negative training images are obtained by warping the image data according to perturbed shape parameters. | 8. A method, comprising: acquiring image data for an image of a person; and aligning a template to the image data by maximizing a strong classifier score, wherein the strong classifier score is based on a plurality of weak classifiers defined by positive and negative training images; wherein the positive training images are obtained by warping image data according to ground truth shape parameters, and the negative training images are obtained by warping the image data according to perturbed shape parameters. 9. The method of claim 8 , comprising recognizing facial expressions of the person based on the aligned template. | 0.720297 |
9,031,967 | 8 | 14 | 8. A computer program product comprising at least one non-transitory computer readable medium storing instructions translatable by a server computer implementing a natural language processing system to perform: determining whether a source string is present in a target string, wherein the source string and the target string represent text strings each comprising a sequence of characters that identify a vehicle characteristic, wherein the source string is from a first source communicatively connected to the server computer over a first network connection, wherein the target string is from a second source communicatively connected to the server computer over a second network connection, and wherein the first source and the second source employ different naming conventions for automotive data collected thereby; if the source string is present in the target string, outputting a match containing the source string and the target string; and if the source string is not present in the target string, computing a similarity factor based at least on a first set of parameters, wherein the first set of parameters comprises a Levenshtein edit distance parameter based on a comparison of characters in the source string and the target string, a single-word matches parameter based on a comparison of words in the source string and the target string, and a multi-word matches parameter based on a comparison of successive words in the source string and the target string, the similarity factor representing a measure of similarity between the source string and the target string; wherein the step of determining whether the source string is present in the target string further comprises: determining if an automotive base term that matches the source string is present in an automotive lexicon; utilizing the automotive base term to create a set of strings that includes one or more terms in the automotive lexicon; and comparing each string in the set of strings with the target string; and utilizing the match or the output to find from the first source, the second source, or both pricing information associated with multiple vehicles having a user-selected trim; wherein the pricing information comprises at least one trade-in price, at least one sale price, at least one list price, or a combination thereof; wherein utilizing the match to find pricing information associated with the vehicles having the user-selected trim comprises aggregating sales information from the first and second sources according to the source string, and determining a value of the vehicles having the user-selected trim based on the aggregated sales information; wherein at least a portion of the sales information is aggregated in real time in response to a user selecting the vehicles having the user-selected trim; and wherein the determined value of the vehicles having the user-selected trim is presented to the user and is dynamically updated to reflect at least the portion of the sales information aggregated in real time. | 8. A computer program product comprising at least one non-transitory computer readable medium storing instructions translatable by a server computer implementing a natural language processing system to perform: determining whether a source string is present in a target string, wherein the source string and the target string represent text strings each comprising a sequence of characters that identify a vehicle characteristic, wherein the source string is from a first source communicatively connected to the server computer over a first network connection, wherein the target string is from a second source communicatively connected to the server computer over a second network connection, and wherein the first source and the second source employ different naming conventions for automotive data collected thereby; if the source string is present in the target string, outputting a match containing the source string and the target string; and if the source string is not present in the target string, computing a similarity factor based at least on a first set of parameters, wherein the first set of parameters comprises a Levenshtein edit distance parameter based on a comparison of characters in the source string and the target string, a single-word matches parameter based on a comparison of words in the source string and the target string, and a multi-word matches parameter based on a comparison of successive words in the source string and the target string, the similarity factor representing a measure of similarity between the source string and the target string; wherein the step of determining whether the source string is present in the target string further comprises: determining if an automotive base term that matches the source string is present in an automotive lexicon; utilizing the automotive base term to create a set of strings that includes one or more terms in the automotive lexicon; and comparing each string in the set of strings with the target string; and utilizing the match or the output to find from the first source, the second source, or both pricing information associated with multiple vehicles having a user-selected trim; wherein the pricing information comprises at least one trade-in price, at least one sale price, at least one list price, or a combination thereof; wherein utilizing the match to find pricing information associated with the vehicles having the user-selected trim comprises aggregating sales information from the first and second sources according to the source string, and determining a value of the vehicles having the user-selected trim based on the aggregated sales information; wherein at least a portion of the sales information is aggregated in real time in response to a user selecting the vehicles having the user-selected trim; and wherein the determined value of the vehicles having the user-selected trim is presented to the user and is dynamically updated to reflect at least the portion of the sales information aggregated in real time. 14. The computer program product of claim 8 , wherein the multi-word matches parameter is computed by: a) reading the source string two consecutive words at a time; b) if a word combination of the two consecutive words is present in the target string, increasing a value of the multi-word matches parameter by one; c) repeating steps a) and b) until all words in the source string have been read; and d) dividing the value of the multi-word matches parameter by a total number of words in the target string. | 0.556818 |
7,716,235 | 1 | 12 | 1. A computer-implemented method for addressing spelling errors comprising: establishing a phonetic database having a plurality of phonetically equivalent formulas stored therein, each of the phonetically equivalent formulas being associated with at least one respective pronounceable unit; receiving an initial search string from a user through a search interface; wherein the initial search string is in a particular language of the user's preference; determining, from the phonetic database, an alternative pronounceable unit that is specified, by a phonetically equivalent formula of the plurality of phonetically equivalent formulas from the phonetic database, to be phonetically similar to a particular pronounceable unit that is represented within the initial search string; generating an alternative search string, in the particular language, based at least in part on the initial search string and the alternative pronounceable unit; and performing at least one of: (a) searching a data set for data items that are associated with the alternative search string, and displaying at least one search result that was obtained through the searching, or (b) outputting the alternative search string; wherein generating the alternative search string comprises generating a search string that contains the initial search string but in which at least one instance of the particular pronounceable unit has been replaced in the initial search string by the alternative pronounceable unit; wherein the method is performed by one or more self improving phonetic search engines. | 1. A computer-implemented method for addressing spelling errors comprising: establishing a phonetic database having a plurality of phonetically equivalent formulas stored therein, each of the phonetically equivalent formulas being associated with at least one respective pronounceable unit; receiving an initial search string from a user through a search interface; wherein the initial search string is in a particular language of the user's preference; determining, from the phonetic database, an alternative pronounceable unit that is specified, by a phonetically equivalent formula of the plurality of phonetically equivalent formulas from the phonetic database, to be phonetically similar to a particular pronounceable unit that is represented within the initial search string; generating an alternative search string, in the particular language, based at least in part on the initial search string and the alternative pronounceable unit; and performing at least one of: (a) searching a data set for data items that are associated with the alternative search string, and displaying at least one search result that was obtained through the searching, or (b) outputting the alternative search string; wherein generating the alternative search string comprises generating a search string that contains the initial search string but in which at least one instance of the particular pronounceable unit has been replaced in the initial search string by the alternative pronounceable unit; wherein the method is performed by one or more self improving phonetic search engines. 12. The method of claim 1 , wherein searching the data set for data items that are associated with the alternative search string comprises searching a set of e-mail messages for e-mail messages that contain the alternative search string. | 0.865188 |
9,552,549 | 9 | 13 | 9. A system for a ranking approach to training deep neural networks for multilabel image annotation, comprising: one or more computers; storage coupled to the one or more computers on which is stored a training data set including training examples, a label corpus, and a semantic structure; and a machine learning system deployed on the one or more computers, the machine learning system comprising a neural network and a neural network trainer, the neural network adapted to receive the label corpus and training examples from the training data set, generate respective label scores for each of at least two labels in the label corpus for at least one training example from the training data set, and receive updated weights, and the neural network trainer adapted to determine an error of the neural network based on a semantic ranking loss of the label scores and to determine the semantic ranking loss according to:
J=Σ i=1 n Σ j=1 c+ Σ k=1 c− D ( y c+ j ,y c− k )max(0,ρ− x i W c+ j +x i W c− k ) where W is a ranking function of the neural network, n is the number of training examples, x i is an ith training example, c+ is the number of positive labels for the training example x i , c− is the number of negative labels for the training example x i , ρ is a margin for hinge loss, y c+ j is the jth positive label, y c− k is kth negative label, D(y c+ j , y c− k ) is a function that evaluates the semantic distance between two labels, y c+ j and y c− k , x i W c+ j is the label score given to the jth positive label when the ranking function W is used to evaluate the training example x i , and x i W c− k is the label score given to the kth negative label when the ranking function W is used to evaluate the training example x i . | 9. A system for a ranking approach to training deep neural networks for multilabel image annotation, comprising: one or more computers; storage coupled to the one or more computers on which is stored a training data set including training examples, a label corpus, and a semantic structure; and a machine learning system deployed on the one or more computers, the machine learning system comprising a neural network and a neural network trainer, the neural network adapted to receive the label corpus and training examples from the training data set, generate respective label scores for each of at least two labels in the label corpus for at least one training example from the training data set, and receive updated weights, and the neural network trainer adapted to determine an error of the neural network based on a semantic ranking loss of the label scores and to determine the semantic ranking loss according to:
J=Σ i=1 n Σ j=1 c+ Σ k=1 c− D ( y c+ j ,y c− k )max(0,ρ− x i W c+ j +x i W c− k ) where W is a ranking function of the neural network, n is the number of training examples, x i is an ith training example, c+ is the number of positive labels for the training example x i , c− is the number of negative labels for the training example x i , ρ is a margin for hinge loss, y c+ j is the jth positive label, y c− k is kth negative label, D(y c+ j , y c− k ) is a function that evaluates the semantic distance between two labels, y c+ j and y c− k , x i W c+ j is the label score given to the jth positive label when the ranking function W is used to evaluate the training example x i , and x i W c− k is the label score given to the kth negative label when the ranking function W is used to evaluate the training example x i . 13. The system of claim 9 , wherein a label is a positive label for one of the at least one training example when the label has been predetermined to describe the content of the training example, and wherein a label is a negative label for the one of the at least one training example when the label has been predetermined to not describe the content of the training example. | 0.50133 |
9,176,668 | 14 | 15 | 14. The method of claim 1 , wherein the computer system is a mobile device, the touch screen is small, and the mobile device includes at least one of an accelerometer and a gyroscope, further comprising: if the mobile device includes the accelerometer, detecting with the accelerometer gestures that include taps on the mobile device or motion of the mobile device; and if the mobile device includes the gyroscope, detecting with the gyroscope gestures that include rotations of the mobile device. | 14. The method of claim 1 , wherein the computer system is a mobile device, the touch screen is small, and the mobile device includes at least one of an accelerometer and a gyroscope, further comprising: if the mobile device includes the accelerometer, detecting with the accelerometer gestures that include taps on the mobile device or motion of the mobile device; and if the mobile device includes the gyroscope, detecting with the gyroscope gestures that include rotations of the mobile device. 15. The method of claim 14 , wherein the mobile device includes a microphone, further comprising: in response to a seventh distinct combination of the determined direction and type of swipe gesture, actuating a voice to text input function and enabling a user to provide the text input using the microphone. | 0.885533 |
9,704,486 | 15 | 17 | 15. The computer-implemented method of claim 5 , wherein providing power to the network interface module causes the network interface module to transition from a deactivated state to an activated state. | 15. The computer-implemented method of claim 5 , wherein providing power to the network interface module causes the network interface module to transition from a deactivated state to an activated state. 17. The computer-implemented method of claim 15 , wherein communications sent via the network interface module are enabled while the network interface module is in the activated state. | 0.945691 |
7,870,087 | 59 | 65 | 59. A method of processing queries of databases, the method comprising: receiving a problem; parsing the problem into subproblems of suitable size to be processed by an analog processor; for each of the subproblems, setting a number of parameters of the analog processor to embed the subproblem into the analog processor; determining a subanswer to the subproblem from a final state of the analog processor. | 59. A method of processing queries of databases, the method comprising: receiving a problem; parsing the problem into subproblems of suitable size to be processed by an analog processor; for each of the subproblems, setting a number of parameters of the analog processor to embed the subproblem into the analog processor; determining a subanswer to the subproblem from a final state of the analog processor. 65. The method of claim 59 , further comprising: determining whether at least one of a number of subanswers is valid or invalid; and resubmitting a respective subproblem if the respective subanswer is determined to be invalid. | 0.856051 |
7,516,468 | 20 | 25 | 20. A system for receiving interactive television information and providing interactive television to a user, comprising: a receiver having a processor coupled to a memory, the memory having computer readable code which when executed by the processor causes the receiver to perform a method comprising: receiving a stream comprising a script and a compiled business data in binary form, wherein said business data comprises descriptions of products and wherein said business data is compiled for use by a set-top box; processing said compiled business data in binary form according to said script; and processing requests within a script, independent from a further user interaction, to map an item of the business data into a named position within an authored page template, wherein a video presentation of the business data will be presented to the user. | 20. A system for receiving interactive television information and providing interactive television to a user, comprising: a receiver having a processor coupled to a memory, the memory having computer readable code which when executed by the processor causes the receiver to perform a method comprising: receiving a stream comprising a script and a compiled business data in binary form, wherein said business data comprises descriptions of products and wherein said business data is compiled for use by a set-top box; processing said compiled business data in binary form according to said script; and processing requests within a script, independent from a further user interaction, to map an item of the business data into a named position within an authored page template, wherein a video presentation of the business data will be presented to the user. 25. The system of claim 20 further including: processing requests within a script to map an array of the business data into an array of locations within an authored page template, wherein a video presentation of the business data will be presented to the user. | 0.575163 |
8,909,528 | 8 | 13 | 8. A system comprising: at least one storage medium configured to store a plurality of machine-readable instructions; and at least one processor programmed to execute the plurality of machine-readable instructions to perform a method comprising; processing input speech to determine if clarification of the input speech is desired because the spoken dialog system has returned at least two speech recognition hypotheses having similar confidence values for at least a portion of the input speech; retrieving, if clarification is desired, a first list of items to be played back to the user; identifying acoustically confusable items on the first list of items using at least one measure of confusability; selecting, based, at least in part, on at least one rule in a collection of rules, a disambiguation strategy from a plurality of disambiguation strategies, wherein of the plurality of disambiguation strategies includes a first disambiguation strategy comprising spelling at least a portion of each of at least two of the items in the first list of items and a second disambiguation strategy comprising repeating at least two of the items in the first list of items and identifying a first letter of a word in each of the at least two of the items; generating a disambiguated list of items by modifying at least one of the acoustically confusable items on the first list according to the disambiguation strategy; and playing a prompt comprising the disambiguated list of items back to the user. | 8. A system comprising: at least one storage medium configured to store a plurality of machine-readable instructions; and at least one processor programmed to execute the plurality of machine-readable instructions to perform a method comprising; processing input speech to determine if clarification of the input speech is desired because the spoken dialog system has returned at least two speech recognition hypotheses having similar confidence values for at least a portion of the input speech; retrieving, if clarification is desired, a first list of items to be played back to the user; identifying acoustically confusable items on the first list of items using at least one measure of confusability; selecting, based, at least in part, on at least one rule in a collection of rules, a disambiguation strategy from a plurality of disambiguation strategies, wherein of the plurality of disambiguation strategies includes a first disambiguation strategy comprising spelling at least a portion of each of at least two of the items in the first list of items and a second disambiguation strategy comprising repeating at least two of the items in the first list of items and identifying a first letter of a word in each of the at least two of the items; generating a disambiguated list of items by modifying at least one of the acoustically confusable items on the first list according to the disambiguation strategy; and playing a prompt comprising the disambiguated list of items back to the user. 13. The system of claim 8 , wherein the disambiguation strategy is selected based on a type of acoustic confusion between the acoustically confusable items. | 0.834746 |
8,131,755 | 12 | 13 | 12. The computer implemented method of claim 1 wherein: comparing at least a portion of the search query against a knowledge-base further includes assigning a score to the subject matter based upon a confidence level of a comparison; and assigning a score to the subject matter determined by the comparison is based upon a confidence of the comparison. | 12. The computer implemented method of claim 1 wherein: comparing at least a portion of the search query against a knowledge-base further includes assigning a score to the subject matter based upon a confidence level of a comparison; and assigning a score to the subject matter determined by the comparison is based upon a confidence of the comparison. 13. The computer implemented method of claim 12 , wherein scores resulting from the comparing at least a portion of the search query against a knowledge-base are lower than the scores resulting from comparing at least a portion of the search query against a plurality of entity lists. | 0.852544 |
6,081,829 | 1 | 8 | 1. A method for processing documents in a network environment in a customized fashion using a browser, the method comprising the steps of: receiving, by a redirector from the browser, at least one request to store custom information associated with a selected network document; storing the associated custom information in the redirector; receiving, by the redirector from the browser, a request for the selected network document; redirecting at least a portion of the request for the selected network document to a network server hosting the selected document, thereby retrieving the selected document; retrieving the custom information; modifying the selected document, by the redirector, so as to replace each original network address within the selected document by a corresponding new network address pointing to the redirector; and transmitting, by the redirector to the browser, the selected network document and a custom response derived using the custom information. | 1. A method for processing documents in a network environment in a customized fashion using a browser, the method comprising the steps of: receiving, by a redirector from the browser, at least one request to store custom information associated with a selected network document; storing the associated custom information in the redirector; receiving, by the redirector from the browser, a request for the selected network document; redirecting at least a portion of the request for the selected network document to a network server hosting the selected document, thereby retrieving the selected document; retrieving the custom information; modifying the selected document, by the redirector, so as to replace each original network address within the selected document by a corresponding new network address pointing to the redirector; and transmitting, by the redirector to the browser, the selected network document and a custom response derived using the custom information. 8. The method of claim 1, further comprising: receiving from a second browser, at least one more request for the selected network document; redirecting at least a portion of the request for the selected network document to a network server hosting the selected document, thereby retrieving the selected document; retrieving the custom information; and transmitting the selected network document and a custom response derived using the custom information to the browser. | 0.509414 |
7,769,755 | 1 | 6 | 1. A query language system, comprising: at least one processor; and at least one computer-readable storage medium storing computer-executable instructions that, when executed by the at least one processor, cause the at least one processor to implement: a query component configured to specify operations for one or more items in a data set; and an aggregator component configured to identify one or more keys associated with the data set, the one or more keys configured to be supplied to multiple aggregators configured to perform direct aggregations from the one or more keys to determine at least one aggregated value for the data set, wherein the aggregator component comprises at least one of an initialization function, an aggregate method or a terminate function, wherein the aggregator component further comprises a merge function configured to aggregate values from the multiple aggregators; an enumerator component configured to process aggregate results, wherein the enumerator component is associated with a hash table or a dictionary to facilitate the aggregations; a translation component configured to facilitate aggregate processing, wherein the translation component is configured to employ a composite argument or a composite result to process the aggregate values, wherein the translation component combines at least two different aggregators of the multiple aggregators into a single aggregator; an instruction for determining binding rules to be employed during language translations, wherein the determining, based, at least, on whether the binding rules are met, whether to use aggregate functions or aggregator patterns, wherein when the binding rules are met, the aggregator patterns are used in conjunction with the binding rules, and wherein when the binding rules are not met, the aggregate functions are used, wherein the processing the aggregate results is based on the determining binding rules. | 1. A query language system, comprising: at least one processor; and at least one computer-readable storage medium storing computer-executable instructions that, when executed by the at least one processor, cause the at least one processor to implement: a query component configured to specify operations for one or more items in a data set; and an aggregator component configured to identify one or more keys associated with the data set, the one or more keys configured to be supplied to multiple aggregators configured to perform direct aggregations from the one or more keys to determine at least one aggregated value for the data set, wherein the aggregator component comprises at least one of an initialization function, an aggregate method or a terminate function, wherein the aggregator component further comprises a merge function configured to aggregate values from the multiple aggregators; an enumerator component configured to process aggregate results, wherein the enumerator component is associated with a hash table or a dictionary to facilitate the aggregations; a translation component configured to facilitate aggregate processing, wherein the translation component is configured to employ a composite argument or a composite result to process the aggregate values, wherein the translation component combines at least two different aggregators of the multiple aggregators into a single aggregator; an instruction for determining binding rules to be employed during language translations, wherein the determining, based, at least, on whether the binding rules are met, whether to use aggregate functions or aggregator patterns, wherein when the binding rules are met, the aggregator patterns are used in conjunction with the binding rules, and wherein when the binding rules are not met, the aggregate functions are used, wherein the processing the aggregate results is based on the determining binding rules. 6. The system of claim 1 , wherein the translation component is configured to employ a composite argument or a composite result to process an aggregate value. | 0.70412 |
8,126,878 | 1 | 3 | 1. An apparatus for transforming multi-source medical research documents comprised of: a housing support structure which inter-operably connects an alpha numeric data entry component support and, at least one data storage component; a network connection component which enables the device to connect to the internet to download the medical research documents from multiple sources; a first screen and a second screen pivotally connected and symmetrical; wherein said first screen displays a first user interface and said second screen displays a second user interface with the first user interface and the second user interface each displaying separate data; a first processor configured to perform a first algorithmic search for said multi-source medical research documents and storing said multi-source medical research documents in a plurality of medical research data files stored on said at least one data storage component; a first user interface configured to display a search result including a plurality of medical research documents, configured to create customized abstractions by adding tags, annotations and outlines to user identified text components, and configured to further search within the first search result to perform a second algorithmic search; wherein said first processor further configured to create text abstraction functions by linking groups of text from the medical research documents, assigning a same identifier to commonly tagged attributes in the text components of the multi-source medical research documents, the text components comprising keywords, concepts and phrases, and storing the result into a relational database stored in one of the storage devices; the plurality of multi-source medical research data files which contain data structures and data values are used by a second processor to create and display a user defined hierarchal data structure and personalized research document file based on the information stored in the relational database; the second processor configured to create said user defined hierarchal data structure to display said plurality of transformed medical research documents and create a personalized research document file which includes hierarchal links systematically connecting multi-source medical research documents; the second user interface configured to display said personal research document; wherein said second processor is further configured to transform said multi-source medical research documents displayed on said first user interface to create a user defined interface on said second display, which reflects a hierarchal linking structure created by said user; and wherein said second processor is further configured to coordinate the display of said plurality of documents on the first display by allowing user to identify and select the corresponding abstract data from the hierarchical linking structure displayed on the second display. | 1. An apparatus for transforming multi-source medical research documents comprised of: a housing support structure which inter-operably connects an alpha numeric data entry component support and, at least one data storage component; a network connection component which enables the device to connect to the internet to download the medical research documents from multiple sources; a first screen and a second screen pivotally connected and symmetrical; wherein said first screen displays a first user interface and said second screen displays a second user interface with the first user interface and the second user interface each displaying separate data; a first processor configured to perform a first algorithmic search for said multi-source medical research documents and storing said multi-source medical research documents in a plurality of medical research data files stored on said at least one data storage component; a first user interface configured to display a search result including a plurality of medical research documents, configured to create customized abstractions by adding tags, annotations and outlines to user identified text components, and configured to further search within the first search result to perform a second algorithmic search; wherein said first processor further configured to create text abstraction functions by linking groups of text from the medical research documents, assigning a same identifier to commonly tagged attributes in the text components of the multi-source medical research documents, the text components comprising keywords, concepts and phrases, and storing the result into a relational database stored in one of the storage devices; the plurality of multi-source medical research data files which contain data structures and data values are used by a second processor to create and display a user defined hierarchal data structure and personalized research document file based on the information stored in the relational database; the second processor configured to create said user defined hierarchal data structure to display said plurality of transformed medical research documents and create a personalized research document file which includes hierarchal links systematically connecting multi-source medical research documents; the second user interface configured to display said personal research document; wherein said second processor is further configured to transform said multi-source medical research documents displayed on said first user interface to create a user defined interface on said second display, which reflects a hierarchal linking structure created by said user; and wherein said second processor is further configured to coordinate the display of said plurality of documents on the first display by allowing user to identify and select the corresponding abstract data from the hierarchical linking structure displayed on the second display. 3. The apparatus for transforming multi-source medical research documents of claim 1 wherein said software component for abstraction allows completion and submission of assignments on said at least one abstracting interface. | 0.796364 |
7,979,442 | 1 | 9 | 1. A method of a server device, comprising: analyzing a media data of a client device to determine at least one meta-data identifier associated with the media data; automatically populating a new mark-up language file using an existing media collection data associated with certain items of the media data wherein the new mark-up language file comprises a non-nesting language without section terminators; and using a widget chosen from a group comprising of a party widget, a personal detail widget, a tag widget, a guestbook widget, an internal messaging widget, a share widget, a photo widget, a tuned-in now widget, a post widget, a reviews widget, and a live event widget to the new mark-up language file; wherein the widget is a drag and drop widget, and wherein a content data created using the post widget is automatically displayed on the new mark-up language file and at least one of an artist mark-up language file, an album mark-up language file, a particular item mark-up language file, and a fan club mark-up language file. | 1. A method of a server device, comprising: analyzing a media data of a client device to determine at least one meta-data identifier associated with the media data; automatically populating a new mark-up language file using an existing media collection data associated with certain items of the media data wherein the new mark-up language file comprises a non-nesting language without section terminators; and using a widget chosen from a group comprising of a party widget, a personal detail widget, a tag widget, a guestbook widget, an internal messaging widget, a share widget, a photo widget, a tuned-in now widget, a post widget, a reviews widget, and a live event widget to the new mark-up language file; wherein the widget is a drag and drop widget, and wherein a content data created using the post widget is automatically displayed on the new mark-up language file and at least one of an artist mark-up language file, an album mark-up language file, a particular item mark-up language file, and a fan club mark-up language file. 9. The method of claim 1 wherein the new mark-up language file includes a 30 second media segment of certain items of the media data that is associated with the existing media-collection data. | 0.737705 |
9,904,560 | 1 | 9 | 1. A computer system for collecting and monitoring performance data for a plurality of application programming interfaces (APIs), comprising: a hardware memory device that stores program instructions; and a processor that executes the program instructions and causes the computer system to: obtain one or more various measurements of performance of the APIs on one or more computing devices operably connected to a network; and assess a performance status for each of the APIs based on the obtained one or more various measurements of performance; display the performance status for each of the APIs; initiate a live API call to a running application on the one or more computing devices using parameters of a method of one of the APIs; and receive data in an open standard format used by the API for transmitting data from a software application on the one or more computing devices, wherein the processor that executes the program instructions further causes the computer system to: display at least a portion of a dashboard including the performance status for each API and the APIs, detect a first input on the dashboard that initiates a comparison of a keyword indicative of a particular API to all fields of JavaScript Object Notation (JSON) objects that have been used to define the APIs; in response to detecting the first input, display methods of the particular API in a first additional window; detect a second input at a location of a method on the first additional window; in response to detecting the second input, display parameters of the method in a second additional window; detect a third input at a location of a mechanism on the second additional window; and in response to detecting the third input, initiate a live API call to a running application on one or more computing devices using the parameters of the method of the particular API. | 1. A computer system for collecting and monitoring performance data for a plurality of application programming interfaces (APIs), comprising: a hardware memory device that stores program instructions; and a processor that executes the program instructions and causes the computer system to: obtain one or more various measurements of performance of the APIs on one or more computing devices operably connected to a network; and assess a performance status for each of the APIs based on the obtained one or more various measurements of performance; display the performance status for each of the APIs; initiate a live API call to a running application on the one or more computing devices using parameters of a method of one of the APIs; and receive data in an open standard format used by the API for transmitting data from a software application on the one or more computing devices, wherein the processor that executes the program instructions further causes the computer system to: display at least a portion of a dashboard including the performance status for each API and the APIs, detect a first input on the dashboard that initiates a comparison of a keyword indicative of a particular API to all fields of JavaScript Object Notation (JSON) objects that have been used to define the APIs; in response to detecting the first input, display methods of the particular API in a first additional window; detect a second input at a location of a method on the first additional window; in response to detecting the second input, display parameters of the method in a second additional window; detect a third input at a location of a mechanism on the second additional window; and in response to detecting the third input, initiate a live API call to a running application on one or more computing devices using the parameters of the method of the particular API. 9. The computer system of claim 1 , wherein the one or more various measurements of performance of the APIs are obtained from stubs on one or more computing devices operably connected to a network. | 0.788627 |
9,836,482 | 8 | 11 | 8. A computer program product, stored on a computer-readable storage device that, when executed by data processing apparatus, is operable to cause the data processing apparatus to perform operations comprising: obtaining images from first image results responsive to a first query, wherein each of a plurality of the obtained images is associated with a score and user behavior data wherein the user behavior data represents interactions of users with the obtained image when the obtained image was presented as a search result for the first query; selecting a plurality of the obtained images as a plurality of selected images, each image of the plurality of selected images having respective user behavior data that satisfies a threshold; associating each image of the plurality of the selected images with one or more annotations based on analysis of content of the selected image, the associating comprising: providing the plurality of the selected images to each of a plurality of different computer image annotators that each visually analyze an image to identify particular visual features in the images; receiving, from the plurality of computer image annotators, the annotations derived from visual analysis of the images to identify particular visual features in the images; and providing the first query and the annotations to a plurality of different machine learning system generated classifiers to associate the first query with one or more categories wherein a respective plurality of the annotations is provided as input to each of the classifiers, and wherein at least one of the categories specifies a presence of one of the particular visual features in an image; receiving a second query, wherein the second query is the same or similar to the first query; obtaining second images responsive to the second query, wherein each of the second images is associated with a respective first rank so that the second images are arranged according to a first order; modifying the respective first rank of one or more of the second images based on one or more of the categories associated with the first query so that the second images are re-ordered according to a second order. | 8. A computer program product, stored on a computer-readable storage device that, when executed by data processing apparatus, is operable to cause the data processing apparatus to perform operations comprising: obtaining images from first image results responsive to a first query, wherein each of a plurality of the obtained images is associated with a score and user behavior data wherein the user behavior data represents interactions of users with the obtained image when the obtained image was presented as a search result for the first query; selecting a plurality of the obtained images as a plurality of selected images, each image of the plurality of selected images having respective user behavior data that satisfies a threshold; associating each image of the plurality of the selected images with one or more annotations based on analysis of content of the selected image, the associating comprising: providing the plurality of the selected images to each of a plurality of different computer image annotators that each visually analyze an image to identify particular visual features in the images; receiving, from the plurality of computer image annotators, the annotations derived from visual analysis of the images to identify particular visual features in the images; and providing the first query and the annotations to a plurality of different machine learning system generated classifiers to associate the first query with one or more categories wherein a respective plurality of the annotations is provided as input to each of the classifiers, and wherein at least one of the categories specifies a presence of one of the particular visual features in an image; receiving a second query, wherein the second query is the same or similar to the first query; obtaining second images responsive to the second query, wherein each of the second images is associated with a respective first rank so that the second images are arranged according to a first order; modifying the respective first rank of one or more of the second images based on one or more of the categories associated with the first query so that the second images are re-ordered according to a second order. 11. The program product of claim 8 , wherein one of the categories indicates that the first query is a diverse query, and increasing the scores of one or more of the second images that is associated with a respective annotation indicating that the second image is diverse. | 0.532646 |
9,953,049 | 2 | 6 | 2. The method of claim 1 , wherein the respective lengths assigned to a link are determined based on a function of the number of outgoing links from the source page of the link. | 2. The method of claim 1 , wherein the respective lengths assigned to a link are determined based on a function of the number of outgoing links from the source page of the link. 6. The method of claim 2 , wherein the function for the length of the link is also a function of a weight of the link. | 0.949659 |
8,103,709 | 13 | 14 | 13. A computer program stored on a non-transitory computer-readable medium with a method for invention life cycle tracking, the program comprising computer-executable steps for: providing a data storage configured to store a plurality of documents, including a first document and a second document; interacting with a user, from an invention disclosure module in a computer processor device, to tag the first document with an attribute indicating an invention, the invention being one of a plurality of inventions, when the first document is stored in the data storage and is not previously filed in an official intellectual property office; prompting the user, from a document creation module in the computer processor device, automatically without manual intervention, to select one of the plurality of inventions previously tagged to one of the plurality of documents, as the invention to which the second document is directed, when the second document is initially created; and tagging the second document with the attribute indicating the invention, when the second document is initially stored in the data storage, wherein the first and second documents collectively reflect progress in the invention life cycle, the attribute is in a predetermined hierarchy of a plurality of attributes, tagging one of the documents, which had not previously been tagged, with the attribute causes the one of the documents to be associated with the attribute and with parent attributes of the attribute according to the predetermined hierarchy, for later retrieval of the documents by searching for the invention and the parent attributes. | 13. A computer program stored on a non-transitory computer-readable medium with a method for invention life cycle tracking, the program comprising computer-executable steps for: providing a data storage configured to store a plurality of documents, including a first document and a second document; interacting with a user, from an invention disclosure module in a computer processor device, to tag the first document with an attribute indicating an invention, the invention being one of a plurality of inventions, when the first document is stored in the data storage and is not previously filed in an official intellectual property office; prompting the user, from a document creation module in the computer processor device, automatically without manual intervention, to select one of the plurality of inventions previously tagged to one of the plurality of documents, as the invention to which the second document is directed, when the second document is initially created; and tagging the second document with the attribute indicating the invention, when the second document is initially stored in the data storage, wherein the first and second documents collectively reflect progress in the invention life cycle, the attribute is in a predetermined hierarchy of a plurality of attributes, tagging one of the documents, which had not previously been tagged, with the attribute causes the one of the documents to be associated with the attribute and with parent attributes of the attribute according to the predetermined hierarchy, for later retrieval of the documents by searching for the invention and the parent attributes. 14. The computer program of claim 13 , wherein the second document is one of: a draft patent application, a white paper, a patent application, a patent, and a license; thereby to track the invention over the invention life cycle including at least two of the draft patent application, the white paper, the patent application, the patent, and the license. | 0.610132 |
8,719,261 | 1 | 7 | 1. A method implemented by a computing device, the method comprising: receiving, from a user device, a search query for video content listings in a video catalog; identifying, based on the search query, a set of relevant video assets from an index of the catalog content; extracting, from the set of relevant video assets, a subset of the relevant video assets, wherein the subset is determined based on filtering usage metrics, for each video asset in the set of relevant video assets, against three different aspects of the search query; calculating a popularity value for each video asset in the subset of the relevant video assets; ranking, based on the respective popularity values, each video asset in the subset of the relevant video assets to form a ranked list; appending, to the ranked list, a remainder of the video assets from the set of relevant video assets; and sending, to the user device, a response to the search query that includes the ranked list and the remainder of the video assets from the set of relevant video assets. | 1. A method implemented by a computing device, the method comprising: receiving, from a user device, a search query for video content listings in a video catalog; identifying, based on the search query, a set of relevant video assets from an index of the catalog content; extracting, from the set of relevant video assets, a subset of the relevant video assets, wherein the subset is determined based on filtering usage metrics, for each video asset in the set of relevant video assets, against three different aspects of the search query; calculating a popularity value for each video asset in the subset of the relevant video assets; ranking, based on the respective popularity values, each video asset in the subset of the relevant video assets to form a ranked list; appending, to the ranked list, a remainder of the video assets from the set of relevant video assets; and sending, to the user device, a response to the search query that includes the ranked list and the remainder of the video assets from the set of relevant video assets. 7. The method of claim 1 , wherein the search query includes: a keyword search, or a browsing category selection. | 0.934908 |
9,424,510 | 4 | 5 | 4. The adaptive fuzzy rule controlling system according to claim 3 , wherein the fuzzy rule links one membership function fir the performance parameter at one specified level to one membership function for the configuration of the storage devices at another specified level. | 4. The adaptive fuzzy rule controlling system according to claim 3 , wherein the fuzzy rule links one membership function fir the performance parameter at one specified level to one membership function for the configuration of the storage devices at another specified level. 5. The adaptive fuzzy rule controlling system according to claim 4 , wherein a fuzzy inference is used to obtain the configuration of the storage devices with at least one given performance parameter by the degrees defined by the membership functions. | 0.885178 |
7,555,711 | 22 | 23 | 22. A storage device storing instructions that, when executed, cause a machine to perform operations comprising: receiving logical blocks extracted from the electronic document including a text block comprising text lines each encompassed by a respective bounding rectangle; extending edges of ones of the bounding rectangles to at least one boundary without changing layout relationships among the logical blocks in the electronic document; generating a text layout boundary from extended and unextended edges of the bounding rectangles; and storing a description of the text layout boundary in a machine-readable medium. | 22. A storage device storing instructions that, when executed, cause a machine to perform operations comprising: receiving logical blocks extracted from the electronic document including a text block comprising text lines each encompassed by a respective bounding rectangle; extending edges of ones of the bounding rectangles to at least one boundary without changing layout relationships among the logical blocks in the electronic document; generating a text layout boundary from extended and unextended edges of the bounding rectangles; and storing a description of the text layout boundary in a machine-readable medium. 23. The storage device of claim 22 , wherein the instructions cause the machine to perform operations comprising identifying at least one boundary to which ones of the bounding rectangles are extendable without changing layout relationships among logical blocks in the electronic document. | 0.523102 |
9,179,250 | 14 | 15 | 14. A non-transitory computer-readable storage medium comprising executable computer program code, the computer program code comprising instructions for: obtaining a plurality of labelled context slices derived from context data associated with a user, each labelled context slice including a time and a user context label and having one of a stay type and a travel type; identifying a plurality of transitions between the labelled context slices, each transition from a source context slice to a destination context slice, a time of the source context slice being within a threshold time of a time of the destination context slice, and identified in response to determining that the source context slice and the destination context slice both have stay types and both have durations equaling or exceeding a threshold duration; determining a plurality of transition rules based on the identified plurality of transitions, each transition rule corresponding to a probability of transition from a source context label to a destination context label; and creating the customized recommendation agent incorporating the plurality of transition rules, the customized recommendation agent configured to provide a recommendation to the user responsive to a current context slice comprising a current time and a current context label; obtaining the current context slice from context data associated with the user; identifying one or more transition rules corresponding to one or more transitions from the current context label to one or more destination context labels; selecting a recommendation for the user from a corpus of recommendations based on the one or more transition rules, the selected recommendation corresponding to a recommended context label selected from the one or more destination context labels; and providing the recommendation for presentation to the user. | 14. A non-transitory computer-readable storage medium comprising executable computer program code, the computer program code comprising instructions for: obtaining a plurality of labelled context slices derived from context data associated with a user, each labelled context slice including a time and a user context label and having one of a stay type and a travel type; identifying a plurality of transitions between the labelled context slices, each transition from a source context slice to a destination context slice, a time of the source context slice being within a threshold time of a time of the destination context slice, and identified in response to determining that the source context slice and the destination context slice both have stay types and both have durations equaling or exceeding a threshold duration; determining a plurality of transition rules based on the identified plurality of transitions, each transition rule corresponding to a probability of transition from a source context label to a destination context label; and creating the customized recommendation agent incorporating the plurality of transition rules, the customized recommendation agent configured to provide a recommendation to the user responsive to a current context slice comprising a current time and a current context label; obtaining the current context slice from context data associated with the user; identifying one or more transition rules corresponding to one or more transitions from the current context label to one or more destination context labels; selecting a recommendation for the user from a corpus of recommendations based on the one or more transition rules, the selected recommendation corresponding to a recommended context label selected from the one or more destination context labels; and providing the recommendation for presentation to the user. 15. The non-transitory computer-readable storage medium of claim 14 , wherein the computer program code further comprises instructions for: identifying a reason why the recommendation was selected; and presenting the reason to the user in conjunction with the recommendation. | 0.757067 |
8,301,436 | 28 | 29 | 28. The hardware computer readable storage media of claim 27 wherein rendering information comprising rendering an option to the user as a function of the data in accordance with the input that has been received. | 28. The hardware computer readable storage media of claim 27 wherein rendering information comprising rendering an option to the user as a function of the data in accordance with the input that has been received. 29. The hardware computer readable storage media of claim 28 wherein rendering information comprises rendering a plurality of options to the user as a function of the data in accordance with the input that has been received. | 0.930478 |
8,086,624 | 6 | 11 | 6. A computer-implemented method for determining a proximity between a content fragment and an advertisement, comprising: receiving a content fragment from a user; determining a set of content keywords associated with the content fragment; selecting an advertisement for display to the user based on an initial topical match between the content keywords and the advertisement; determining a set of ad keywords associated with the advertisement; mapping the ad keywords to at least one keyword cluster, where each keyword cluster is a group of terms related to a topic of the advertisement; computing a first probability that the ad keywords occur in the at least one keyword cluster; computing a second probability that the content keywords occur in the at least one keyword cluster; determining a threshold value based in part on at least one of the content keywords and the ad keywords; and determining the topical proximity between the content fragment and the advertisement from the first probability, the second probability, and the threshold value. | 6. A computer-implemented method for determining a proximity between a content fragment and an advertisement, comprising: receiving a content fragment from a user; determining a set of content keywords associated with the content fragment; selecting an advertisement for display to the user based on an initial topical match between the content keywords and the advertisement; determining a set of ad keywords associated with the advertisement; mapping the ad keywords to at least one keyword cluster, where each keyword cluster is a group of terms related to a topic of the advertisement; computing a first probability that the ad keywords occur in the at least one keyword cluster; computing a second probability that the content keywords occur in the at least one keyword cluster; determining a threshold value based in part on at least one of the content keywords and the ad keywords; and determining the topical proximity between the content fragment and the advertisement from the first probability, the second probability, and the threshold value. 11. The method of claim 6 , wherein the first probability is calculated using an average Bayesian probability function and the second probability is calculated using an average Bayesian probability function, and wherein determining the topical proximity further includes comparing the difference between the first probability and the second probability to the threshold value in order to determine a measure of topicality. | 0.542299 |
8,738,418 | 13 | 14 | 13. The method of claim 9 , wherein the user is a merchant; and the set of financial transaction based statistics includes a first set of statistics of purchases from peers of the merchant. | 13. The method of claim 9 , wherein the user is a merchant; and the set of financial transaction based statistics includes a first set of statistics of purchases from peers of the merchant. 14. The method of claim 13 , wherein the set of financial transaction based statistics further includes a second set of statistics of purchases from the merchant presented in relation to the first set of statistics of purchases from peers of the merchant. | 0.855606 |
9,250,805 | 1 | 8 | 1. A method for entering a string of symbols, the method comprising: generating for display a sequence of symbols arranged in a row, wherein the symbols are grouped in groupings; monitoring user navigation between the groupings of symbols; determining a navigation pace based on the monitored user navigation, the navigation pace representing an interval of time taken by the user to navigate from a first grouping of symbols to a second grouping of symbols; receiving a user input to navigate to a third grouping of symbols; and selecting symbols for the third grouping of symbols based on the determined navigation pace in response to receiving the user input. | 1. A method for entering a string of symbols, the method comprising: generating for display a sequence of symbols arranged in a row, wherein the symbols are grouped in groupings; monitoring user navigation between the groupings of symbols; determining a navigation pace based on the monitored user navigation, the navigation pace representing an interval of time taken by the user to navigate from a first grouping of symbols to a second grouping of symbols; receiving a user input to navigate to a third grouping of symbols; and selecting symbols for the third grouping of symbols based on the determined navigation pace in response to receiving the user input. 8. The method of claim 1 , further comprising: generating for display the sequence of symbols on the first device; and receiving the user input to navigate to the third grouping of symbols on the first device. | 0.868719 |
8,471,846 | 1 | 2 | 1. A method performed by a computer system for determining a position in an image of an object, comprising: displaying a volume rendering of image data acquired from the object, pointing at a structure of interest displayed in the volume rendering of the image data, generating a viewing ray profile comprising information characterizing a ray miming through said structure of interest, selecting a contextual profile from various contextual profiles, each of said contextual profiles comprising a representative ray profile representing a viewing ray profile of a structure and comprising profile information, and determining a position within said structure of interest based on said profile information of said selected contextual profile in the case that the representative ray profile of said selected contextual profile matches with at least a part of said viewing ray profile. | 1. A method performed by a computer system for determining a position in an image of an object, comprising: displaying a volume rendering of image data acquired from the object, pointing at a structure of interest displayed in the volume rendering of the image data, generating a viewing ray profile comprising information characterizing a ray miming through said structure of interest, selecting a contextual profile from various contextual profiles, each of said contextual profiles comprising a representative ray profile representing a viewing ray profile of a structure and comprising profile information, and determining a position within said structure of interest based on said profile information of said selected contextual profile in the case that the representative ray profile of said selected contextual profile matches with at least a part of said viewing ray profile. 2. The method according to claim 1 , wherein the image is a medical image of a patient and the structure is an anatomical structure of the patient. | 0.81941 |
9,633,075 | 4 | 7 | 4. A method as in claim 1 further comprising: causing the engine to reference the rule catalog to generate a further re-written query plan by applying a third query plan re-write rule to the re-written query plan. | 4. A method as in claim 1 further comprising: causing the engine to reference the rule catalog to generate a further re-written query plan by applying a third query plan re-write rule to the re-written query plan. 7. A method as in claim 4 wherein the rule catalog receives a user input specifying a sequence of applying the first query plan re-write rule prior to application of the third query plan re-write rule. | 0.936951 |
9,495,128 | 14 | 17 | 14. The wireless computing device of claim 10 receiving a second speech input via a wireless communications device; receiving a second touch gesture via the wireless communications device, wherein the touch gesture indicates the area of the document on which an action is to be performed and the speech indicates the action to be performed on the document area. | 14. The wireless computing device of claim 10 receiving a second speech input via a wireless communications device; receiving a second touch gesture via the wireless communications device, wherein the touch gesture indicates the area of the document on which an action is to be performed and the speech indicates the action to be performed on the document area. 17. The wireless computing device of claim 14 wherein the second speech input comprises a search command and wherein the touch gesture comprises the area of the document to be searched. | 0.938863 |
10,106,173 | 14 | 16 | 14. The method of claim 13 , further comprises determining whether the explicit user request has been previously stored at the level of abstraction. | 14. The method of claim 13 , further comprises determining whether the explicit user request has been previously stored at the level of abstraction. 16. The method of claim 14 , wherein the explicit request is stored at the level of abstraction determined by a classification of user input into the system. | 0.936282 |
8,775,932 | 1 | 10 | 1. A color management system comprising: a non-transitory computer readable memory which stores a guided natural language interface, the guided natural language interface comprising a set of issue description templates, each of the issue description templates being configured for guiding a user in formulating a problem statement, the user-formulated problem statement characterizing, in natural language, a perceived problem related to color identified in an input document and color of the input document when rendered on an associated printer; and a plurality of automated problem detectors which operate on an input document, each of the automated problem detectors being configured for automatically identifying a respective color-related problem when there is an expected difference in color between the input document and color of the input document when it is rendered using characteristics of a specific printer, each detector being configured to provide input to the guided natural language interface when the detector detects the color-related problem for the input document, the detector input specifying one of the set of issue description templates or being used for partially filling in one of the issue description templates based on the identified color-related problem; the guided natural language interface further comprising a natural language rendering engine, executed by a processor, which is configured for receiving information input by at least one of the user and at least one of the problem detectors, and which instantiates one of the issue description templates in response to receiving the information input by the at least one of the user and the at least one problem detector, the natural language rendering engine configured for presenting the problem statement and accepting user input to refine the problem statement in accordance with options provided from the instantiated template, and communicating information based on the refined problem statement to an associated color management problem corrector. | 1. A color management system comprising: a non-transitory computer readable memory which stores a guided natural language interface, the guided natural language interface comprising a set of issue description templates, each of the issue description templates being configured for guiding a user in formulating a problem statement, the user-formulated problem statement characterizing, in natural language, a perceived problem related to color identified in an input document and color of the input document when rendered on an associated printer; and a plurality of automated problem detectors which operate on an input document, each of the automated problem detectors being configured for automatically identifying a respective color-related problem when there is an expected difference in color between the input document and color of the input document when it is rendered using characteristics of a specific printer, each detector being configured to provide input to the guided natural language interface when the detector detects the color-related problem for the input document, the detector input specifying one of the set of issue description templates or being used for partially filling in one of the issue description templates based on the identified color-related problem; the guided natural language interface further comprising a natural language rendering engine, executed by a processor, which is configured for receiving information input by at least one of the user and at least one of the problem detectors, and which instantiates one of the issue description templates in response to receiving the information input by the at least one of the user and the at least one problem detector, the natural language rendering engine configured for presenting the problem statement and accepting user input to refine the problem statement in accordance with options provided from the instantiated template, and communicating information based on the refined problem statement to an associated color management problem corrector. 10. The system of claim 1 , wherein the instantiated template includes a plurality of field nodes, each of the plurality of field nodes listing a plurality of user selectable options displayable to a user. | 0.879977 |
8,321,396 | 1 | 7 | 1. A processor-implemented system for automatically extracting by-line information in a document, wherein said document contains a single news article, comprising: a non-transitory computer storage medium storing: a detagging module configured to remove formatting tags from said document to create a de-tagged version of said document; a headline detection module configured to detect a set of potential headlines of the document from a title meta-tag of the document; a headline evaluation module configured to select a candidate headline from the set of potential headlines, wherein the headline evaluation module evaluates the potential headlines from the set of potential headlines in order of lengths of the potential headlines, by: identifying a location of the selected candidate headline being evaluated in a de-tagged version of the document, verifying the selected candidate headline as comprising a complete line at the identified location in the de-tagged content, verifying the length of the selected candidate headline exceeds a minimum length in the de-tagged content, and ensuring that the selected candidate headline comprises regular text in the de-tagged version of said document; and a by-line extraction module configured to extract the by-line information from the de-tagged version of said document using the location of the selected candidate headline, wherein the selected candidate headline is the longest of the set of potential headlines, wherein the headline detection module is configured to detect the selected candidate headline from the de-tagged version of the document, and wherein in response to the selected candidate headline's not being detected in the de-tagged version of the document, selecting the next longest remaining of the set of potential headlines as the selected candidate headline. | 1. A processor-implemented system for automatically extracting by-line information in a document, wherein said document contains a single news article, comprising: a non-transitory computer storage medium storing: a detagging module configured to remove formatting tags from said document to create a de-tagged version of said document; a headline detection module configured to detect a set of potential headlines of the document from a title meta-tag of the document; a headline evaluation module configured to select a candidate headline from the set of potential headlines, wherein the headline evaluation module evaluates the potential headlines from the set of potential headlines in order of lengths of the potential headlines, by: identifying a location of the selected candidate headline being evaluated in a de-tagged version of the document, verifying the selected candidate headline as comprising a complete line at the identified location in the de-tagged content, verifying the length of the selected candidate headline exceeds a minimum length in the de-tagged content, and ensuring that the selected candidate headline comprises regular text in the de-tagged version of said document; and a by-line extraction module configured to extract the by-line information from the de-tagged version of said document using the location of the selected candidate headline, wherein the selected candidate headline is the longest of the set of potential headlines, wherein the headline detection module is configured to detect the selected candidate headline from the de-tagged version of the document, and wherein in response to the selected candidate headline's not being detected in the de-tagged version of the document, selecting the next longest remaining of the set of potential headlines as the selected candidate headline. 7. The system of claim 1 wherein the by-line extraction module extracts a string representing a source of the document that is located within a minimum distance from the location of the potential headline. | 0.749389 |
7,734,458 | 1 | 3 | 1. A translating apparatus of an image forming system, comprising: a translating unit of the image forming system for translating document data into another language; an output unit for outputting the translated document data translated by said translating unit in printed form; a mode setting unit for setting the translating apparatus in a first mode or a second mode; and a controller of the image forming system; wherein, in a case where the first mode is set, said controller controls said translating unit so as to translate the document data into a plurality of languages different from one another and different from an original language of the document data, and controls said output unit so as to output the translated document data by language groups of printed documents, the language of each language group of printed documents consisting of one of the plurality of languages, and wherein, in a case where the second mode is set, said controller controls said translating unit so as to translate the document data into a plurality of languages different from one another and different from the original language of the document data, and controls said output unit so as to output the document data by groups, each group of the document data comprising a printed document in the original language and printed documents of the translated document data translated in each of the plurality of languages with each of the printed documents being distinct from one another. | 1. A translating apparatus of an image forming system, comprising: a translating unit of the image forming system for translating document data into another language; an output unit for outputting the translated document data translated by said translating unit in printed form; a mode setting unit for setting the translating apparatus in a first mode or a second mode; and a controller of the image forming system; wherein, in a case where the first mode is set, said controller controls said translating unit so as to translate the document data into a plurality of languages different from one another and different from an original language of the document data, and controls said output unit so as to output the translated document data by language groups of printed documents, the language of each language group of printed documents consisting of one of the plurality of languages, and wherein, in a case where the second mode is set, said controller controls said translating unit so as to translate the document data into a plurality of languages different from one another and different from the original language of the document data, and controls said output unit so as to output the document data by groups, each group of the document data comprising a printed document in the original language and printed documents of the translated document data translated in each of the plurality of languages with each of the printed documents being distinct from one another. 3. The translating apparatus as recited in claim 1 , wherein said output unit further includes a display for displaying the translated document data. | 0.845436 |
7,904,451 | 13 | 14 | 13. The method of claim 1 , further comprising linking the audience profile to a concept instance having a property value. | 13. The method of claim 1 , further comprising linking the audience profile to a concept instance having a property value. 14. The method of claim 13 , wherein the property value is chosen from the group consisting of a feature, a differentiator, a legal note, a need, an application, a frequently asked question, and a success story. | 0.918909 |
10,127,226 | 1 | 3 | 1. A method for performing a dialog between a machine and at least one human speaker, comprising the following steps, implemented by said machine: a) identifying said human speaker with a processor; b) extracting from a database a speaker profile comprising a plurality of dialog variables, at least one value being assigned to at least one of said plurality of dialog variables; c) receiving with a sound acquisition device at least one sentence originating from said speaker, analyzing said sentence or each said sentence originating from said speaker with the processor to extract therefrom at least one value to be assigned to at least one dialog variable of said speaker profile and store said value or each said value in said speaker profile in the database; and d) formulating with the processor and emitting at least one response sentence through a sound emission device as a function of at least of said sentence received and interpreted in step c) and of one said dialog variable of said speaker profile; wherein said sentence or at least one said sentence received and analyzed in step c) is a sentence spoken by said speaker spontaneously or following a non-interrogative sentence emitted by the sound emission device of said machine; and wherein the analysis of said sentence or at least one sentence originating from said speaker and the formulation of said or at least one response sentence are performed by means of a plurality of sentence patterns represented by respective syntax trees. | 1. A method for performing a dialog between a machine and at least one human speaker, comprising the following steps, implemented by said machine: a) identifying said human speaker with a processor; b) extracting from a database a speaker profile comprising a plurality of dialog variables, at least one value being assigned to at least one of said plurality of dialog variables; c) receiving with a sound acquisition device at least one sentence originating from said speaker, analyzing said sentence or each said sentence originating from said speaker with the processor to extract therefrom at least one value to be assigned to at least one dialog variable of said speaker profile and store said value or each said value in said speaker profile in the database; and d) formulating with the processor and emitting at least one response sentence through a sound emission device as a function of at least of said sentence received and interpreted in step c) and of one said dialog variable of said speaker profile; wherein said sentence or at least one said sentence received and analyzed in step c) is a sentence spoken by said speaker spontaneously or following a non-interrogative sentence emitted by the sound emission device of said machine; and wherein the analysis of said sentence or at least one sentence originating from said speaker and the formulation of said or at least one response sentence are performed by means of a plurality of sentence patterns represented by respective syntax trees. 3. The method for performing a dialog as claimed claim 1 , wherein at least some of said sentence patterns contain at least one pointer to at least one set of terms that are interchangeable in a sentence, called concept. | 0.554656 |
7,693,818 | 1 | 9 | 1. A system that facilitates providing query results to a user, comprising: a processor; system memory; an interface that receives data related to a query associated with a specific user; a user log component that comprises at least a repository of historic activities, behaviors, or combinations thereof specific to a user, wherein the logged historic user activities and/or behaviors are related to prospective interactions with objects related to the query results; a rank component that provides ranked query results adapted in relation to a specific user log, wherein the query results are at least in part prioritized utilizing a transition probability determination related to the specific user for user transitions between objects related to prospective query results based on historical user activity, user behavior, or combinations thereof, wherein the transition probability determination comprises utilizing a weighting technique that implements the following representation of a Markov model: M = ( M 11 M 12 M 13 M 21 M 22 M 23 M 31 M 32 M 33 ) , where ∑ y M iy = 1 Equation 1 and wherein the weighting technique uses the following to normalize aggregated counts related to the document to identify a probability: M ij = M ij ∑ y M iy , where i is a first document and j is a disparate document, and M ij represents the probability of transitioning from document i to document j, and wherein the weighting technique uses the following to calculate a user rank of a document, wherein the user rank is recursively defined by the user rank of documents and user has followed to locate the document:
UserRank( X )=(1− d )+ d Σ X P PR ( P→X )(UserRank( P )), where d is a damping factor and P→X is going to X from P; and a results providing component configured to provide prioritized query results that incorporate transition probability related to a document. | 1. A system that facilitates providing query results to a user, comprising: a processor; system memory; an interface that receives data related to a query associated with a specific user; a user log component that comprises at least a repository of historic activities, behaviors, or combinations thereof specific to a user, wherein the logged historic user activities and/or behaviors are related to prospective interactions with objects related to the query results; a rank component that provides ranked query results adapted in relation to a specific user log, wherein the query results are at least in part prioritized utilizing a transition probability determination related to the specific user for user transitions between objects related to prospective query results based on historical user activity, user behavior, or combinations thereof, wherein the transition probability determination comprises utilizing a weighting technique that implements the following representation of a Markov model: M = ( M 11 M 12 M 13 M 21 M 22 M 23 M 31 M 32 M 33 ) , where ∑ y M iy = 1 Equation 1 and wherein the weighting technique uses the following to normalize aggregated counts related to the document to identify a probability: M ij = M ij ∑ y M iy , where i is a first document and j is a disparate document, and M ij represents the probability of transitioning from document i to document j, and wherein the weighting technique uses the following to calculate a user rank of a document, wherein the user rank is recursively defined by the user rank of documents and user has followed to locate the document:
UserRank( X )=(1− d )+ d Σ X P PR ( P→X )(UserRank( P )), where d is a damping factor and P→X is going to X from P; and a results providing component configured to provide prioritized query results that incorporate transition probability related to a document. 9. The system of claim 1 , further comprising a weight component that implements accruing weight to the query result based at least in part upon the transition probability. | 0.695035 |
9,858,609 | 1 | 3 | 1. An information processing apparatus comprising: at least one memory operable to store program code; at least one processor operable to read the program code and operate as instructed by the program code, the program code including: object search code that causes the at least one processor to receive a search word through a search condition setting area in a web page from a user and search based on the received search word; category identification code that causes the at least one processor to, when a first search word has been completed and entered by the user and a second search word has not been completed and is being currently inputted by the user, identify, from a plurality of search categories, a child search category based on the first search word and at least two different parent search categories to which the child search category belongs; attribute value acquisition code that causes the at least one processor to, in response to the second search word being currently input by the user, in a state in which the child search category and the at least two different parent search categories have been identified, acquire, from a storage that stores at least one attribute name, indicating a name of an attribute of an item corresponding to each of the plurality of search categories, and stores attribute values, indicating values of the attribute of the item corresponding to each of the plurality of search categories and associated with each of the at least one attribute name, a plurality of attribute values, each corresponding to the child search category that belongs to each of the at least two different parent search categories, based on the second search word that is being currently inputted; and presentation control code that causes the at least one processor to present, at the search condition setting area in the web page, for each of the plurality of attribute values acquired by the attribute value acquisition code, a combination of the child search category, a corresponding parent search category, an acquired attribute value and an attribute name associated with the acquired attribute value, as a candidate for a search condition such that the child search category, the corresponding parent search category, the attribute value, and the attribute name of the combination are concurrently selected upon selection of the combination by the user, wherein a plurality of combinations are respectively presented for the at least two different parent search categories, and attribute values, acquired based on the second search word that is being currently inputted, are associated with different attribute names in the combinations corresponding to different parent search categories, wherein the object search code causes the at least one processor to, when any combination of the combinations presented by the presentation control code is selected by the user, search for at least one search object that is included in the child search category having been identified and the corresponding parent search category and has an attribute indicated by the selected combination. | 1. An information processing apparatus comprising: at least one memory operable to store program code; at least one processor operable to read the program code and operate as instructed by the program code, the program code including: object search code that causes the at least one processor to receive a search word through a search condition setting area in a web page from a user and search based on the received search word; category identification code that causes the at least one processor to, when a first search word has been completed and entered by the user and a second search word has not been completed and is being currently inputted by the user, identify, from a plurality of search categories, a child search category based on the first search word and at least two different parent search categories to which the child search category belongs; attribute value acquisition code that causes the at least one processor to, in response to the second search word being currently input by the user, in a state in which the child search category and the at least two different parent search categories have been identified, acquire, from a storage that stores at least one attribute name, indicating a name of an attribute of an item corresponding to each of the plurality of search categories, and stores attribute values, indicating values of the attribute of the item corresponding to each of the plurality of search categories and associated with each of the at least one attribute name, a plurality of attribute values, each corresponding to the child search category that belongs to each of the at least two different parent search categories, based on the second search word that is being currently inputted; and presentation control code that causes the at least one processor to present, at the search condition setting area in the web page, for each of the plurality of attribute values acquired by the attribute value acquisition code, a combination of the child search category, a corresponding parent search category, an acquired attribute value and an attribute name associated with the acquired attribute value, as a candidate for a search condition such that the child search category, the corresponding parent search category, the attribute value, and the attribute name of the combination are concurrently selected upon selection of the combination by the user, wherein a plurality of combinations are respectively presented for the at least two different parent search categories, and attribute values, acquired based on the second search word that is being currently inputted, are associated with different attribute names in the combinations corresponding to different parent search categories, wherein the object search code causes the at least one processor to, when any combination of the combinations presented by the presentation control code is selected by the user, search for at least one search object that is included in the child search category having been identified and the corresponding parent search category and has an attribute indicated by the selected combination. 3. The information processing apparatus according to claim 1 , wherein the presentation control code causes the at least one processor to determine a priority of presentation of the combinations on the basis of a relationship between the selected child search category and the second search word. | 0.755776 |
8,311,957 | 18 | 20 | 18. A tangible, non-transitory, computer-readable medium, comprising code configured to direct a processor to: generate a classification score for an instance of an unlabeled case; generate a desirability factor for the unlabeled case, based, at least in part, on the classification score, the desirability factor corresponding to a level of desirability of selecting the unlabeled case as the next case for which to obtain training data; and select the unlabeled case as the next case for which to obtain input based, at least in part, on the desirability factor. | 18. A tangible, non-transitory, computer-readable medium, comprising code configured to direct a processor to: generate a classification score for an instance of an unlabeled case; generate a desirability factor for the unlabeled case, based, at least in part, on the classification score, the desirability factor corresponding to a level of desirability of selecting the unlabeled case as the next case for which to obtain training data; and select the unlabeled case as the next case for which to obtain input based, at least in part, on the desirability factor. 20. The tangible, non-transitory, computer-readable medium of claim 18 , comprising code configured to direct the processor to generate an uncertainty value for the instance based, at least in part, on the proximity of the classification score to the classification threshold, and the desirability factor is based, at least in part, on the uncertainty values. | 0.773359 |
10,097,631 | 13 | 14 | 13. The method of claim 1 , wherein a content item comprises an interactive feature comprising a conversation thread of one or more user comments. | 13. The method of claim 1 , wherein a content item comprises an interactive feature comprising a conversation thread of one or more user comments. 14. The method of claim 13 , wherein synchronizing the first interactive feature and the second interactive feature comprises synchronizing the content items of the first document and the second document at the same time. | 0.948676 |
8,543,834 | 13 | 17 | 13. A system comprising: a data processing apparatus; and a data store storing instructions executable by the data processing apparatus that, upon execution by the data processing apparatus, cause the data processing apparatus to perform operations comprising: receiving, by the data processing apparatus that is operating in a locked mode, audio data that encodes an utterance of a user, wherein the locked mode prevents the data processing apparatus from performing at least one action; providing, while the data processing apparatus is operating in the locked mode, the audio data to a voice biometric engine and a voice action engine; receiving, while the data processing apparatus is operating in the locked mode, data from the voice action engine that identifies a voice action that is associated with the utterance; determining, while the data processing apparatus is operating in the locked mode, that the voice action that is associated with the utterance is classified as a voice action that requires authentication to perform; based on determining that the voice action that is associated with the utterance is classified as a voice action that requires authentication to perform, queuing, while the data processing apparatus is operating in the locked mode, data that identifies the voice action that is associated with the utterance; after queuing the data that identifies the voice action that is associated with the utterance, receiving, while the data processing apparatus is operating in the locked mode, an indication from the voice biometric engine that the user has been biometrically authenticated; and in response to receiving the indication, placing the data processing apparatus in an unlocked mode, and triggering the voice action engine to process a voice the queued action that is associated with the utterance. | 13. A system comprising: a data processing apparatus; and a data store storing instructions executable by the data processing apparatus that, upon execution by the data processing apparatus, cause the data processing apparatus to perform operations comprising: receiving, by the data processing apparatus that is operating in a locked mode, audio data that encodes an utterance of a user, wherein the locked mode prevents the data processing apparatus from performing at least one action; providing, while the data processing apparatus is operating in the locked mode, the audio data to a voice biometric engine and a voice action engine; receiving, while the data processing apparatus is operating in the locked mode, data from the voice action engine that identifies a voice action that is associated with the utterance; determining, while the data processing apparatus is operating in the locked mode, that the voice action that is associated with the utterance is classified as a voice action that requires authentication to perform; based on determining that the voice action that is associated with the utterance is classified as a voice action that requires authentication to perform, queuing, while the data processing apparatus is operating in the locked mode, data that identifies the voice action that is associated with the utterance; after queuing the data that identifies the voice action that is associated with the utterance, receiving, while the data processing apparatus is operating in the locked mode, an indication from the voice biometric engine that the user has been biometrically authenticated; and in response to receiving the indication, placing the data processing apparatus in an unlocked mode, and triggering the voice action engine to process a voice the queued action that is associated with the utterance. 17. The system of claim 13 , wherein the voice action is derived from a transcription of the utterance. | 0.885045 |
8,346,879 | 13 | 14 | 13. An electronic out-of-office message analysis system comprising: a mailer module comprising instructions stored in memory for receiving an electronic out-of-office message generated by a user in a natural language, the electronic out-of-office message including a time window of absence and an alternate named contact; a temporal expression module comprising instructions stored in memory for identifying and normalizing a temporal expression from text content of the user's out-of-office message to generate a normalized representation of the time window of absence; a named entity recognition module comprising instructions stored in memory for identifying the alternate named contact from the text content of the user's out-of-office message by recognizing named entities in the user's out-of-office message and cross-referencing the recognized named entities with a named entity directory for identifying an alternate named contact corresponding to one of the recognized named entities; a representation module comprising instructions stored in memory for generating a structured representation of the user's out-of-office message which includes a reference to the user, a reference to the identified alternate named contact, and the normalized representation of the time window; an out-of-office module comprising instructions stored in memory for storing the structured representation of the out-of-office message in a database and notifying the user that a conflict exists between the user's out-of-office message and an out-of-office message of the identified alternate named contact, by comparing the normalized representation of the time window included in the structured representation of the user's out-of-office message with a normalized representation of a time window included in a structured representation of the identified alternate named contact's out-of-office message; and a processor which executes the instructions. | 13. An electronic out-of-office message analysis system comprising: a mailer module comprising instructions stored in memory for receiving an electronic out-of-office message generated by a user in a natural language, the electronic out-of-office message including a time window of absence and an alternate named contact; a temporal expression module comprising instructions stored in memory for identifying and normalizing a temporal expression from text content of the user's out-of-office message to generate a normalized representation of the time window of absence; a named entity recognition module comprising instructions stored in memory for identifying the alternate named contact from the text content of the user's out-of-office message by recognizing named entities in the user's out-of-office message and cross-referencing the recognized named entities with a named entity directory for identifying an alternate named contact corresponding to one of the recognized named entities; a representation module comprising instructions stored in memory for generating a structured representation of the user's out-of-office message which includes a reference to the user, a reference to the identified alternate named contact, and the normalized representation of the time window; an out-of-office module comprising instructions stored in memory for storing the structured representation of the out-of-office message in a database and notifying the user that a conflict exists between the user's out-of-office message and an out-of-office message of the identified alternate named contact, by comparing the normalized representation of the time window included in the structured representation of the user's out-of-office message with a normalized representation of a time window included in a structured representation of the identified alternate named contact's out-of-office message; and a processor which executes the instructions. 14. The electronic out-of-office message analysis system of claim 13 , wherein the structured representation comprises a directed link from the user to the identified alternate named contact and the normalized representation of the time window included in the structured representation of the user's out-of-office message. | 0.656716 |
9,501,560 | 6 | 7 | 6. A system to facilitate user productivity in visualizing and reviewing a set of document search results, the system comprising: a processing device; and a non-transitory, processor-readable storage medium, the non-transitory, processor-readable storage medium comprising one or more programming instructions that, when executed, cause the processing device to: receive a query request comprising two or more search terms as a computer machine input, wherein each search term from the one or more search terms is assigned a graphical indicator, search a corpora of electronically stored content for a set of at least two documents relevant to the query request, score a set of paragraphs associated with the set of at least two documents, rank the set of paragraphs based on the scoring, and display at least one boxed abacus icon that indicates whether the two or more search terms in the query request are present in a subset of the set of paragraphs, wherein: the subset comprises a preset number of paragraphs receiving higher scores determined in the ranking step than a set of paragraphs not included in the subset, each paragraph in the subset is assigned to a vertical line in a set of vertical lines, and the at least one boxed abacus icon comprises a depiction of the graphical indicators on each vertical line corresponding to a presence of the search term in the paragraph. | 6. A system to facilitate user productivity in visualizing and reviewing a set of document search results, the system comprising: a processing device; and a non-transitory, processor-readable storage medium, the non-transitory, processor-readable storage medium comprising one or more programming instructions that, when executed, cause the processing device to: receive a query request comprising two or more search terms as a computer machine input, wherein each search term from the one or more search terms is assigned a graphical indicator, search a corpora of electronically stored content for a set of at least two documents relevant to the query request, score a set of paragraphs associated with the set of at least two documents, rank the set of paragraphs based on the scoring, and display at least one boxed abacus icon that indicates whether the two or more search terms in the query request are present in a subset of the set of paragraphs, wherein: the subset comprises a preset number of paragraphs receiving higher scores determined in the ranking step than a set of paragraphs not included in the subset, each paragraph in the subset is assigned to a vertical line in a set of vertical lines, and the at least one boxed abacus icon comprises a depiction of the graphical indicators on each vertical line corresponding to a presence of the search term in the paragraph. 7. The system of claim 6 , wherein: the at least one boxed abacus icon comprises a set of tiles arranged in a plurality of rows; and each row in the set of tiles represents a surfaced paragraph based on the scoring of the set of paragraphs. | 0.693095 |
8,224,832 | 16 | 17 | 16. An automated data processing system for monitoring data for changes, comprising: a monitored document, which is subject to change and includes one or more logical entities; an updatable reference of the monitored document at a given time, the updatable reference including the logical entities of the monitored document and all of the material to be monitored in the monitored document; a memory configured to store one or more criteria and the updatable reference; and at least one processor configured to: identify one or more differences between the monitored document and the updatable reference; determine that one or more of the identified differences does not represent drift, where drift is a change in position within the document of a logical entity that has not itself been changed; determine if the one or more criteria is satisfied in an identified difference between the monitored document and the updatable reference, the identified difference having been determined not to represent drift; provide notification if at least one of the one or more criteria is satisfied; and update the updatable reference to include any differences between the monitored document and the updatable reference. | 16. An automated data processing system for monitoring data for changes, comprising: a monitored document, which is subject to change and includes one or more logical entities; an updatable reference of the monitored document at a given time, the updatable reference including the logical entities of the monitored document and all of the material to be monitored in the monitored document; a memory configured to store one or more criteria and the updatable reference; and at least one processor configured to: identify one or more differences between the monitored document and the updatable reference; determine that one or more of the identified differences does not represent drift, where drift is a change in position within the document of a logical entity that has not itself been changed; determine if the one or more criteria is satisfied in an identified difference between the monitored document and the updatable reference, the identified difference having been determined not to represent drift; provide notification if at least one of the one or more criteria is satisfied; and update the updatable reference to include any differences between the monitored document and the updatable reference. 17. The system of claim 16 , wherein the monitored document is a court docket. | 0.920408 |
8,972,436 | 1 | 2 | 1. A method, comprising: obtaining a review including a set of text, wherein the review includes user-generated content; determining, for the review, a numerical value for each of a plurality of objects, the numerical value indicating a likelihood that a corresponding one of the plurality of objects could have generated the review, the plurality of objects each representing a corresponding one of a plurality of entities; identifying one of the plurality of objects that, if the review were generated from one of the objects, is most likely to have generated the review based, at least in part, upon the numerical value that has been determined for each of the plurality of objects, wherein the identified one of the plurality of objects indicates the one of the plurality of entities that is most likely to be a primary subject of the review; associating the review with the identified one of the plurality of objects such that a plurality of reviews associated with the identified one of the plurality of objects includes the review; and aggregating information from at least a portion of the plurality of reviews. | 1. A method, comprising: obtaining a review including a set of text, wherein the review includes user-generated content; determining, for the review, a numerical value for each of a plurality of objects, the numerical value indicating a likelihood that a corresponding one of the plurality of objects could have generated the review, the plurality of objects each representing a corresponding one of a plurality of entities; identifying one of the plurality of objects that, if the review were generated from one of the objects, is most likely to have generated the review based, at least in part, upon the numerical value that has been determined for each of the plurality of objects, wherein the identified one of the plurality of objects indicates the one of the plurality of entities that is most likely to be a primary subject of the review; associating the review with the identified one of the plurality of objects such that a plurality of reviews associated with the identified one of the plurality of objects includes the review; and aggregating information from at least a portion of the plurality of reviews. 2. The method as recited in claim 1 , further comprising: ascertaining a type of entity that is the primary subject of the review. | 0.848131 |
9,817,991 | 1 | 8 | 1. A method for improving the operation of a computer system, the method comprising: creating a data record having data that can be accessed by credentialed users of a multi-tenant computing system; establishing restricted access for the created record and storing the restricted-access record in a tenant data store in the multi-tenant computing system such that a first subset of the credentialed users of the multi-tenant computing system may access the restricted-access record; accessing the restricted-access record stored in the tenant data store using access credentials of a user in the first subset of users; generating a note associated with the record, the note having restricted access that is different from the restricted access of the record that corresponds to a second subset of the credentialed users of the multi-tenant computing system; accessing the restricted-access record using access credentials of a user in the second subset; and displaying the record on the display with the note displayed over the record if the access credentials allow for access to both the restricted-access record and the note. | 1. A method for improving the operation of a computer system, the method comprising: creating a data record having data that can be accessed by credentialed users of a multi-tenant computing system; establishing restricted access for the created record and storing the restricted-access record in a tenant data store in the multi-tenant computing system such that a first subset of the credentialed users of the multi-tenant computing system may access the restricted-access record; accessing the restricted-access record stored in the tenant data store using access credentials of a user in the first subset of users; generating a note associated with the record, the note having restricted access that is different from the restricted access of the record that corresponds to a second subset of the credentialed users of the multi-tenant computing system; accessing the restricted-access record using access credentials of a user in the second subset; and displaying the record on the display with the note displayed over the record if the access credentials allow for access to both the restricted-access record and the note. 8. The method of claim 1 , wherein the display of the note comprises text data entered at the time of the creation of the note. | 0.840852 |
8,576,430 | 1 | 17 | 1. A method for determining a print job schedule for a printing production facility having a set of availably printing resources, comprising: defining one or more scheduling classifications; receiving one or more print jobs, each print job having a print job description specified by a set of print job attributes; determining one or more scheduling classification corresponding to the received print jobs; using a processor to automatically determine the print job schedule for the received print jobs using an answer set programming language solver responsive to: the print job descriptions; a set of resource descriptions for the available printing resources; a set of scheduling rules, wherein the scheduling rules are answer set programming statements; and a historical decision database stored in a processor accessible memory, wherein the historical decision database stores an indication of previously successful decision frequencies as a function of scheduling classification; wherein the print job schedule assigns a time schedule and one or more printing resources for each of the received print jobs. | 1. A method for determining a print job schedule for a printing production facility having a set of availably printing resources, comprising: defining one or more scheduling classifications; receiving one or more print jobs, each print job having a print job description specified by a set of print job attributes; determining one or more scheduling classification corresponding to the received print jobs; using a processor to automatically determine the print job schedule for the received print jobs using an answer set programming language solver responsive to: the print job descriptions; a set of resource descriptions for the available printing resources; a set of scheduling rules, wherein the scheduling rules are answer set programming statements; and a historical decision database stored in a processor accessible memory, wherein the historical decision database stores an indication of previously successful decision frequencies as a function of scheduling classification; wherein the print job schedule assigns a time schedule and one or more printing resources for each of the received print jobs. 17. The method of claim 1 wherein the indication of previously successful decision frequencies is stored as a number of previously successful decisions. | 0.659193 |
7,797,673 | 1 | 12 | 1. A computer-implemented method for applying a coding standard to a simulatable graphical model in a graphical modeling environment, the method comprising the steps of: providing a coding standard in the graphical modeling environment; applying the coding standard to the simulatable graphical model to detect violations of the coding standard in the simulatable graphical model; displaying violating segments of the simulatable graphical model differently than non-violating segments of the simulatable graphical model; and in response to users' selection of a selected one of violating segments, displaying information on a violation of the coding standard in the selected violating segment. | 1. A computer-implemented method for applying a coding standard to a simulatable graphical model in a graphical modeling environment, the method comprising the steps of: providing a coding standard in the graphical modeling environment; applying the coding standard to the simulatable graphical model to detect violations of the coding standard in the simulatable graphical model; displaying violating segments of the simulatable graphical model differently than non-violating segments of the simulatable graphical model; and in response to users' selection of a selected one of violating segments, displaying information on a violation of the coding standard in the selected violating segment. 12. The method of claim 1 , further comprising the step of: compiling the simulatable graphical model to automatically avoid violations of the coding standard in the simulatable graphical model, wherein at least a portion of the simulatable graphical model violating the coding standard is automatically replaced with an alternative of the portion. | 0.609865 |
5,529,496 | 1 | 13 | 1. A method for teaching a language based on the use of kanji characters, comprising the steps of: displaying a compilation of key kanji in a systematic order; providing a first corresponding compilation of on-yomi readings of said key kanji; and reinforcing the understanding of the first compilation of on-yomi readings by presenting a second corresponding compilation of on-yomi readings. | 1. A method for teaching a language based on the use of kanji characters, comprising the steps of: displaying a compilation of key kanji in a systematic order; providing a first corresponding compilation of on-yomi readings of said key kanji; and reinforcing the understanding of the first compilation of on-yomi readings by presenting a second corresponding compilation of on-yomi readings. 13. The method of claim 1 which further comprises teaching a student to read text of kanji by having the student learn the meanings of the key kanji. | 0.857824 |
8,346,815 | 18 | 19 | 18. The method of claim 13 , wherein determining an insertion score comprises: determining central tendency score from relevance scores of images that are to be displayed in the image display environment, each relevance score being a measure of relevance of a corresponding image to the search query. | 18. The method of claim 13 , wherein determining an insertion score comprises: determining central tendency score from relevance scores of images that are to be displayed in the image display environment, each relevance score being a measure of relevance of a corresponding image to the search query. 19. The method of claim 18 , wherein determining an insertion score further comprises: determining an image intent score for the search query; and determining the insertion score from the image intent score and the central tendency score. | 0.942373 |
7,672,936 | 1 | 5 | 1. A method of controlling access to data stored in a data repository, comprising: receiving, from a requesting entity, an abstract query composed from a set of logical fields, wherein each logical field provides an access method that specifies at least a method for accessing the data and a security domain associated with the logical field, and for each logical field: generating a query contribution for retrieving query result data; modifying each query contribution to additionally retrieve security account information corresponding to query result data to be retrieved by the query contribution; retrieving the query result data using the modified query contribution for the logical field; and determining, using a programmed microprocessor whether the requesting entity is authorized to access the query result data by: identifying the requesting entity, determining whether the requesting entity has previously accessed data from the security domain associated with the logical, and if not, including an indication in a set of combined query results that data for the logical field is available for access, and otherwise, comparing the security account information associated with the query result data with a security account of data previously accessed by the requesting entity, and if the security accounts match, including the query result data in the combined query results; and combining the query result data into the set of combined query results; and returning an indication of the combined query results to the requesting entity. | 1. A method of controlling access to data stored in a data repository, comprising: receiving, from a requesting entity, an abstract query composed from a set of logical fields, wherein each logical field provides an access method that specifies at least a method for accessing the data and a security domain associated with the logical field, and for each logical field: generating a query contribution for retrieving query result data; modifying each query contribution to additionally retrieve security account information corresponding to query result data to be retrieved by the query contribution; retrieving the query result data using the modified query contribution for the logical field; and determining, using a programmed microprocessor whether the requesting entity is authorized to access the query result data by: identifying the requesting entity, determining whether the requesting entity has previously accessed data from the security domain associated with the logical, and if not, including an indication in a set of combined query results that data for the logical field is available for access, and otherwise, comparing the security account information associated with the query result data with a security account of data previously accessed by the requesting entity, and if the security accounts match, including the query result data in the combined query results; and combining the query result data into the set of combined query results; and returning an indication of the combined query results to the requesting entity. 5. The method of claim 1 , wherein determining whether the requesting entity has previously accessed data from the same security domain as the security domain provided by the logical field, comprises accessing a security matrix that indicates the security accounts, within each security domain, for which the requesting entity has previously accessed data. | 0.598194 |
9,753,967 | 17 | 18 | 17. A non-transitory computer readable medium including instructions for operating a computing system comprising: receiving an input query; identifying input query components in the input query; detecting a query conflict between one or more of the input query components based on inclusion of the input query components in a conflict set, wherein the conflict set is a set of associated semantic concepts defining a scope of the conflict; generating a conflict free query by replacing one of the input query components based on query context including a historical context, a user context, and a current context of a user making the input query, wherein: the historical context includes past usage or behavior of the user; the user context includes preferences and other factors associated with the user, including appointments and personal relationships of the user; the current context includes events occurring at the time the input query is made, including communications received by the user, a time of day, a location of the user, and current activities of the user; and generating a query response for the conflict free query for displaying on a device. | 17. A non-transitory computer readable medium including instructions for operating a computing system comprising: receiving an input query; identifying input query components in the input query; detecting a query conflict between one or more of the input query components based on inclusion of the input query components in a conflict set, wherein the conflict set is a set of associated semantic concepts defining a scope of the conflict; generating a conflict free query by replacing one of the input query components based on query context including a historical context, a user context, and a current context of a user making the input query, wherein: the historical context includes past usage or behavior of the user; the user context includes preferences and other factors associated with the user, including appointments and personal relationships of the user; the current context includes events occurring at the time the input query is made, including communications received by the user, a time of day, a location of the user, and current activities of the user; and generating a query response for the conflict free query for displaying on a device. 18. The non-transitory computer readable medium as claimed in claim 17 wherein detecting the query conflict includes detecting the query conflict from a conflict list including the conflict set. | 0.533654 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.