patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|---|---|---|
9,020,806 | 17 | 19 | 17. One or more computer-readable devices having computer-executable instructions, which when executed perform steps, comprising, obtaining candidate sentences for a sentence completion question; filtering the candidate sentences into a selected sentence based at least in part on a language model; using a class-based maximum entropy N-gram language model to generate a plurality of candidate alternates for the selected sentence based at least in part on the class-based maximum entropy N-gram language model; filtering the candidate alternates; ranking the candidate alternates based on probability data determined from the class-based maximum entropy N-gram language model; and outputting the sentence completion question comprising the selected sentence with a removed word set comprising one or more removed words and a set of options for completing the sentence, the set of options comprising the removed word set and selected alternates chosen from among the candidate alternates. | 17. One or more computer-readable devices having computer-executable instructions, which when executed perform steps, comprising, obtaining candidate sentences for a sentence completion question; filtering the candidate sentences into a selected sentence based at least in part on a language model; using a class-based maximum entropy N-gram language model to generate a plurality of candidate alternates for the selected sentence based at least in part on the class-based maximum entropy N-gram language model; filtering the candidate alternates; ranking the candidate alternates based on probability data determined from the class-based maximum entropy N-gram language model; and outputting the sentence completion question comprising the selected sentence with a removed word set comprising one or more removed words and a set of options for completing the sentence, the set of options comprising the removed word set and selected alternates chosen from among the candidate alternates. 19. The one or more computer-readable devices of claim 17 wherein filtering the candidate alternates comprises performing automated conjugation filtering. | 0.694444 |
7,957,970 | 5 | 6 | 5. The method of claim 1 , wherein the probability threshold is a first threshold, the method further comprising: determining whether a probability of conducting a successful dialog with the user exceeds a second threshold, the second threshold being greater than the probability threshold, wherein if the second threshold is exceeded, further dialog is conducted with the user using a current dialog strategy. | 5. The method of claim 1 , wherein the probability threshold is a first threshold, the method further comprising: determining whether a probability of conducting a successful dialog with the user exceeds a second threshold, the second threshold being greater than the probability threshold, wherein if the second threshold is exceeded, further dialog is conducted with the user using a current dialog strategy. 6. The method of claim 5 , wherein if the second threshold is not exceeded, further dialog is conducted with the user using an adapted dialog strategy. | 0.5 |
9,613,621 | 10 | 14 | 10. An electronic apparatus, comprising: an input unit, receiving a speech signal; a storage unit, storing a plurality of program code segments; and a processing unit, coupled to the input unit and the storage unit, the processing unit executing a plurality of commands through the program code segments, and the commands comprising: obtaining a phonetic transcription sequence of the speech signal according to an acoustic model; obtaining a plurality of syllable sequences and a plurality of corresponding phonetic spelling matching probabilities according to the phonetic transcription sequence and a syllable acoustic lexicon; obtaining an intonation information corresponding to each of the syllable sequences according to a tone of the phonetic transcription sequence; obtaining a plurality of phonetic spelling sequences and a plurality of phonetic spelling sequence probabilities, from the language model, according to each phonetic spelling of phonetic spelling sequences and the intonation information; obtaining, from the language model, a plurality of text sequences corresponding to the phonetic transcription sequence, and a plurality of spelling sequence probabilities; generating a plurality of associated probabilities by multiplying each of the phonetic spelling matching probabilities and each of the spelling sequence probabilities; and selecting the text sequence corresponding to a largest one among the associated probabilities to be used as a recognition result of the speech signal, wherein different intonation information in the language model is divided into different semantemes, and the semantemes are corresponding to different phonetic spelling sequences. | 10. An electronic apparatus, comprising: an input unit, receiving a speech signal; a storage unit, storing a plurality of program code segments; and a processing unit, coupled to the input unit and the storage unit, the processing unit executing a plurality of commands through the program code segments, and the commands comprising: obtaining a phonetic transcription sequence of the speech signal according to an acoustic model; obtaining a plurality of syllable sequences and a plurality of corresponding phonetic spelling matching probabilities according to the phonetic transcription sequence and a syllable acoustic lexicon; obtaining an intonation information corresponding to each of the syllable sequences according to a tone of the phonetic transcription sequence; obtaining a plurality of phonetic spelling sequences and a plurality of phonetic spelling sequence probabilities, from the language model, according to each phonetic spelling of phonetic spelling sequences and the intonation information; obtaining, from the language model, a plurality of text sequences corresponding to the phonetic transcription sequence, and a plurality of spelling sequence probabilities; generating a plurality of associated probabilities by multiplying each of the phonetic spelling matching probabilities and each of the spelling sequence probabilities; and selecting the text sequence corresponding to a largest one among the associated probabilities to be used as a recognition result of the speech signal, wherein different intonation information in the language model is divided into different semantemes, and the semantemes are corresponding to different phonetic spelling sequences. 14. The electronic apparatus of claim 10 , wherein the commands further comprise: obtaining the syllable sequences matching the phonetic transcription sequence and obtaining the phonetic spelling matching probabilities of the phonetic transcription sequence matching each of the syllable sequences according to the phonetic transcription sequence and the syllable acoustic lexicon; and selecting the syllable sequence corresponding to a largest one among the phonetic spelling matching probabilities and the intonation information to be used as the syllable sequence and the intonation information matching the phonetic transcription sequence. | 0.5 |
8,874,581 | 18 | 19 | 18. A computer readable storage medium comprising processor-executable instructions that, when executed on one or more processors, perform operations comprising: responsive to receiving a query item, applying a predefined pattern to a plurality of web pages to extract a collection of semantic classes; identifying a first semantic class collection from the collection of semantic classes, each semantic class containing the query item; conducting a preprocessing operation on the first semantic class collection to remove one or more items with a semantic class frequency less than a predetermined threshold and to create a second semantic class collection comprising the semantic classes remaining after the removing from the first semantic class collection, each remaining semantic class containing the query item; applying a topic model to a specific semantic class collection to create a plurality of topics, the topic model configured to set a topic number for each of the plurality of topics that is based on a number of semantic classes to which each of the plurality of topics could belong and is larger than the number of semantic classes to which each of the plurality of topics could belong; and conducting a postprocessing operation on results of the topic model for each of the one or more items to merge the plurality of topics and generate a final semantic class collection used to generate a response to the query item. | 18. A computer readable storage medium comprising processor-executable instructions that, when executed on one or more processors, perform operations comprising: responsive to receiving a query item, applying a predefined pattern to a plurality of web pages to extract a collection of semantic classes; identifying a first semantic class collection from the collection of semantic classes, each semantic class containing the query item; conducting a preprocessing operation on the first semantic class collection to remove one or more items with a semantic class frequency less than a predetermined threshold and to create a second semantic class collection comprising the semantic classes remaining after the removing from the first semantic class collection, each remaining semantic class containing the query item; applying a topic model to a specific semantic class collection to create a plurality of topics, the topic model configured to set a topic number for each of the plurality of topics that is based on a number of semantic classes to which each of the plurality of topics could belong and is larger than the number of semantic classes to which each of the plurality of topics could belong; and conducting a postprocessing operation on results of the topic model for each of the one or more items to merge the plurality of topics and generate a final semantic class collection used to generate a response to the query item. 19. The computer readable storage medium of claim 18 , wherein the topic number is used to determine the plurality of topics used in the postprocessing operation to generate the final semantic class collection. | 0.738806 |
8,700,621 | 16 | 18 | 16. An system for offering suggested queries, the system comprising: a network device comprising a processor, a memory, and an application executed by the processor and accessing the memory, the application being configured to: receive a keyword or phrase for a search query; search online user generated content of product review information for content related to the keyword or phrase; extract word combinations from the user generated content, wherein the extracted word combinations are at least two word phrases that are repeated a predetermined number of times in the content; combine one or more words from each extracted word combination with one or more words from other extracted word combinations to form composite phrases; identify each of the composite phrases that are repeated a predetermined number of times in the content; rank the identified composite phrases the number of occurrences in the search of user generated content; select query suggestions from the ranked composite phrases by selecting a defined quantity of query suggestions in order of the ranking; and present selected query suggestions. | 16. An system for offering suggested queries, the system comprising: a network device comprising a processor, a memory, and an application executed by the processor and accessing the memory, the application being configured to: receive a keyword or phrase for a search query; search online user generated content of product review information for content related to the keyword or phrase; extract word combinations from the user generated content, wherein the extracted word combinations are at least two word phrases that are repeated a predetermined number of times in the content; combine one or more words from each extracted word combination with one or more words from other extracted word combinations to form composite phrases; identify each of the composite phrases that are repeated a predetermined number of times in the content; rank the identified composite phrases the number of occurrences in the search of user generated content; select query suggestions from the ranked composite phrases by selecting a defined quantity of query suggestions in order of the ranking; and present selected query suggestions. 18. The system of claim 16 , wherein the composite phrases are further combined with non-redundant words from other composite phrases from the identified composite phrases to form aggregated composite phrases. | 0.651667 |
9,658,824 | 3 | 6 | 3. A system, comprising: at least one computing device; and at least one application executable in the at least one computing device, wherein, when executed, the at least one application causes the at least one computing device to at least: obtain a plurality of customer review search queries from a plurality of users, the plurality of customer review search queries being obtained to search a collection of customer reviews for a specific item; extract a set of relevant topics for the specific item by analyzing the plurality of customer review search queries; and generate a user interface based at least in part on at least some of the set of relevant topics for the specific item. | 3. A system, comprising: at least one computing device; and at least one application executable in the at least one computing device, wherein, when executed, the at least one application causes the at least one computing device to at least: obtain a plurality of customer review search queries from a plurality of users, the plurality of customer review search queries being obtained to search a collection of customer reviews for a specific item; extract a set of relevant topics for the specific item by analyzing the plurality of customer review search queries; and generate a user interface based at least in part on at least some of the set of relevant topics for the specific item. 6. The system of claim 3 , wherein the user interface is configured to present the at least some of the set of relevant topics for the specific item as refinement attributes for item search functionality provided by the user interface. | 0.803512 |
9,613,323 | 1 | 4 | 1. A computer-implemented method for determining organizational agility of an organization across multiple computing domains, comprising: extracting, from one or more mail servers of the organization, a set of relevant historical organizational e-mail documents associated with an organization in a computer memory medium; fetching a set of electronic documents from an intranet of the organization via a web crawler; analyzing, by a computer system, the set of relevant historical organizational e-mail documents and the set of electronic documents by parsing the set of relevant historical organizational e-mail documents and the set of electronic documents for a set of keywords that is indicative of the organizational agility of the organization, each of the set of keywords having an associated score, the organizational agility based on an amount of governance within the organization; determining trends across disparate documents in the set of relevant historical organizational e-mail documents and the set of electronic documents combined with customer and enterprise insights mined from social media content using deep text and data analytics; calculating, by the computer system, a set of agility scores based on the trends and the analyzing of scores associated with the set of keywords using a set of agility computation rules, wherein a higher agility score is calculated in the case that the set of keywords indicate a lower amount of governance; weighting, by the computer system, the set of agility scores based on a geographic region associated with the organization; providing output based on the calculating and the weighting; and altering work tasks in a workload to an ordering that is optimal for the organization based on the weighted agility scores. | 1. A computer-implemented method for determining organizational agility of an organization across multiple computing domains, comprising: extracting, from one or more mail servers of the organization, a set of relevant historical organizational e-mail documents associated with an organization in a computer memory medium; fetching a set of electronic documents from an intranet of the organization via a web crawler; analyzing, by a computer system, the set of relevant historical organizational e-mail documents and the set of electronic documents by parsing the set of relevant historical organizational e-mail documents and the set of electronic documents for a set of keywords that is indicative of the organizational agility of the organization, each of the set of keywords having an associated score, the organizational agility based on an amount of governance within the organization; determining trends across disparate documents in the set of relevant historical organizational e-mail documents and the set of electronic documents combined with customer and enterprise insights mined from social media content using deep text and data analytics; calculating, by the computer system, a set of agility scores based on the trends and the analyzing of scores associated with the set of keywords using a set of agility computation rules, wherein a higher agility score is calculated in the case that the set of keywords indicate a lower amount of governance; weighting, by the computer system, the set of agility scores based on a geographic region associated with the organization; providing output based on the calculating and the weighting; and altering work tasks in a workload to an ordering that is optimal for the organization based on the weighted agility scores. 4. The computer-implemented method of claim 1 , further comprising identifying, by the computer system, one or more areas where information associated with the organization agility was lacking. | 0.782167 |
7,640,497 | 2 | 3 | 2. The method of claim 1 , wherein generating the output hierarchical data structure comprises modifying structure of the input hierarchical data structure. | 2. The method of claim 1 , wherein generating the output hierarchical data structure comprises modifying structure of the input hierarchical data structure. 3. The method of claim 2 , wherein generating the output hierarchical data structure comprises modifying structure of the input hierarchical data structure by promoting a key in the input hierarchical data structure by raising the key in the hierarchy of the input hierarchical data structure or demoting a key in the input hierarchical data structure by lowering the key in the hierarchy of the input hierarchical data structure. | 0.5 |
9,613,054 | 7 | 8 | 7. A computer-implemented method comprising: selecting entries from a location store associated with a physical location within an area, wherein each entry from the location store includes a physical location description and one or more terms associated with the physical location description; identifying candidate descriptive terms by identifying a candidate descriptive term from each of the selected entries, the candidate descriptive term from each of the selected entries being a term in an entry having a minimum global frequency of the one or more terms in the entry; determining a frequency that a first candidate descriptive term occurs in the candidate descriptive terms; modifying the global frequency of the first candidate descriptive term by the frequency of the first candidate descriptive term to obtain a modified global frequency for the first candidate descriptive term in the entry; identifying additional candidate descriptive terms, wherein the identifying comprises: identifying a second candidate descriptive term having a minimum modified global frequency of the one or more terms in an entry from the selected entries as an additional candidate descriptive term, and determining whether a frequency of occurrence of the additional candidate descriptive term has changed in a current iteration in comparison to a preceding iteration; responsive to determining that the frequency of occurrence of the additional candidate descriptive term is unchanged, identifying the additional candidate descriptive term as a descriptive term associated with the physical location description; receiving a physical location description from a client device; retrieving, from the location store, a plurality of entries for the physical location description; and providing for display, from the plurality of retrieved entries, one or more entries to the client device for presentation to a user of the client device, wherein the one or more entries being presented on the client device are based on the additional candidate descriptive term associated with the physical location description. | 7. A computer-implemented method comprising: selecting entries from a location store associated with a physical location within an area, wherein each entry from the location store includes a physical location description and one or more terms associated with the physical location description; identifying candidate descriptive terms by identifying a candidate descriptive term from each of the selected entries, the candidate descriptive term from each of the selected entries being a term in an entry having a minimum global frequency of the one or more terms in the entry; determining a frequency that a first candidate descriptive term occurs in the candidate descriptive terms; modifying the global frequency of the first candidate descriptive term by the frequency of the first candidate descriptive term to obtain a modified global frequency for the first candidate descriptive term in the entry; identifying additional candidate descriptive terms, wherein the identifying comprises: identifying a second candidate descriptive term having a minimum modified global frequency of the one or more terms in an entry from the selected entries as an additional candidate descriptive term, and determining whether a frequency of occurrence of the additional candidate descriptive term has changed in a current iteration in comparison to a preceding iteration; responsive to determining that the frequency of occurrence of the additional candidate descriptive term is unchanged, identifying the additional candidate descriptive term as a descriptive term associated with the physical location description; receiving a physical location description from a client device; retrieving, from the location store, a plurality of entries for the physical location description; and providing for display, from the plurality of retrieved entries, one or more entries to the client device for presentation to a user of the client device, wherein the one or more entries being presented on the client device are based on the additional candidate descriptive term associated with the physical location description. 8. The computer-implemented method of claim 7 further comprising: identifying a term having a minimum frequency of occurrence in the candidate descriptive terms as a category term associated with the physical location; and withholding the category term from being presented to the user on the client device. | 0.700195 |
9,064,489 | 1 | 5 | 1. A system comprising: one or more processors; a computer-readable memory; and a module comprising executable instructions stored in the computer-readable memory, the module, when executed by the one or more processors, configured to: obtain a voice recording and a corresponding sequence of speech units; select a first speech segment, wherein the first speech segment corresponds to a portion of the voice recording and wherein the first speech segment corresponds to a first speech unit; apply a first compression technique to the first speech segment to create a first compressed speech segment, wherein the first compression technique comprises one of time domain compression or perceptual compression; apply a second compression technique to the first compressed speech segment to create a second compressed speech segment, wherein the second compression technique comprises one of time domain compression or perceptual compression, and wherein the second compression technique is different from the first compression technique; distribute the second compressed speech segment to a client computing device for use in a text-to-speech system. | 1. A system comprising: one or more processors; a computer-readable memory; and a module comprising executable instructions stored in the computer-readable memory, the module, when executed by the one or more processors, configured to: obtain a voice recording and a corresponding sequence of speech units; select a first speech segment, wherein the first speech segment corresponds to a portion of the voice recording and wherein the first speech segment corresponds to a first speech unit; apply a first compression technique to the first speech segment to create a first compressed speech segment, wherein the first compression technique comprises one of time domain compression or perceptual compression; apply a second compression technique to the first compressed speech segment to create a second compressed speech segment, wherein the second compression technique comprises one of time domain compression or perceptual compression, and wherein the second compression technique is different from the first compression technique; distribute the second compressed speech segment to a client computing device for use in a text-to-speech system. 5. The system of claim 1 , wherein the first compression technique is time domain compression and a compression rate is based at least in part on the speech unit. | 0.689655 |
9,236,051 | 1 | 5 | 1. A method comprising: receiving private data, the private data (1) comprising private time-sensitive data associated with activities of a user, and (2) being stored in a computer system; generating an alphanumeric word using the private data; prompting the user to speak the alpha-numeric word; extracting a voice feature from a received phrase in response to the prompting; comparing, via a processor, the voice feature with a voice profile, to yield a comparison; and determining whether to accept a speaker identity based on the comparison. | 1. A method comprising: receiving private data, the private data (1) comprising private time-sensitive data associated with activities of a user, and (2) being stored in a computer system; generating an alphanumeric word using the private data; prompting the user to speak the alpha-numeric word; extracting a voice feature from a received phrase in response to the prompting; comparing, via a processor, the voice feature with a voice profile, to yield a comparison; and determining whether to accept a speaker identity based on the comparison. 5. The method of claim 1 , wherein the private data associated with the user further comprises email data. | 0.780992 |
9,965,232 | 1 | 7 | 1. A computer-implemented method for automatically verifying default printing selections, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: receiving a digital printing request from a user of the computing device to print a document; identifying, in response to receiving the digital printing request, a default printer to which the computing device is configured to transmit instructions to print the document; identifying a policy, wherein: the policy comprises a printer-selection directive to: automatically print to the default printer without requesting a user verification whenever the default printer is within a designated area of the computing device; and verify a default printer selection prior to printing to the default printer whenever the default printer is not within the designated area of the computing device; and the policy further comprises a security policy directive to scan one or more portions of the document for sensitive information by scanning the one or more portions for at least one of a particular word and a particular phrase; determining that the default printer is not within the designated area of the computing device; performing a scan as directed by the security policy directive and determining, based on a result of the scan, that the document includes sensitive information; and based on the policy, and in response to determining both that the default printer is not within the designated area of the computing device and that the document includes the sensitive information, presenting the user with a verification prompt that cautions the user that the default printer is not within the designated area of the computing device and allows the user to: affirmatively select the default printer to print the document; or select a different printer to print the document. | 1. A computer-implemented method for automatically verifying default printing selections, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: receiving a digital printing request from a user of the computing device to print a document; identifying, in response to receiving the digital printing request, a default printer to which the computing device is configured to transmit instructions to print the document; identifying a policy, wherein: the policy comprises a printer-selection directive to: automatically print to the default printer without requesting a user verification whenever the default printer is within a designated area of the computing device; and verify a default printer selection prior to printing to the default printer whenever the default printer is not within the designated area of the computing device; and the policy further comprises a security policy directive to scan one or more portions of the document for sensitive information by scanning the one or more portions for at least one of a particular word and a particular phrase; determining that the default printer is not within the designated area of the computing device; performing a scan as directed by the security policy directive and determining, based on a result of the scan, that the document includes sensitive information; and based on the policy, and in response to determining both that the default printer is not within the designated area of the computing device and that the document includes the sensitive information, presenting the user with a verification prompt that cautions the user that the default printer is not within the designated area of the computing device and allows the user to: affirmatively select the default printer to print the document; or select a different printer to print the document. 7. The computer-implemented method of claim 1 , wherein: the policy to verify the default printer selection whenever the default printer is not within the designated area comprises a policy to only verify the default printer selection if both: the default printer is not within the designated area of the computing device; and the scan identifies sensitive information. | 0.56383 |
9,201,666 | 1 | 2 | 1. In a computing environment, a system comprising: a sensing mechanism configured to provide data corresponding to gesture input; and logic configured to process the data to automatically position one or more content elements relative to a gesture curve of the gesture input while a gesture corresponding to the gesture input is still in progress, by: generating div elements in hypertext markup language (HTML) code with margins set to values that position the one or more content elements based on the gesture curve of the gesture input; aligning a set of at least two vertically adjacent div elements that are within a threshold alignment distance of one another into an aligned set; and encoding the aligned set into a single div element with an increased height. | 1. In a computing environment, a system comprising: a sensing mechanism configured to provide data corresponding to gesture input; and logic configured to process the data to automatically position one or more content elements relative to a gesture curve of the gesture input while a gesture corresponding to the gesture input is still in progress, by: generating div elements in hypertext markup language (HTML) code with margins set to values that position the one or more content elements based on the gesture curve of the gesture input; aligning a set of at least two vertically adjacent div elements that are within a threshold alignment distance of one another into an aligned set; and encoding the aligned set into a single div element with an increased height. 2. The system of claim 1 wherein the gesture curve traces a curve relative to an image contour, wherein the content elements comprise text, and wherein the logic processes the data to flow the text relative to the curve to appear to flow content based upon a gesture trace of the image contour. | 0.680435 |
8,060,492 | 1 | 7 | 1. A method comprising: receiving a request over a network from a user for generation of at least one URL based context query, wherein the request comprises at least one query generation criteria; searching, via the network, for clusters of related data objects within a multidimensional dataspace having at least one spatial axis, at least one temporal axis, at least one topical axis and at least one social axis using the at least one query generation criteria, wherein at least one cluster of data objects relating to the at least one query generation criteria is identified; checking permissions, via the network, relating to each data object in the at least one cluster of related data objects to determine if the user is permitted to access the data object, wherein if the user does not have permission to view the data object, the data object is removed from the cluster; generating, via the network, a URL having a context query comprising at least one context criteria, wherein the at least one context criteria is derived from the properties of the at least one cluster of data objects; and transmitting the URL having a context query to the end user. | 1. A method comprising: receiving a request over a network from a user for generation of at least one URL based context query, wherein the request comprises at least one query generation criteria; searching, via the network, for clusters of related data objects within a multidimensional dataspace having at least one spatial axis, at least one temporal axis, at least one topical axis and at least one social axis using the at least one query generation criteria, wherein at least one cluster of data objects relating to the at least one query generation criteria is identified; checking permissions, via the network, relating to each data object in the at least one cluster of related data objects to determine if the user is permitted to access the data object, wherein if the user does not have permission to view the data object, the data object is removed from the cluster; generating, via the network, a URL having a context query comprising at least one context criteria, wherein the at least one context criteria is derived from the properties of the at least one cluster of data objects; and transmitting the URL having a context query to the end user. 7. The method of claim 1 the searching step uses a global index of data available to the network to identify the at least one cluster of data objects. | 0.877651 |
9,852,648 | 5 | 6 | 5. The method of claim 4 , wherein the extracting knowledge points includes: receiving the segmented term sequences having positional information indicating a position in the electronic learning materials of the segmented term sequence; after the receiving the segmented term sequences, unifying abbreviations of the segmented term sequences; after the unifying the abbreviations, constructing generalized suffix trees of the segmented term sequences; after the constructing the generalized suffix trees, discovering repeated phrase instances of the segmented term sequences using the generalized suffix trees, wherein the phrase instances are limited by a particular maximum length; after the discovering the repeated phrase instances, adjusting frequency of the discovered repeated phrases instances based on positions of phrase instances in the learning materials; after the adjusting the frequency, measuring a cohesion and a separation of the segmented term sequences; after the measuring the cohesion and the separation, removing stop phrases from the segmented term sequences; after the removing the stop phrases, generating candidate knowledge points from the segmented term sequences; after the generating the candidate knowledge points, calculating weights of the candidate knowledge points based on the adjusted frequency; after the calculating the weights, analyzing appearance positions of the candidate knowledge points; after the analyzing the appearance positions, constructing a hierarchy of knowledge points based on the appearance positions; and after the constructing the hierarchy, presenting coverage overview of the learning materials. | 5. The method of claim 4 , wherein the extracting knowledge points includes: receiving the segmented term sequences having positional information indicating a position in the electronic learning materials of the segmented term sequence; after the receiving the segmented term sequences, unifying abbreviations of the segmented term sequences; after the unifying the abbreviations, constructing generalized suffix trees of the segmented term sequences; after the constructing the generalized suffix trees, discovering repeated phrase instances of the segmented term sequences using the generalized suffix trees, wherein the phrase instances are limited by a particular maximum length; after the discovering the repeated phrase instances, adjusting frequency of the discovered repeated phrases instances based on positions of phrase instances in the learning materials; after the adjusting the frequency, measuring a cohesion and a separation of the segmented term sequences; after the measuring the cohesion and the separation, removing stop phrases from the segmented term sequences; after the removing the stop phrases, generating candidate knowledge points from the segmented term sequences; after the generating the candidate knowledge points, calculating weights of the candidate knowledge points based on the adjusted frequency; after the calculating the weights, analyzing appearance positions of the candidate knowledge points; after the analyzing the appearance positions, constructing a hierarchy of knowledge points based on the appearance positions; and after the constructing the hierarchy, presenting coverage overview of the learning materials. 6. The method of claim 5 , wherein: the cohesion is measured according to a mutual information cohesion metric; the separation is measured according to an accessor variety separation metric; the abbreviations are unified according to a principal component analysis or a singular value decomposition; and the weights are calculated according to a number of appearances and an authority of a particular learning material in which the segmented term sequences appear. | 0.5 |
8,874,577 | 1 | 4 | 1. A system for triaging information feeds, comprising: a processor to execute the following: a feed module to receive a plurality of information feeds, wherein each information feed comprises at least one or more feed items; a facet identification module to generate one or more facets wherein the facets comprise at least one of a creator facet comprising creators, a source facet comprising sources, and a time facet comprising times by directly extracting the creators, sources and times from each of the feed items and by generating a topic facet comprising at least one topic for each feed item based on at least one of nouns and noun phrases associated with that feed item and designating the nouns and noun phrases as the topics for that feed item; a presentation module to display within a user interface, the creator, source, time and topic facets; a topic selection module to receive from the user a selection of one of the plurality of topics from the topic facet displayed within the user interface; a display module to display only the feed items that are associated with the selected topic within the user interface and to update the topics in the topic facet displayed within the user interface by presenting for display only those topics that are associated with the displayed feed items; and a facet update module to filter in or filter out one or more of the extracted creators, sources, and times within the display of the user interface based on the feed items associated with the selected topic in the user interface. | 1. A system for triaging information feeds, comprising: a processor to execute the following: a feed module to receive a plurality of information feeds, wherein each information feed comprises at least one or more feed items; a facet identification module to generate one or more facets wherein the facets comprise at least one of a creator facet comprising creators, a source facet comprising sources, and a time facet comprising times by directly extracting the creators, sources and times from each of the feed items and by generating a topic facet comprising at least one topic for each feed item based on at least one of nouns and noun phrases associated with that feed item and designating the nouns and noun phrases as the topics for that feed item; a presentation module to display within a user interface, the creator, source, time and topic facets; a topic selection module to receive from the user a selection of one of the plurality of topics from the topic facet displayed within the user interface; a display module to display only the feed items that are associated with the selected topic within the user interface and to update the topics in the topic facet displayed within the user interface by presenting for display only those topics that are associated with the displayed feed items; and a facet update module to filter in or filter out one or more of the extracted creators, sources, and times within the display of the user interface based on the feed items associated with the selected topic in the user interface. 4. A system according to claim 1 , wherein the at least one topic is identified from one of content of the information feed, content related to the information feed, and tag metadata associated with the information feed. | 0.819376 |
9,043,339 | 6 | 7 | 6. The computer-implemented system according to claim 3 , wherein the first extraction unit further: collects the same noun words from the noun words Ki and sets the same noun words as a certain one of noun words Si (i=1, 2, . . . , k) (n≧k); assigns a weight to each of the noun words Si based on the weights assigned to the corresponding noun words Ki; and extracts the noun word Si assigned a weight equal to or greater than a predetermined threshold value. | 6. The computer-implemented system according to claim 3 , wherein the first extraction unit further: collects the same noun words from the noun words Ki and sets the same noun words as a certain one of noun words Si (i=1, 2, . . . , k) (n≧k); assigns a weight to each of the noun words Si based on the weights assigned to the corresponding noun words Ki; and extracts the noun word Si assigned a weight equal to or greater than a predetermined threshold value. 7. The computer-implemented system according to claim 6 , wherein: the first extraction unit determines whether or not the weight of each noun word Si is in a predetermined threshold value range; and when the weight of the noun word Si is in the predetermined threshold value range, the first extraction unit determines whether or not a character type of the noun word Si is adequate as a term; when determining the character type as adequate, the first extraction unit sets the noun word Si as a noun word to be extracted; when determining the character type as inadequate, the first extraction unit sets the weight of the noun word Si to zero; and when the weight of the noun word Si is not in the predetermined threshold value range, the first extraction unit sets the weight of the noun word Si to zero. | 0.5 |
10,083,009 | 12 | 14 | 12. A computer program product, comprising a non-transitory computer-readable medium having a computer-readable program code embodied therein to be executed by one or more processors, the program code including instructions to: form an intent based on a user input using a natural language intent interpreter, the intent being associated with an input concept object; create a first plan based on the intent, the first plan comprising a first input action object that transforms the input concept object into an intermediate concept object and a first output action object that transforms another intermediate concept object into an output concept object associated with a goal of the intent, the other intermediate concept object comprising one of a same object as the intermediate concept object and a different object from the intermediate concept object, the first input action object and the first output action object being selected from a plurality of action objects; create a second plan based on the intent, wherein the second plan comprises a second input action object that transforms the input concept object into an alternative intermediate concept object and a second output action object that transforms another alternative intermediate concept object into the output concept object associated with the goal of the intent, the other alternative intermediate concept object comprising one of a same object as the alternative intermediate concept object and a different object from the alternative intermediate concept object, the second input action object and the second output action object being selected from the plurality of action objects; compare the first plan with the second plan, the first plan and the second plan each having an action object cost, an action quality cost, and a number of planned action objects; select a plan from the first plan and the second plan for execution based on the comparison of the first plan to the second plan, the selected plan having at least one of a lower action object cost, a best action object quality, and a fewer number of planned action objects; execute the selected plan, and output a value associated with the output concept object of the selected plan. | 12. A computer program product, comprising a non-transitory computer-readable medium having a computer-readable program code embodied therein to be executed by one or more processors, the program code including instructions to: form an intent based on a user input using a natural language intent interpreter, the intent being associated with an input concept object; create a first plan based on the intent, the first plan comprising a first input action object that transforms the input concept object into an intermediate concept object and a first output action object that transforms another intermediate concept object into an output concept object associated with a goal of the intent, the other intermediate concept object comprising one of a same object as the intermediate concept object and a different object from the intermediate concept object, the first input action object and the first output action object being selected from a plurality of action objects; create a second plan based on the intent, wherein the second plan comprises a second input action object that transforms the input concept object into an alternative intermediate concept object and a second output action object that transforms another alternative intermediate concept object into the output concept object associated with the goal of the intent, the other alternative intermediate concept object comprising one of a same object as the alternative intermediate concept object and a different object from the alternative intermediate concept object, the second input action object and the second output action object being selected from the plurality of action objects; compare the first plan with the second plan, the first plan and the second plan each having an action object cost, an action quality cost, and a number of planned action objects; select a plan from the first plan and the second plan for execution based on the comparison of the first plan to the second plan, the selected plan having at least one of a lower action object cost, a best action object quality, and a fewer number of planned action objects; execute the selected plan, and output a value associated with the output concept object of the selected plan. 14. The computer program product of claim 12 , wherein forming the intent comprises outputting dialog that requests an additional user input. | 0.729885 |
8,996,922 | 12 | 14 | 12. The computer-readable storage medium of claim 11 , wherein the operations further comprise: eliminating the quantifier through instantiating the quantifier with a symbolic variable; and determining whether the set of constraints is satisfiable based on the instantiation of the quantifier with the symbolic variable. | 12. The computer-readable storage medium of claim 11 , wherein the operations further comprise: eliminating the quantifier through instantiating the quantifier with a symbolic variable; and determining whether the set of constraints is satisfiable based on the instantiation of the quantifier with the symbolic variable. 14. The computer-readable storage medium of claim 12 , wherein the quantifier is a “for all” quantifier. | 0.826667 |
9,630,090 | 11 | 12 | 11. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: automatically identifying an object depicted in an image; automatically determining one or more characteristics of the object to compose a first question about the object; causing to be presented, on a first device, the first question about the object; receiving, from the first device, a first answer to the first question; converting, on a system that is remote relative to the first device, at least a portion of the first answer into searchable information; fact checking, on the system, the first answer by comparing the searchable information with information from one or more sources to determine factual correctness of the first answer to the first question; causing to be presented, on the first device, a second question about the object in accordance with fact checking results of the first answer. | 11. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: automatically identifying an object depicted in an image; automatically determining one or more characteristics of the object to compose a first question about the object; causing to be presented, on a first device, the first question about the object; receiving, from the first device, a first answer to the first question; converting, on a system that is remote relative to the first device, at least a portion of the first answer into searchable information; fact checking, on the system, the first answer by comparing the searchable information with information from one or more sources to determine factual correctness of the first answer to the first question; causing to be presented, on the first device, a second question about the object in accordance with fact checking results of the first answer. 12. The one or more non-transitory machine-readable media of claim 11 , wherein the instructions, when executed by the one or more processors, further cause receiving the image from a portable device, the image acquired by a user using the portable device, and wherein receiving the image initiates presenting the first question. | 0.5 |
8,781,989 | 27 | 28 | 27. A method for predicting a data value, said method comprising; receiving a first data set; receiving a base dimension value having a base focus topic value; receiving a predicted dimension value having a difference dimension value from the base dimension value; analyzing a focus topic profile over at least one dimension value to identify a most similar focus topic value to the base focus topic value; the dimension value at the most similar focus topic value being a selected dimension value; and selecting at least one data value from the first data set at the difference dimension value from the selected dimension value as the predicted data value at the predicted dimension value. | 27. A method for predicting a data value, said method comprising; receiving a first data set; receiving a base dimension value having a base focus topic value; receiving a predicted dimension value having a difference dimension value from the base dimension value; analyzing a focus topic profile over at least one dimension value to identify a most similar focus topic value to the base focus topic value; the dimension value at the most similar focus topic value being a selected dimension value; and selecting at least one data value from the first data set at the difference dimension value from the selected dimension value as the predicted data value at the predicted dimension value. 28. The method of claim 27 further comprising: analyzing a second data set using a latent variable method using at least one focus topic; and the focus topic profile comprises at least one focus topic value of the at least one focus topic from the second data set. | 0.5 |
8,935,638 | 1 | 2 | 1. A method, comprising: receiving, by a computing device, an indication of a user input received at a presence-sensitive input device, wherein the user input corresponds to a portion of a desired non-textual object; determining, by the computing device, based at least in part on the user input, a non-textual object suggestion; outputting, by the computing device, for display, a graphical representation of the user input and the non-textual object suggestion, the non-textual object suggestion having a property that visibly indicates that the non-textual object suggestion is not a completed object; receiving, by the computing device, an indication of whether the non-textual object suggestion corresponds to the desired non-textual object; and in response to determining that the indication indicates that the non-textual object suggestion corresponds to the desired non-textual object: outputting, by the computing device, for display, the non-textual object suggestion as the completed object; and removing, by the computing device, from display, the graphical representation of the user input. | 1. A method, comprising: receiving, by a computing device, an indication of a user input received at a presence-sensitive input device, wherein the user input corresponds to a portion of a desired non-textual object; determining, by the computing device, based at least in part on the user input, a non-textual object suggestion; outputting, by the computing device, for display, a graphical representation of the user input and the non-textual object suggestion, the non-textual object suggestion having a property that visibly indicates that the non-textual object suggestion is not a completed object; receiving, by the computing device, an indication of whether the non-textual object suggestion corresponds to the desired non-textual object; and in response to determining that the indication indicates that the non-textual object suggestion corresponds to the desired non-textual object: outputting, by the computing device, for display, the non-textual object suggestion as the completed object; and removing, by the computing device, from display, the graphical representation of the user input. 2. The method of claim 1 , wherein determining the non-textual object suggestion further comprises: comparing, by the computing device, the graphical representation of the user input to a plurality of non-textual objects; ranking, by the computing device, the plurality of non-textual objects based at least on the comparison of the graphical representation of the user input to the plurality of non-textual objects; and selecting, by the computing device, based at least in part on the ranking of the plurality of non-textual objects, a particular non-textual object from the plurality of non-textual objects as the non-textual object suggestion. | 0.5 |
9,053,097 | 11 | 17 | 11. A method according to claim 10 , wherein associating the first with the second wireless communication device comprises automatically selecting the first and second wireless communication devices from among a plurality of wireless communication devices, based on the similarity of the first and second signals. | 11. A method according to claim 10 , wherein associating the first with the second wireless communication device comprises automatically selecting the first and second wireless communication devices from among a plurality of wireless communication devices, based on the similarity of the first and second signals. 17. A method according to claim 11 , wherein: receiving the first signal comprises receiving an acceleration signal from an accelerometer of the first wireless communication device; and receiving the second signal comprises receiving an acceleration signal from an accelerometer of the second wireless communication device. | 0.562331 |
8,433,998 | 23 | 24 | 23. The method of annotating an event map, comprising: generating an event map depicting a schedule of activities for an event including plural sessions; annotating said event map based on a user input and updating said annotated event map based on information pertaining to the event, the annotating of the event map comprising tagging information to a feature of the event map; generating a zoomable and pannable view of the schedule of activities depicted by the updated annotated event map; and displaying said zoomable and pannable view of the schedule of activities depicted by said updated annotated event map. | 23. The method of annotating an event map, comprising: generating an event map depicting a schedule of activities for an event including plural sessions; annotating said event map based on a user input and updating said annotated event map based on information pertaining to the event, the annotating of the event map comprising tagging information to a feature of the event map; generating a zoomable and pannable view of the schedule of activities depicted by the updated annotated event map; and displaying said zoomable and pannable view of the schedule of activities depicted by said updated annotated event map. 24. The method of claim 23 , wherein said tagged information comprises at least one of a comment, a question, a discussion, a text message, an instant message, a text file, an image file, a video file and a widget to a feature of said event map. | 0.823232 |
7,580,926 | 10 | 11 | 10. The method of claim 1 , wherein the target is a search query communicated to the search engine by an Internet user and each of the plurality of candidates is an advertising message represented by an advertising message vector. | 10. The method of claim 1 , wherein the target is a search query communicated to the search engine by an Internet user and each of the plurality of candidates is an advertising message represented by an advertising message vector. 11. The method of claim 10 , further comprising displaying the original search results with one or more advertising messages selected based on a comparison among the distances between the advertising message vectors and the target vector. | 0.5 |
9,491,143 | 1 | 5 | 1. A method comprising: receiving, by a first stage of a context-aware pattern matching and parsing (CPMP) hardware accelerator of a network device, a packet stream; performing, by the first stage, a pre-matching process, including string matching and overflow pattern matching, on packets within the packet stream to identify a candidate packet within the packet stream that matches one or more strings or over-flow patterns associated with a set of Intrusion Prevention System (IPS) or Application Delivery Controller (ADC) rules; identifying, by the first stage, a candidate rule from the set of IPS or ADC rules based on a correlation of results of the pre-matching process; tokenizing, by the first stage, packet data of the candidate packet to produce matching tokens and corresponding locations of the matching token within the candidate packet; performing, by a second stage of the CPMP hardware accelerator including a plurality of CPMP processors, a full-match process on the candidate packet to determine whether the candidate packet satisfies the candidate rule by fetching and executing special purpose CPMP instructions to perform one or more of (i) context-aware pattern matching on one or more packet field values of the candidate packet, (ii) context-aware string matching on packet data of the candidate packet and (iii) regular expression matching on the packet data based on a plurality of predefined conditions associated with the candidate rule, corresponding contextual information provided by the candidate rule, the matching tokens and the corresponding locations; and providing, by the second stage, results of the full-match process to a general purpose processor of the network device. | 1. A method comprising: receiving, by a first stage of a context-aware pattern matching and parsing (CPMP) hardware accelerator of a network device, a packet stream; performing, by the first stage, a pre-matching process, including string matching and overflow pattern matching, on packets within the packet stream to identify a candidate packet within the packet stream that matches one or more strings or over-flow patterns associated with a set of Intrusion Prevention System (IPS) or Application Delivery Controller (ADC) rules; identifying, by the first stage, a candidate rule from the set of IPS or ADC rules based on a correlation of results of the pre-matching process; tokenizing, by the first stage, packet data of the candidate packet to produce matching tokens and corresponding locations of the matching token within the candidate packet; performing, by a second stage of the CPMP hardware accelerator including a plurality of CPMP processors, a full-match process on the candidate packet to determine whether the candidate packet satisfies the candidate rule by fetching and executing special purpose CPMP instructions to perform one or more of (i) context-aware pattern matching on one or more packet field values of the candidate packet, (ii) context-aware string matching on packet data of the candidate packet and (iii) regular expression matching on the packet data based on a plurality of predefined conditions associated with the candidate rule, corresponding contextual information provided by the candidate rule, the matching tokens and the corresponding locations; and providing, by the second stage, results of the full-match process to a general purpose processor of the network device. 5. The method of claim 1 , wherein said performing, by the first stage, a pre-matching process further comprises performing passive matching of overflow patterns that occur between characters or strings within the packet data. | 0.727711 |
8,245,186 | 13 | 14 | 13. The method of claim 3 , wherein the aspect-oriented action is related to a security check. | 13. The method of claim 3 , wherein the aspect-oriented action is related to a security check. 14. The method of claim 13 , wherein during the applying step, the security check is applied to one or more identified units of source code to determine if the one or more selected units of source code meet a plurality of security guidelines associated with the security check. | 0.5 |
8,725,771 | 2 | 3 | 2. The method of claim 1 , wherein the step of providing at least one search result includes providing a date associated with the identified document. | 2. The method of claim 1 , wherein the step of providing at least one search result includes providing a date associated with the identified document. 3. The method of claim 2 , wherein the step of providing at least one search result includes providing an indication of a portion of the identified document not copied from an earlier document. | 0.5 |
7,752,501 | 11 | 13 | 11. An apparatus for performing dynamic globalization verification testing of a software user interface, comprising: one or more machine readable storage media, said one or more machine readable storage media comprising: a user interface control identifier adapted to identify one or more user interface controls in said software user interface having text strings that have been pseudo translated; a test case generator adapted to generate one or more applicable test cases that test for display defects stemming from said pseudo translations; a test case executor adapted to execute said test cases; and a defect logger adapted to log defects discovered by executing said test cases. | 11. An apparatus for performing dynamic globalization verification testing of a software user interface, comprising: one or more machine readable storage media, said one or more machine readable storage media comprising: a user interface control identifier adapted to identify one or more user interface controls in said software user interface having text strings that have been pseudo translated; a test case generator adapted to generate one or more applicable test cases that test for display defects stemming from said pseudo translations; a test case executor adapted to execute said test cases; and a defect logger adapted to log defects discovered by executing said test cases. 13. An apparatus in accordance with claim 11 wherein said user interface control identifier is adapted to receive an identification of said one or more user interface controls by querying a software program that implements said software user interface. | 0.5 |
8,038,140 | 8 | 9 | 8. The control method according to claim 7 , wherein each of the second and subsequent documents is subjected to a pre-separation control which first drives the drawing device to rotate in a direction away from a reading position and then drives the drawing device to rotate in the opposite direction to convey the document toward the reading position. | 8. The control method according to claim 7 , wherein each of the second and subsequent documents is subjected to a pre-separation control which first drives the drawing device to rotate in a direction away from a reading position and then drives the drawing device to rotate in the opposite direction to convey the document toward the reading position. 9. The control method according to claim 8 , wherein the control to perform the high-speed conveyance and the pre-separation is determined on the basis of whether or not the first document detector has detected the trailing end of the document preceding each of the second and subsequent documents. | 0.5 |
7,945,557 | 19 | 20 | 19. The article of manufacture of claim 16 , wherein the query contains a correlation predicate. | 19. The article of manufacture of claim 16 , wherein the query contains a correlation predicate. 20. The article of manufacture of claim 19 , wherein the operations further comprise: translating the correlation predicate into a join predicate in a context of the outlier materialized query table; when the translated join predicate matches the join predicate in the outlier materialized query table, deriving a new predicate for the correlation predicate in a child query block using a source predicate on a quantifier of a parent query block; and wherein searching the query for the source predicate further includes searching the parent query block for the source predicate. | 0.5 |
9,454,582 | 1 | 4 | 1. A computer-implemented method comprising: receiving a search query; obtaining search results that satisfy the search query, wherein the search results identify a plurality of web pages, wherein each web page is a web page on a corresponding website of a plurality of websites; computing a respective global ranking score for each website of the plurality of websites, wherein the global ranking score represents an indication of relevance of the website to the search query relative to other websites of the plurality of websites; computing an onsite ranking score for each of the plurality of web pages, wherein the onsite ranking score is computed from onsite data that is controlled by a webmaster or a developer of the corresponding website for the web page, wherein the onsite ranking score represents an indication of relevance of the web page as responsive to the search query relative to other web pages within the corresponding website; selecting, as a representative web page for a particular website from among a plurality of web pages for the particular website, a particular web page having a highest onsite ranking score among the plurality of web pages for the particular website; comparing the onsite ranking score for the representative web page to the global ranking score for the particular website; determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website; in response to determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website, assigning a new global ranking score for the particular website including modifying the global ranking score for the particular website; computing a combined ranking score for each web page of the plurality of web pages including combining a respective global ranking score for a website associated with the web page and an onsite ranking score for the web page, including using the new global ranking score for the particular website when computing the combined ranking score for web pages on the particular website; and ranking the search results according to the combined ranking scores computed for respective web pages identified by the search results. | 1. A computer-implemented method comprising: receiving a search query; obtaining search results that satisfy the search query, wherein the search results identify a plurality of web pages, wherein each web page is a web page on a corresponding website of a plurality of websites; computing a respective global ranking score for each website of the plurality of websites, wherein the global ranking score represents an indication of relevance of the website to the search query relative to other websites of the plurality of websites; computing an onsite ranking score for each of the plurality of web pages, wherein the onsite ranking score is computed from onsite data that is controlled by a webmaster or a developer of the corresponding website for the web page, wherein the onsite ranking score represents an indication of relevance of the web page as responsive to the search query relative to other web pages within the corresponding website; selecting, as a representative web page for a particular website from among a plurality of web pages for the particular website, a particular web page having a highest onsite ranking score among the plurality of web pages for the particular website; comparing the onsite ranking score for the representative web page to the global ranking score for the particular website; determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website; in response to determining that the onsite ranking score for the representative web page is not consistent with the global ranking score for the particular website, assigning a new global ranking score for the particular website including modifying the global ranking score for the particular website; computing a combined ranking score for each web page of the plurality of web pages including combining a respective global ranking score for a website associated with the web page and an onsite ranking score for the web page, including using the new global ranking score for the particular website when computing the combined ranking score for web pages on the particular website; and ranking the search results according to the combined ranking scores computed for respective web pages identified by the search results. 4. The method of claim 1 , wherein the onsite ranking score for the representative web page is based on a placement of the representative web page within a structure of the particular website. | 0.81323 |
7,734,628 | 11 | 13 | 11. The method of claim 10 , wherein the step of displaying the single graph comprises displaying a graphical representation of the associated priority versus a second variable. | 11. The method of claim 10 , wherein the step of displaying the single graph comprises displaying a graphical representation of the associated priority versus a second variable. 13. The method of claim 11 , wherein the step of displaying a graphical representation comprises displaying a two-dimensional graphical representation of the associated priority versus the second variable. | 0.5 |
8,255,219 | 25 | 41 | 25. An apparatus for improving performance of a speech recognition system comprising: a processor that is configured to determine a performance of the speech recognition system based on either recognition of instances of a word or recognition of instances of various words among a set of words; the processor further configured to determine a corrective action based on the previously determined performance to improve the performance of the speech recognition system. | 25. An apparatus for improving performance of a speech recognition system comprising: a processor that is configured to determine a performance of the speech recognition system based on either recognition of instances of a word or recognition of instances of various words among a set of words; the processor further configured to determine a corrective action based on the previously determined performance to improve the performance of the speech recognition system. 41. The apparatus of claim 25 , wherein the performance is based on an error rate comprising: a rate at which the system substitutes an instance of the word or one of he various words in the system's hypothesis for a first utterance, followed by a user repeating the first utterance in a second utterance, followed by the system recognizing and accepting the second utterance. | 0.5 |
7,565,345 | 4 | 5 | 4. The method of claim 1 , wherein automatically selecting the subset of the revised queries comprises: sorting the revised queries by the confidence measure to create a ranking of the revised queries. | 4. The method of claim 1 , wherein automatically selecting the subset of the revised queries comprises: sorting the revised queries by the confidence measure to create a ranking of the revised queries. 5. The method of claim 4 , further comprising: obtaining the search results for the subset of the revised queries; and selecting the subset of the revised queries by evaluating the search results. | 0.5 |
7,895,514 | 1 | 7 | 1. A method comprising: providing, by a computing system, a development environment, the development environment including a web page editor; receiving a command at the development environment, the command referencing an electronic document being edited or viewed in a graphical user interface of the development environment, the electronic document comprising a first element written in a markup language and a second element written in a style sheet language; analyzing a structure of the electronic document responsive to the command; identifying a relationship between the first and second elements, wherein the relationship is known to cause a rendering problem associated with a document viewer that supports the first and second elements, the rendering problem occurring when the first and second elements are specified using correct syntax and used in combination in rendering a document by the document viewer; and presenting information about the rendering problem via the development environment. | 1. A method comprising: providing, by a computing system, a development environment, the development environment including a web page editor; receiving a command at the development environment, the command referencing an electronic document being edited or viewed in a graphical user interface of the development environment, the electronic document comprising a first element written in a markup language and a second element written in a style sheet language; analyzing a structure of the electronic document responsive to the command; identifying a relationship between the first and second elements, wherein the relationship is known to cause a rendering problem associated with a document viewer that supports the first and second elements, the rendering problem occurring when the first and second elements are specified using correct syntax and used in combination in rendering a document by the document viewer; and presenting information about the rendering problem via the development environment. 7. The method of claim 1 , further comprising: retrieving the information about the rendering problem from a remote database. | 0.719731 |
8,185,816 | 1 | 5 | 1. A method in a data processing system, comprising the steps of: receiving a first markup document and a second markup document, both the first markup document and the second markup document including numerical values and tags reflecting characteristics of the numerical values, wherein the characteristics indicate that the numerical values of the first markup document differ in format from the numerical values of the second markup document; automatically transforming the numerical values of at least one of the first markup document and the second markup document, so that the numerical values of the first markup document and the second markup document have a common format; combining the first markup document and the second markup document into a single data set; and displaying the single data set. | 1. A method in a data processing system, comprising the steps of: receiving a first markup document and a second markup document, both the first markup document and the second markup document including numerical values and tags reflecting characteristics of the numerical values, wherein the characteristics indicate that the numerical values of the first markup document differ in format from the numerical values of the second markup document; automatically transforming the numerical values of at least one of the first markup document and the second markup document, so that the numerical values of the first markup document and the second markup document have a common format; combining the first markup document and the second markup document into a single data set; and displaying the single data set. 5. The method of claim 1 , wherein the characteristics include a magnitude of the numerical values, and wherein the method further includes: manipulating the display of the single data set using one of the tags, the tag reflecting the magnitude of the numerical values. | 0.653351 |
8,825,468 | 6 | 10 | 6. The apparatus of claim 5 wherein the avatar is configured to provide simulated human attributes to the apparatus including visual graphical elements displayed on the display. | 6. The apparatus of claim 5 wherein the avatar is configured to provide simulated human attributes to the apparatus including visual graphical elements displayed on the display. 10. The apparatus of claim 6 wherein the avatar includes multimedia content. | 0.623762 |
8,744,851 | 1 | 2 | 1. A method comprising: receiving text as part of a text-to-speech process; selecting, via a processor, a speech segment associated with the text, wherein the speech segment is selected from a primary speech database which has been modified by: identifying primary speech segments in the primary speech database which do not meet a need of the text-to-speech process, wherein the primary speech segments comprise one of half-phones, half-phonemes, demi-syllables, and polyphones; identifying replacement speech segments which satisfy the need in a secondary speech database; and enhancing the primary speech database by substituting, in the primary database, the primary speech segments with the replacement speech segments; and generating, via the processor, speech corresponding to the text using the speech segment. | 1. A method comprising: receiving text as part of a text-to-speech process; selecting, via a processor, a speech segment associated with the text, wherein the speech segment is selected from a primary speech database which has been modified by: identifying primary speech segments in the primary speech database which do not meet a need of the text-to-speech process, wherein the primary speech segments comprise one of half-phones, half-phonemes, demi-syllables, and polyphones; identifying replacement speech segments which satisfy the need in a secondary speech database; and enhancing the primary speech database by substituting, in the primary database, the primary speech segments with the replacement speech segments; and generating, via the processor, speech corresponding to the text using the speech segment. 2. The method of claim 1 , wherein the need is based on one of dialect differences, geographic language differences, regional language differences, accent differences, national language differences, idiosyncratic speech differences, and database coverage differences. | 0.718947 |
9,318,108 | 17 | 18 | 17. The automated assistant of claim 1 , wherein: the input device receives a natural language question from a user; and the output processor component causes a third output to be displayed comprising an echo of the natural language question, a natural language answer to the natural language question, and an excerpt retrieved from an information source based on which the natural language answer is produced. | 17. The automated assistant of claim 1 , wherein: the input device receives a natural language question from a user; and the output processor component causes a third output to be displayed comprising an echo of the natural language question, a natural language answer to the natural language question, and an excerpt retrieved from an information source based on which the natural language answer is produced. 18. The automated assistant of claim 17 , wherein the natural language question is related to weather, the natural language answer describes the weather in a natural language format, and the excerpt is a weather forecast excerpt. | 0.5 |
8,190,902 | 7 | 8 | 7. The method of claim 1 , further comprising: invoking a first application-specific library for parsing the application document in accordance with a first structured storage format associated with a first corresponding application. | 7. The method of claim 1 , further comprising: invoking a first application-specific library for parsing the application document in accordance with a first structured storage format associated with a first corresponding application. 8. The method of claim 7 , further comprising: invoking a second application-specific library for parsing another application document in accordance with another structured storage format associated with a second corresponding application different than the first corresponding application. | 0.5 |
9,317,676 | 1 | 8 | 1. A computer storage device storing computer-executable instructions that, when executed, perform acts comprising: displaying, on a device interface, an image and a set of candidate objects for object recognition, the set of candidate objects including a specific candidate object and one or more other candidate objects, the specific candidate object corresponding to a missing portion of the image, the one or more other candidate objects including at least a first candidate object that does not correspond to the image; detecting a selection of a candidate object from the set of candidate objects; and determining whether the selection was made by a human based on whether the candidate object corresponds to the specific candidate object. | 1. A computer storage device storing computer-executable instructions that, when executed, perform acts comprising: displaying, on a device interface, an image and a set of candidate objects for object recognition, the set of candidate objects including a specific candidate object and one or more other candidate objects, the specific candidate object corresponding to a missing portion of the image, the one or more other candidate objects including at least a first candidate object that does not correspond to the image; detecting a selection of a candidate object from the set of candidate objects; and determining whether the selection was made by a human based on whether the candidate object corresponds to the specific candidate object. 8. The computer storage device of claim 1 , wherein the image is obtained by one of crawling for the image from an Internet, querying for the image using keywords for the image through a search engine, or obtaining the image from a private collection. | 0.800794 |
8,423,352 | 17 | 19 | 17. A data processing system for enhancing language detection in short communications, the data processing system comprising: a storage device including a storage medium, wherein the storage device stores computer usable program code; and a processor, wherein the processor executes the computer usable program code, and wherein the computer usable program code comprises: computer usable code for storing a short communication in an element of a line cache accessible to an application executing in a data processing system, the element being an element in a set of elements in the line cache; computer usable code for assembling a compound text from contents of a subset of the elements of the line cache; computer usable code for receiving a language identifier (language ID) for the compound text from a language detection algorithm; computer usable code for storing the language ID in a language cache element of a language ID cache accessible to the application, the language ID cache including a set of language cache elements; and computer usable code for determining, using contents of a subset of language cache elements, a language of the short communication. | 17. A data processing system for enhancing language detection in short communications, the data processing system comprising: a storage device including a storage medium, wherein the storage device stores computer usable program code; and a processor, wherein the processor executes the computer usable program code, and wherein the computer usable program code comprises: computer usable code for storing a short communication in an element of a line cache accessible to an application executing in a data processing system, the element being an element in a set of elements in the line cache; computer usable code for assembling a compound text from contents of a subset of the elements of the line cache; computer usable code for receiving a language identifier (language ID) for the compound text from a language detection algorithm; computer usable code for storing the language ID in a language cache element of a language ID cache accessible to the application, the language ID cache including a set of language cache elements; and computer usable code for determining, using contents of a subset of language cache elements, a language of the short communication. 19. The data processing system of claim 17 , wherein the short communication is a set of short communications, further comprising: computer usable code for receiving the set of short communications at the application; computer usable code for storing the set of short communications using a subset of elements of the line cache; computer usable code for determining whether the compound text can be assembled from contents of a second subset of the elements of the line cache; computer usable code for assembling, responsive to the determining whether the compound text can be assembled being affirmative, the compound text using a subset of the short communications, the compound text being of a length at least equal to a threshold length of text required by the language detection algorithm for language detection; and computer usable code for sending the compound text to the language detection algorithm. | 0.5 |
9,965,534 | 11 | 13 | 11. A computer system comprising: one or more processors; one or more non-transitory data storage media coupled to the one or more processors and storing instructions which, when executed by the one or more processors, cause: processing a table definition composed in a domain-specific language, the table definition comprising a sequence of one or more dataset transformations to be performed on one or more source tables to generate a target table; retrieving an intermediate table that was generated based on performing a first dataset transformation of the one or more dataset transformations on a previous version of a particular source table of the one or more source tables; generating a supplemental portion for the intermediate table based on performing a second dataset transformation on an appended portion of an updated version of the particular source table; generating the target table based on performing a third dataset transformation on the intermediate table and the supplemental portion for the intermediate table. | 11. A computer system comprising: one or more processors; one or more non-transitory data storage media coupled to the one or more processors and storing instructions which, when executed by the one or more processors, cause: processing a table definition composed in a domain-specific language, the table definition comprising a sequence of one or more dataset transformations to be performed on one or more source tables to generate a target table; retrieving an intermediate table that was generated based on performing a first dataset transformation of the one or more dataset transformations on a previous version of a particular source table of the one or more source tables; generating a supplemental portion for the intermediate table based on performing a second dataset transformation on an appended portion of an updated version of the particular source table; generating the target table based on performing a third dataset transformation on the intermediate table and the supplemental portion for the intermediate table. 13. The system of claim 11 , wherein the one or more storage media further comprise sequences of instructions which when executed cause performing the second dataset transformation and the third dataset transformation without being specified by an end user. | 0.627536 |
10,048,765 | 1 | 3 | 1. A non-transitory program storage device, readable by a processor and comprising instructions stored thereon to cause one or more processors to: acquire a depth image of a scene in a vicinity of a device, the first depth image having a first plurality of pixels, each pixel having a value indicative of a distance; store the depth image in a memory; develop a scene geometry based upon the depth image; determine that a user is engaging the device; identify a human hand in a region of space based on the values indicative of the distances of the first plurality of pixels; identify a three-dimensional region about the human hand, wherein the three-dimensional region includes at least some of the first plurality of pixels; partition the three-dimensional region about the human hand into a second plurality of sub-regions, each sub-region having a corresponding value and size, wherein the value of a particular sub-region comprises a number of human hand pixels within the particular sub-region, wherein the sizes of the sub-regions are configured so that the number of human hand pixels within each sub-region is approximately equal, and wherein the sizes of the sub-regions are non-uniform; generate a feature vector for the human hand based on the values of the second plurality of sub-regions; apply the feature vector to a classifier; determine that the human hand is making an identified gesture based on output from the classifier; and cause an action to be taken by the device, based, at least in part, upon the identified gesture and the scene geometry. | 1. A non-transitory program storage device, readable by a processor and comprising instructions stored thereon to cause one or more processors to: acquire a depth image of a scene in a vicinity of a device, the first depth image having a first plurality of pixels, each pixel having a value indicative of a distance; store the depth image in a memory; develop a scene geometry based upon the depth image; determine that a user is engaging the device; identify a human hand in a region of space based on the values indicative of the distances of the first plurality of pixels; identify a three-dimensional region about the human hand, wherein the three-dimensional region includes at least some of the first plurality of pixels; partition the three-dimensional region about the human hand into a second plurality of sub-regions, each sub-region having a corresponding value and size, wherein the value of a particular sub-region comprises a number of human hand pixels within the particular sub-region, wherein the sizes of the sub-regions are configured so that the number of human hand pixels within each sub-region is approximately equal, and wherein the sizes of the sub-regions are non-uniform; generate a feature vector for the human hand based on the values of the second plurality of sub-regions; apply the feature vector to a classifier; determine that the human hand is making an identified gesture based on output from the classifier; and cause an action to be taken by the device, based, at least in part, upon the identified gesture and the scene geometry. 3. The non-transitory program storage device of claim 1 , wherein the instructions further cause the one or more processors to monitor and analyze body or limb activity of a second user. | 0.701923 |
8,018,441 | 9 | 10 | 9. A character input method for automatically switching an input mode in a terminal having a touch screen, the character input method comprising: in a text input mode for inputting a word including one of characters from character groups, each of which includes at least two characters, assigning the character groups to at least two key regions acquired by dividing a region of the touch screen and displaying the character groups in the corresponding key regions based on one-to-one correspondence; if a press event occurs in a first of the key regions, counting time from a point of time at which the press event occurs; if the counted time exceeds a previously stored threshold value, switching to a separate input mode for inputting one of characters from a corresponding character group; upon execution of the separate input mode, assigning each character of the character group associated with the first key region to a different one of the key regions other than the first key region key region and displaying the characters of the character group in the other key regions; determining whether a release event occurs in one of the other key regions assigned to the each character; and outputting a character in the key region where the release event occurs onto a predetermined input editor window of the touch screen. | 9. A character input method for automatically switching an input mode in a terminal having a touch screen, the character input method comprising: in a text input mode for inputting a word including one of characters from character groups, each of which includes at least two characters, assigning the character groups to at least two key regions acquired by dividing a region of the touch screen and displaying the character groups in the corresponding key regions based on one-to-one correspondence; if a press event occurs in a first of the key regions, counting time from a point of time at which the press event occurs; if the counted time exceeds a previously stored threshold value, switching to a separate input mode for inputting one of characters from a corresponding character group; upon execution of the separate input mode, assigning each character of the character group associated with the first key region to a different one of the key regions other than the first key region key region and displaying the characters of the character group in the other key regions; determining whether a release event occurs in one of the other key regions assigned to the each character; and outputting a character in the key region where the release event occurs onto a predetermined input editor window of the touch screen. 10. The character input method of claim 9 , further comprising: if the counted time does not exceed the previously stored threshold value, determining whether the release event occurs; if the release event occurs, searching for words including characters of the key region where the release event occurs; detecting a word that is most frequently used based on a search result; and outputting the detected word. | 0.5 |
10,080,114 | 11 | 12 | 11. The system of claim 10 , wherein the memory further stores instructions that, when executed by the at least one processor, causes the system to: determine that a first candidate entity and a second candidate entity each correspond to a same recognized item for a first image in the first portion of the window; determine that the first candidate entity shares a category with a mobile application associated with the first image; and select the first candidate entity over the second candidate entity based on sharing the category. | 11. The system of claim 10 , wherein the memory further stores instructions that, when executed by the at least one processor, causes the system to: determine that a first candidate entity and a second candidate entity each correspond to a same recognized item for a first image in the first portion of the window; determine that the first candidate entity shares a category with a mobile application associated with the first image; and select the first candidate entity over the second candidate entity based on sharing the category. 12. The system of claim 11 , wherein the second candidate entity has a higher prior probability than the first candidate entity. | 0.5 |
9,953,065 | 5 | 6 | 5. A computer system for processing a query in a database, the computer system comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising; determining a plurality of reference values for a plurality of datasets with entries associated with the database, wherein the database is stored on a first computer, wherein a number of characters in each reference value within the determined plurality of reference values is equal to or less than a maximum number of characters per entry of the datasets, wherein determining the plurality of reference values comprises determining a frequency of a certain character on a certain digit of the entries of the database and selecting each reference value within the plurality of reference values based on a plurality of characters being found with a highest frequency on a plurality of individual digits per entry of the datasets, and wherein a sequence of the plurality of characters associated with each reference value within the plurality of reference values is adapted to a plurality of sequences of characters of the plurality of values of the entries of the dataset; assigning the determined plurality of reference values to the plurality of datasets with entries associated with the database; assigning a plurality of distance statistics to the plurality of datasets associated with the database, wherein the assigned plurality of distance statistics describe a minimum and a maximum distance between a plurality of values of the entries of a dataset within the plurality of datasets and an assigned reference value within the assigned plurality of reference values; receiving, from a second computer, the query associated with the database, wherein the received query comprises a search value; identifying the search value within the received query; determining a search reference value based on the identified search value, wherein a first three characters of the identified search value matches a first three characters of the determined search reference value; determining the distance between the identified search value and the determined search reference value, said determination resulting in a search distance; determining a subset of datasets from the plurality of datasets for which the search distance is within a limit given by the minimum and maximum distances described by the respective distance statistics; and searching for the search value in the subset of datasets. | 5. A computer system for processing a query in a database, the computer system comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising; determining a plurality of reference values for a plurality of datasets with entries associated with the database, wherein the database is stored on a first computer, wherein a number of characters in each reference value within the determined plurality of reference values is equal to or less than a maximum number of characters per entry of the datasets, wherein determining the plurality of reference values comprises determining a frequency of a certain character on a certain digit of the entries of the database and selecting each reference value within the plurality of reference values based on a plurality of characters being found with a highest frequency on a plurality of individual digits per entry of the datasets, and wherein a sequence of the plurality of characters associated with each reference value within the plurality of reference values is adapted to a plurality of sequences of characters of the plurality of values of the entries of the dataset; assigning the determined plurality of reference values to the plurality of datasets with entries associated with the database; assigning a plurality of distance statistics to the plurality of datasets associated with the database, wherein the assigned plurality of distance statistics describe a minimum and a maximum distance between a plurality of values of the entries of a dataset within the plurality of datasets and an assigned reference value within the assigned plurality of reference values; receiving, from a second computer, the query associated with the database, wherein the received query comprises a search value; identifying the search value within the received query; determining a search reference value based on the identified search value, wherein a first three characters of the identified search value matches a first three characters of the determined search reference value; determining the distance between the identified search value and the determined search reference value, said determination resulting in a search distance; determining a subset of datasets from the plurality of datasets for which the search distance is within a limit given by the minimum and maximum distances described by the respective distance statistics; and searching for the search value in the subset of datasets. 6. The computer system of claim 5 , wherein the reference value is one of a plurality of reference values, wherein the distance statistics comprise minimum and maximum distances for each of the reference values, wherein the determination of the search distance is performed for each of the reference values resulting in a set of search distances, wherein the determination of the subset of datasets is performed for each search distance of the set of search distances. | 0.5 |
8,938,393 | 9 | 10 | 9. The method of claim 8 further comprising recognizing the aspect by: comparing the identified portion with a set of voice samples to find at least one best matching sample; and outputting at least one of a speaker name and a character name. | 9. The method of claim 8 further comprising recognizing the aspect by: comparing the identified portion with a set of voice samples to find at least one best matching sample; and outputting at least one of a speaker name and a character name. 10. The method of claim 9 wherein the comparing comprises: representing a voice sample as one of a MFC coefficient vector and a feature vector; computing at least one of a Euclidean distance and a correlation measure from the representation; and outputting at least one best matching sample in probability order having at least one of a low Euclidean distance and a high correlation measure. | 0.5 |
10,162,690 | 1 | 8 | 1. A computer-implemented method, comprising: operating an application on at least one computer in a first computer language; operating a platform for the application on the at least one computer in a second computer language; binding the first computer language with the second computer language; and communicating between the application and the platform using the binding of the first computer language and the second computer language, wherein communicating between the application and the platform comprises: executing a coroutine thread in one of the first and second computer languages; and tracking the coroutine thread in another one of the first and second computer languages. | 1. A computer-implemented method, comprising: operating an application on at least one computer in a first computer language; operating a platform for the application on the at least one computer in a second computer language; binding the first computer language with the second computer language; and communicating between the application and the platform using the binding of the first computer language and the second computer language, wherein communicating between the application and the platform comprises: executing a coroutine thread in one of the first and second computer languages; and tracking the coroutine thread in another one of the first and second computer languages. 8. The method of claim 1 , wherein the platform comprises a database comprising data for the application. | 0.803371 |
8,098,409 | 1 | 6 | 1. An image distribution system via e-mail comprising: a first user terminal; a server serving to receive a message consisting of an ideogram string input from said first user terminal and to transmit the received message together with an image attached thereto to said first user terminal; and an internetwork via which said first user terminal and said server are connected to each other, wherein said server comprises: storage means adapted to store an ideogram string element or elements including characters, symbols, graphics or combination thereof respectively corresponding to an expression, attitude or posture representing an emotion or situation put into a message inputted by a user of said first user terminal, said storage means being adapted to store images corresponding to said ideogram string element or elements, recognizing means adapted to recognize the ideogram string element or elements from the message inputted by the user of said first user terminal, and image distribution means adapted to pick up the image corresponding to the ideogram string element or elements having been recognized by said recognizing means and to distribute the corresponding image to said first user terminal via the internetwork. | 1. An image distribution system via e-mail comprising: a first user terminal; a server serving to receive a message consisting of an ideogram string input from said first user terminal and to transmit the received message together with an image attached thereto to said first user terminal; and an internetwork via which said first user terminal and said server are connected to each other, wherein said server comprises: storage means adapted to store an ideogram string element or elements including characters, symbols, graphics or combination thereof respectively corresponding to an expression, attitude or posture representing an emotion or situation put into a message inputted by a user of said first user terminal, said storage means being adapted to store images corresponding to said ideogram string element or elements, recognizing means adapted to recognize the ideogram string element or elements from the message inputted by the user of said first user terminal, and image distribution means adapted to pick up the image corresponding to the ideogram string element or elements having been recognized by said recognizing means and to distribute the corresponding image to said first user terminal via the internetwork. 6. The image distribution system via e-mail according to claim 1 , wherein the ideogram string element or elements comprises character(s). | 0.884228 |
10,069,770 | 15 | 18 | 15. A non-transitory computer readable storage medium configured to store instructions that when executed cause a processor to perform: pre-processing a message at a message processing server to determine a particular contextual classification associated with at least one word included in the message; assigning the message to a predefined message bucket comprising a plurality of automated responses by selecting at least one of a plurality of different predefined message buckets, wherein one of the predefined message buckets has a higher relevancy rating than the other plurality of different predefined message buckets based on a relevancy rating of the particular contextual classification associated with the at least one word included in the message; and processing the message to determine whether to generate the automated response and transmit the automated response to an end user device; wherein prior to assigning the message to the predefined message bucket, at least one term in the message is replaced with a known alias term linked to the predefined message bucket. | 15. A non-transitory computer readable storage medium configured to store instructions that when executed cause a processor to perform: pre-processing a message at a message processing server to determine a particular contextual classification associated with at least one word included in the message; assigning the message to a predefined message bucket comprising a plurality of automated responses by selecting at least one of a plurality of different predefined message buckets, wherein one of the predefined message buckets has a higher relevancy rating than the other plurality of different predefined message buckets based on a relevancy rating of the particular contextual classification associated with the at least one word included in the message; and processing the message to determine whether to generate the automated response and transmit the automated response to an end user device; wherein prior to assigning the message to the predefined message bucket, at least one term in the message is replaced with a known alias term linked to the predefined message bucket. 18. The non-transitory computer readable storage medium of claim 15 , wherein the processor is configured to identify an automated response to the message that includes the contextual information. | 0.666667 |
8,212,695 | 1 | 5 | 1. A method for generating a hierarchical data structure associated with a plurality of arbitrary-length bit strings, the method comprising: a) for each of the plurality of arbitrary-length bit strings within a group, hashing the arbitrary-length bit string, using a selected hash function from a plurality of hash functions, to generate a hash value representing an n-bit binary address defining a location of a virtual bin; b) for each of n bit locations, determining a bit location count of all of the generated n-bit binary addresses; c) determining a representative bit location corresponding to one of the n bit locations; d) storing an indication of the hash function and the representative bit location; e) for each of the plurality of arbitrary-length bit strings, assigning the arbitrary-length bit string to one of a first group and a second group using a bit value at the representative bit location of its hash value, wherein the arbitrary-length bit string is assigned to a first group if the bit value is of a fist bit value and a second group if the bit value is of a second bit value; f) for each of the groups, repeating acts (a) through (e) to generate two further sub-groups until each of the two further sub-groups has one or no assigned arbitrary-length bit string; and g) storing, for each of the plurality of arbitrary-length bit strings, the arbitrary-length bit string or a pointer thereto, in a memory location defined by a concatenation of the bit values. | 1. A method for generating a hierarchical data structure associated with a plurality of arbitrary-length bit strings, the method comprising: a) for each of the plurality of arbitrary-length bit strings within a group, hashing the arbitrary-length bit string, using a selected hash function from a plurality of hash functions, to generate a hash value representing an n-bit binary address defining a location of a virtual bin; b) for each of n bit locations, determining a bit location count of all of the generated n-bit binary addresses; c) determining a representative bit location corresponding to one of the n bit locations; d) storing an indication of the hash function and the representative bit location; e) for each of the plurality of arbitrary-length bit strings, assigning the arbitrary-length bit string to one of a first group and a second group using a bit value at the representative bit location of its hash value, wherein the arbitrary-length bit string is assigned to a first group if the bit value is of a fist bit value and a second group if the bit value is of a second bit value; f) for each of the groups, repeating acts (a) through (e) to generate two further sub-groups until each of the two further sub-groups has one or no assigned arbitrary-length bit string; and g) storing, for each of the plurality of arbitrary-length bit strings, the arbitrary-length bit string or a pointer thereto, in a memory location defined by a concatenation of the bit values. 5. The method of claim 1 wherein a representative bit location is a bit location such that its bit location count has a value equal to half the number of all of the generated n-bit binary addresses. | 0.512315 |
4,427,848 | 28 | 30 | 28. The system of claim 27 wherein said counter means includes means, responsive to said strobe signal, for resetting said count to a predetermined value. | 28. The system of claim 27 wherein said counter means includes means, responsive to said strobe signal, for resetting said count to a predetermined value. 30. The system of claim 28 wherein said counter means includes means responsive to a predetermined first particular supervisory signal for selectively enabling said counter means; and means, responsive to a predetermined second particular supervisory signal for inhibiting said counter means and maintaining said count at said predetermined value. | 0.5 |
7,667,692 | 1 | 2 | 1. A method for configuring a human interface and input system for use with a host hand-held electronic device configured to run applications, wherein at least one of the applications is associated with multiple input functions, the method comprising: selectively disposing on a first surface of the system a first input assembly having input elements configured to receive input from a human user through manipulation of the input elements, wherein at least one of the input elements of the first input assembly is further configured to map to one or more of the input functions associated with a selected one of the applications; selectively disposing on a second surface a second input assembly having one or more input elements configured to be manipulated by one or more of the human user's fingers, wherein at least one of the input elements of the second input assembly is further configured to selectively map to one or more of the input functions associated with the selected application; and selectively arranging the first input assembly and the second input assembly in substantial opposition to each other. | 1. A method for configuring a human interface and input system for use with a host hand-held electronic device configured to run applications, wherein at least one of the applications is associated with multiple input functions, the method comprising: selectively disposing on a first surface of the system a first input assembly having input elements configured to receive input from a human user through manipulation of the input elements, wherein at least one of the input elements of the first input assembly is further configured to map to one or more of the input functions associated with a selected one of the applications; selectively disposing on a second surface a second input assembly having one or more input elements configured to be manipulated by one or more of the human user's fingers, wherein at least one of the input elements of the second input assembly is further configured to selectively map to one or more of the input functions associated with the selected application; and selectively arranging the first input assembly and the second input assembly in substantial opposition to each other. 2. The method of claim 1 further comprising connecting a controller to the input elements of the first input assembly or the second input assembly to receive signals generated by a manipulation of one or more of the input elements-of first input assembly or the second input assembly. | 0.5 |
9,177,346 | 1 | 9 | 1. A method comprising: by one or more computing systems, receiving an indication of a first user action by a first user; by one or more computing systems, when the indication is received: analyzing content of the first user action; determining a topic of the first user action based at least in part on the analysis; determining whether the topic is trending; determining whether the first user has indicated a preference to exclude posts associated with the topic or a category associated with the topic; and in response to a determining that the topic is trending and there is no indication of the preference, then: notifying the first user that the topic is trending; identifying a second user action by a second user that relates to the topic; determining whether the first user has indicated a preference to exclude posts associated with the second user; and in response to a determining that there is no indication of the preference, sending to the first user information associated with the second user action with a graphical user interface (GUI) element configured to enable the first user to interact with the second user action. | 1. A method comprising: by one or more computing systems, receiving an indication of a first user action by a first user; by one or more computing systems, when the indication is received: analyzing content of the first user action; determining a topic of the first user action based at least in part on the analysis; determining whether the topic is trending; determining whether the first user has indicated a preference to exclude posts associated with the topic or a category associated with the topic; and in response to a determining that the topic is trending and there is no indication of the preference, then: notifying the first user that the topic is trending; identifying a second user action by a second user that relates to the topic; determining whether the first user has indicated a preference to exclude posts associated with the second user; and in response to a determining that there is no indication of the preference, sending to the first user information associated with the second user action with a graphical user interface (GUI) element configured to enable the first user to interact with the second user action. 9. The method of claim 1 , wherein: the first and second users are users of a social-networking system; and determining whether the topic is trending comprises determining whether the topic is trending across a portion of the social-networking system that is relevant to the first user. | 0.719608 |
9,208,472 | 13 | 16 | 13. In a computing environment, a method performed at least in part on at least one processor, comprising: maintaining a set of models, each model comprising one or more of the following: rules, constraints, and equations by which that model generates one or more searches to obtain a set of content objects and filters the set of content objects obtained from the one or more searches to generate a plan comprising plan objects; providing a first user access to a selected model for authoring a new model therefrom, including one or more of the following: allowing content of the selected model to be used for editing into the new model, and allowing content of the selected model to be combined with content from one or more other models from the set of models into the new model; maintaining the new model as a model of the set of models; locating the new model for a second user; generating a plan from the new model based upon the new model and user parameter input; and producing an interactive presentation from the plan for presenting to the second user. | 13. In a computing environment, a method performed at least in part on at least one processor, comprising: maintaining a set of models, each model comprising one or more of the following: rules, constraints, and equations by which that model generates one or more searches to obtain a set of content objects and filters the set of content objects obtained from the one or more searches to generate a plan comprising plan objects; providing a first user access to a selected model for authoring a new model therefrom, including one or more of the following: allowing content of the selected model to be used for editing into the new model, and allowing content of the selected model to be combined with content from one or more other models from the set of models into the new model; maintaining the new model as a model of the set of models; locating the new model for a second user; generating a plan from the new model based upon the new model and user parameter input; and producing an interactive presentation from the plan for presenting to the second user. 16. The method of claim 13 further comprising: authoring another new model from the new model, wherein authoring another new model from the new model includes one or more of the following: allowing content of the new model to be used for editing into other new model, and allowing content of the new model to be combined with content from one or more other models. | 0.5 |
7,680,335 | 13 | 17 | 13. A system for identifying a structure of interest within image data, comprising: an image receiving unit for receiving image data; a first graphical user interface for displaying the received image data and soliciting an initial point within the received image data from a user; an image processing unit for transforming the received image data into a scale-space for performing geometric fitting using prior-constrained mean shift on the scale-space image data to identify a structure candidate in a vicinity of the initial point and for setting up a prior constraint for subsequent iterations; and a second graphical user interface for presenting the identified structure candidate to a user and querying the user to determine whether the identified structure candidate is a structure of interest, wherein when the identified structure candidate is determined to not be a structure of interest, performing geometric fitting using prior-constrained mean shift and presenting an identified structure candidate are repeated until it is determined that an identified structure candidate is a structure of interest. | 13. A system for identifying a structure of interest within image data, comprising: an image receiving unit for receiving image data; a first graphical user interface for displaying the received image data and soliciting an initial point within the received image data from a user; an image processing unit for transforming the received image data into a scale-space for performing geometric fitting using prior-constrained mean shift on the scale-space image data to identify a structure candidate in a vicinity of the initial point and for setting up a prior constraint for subsequent iterations; and a second graphical user interface for presenting the identified structure candidate to a user and querying the user to determine whether the identified structure candidate is a structure of interest, wherein when the identified structure candidate is determined to not be a structure of interest, performing geometric fitting using prior-constrained mean shift and presenting an identified structure candidate are repeated until it is determined that an identified structure candidate is a structure of interest. 17. The system of claim 13 , wherein a goodness fit is performed on the identified structure candidate prior to presenting the identified structure candidate. | 0.789894 |
9,147,395 | 13 | 14 | 13. The mobile terminal of claim 9 , further comprising: a display unit configured to display a menu button for executing the personal information protection function. | 13. The mobile terminal of claim 9 , further comprising: a display unit configured to display a menu button for executing the personal information protection function. 14. The mobile terminal of claim 13 , wherein the controller blocks the received voice from being provided to the first voice recognition engine when the personal information protection function is executed in response to a touch input to the menu button. | 0.5 |
9,268,615 | 13 | 17 | 13. A method as claimed in claim 1 which comprises storing the graph layout view, the distributed computing graph and visualization elements associated with the distributed computing graph as a document; and replicating and synchronizing that document at a plurality of entities in the distributed computing system. | 13. A method as claimed in claim 1 which comprises storing the graph layout view, the distributed computing graph and visualization elements associated with the distributed computing graph as a document; and replicating and synchronizing that document at a plurality of entities in the distributed computing system. 17. A method as claimed in claim 13 which comprises: using a tree structure to store the document where nodes of the tree represent components of the document and have associated properties; and storing each node of the tree and each property as a row in a relational database. | 0.5 |
7,801,644 | 9 | 14 | 9. A computer readable medium having computer executable instructions thereon, which when executed on a processor provide a generic robot architecture, comprising: a hardware abstraction level configured for developing a plurality of hardware abstractions for defining, monitoring, and controlling a plurality of hardware modules available on a robot platform; a robot abstraction level configured for defining a plurality of robot attributes comprising at least one of the plurality of hardware abstractions; and providing a robot behavior level configured for defining a plurality of robot behaviors comprising at least one of the plurality of robot attributes; wherein: each robot attribute of the plurality is configured for substantially isolating the robot behaviors from the plurality of hardware abstractions; each hardware abstraction of the plurality is configured for substantially isolating the plurality of robot attributes from a corresponding hardware module of the plurality; at least two hardware abstractions provide substantially similar hardware information to at least one of the plurality of robot attributes; and the at least one of the plurality of robot attributes combines the hardware information from each of the at least two hardware abstractions to form attribute information for the at least one of the plurality of robot attributes and can disregard the hardware information from one of the at least two hardware abstractions in forming the attribute information. | 9. A computer readable medium having computer executable instructions thereon, which when executed on a processor provide a generic robot architecture, comprising: a hardware abstraction level configured for developing a plurality of hardware abstractions for defining, monitoring, and controlling a plurality of hardware modules available on a robot platform; a robot abstraction level configured for defining a plurality of robot attributes comprising at least one of the plurality of hardware abstractions; and providing a robot behavior level configured for defining a plurality of robot behaviors comprising at least one of the plurality of robot attributes; wherein: each robot attribute of the plurality is configured for substantially isolating the robot behaviors from the plurality of hardware abstractions; each hardware abstraction of the plurality is configured for substantially isolating the plurality of robot attributes from a corresponding hardware module of the plurality; at least two hardware abstractions provide substantially similar hardware information to at least one of the plurality of robot attributes; and the at least one of the plurality of robot attributes combines the hardware information from each of the at least two hardware abstractions to form attribute information for the at least one of the plurality of robot attributes and can disregard the hardware information from one of the at least two hardware abstractions in forming the attribute information. 14. The computer readable medium of claim 9 , wherein the robot abstraction level further comprises a plurality of environment abstractions wherein the plurality of environment abstractions provide environment information about an environment around the robot to an operator, to the robot behaviors, to another robot, or to combinations thereof. | 0.681734 |
8,688,444 | 15 | 16 | 15. A computer-readable storage medium having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: transmitting automatic speech recognition data from a first device to a second device, wherein the first device performs speech recognition using automatic speech recognition parameters based on the automatic speech recognition data; receiving, at the first device, a new set of automatic speech recognition adaptation parameters from the second device, wherein the new set of automatic speech recognition adaptation parameters is based on the automatic speech recognition data; and using the new set of automatic speech recognition adaptation parameters to update the automatic speech recognition adaptation parameters on the first device. | 15. A computer-readable storage medium having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: transmitting automatic speech recognition data from a first device to a second device, wherein the first device performs speech recognition using automatic speech recognition parameters based on the automatic speech recognition data; receiving, at the first device, a new set of automatic speech recognition adaptation parameters from the second device, wherein the new set of automatic speech recognition adaptation parameters is based on the automatic speech recognition data; and using the new set of automatic speech recognition adaptation parameters to update the automatic speech recognition adaptation parameters on the first device. 16. The computer-readable storage medium of claim 15 , wherein the new set of automatic speech recognition adaptation parameters is also based on stored user specific adaptation data. | 0.596916 |
8,219,315 | 1 | 5 | 1. A method of creating and playing customizable audio alerts in a personal navigation device, the method comprising: adding, by a user of the personal navigation device via the personal navigation device, a user-customizable text message to a message field of a point of interest (POI) data structure for a POI to create an updated POI data structure, the message field of the POI data structure comprising a plurality of text messages, the POI data structure further comprising a text message category field comprising a plurality of text message categories, each of the plurality of text messages having a corresponding text message category for indicating a content type of the text message; storing the updated POI data structure in a memory of the personal navigation device; receiving current position information of the personal navigation device; comparing the current position information of the personal navigation device with position coordinates associated with the updated POI data structure; and converting the text message of the updated POI data structure to speech and playing the speech through a speaker of the personal navigation device when the position comparison indicates that the personal navigation device is within a predetermined radius of the POI. | 1. A method of creating and playing customizable audio alerts in a personal navigation device, the method comprising: adding, by a user of the personal navigation device via the personal navigation device, a user-customizable text message to a message field of a point of interest (POI) data structure for a POI to create an updated POI data structure, the message field of the POI data structure comprising a plurality of text messages, the POI data structure further comprising a text message category field comprising a plurality of text message categories, each of the plurality of text messages having a corresponding text message category for indicating a content type of the text message; storing the updated POI data structure in a memory of the personal navigation device; receiving current position information of the personal navigation device; comparing the current position information of the personal navigation device with position coordinates associated with the updated POI data structure; and converting the text message of the updated POI data structure to speech and playing the speech through a speaker of the personal navigation device when the position comparison indicates that the personal navigation device is within a predetermined radius of the POI. 5. The method of claim 1 further comprising editing the text message directly through the personal navigation device. | 0.893829 |
8,096,713 | 8 | 12 | 8. A method comprising: scanning a first copy of a project document including updates to generate image data; sending the image data to a database; locating an existing mark on a second copy of the project document; determining position data of a hand-propelled printer in response to movement of the hand-propelled printer with respect to the existing mark on the second copy of the project document, wherein the position data includes a location and an orientation of the hand-propelled printer relative to an origin and an initial orientation; receiving the image data corresponding to the updates to the project document from the database; and communicating print data to a print mechanism to selectively print the updates at correct locations on the second copy of the project document according to the position data. | 8. A method comprising: scanning a first copy of a project document including updates to generate image data; sending the image data to a database; locating an existing mark on a second copy of the project document; determining position data of a hand-propelled printer in response to movement of the hand-propelled printer with respect to the existing mark on the second copy of the project document, wherein the position data includes a location and an orientation of the hand-propelled printer relative to an origin and an initial orientation; receiving the image data corresponding to the updates to the project document from the database; and communicating print data to a print mechanism to selectively print the updates at correct locations on the second copy of the project document according to the position data. 12. The method of claim 8 further comprising determining a reference point of the project document based on scan data. | 0.865604 |
9,245,278 | 18 | 21 | 18. A method comprising: performing by one or more computer processors: obtaining an original text message in a first language authored by a first user: obtaining an initial translation of the original text message in a second language; obtaining a translation correction of the initial translation, wherein the translation correction is authored by a second user; calculating at least one metric associated with the translation correction, the at least one metric being based on a grammar-based feature of the translation correction, wherein calculating the at least one metric comprises: generating a part-of-speech n-gram representation of the translation correction; and computing a probability of the n-gram representation for the second language; and determining an accuracy of the translation correction based on the at least one metric. | 18. A method comprising: performing by one or more computer processors: obtaining an original text message in a first language authored by a first user: obtaining an initial translation of the original text message in a second language; obtaining a translation correction of the initial translation, wherein the translation correction is authored by a second user; calculating at least one metric associated with the translation correction, the at least one metric being based on a grammar-based feature of the translation correction, wherein calculating the at least one metric comprises: generating a part-of-speech n-gram representation of the translation correction; and computing a probability of the n-gram representation for the second language; and determining an accuracy of the translation correction based on the at least one metric. 21. The method of claim 18 , further comprising: offering an incentive to the second user to provide the translation correction; and rewarding the second user with the respective incentive when the translation correction is determined to be accurate. | 0.565972 |
8,583,685 | 10 | 11 | 10. The system of claim 9 , wherein the one or more processors are further configured to: determine a plurality of importance levels of the search key word units; determine, based at least on the plurality of importance levels of the search key word units, a plurality of current importance levels of the current search key word units; select among the current key word units selective current key word units whose importance levels satisfy a precondition; determine, using the plurality of search key word tables corresponding to the plurality of stages, category information that corresponds to the selective current key word unit as the current category information. | 10. The system of claim 9 , wherein the one or more processors are further configured to: determine a plurality of importance levels of the search key word units; determine, based at least on the plurality of importance levels of the search key word units, a plurality of current importance levels of the current search key word units; select among the current key word units selective current key word units whose importance levels satisfy a precondition; determine, using the plurality of search key word tables corresponding to the plurality of stages, category information that corresponds to the selective current key word unit as the current category information. 11. The system of claim 10 , wherein selecting among the current key word units selective current key word units whose importance levels satisfy a precondition that includes selecting current key word units whose importance levels meet a specified threshold. | 0.656915 |
9,607,038 | 3 | 5 | 3. The computer program product of claim 1 , wherein the linkage metadata associates at least two fragments that are members of a set of fragments comprising the target fragment and at least one matching source fragment that have a same value for a metadata attribute. | 3. The computer program product of claim 1 , wherein the linkage metadata associates at least two fragments that are members of a set of fragments comprising the target fragment and at least one matching source fragment that have a same value for a metadata attribute. 5. The computer program product of claim 3 , wherein one of the at least one matching source fragment is associated in multiple linkage metadata instances for the target fragment, wherein the multiple linkage metadata instances are based on different metadata attributes. | 0.5 |
7,953,593 | 6 | 10 | 6. The memory medium of claim 1 wherein the base component specifies values for the desired relationship parameters in a general relationship form of:
Entity 1 Directional-operator 1 Action Directional-operator 2 Entity 2 wherein at least one of Entity 1 , Entity 2 , and Action parameters contains a non null value that indicates a search term, the Directional-operator 1 parameter specifies the direction of the relationship between the Entity 1 and the Action parameters, and the Directional-operator 2 parameter specifies the direction of the relationship between the Entity 2 and the Action parameters. | 6. The memory medium of claim 1 wherein the base component specifies values for the desired relationship parameters in a general relationship form of:
Entity 1 Directional-operator 1 Action Directional-operator 2 Entity 2 wherein at least one of Entity 1 , Entity 2 , and Action parameters contains a non null value that indicates a search term, the Directional-operator 1 parameter specifies the direction of the relationship between the Entity 1 and the Action parameters, and the Directional-operator 2 parameter specifies the direction of the relationship between the Entity 2 and the Action parameters. 10. The memory medium of claim 6 wherein a specification of a value of “>” or “->” for Directional-operator 2 parameter indicates that the value indicated by the Entity 2 parameter is an object of the value indicated by the Action parameter. | 0.668956 |
8,065,302 | 1 | 4 | 1. A computer-implemented method for an aggregated annotation of a multimedia content based on a plurality of key-concepts associated with a plurality of segments of said multimedia content, and a plurality of relevance graphs, said method comprising: selecting a key-concept from said plurality of key-concepts; determining a plurality of key-concept segments of said plurality of segments; wherein said key-concept is associated with each of said plurality key-concept segments; locating a plurality of key-concept objects in said plurality of key-concept segments, wherein each of said plurality of key-concept objects corresponds with said key-concept; selecting a key-concept object from said plurality of key-concept objects; computing a count of number of objects in said plurality of key-concept objects that are similar to said key-concept object; determining a plurality of recognition accuracies of said key-concept with respect to a plurality of key-concept similar objects, wherein each of said key-concept similar objects is similar to said key-concept object; computing a mean value based on said plurality of recognition accuracies; computing a relevant factor of a plurality of relevance relevant factors of said key-concept with respect to said key-concept object of said plurality of key-concept objects based on said count and said mean value; computing a maximum relevant factor of a plurality of maximum relevant factors of said key-concept based on said plurality of relevant factors, wherein said plurality of maximum relevance factors is associated with said plurality of key-concepts; computing a plurality of most relevant key-concepts based on said plurality of maximum relevant factors; selecting a relevance graph from said plurality of relevance graphs; computing a max match factor based on said relevance graph; binding a key-concept of said plurality of most relevant key-concepts with a best matching node of said relevance graph; determining a key-concept weight associated with said key-concept based on said plurality of maximum relevant factors; determining a node weight associated with said best matching node; updating said relevance graph based on multiplying said node weight with said key-concept weight resulting in an updated relevance graph; making said updated relevance graph a part of said plurality of relevance graphs; setting of weight of each of a plurality of unbound nodes of said updated relevance graph to zero; computing a match factor based on said updated relevance graph; computing a normalized match factor of a plurality of normalized match factors based on said match factor and said max match factor, wherein said plurality of normalized match factors is associated with said plurality of relevance graphs; computing a plurality of best relevance graphs based on said plurality of relevance graphs and said plurality of normalized match factors; selecting a first relevance graph from said plurality of best relevance graphs; selecting a second relevance graph from said plurality of best relevance graphs; selecting a first node associated with a first node weight from said first relevance graph, wherein said first weight node is greater than zero; determining a second node associated with a second node weight in said second relevance graph, wherein said second node corresponds with said first node; computing a revised node weight based on said first node weight and said second node weight; updating said first node weight based on said revised node weight; determining a third node of said second relevance graph, wherein said third node has an edge with a node of second relevance graph, wherein said node corresponds with a node of said first relevance graph; making said third node a part of said first relevance graph; computing a merged graph normalized match factor of a plurality of merged graph normalized match factors based on said plurality of best relevance graphs, wherein said plurality of merged graph normalized match factors is associated with said plurality of best relevance graphs; and computing using a computer, a most relevant relevance graph based on said plurality of best relevance graphs and said plurality of merged graph normalized match factors, wherein said most relevant relevance graph is said aggregated annotation of said multimedia content. | 1. A computer-implemented method for an aggregated annotation of a multimedia content based on a plurality of key-concepts associated with a plurality of segments of said multimedia content, and a plurality of relevance graphs, said method comprising: selecting a key-concept from said plurality of key-concepts; determining a plurality of key-concept segments of said plurality of segments; wherein said key-concept is associated with each of said plurality key-concept segments; locating a plurality of key-concept objects in said plurality of key-concept segments, wherein each of said plurality of key-concept objects corresponds with said key-concept; selecting a key-concept object from said plurality of key-concept objects; computing a count of number of objects in said plurality of key-concept objects that are similar to said key-concept object; determining a plurality of recognition accuracies of said key-concept with respect to a plurality of key-concept similar objects, wherein each of said key-concept similar objects is similar to said key-concept object; computing a mean value based on said plurality of recognition accuracies; computing a relevant factor of a plurality of relevance relevant factors of said key-concept with respect to said key-concept object of said plurality of key-concept objects based on said count and said mean value; computing a maximum relevant factor of a plurality of maximum relevant factors of said key-concept based on said plurality of relevant factors, wherein said plurality of maximum relevance factors is associated with said plurality of key-concepts; computing a plurality of most relevant key-concepts based on said plurality of maximum relevant factors; selecting a relevance graph from said plurality of relevance graphs; computing a max match factor based on said relevance graph; binding a key-concept of said plurality of most relevant key-concepts with a best matching node of said relevance graph; determining a key-concept weight associated with said key-concept based on said plurality of maximum relevant factors; determining a node weight associated with said best matching node; updating said relevance graph based on multiplying said node weight with said key-concept weight resulting in an updated relevance graph; making said updated relevance graph a part of said plurality of relevance graphs; setting of weight of each of a plurality of unbound nodes of said updated relevance graph to zero; computing a match factor based on said updated relevance graph; computing a normalized match factor of a plurality of normalized match factors based on said match factor and said max match factor, wherein said plurality of normalized match factors is associated with said plurality of relevance graphs; computing a plurality of best relevance graphs based on said plurality of relevance graphs and said plurality of normalized match factors; selecting a first relevance graph from said plurality of best relevance graphs; selecting a second relevance graph from said plurality of best relevance graphs; selecting a first node associated with a first node weight from said first relevance graph, wherein said first weight node is greater than zero; determining a second node associated with a second node weight in said second relevance graph, wherein said second node corresponds with said first node; computing a revised node weight based on said first node weight and said second node weight; updating said first node weight based on said revised node weight; determining a third node of said second relevance graph, wherein said third node has an edge with a node of second relevance graph, wherein said node corresponds with a node of said first relevance graph; making said third node a part of said first relevance graph; computing a merged graph normalized match factor of a plurality of merged graph normalized match factors based on said plurality of best relevance graphs, wherein said plurality of merged graph normalized match factors is associated with said plurality of best relevance graphs; and computing using a computer, a most relevant relevance graph based on said plurality of best relevance graphs and said plurality of merged graph normalized match factors, wherein said most relevant relevance graph is said aggregated annotation of said multimedia content. 4. The method of claim 1 , wherein said computing said match factor further comprising: performing a traversal of said relevance graph; determining a source node of said relevance graph during said traversal, wherein said source node is associated with a source weight; determining a destination node of said updated relevance graph during said traversal, wherein said destination node is associated with a destination weight; determining an edge of said updated relevance graph connecting said source node and said destination node, wherein said edge is associated with an edge weight; computing a new weight based on said source node weight, said destination node weight, and said edge weight; computing a plurality of new weights associated with a plurality of terminating nodes associated with said traversal; determining a graph traversal match factor based on said plurality of new weights; computing a plurality of graph traversal match factors based on a plurality of traversals of said relevance graph; and computing said match factor based on said plurality of graph traversal match factors. | 0.509795 |
9,477,673 | 13 | 17 | 13. One or more non-transitory computer-readable media storing a first application for execution by one or more processors of a computing device comprising a touch screen display, the first application comprising instructions for: after the first application is opened, entering a first application state comprising a plurality of content item collection indicators displayed on the touch screen display; after entering the first application state, detecting a first touch gesture directed to one content item collection indicator of the plurality of content item collection indicators; wherein each content item collection indicator, of the plurality of content item collection indicators, represents one content item collection, of a plurality of content item collections, under management of a content management system; wherein performance of an earlier touch gesture directed to a graphical representation of a content item, displayed on the touch screen display, by a second application of the computing device that is not the first application, causes the first application to open and enter the first application state; after detecting the first touch gesture, assigning a copy of the content item to the content item collection, of the plurality of content item collections, represented by the one content item collection indicator to which the first touch gesture is directed. | 13. One or more non-transitory computer-readable media storing a first application for execution by one or more processors of a computing device comprising a touch screen display, the first application comprising instructions for: after the first application is opened, entering a first application state comprising a plurality of content item collection indicators displayed on the touch screen display; after entering the first application state, detecting a first touch gesture directed to one content item collection indicator of the plurality of content item collection indicators; wherein each content item collection indicator, of the plurality of content item collection indicators, represents one content item collection, of a plurality of content item collections, under management of a content management system; wherein performance of an earlier touch gesture directed to a graphical representation of a content item, displayed on the touch screen display, by a second application of the computing device that is not the first application, causes the first application to open and enter the first application state; after detecting the first touch gesture, assigning a copy of the content item to the content item collection, of the plurality of content item collections, represented by the one content item collection indicator to which the first touch gesture is directed. 17. The one or more non-transitory computer-readable media of claim 13 , wherein assigning the copy of the content item comprises storing the copy of the content item in a file system folder of the computing device that is configured for synchronization with the content item collection represented by the one content item collection indicator to which the first touch gesture is directed. | 0.523284 |
9,613,007 | 1 | 3 | 1. A method implemented by a computing device, the method comprising: identifying, by the computing device and for primary text located in a non-rectangular frame, one or more anchored text elements referenced in the primary text; and fitting, by the computing device, the one or more anchored text elements within the non-rectangular frame and at a bottom of the non-rectangular frame by iteratively repositioning the one or more anchored text elements, including: initially positioning the one or more anchored text elements at a top of the non-rectangular frame; and repositioning the one or more anchored text elements at a next computed position, including composing the one or more anchored text elements starting from the next computed position, until there are zero points of space between a bottom of the one or more anchored text elements and the bottom of the non-rectangular frame and until the one or more anchored text elements fit entirely within the non-rectangular frame. | 1. A method implemented by a computing device, the method comprising: identifying, by the computing device and for primary text located in a non-rectangular frame, one or more anchored text elements referenced in the primary text; and fitting, by the computing device, the one or more anchored text elements within the non-rectangular frame and at a bottom of the non-rectangular frame by iteratively repositioning the one or more anchored text elements, including: initially positioning the one or more anchored text elements at a top of the non-rectangular frame; and repositioning the one or more anchored text elements at a next computed position, including composing the one or more anchored text elements starting from the next computed position, until there are zero points of space between a bottom of the one or more anchored text elements and the bottom of the non-rectangular frame and until the one or more anchored text elements fit entirely within the non-rectangular frame. 3. A method as described in claim 1 , wherein a font size of the primary text and the one or more anchored text elements is measured in points, and the zero points of space corresponds to a font size measurement. | 0.747619 |
9,665,275 | 12 | 21 | 12. A computing device having one or more processors configured to perform operations comprising: displaying, at a touch display of the computing device, a first virtual keyboard having characters in a source language; receiving, at the touch display, a particular spot input indicating a start character of the first virtual keyboard; displaying, at the touch display, a second virtual keyboard having characters in the source language, the second virtual keyboard simultaneously displaying all characters for inputting a remainder of all possible multi-character compound consonants or vowels beginning with the start character using a single slide input; receiving, at the touch display, a particular slide input from the start character to an end character from the second virtual keyboard; determining a string of characters including the (i) start character, (ii) one or more additional characters of the second virtual keyboard along a path of the particular slide input, and (iii) the end character; and displaying, at the touch display, the string of characters. | 12. A computing device having one or more processors configured to perform operations comprising: displaying, at a touch display of the computing device, a first virtual keyboard having characters in a source language; receiving, at the touch display, a particular spot input indicating a start character of the first virtual keyboard; displaying, at the touch display, a second virtual keyboard having characters in the source language, the second virtual keyboard simultaneously displaying all characters for inputting a remainder of all possible multi-character compound consonants or vowels beginning with the start character using a single slide input; receiving, at the touch display, a particular slide input from the start character to an end character from the second virtual keyboard; determining a string of characters including the (i) start character, (ii) one or more additional characters of the second virtual keyboard along a path of the particular slide input, and (iii) the end character; and displaying, at the touch display, the string of characters. 21. The computing device of claim 12 , wherein the second virtual keyboard is displayed via a pop-up window overlaying the first virtual keyboard. | 0.72963 |
7,992,130 | 1 | 3 | 1. A program transformation system, comprising: a processor coupled to a memory, the processor configured to execute the following computer-executable components stored in the memory: a code generation component that generates semantically equivalent code in a class-less scripting language from an object-oriented programming language representation of a hierarchy of one or more classes or interfaces and a virtual constructor component that produces a dispatch construct that captures class and/or interface method implementation to facilitate dynamic dispatch. | 1. A program transformation system, comprising: a processor coupled to a memory, the processor configured to execute the following computer-executable components stored in the memory: a code generation component that generates semantically equivalent code in a class-less scripting language from an object-oriented programming language representation of a hierarchy of one or more classes or interfaces and a virtual constructor component that produces a dispatch construct that captures class and/or interface method implementation to facilitate dynamic dispatch. 3. The system of claim 1 , a dictionary object maps method names to one or more method implementations. | 0.78178 |
9,256,650 | 9 | 10 | 9. A computer program product comprising a non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer executable program code instructions comprising program code instructions for: obtaining topic information regarding a topic to be presented to an intended audience; obtaining knowledge information regarding the intended audience; determining one or more metaphors relating to the topic and the intended audience based at least in part on the topic information and the knowledge information, wherein a metaphor of the one or more metaphors a is term, phrase, or image which when applied to the topic information suggests a resemblance to the topic information, but is not literally relevant to the topic information; determining one or more terms related to at least one metaphor of the one or more metaphors that correlate to the one or more terms of the topic information, wherein the determining one or more terms comprises performing a comparative analysis between the topic information and the at least one metaphors; and preparing content for the topic information targeted to the intended audience based at least in part on the one or more terms related to the at least one metaphor. | 9. A computer program product comprising a non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer executable program code instructions comprising program code instructions for: obtaining topic information regarding a topic to be presented to an intended audience; obtaining knowledge information regarding the intended audience; determining one or more metaphors relating to the topic and the intended audience based at least in part on the topic information and the knowledge information, wherein a metaphor of the one or more metaphors a is term, phrase, or image which when applied to the topic information suggests a resemblance to the topic information, but is not literally relevant to the topic information; determining one or more terms related to at least one metaphor of the one or more metaphors that correlate to the one or more terms of the topic information, wherein the determining one or more terms comprises performing a comparative analysis between the topic information and the at least one metaphors; and preparing content for the topic information targeted to the intended audience based at least in part on the one or more terms related to the at least one metaphor. 10. The computer program product of claim 9 , wherein the program code instructions for determining the one or more metaphors comprise program code instructions for searching one or more repositories for a relation between the topic information and the knowledge information. | 0.657107 |
6,052,657 | 25 | 26 | 25. The computer program of claim 24, further comprising instructions to, for each language model transition in the sequence of language models, add to the language model sequence score a switch penalty. | 25. The computer program of claim 24, further comprising instructions to, for each language model transition in the sequence of language models, add to the language model sequence score a switch penalty. 26. The computer program of claim 25, wherein the switch penalty is the same for each language model transition in the sequence of language models. | 0.5 |
9,792,908 | 18 | 20 | 18. A non-transitory computer readable medium comprising instructions for analyzing the speech delivery of a user that, when executed by at least one processor, configure the at least one processor to: present to the user, via a graphical user interface on a display of a computing device, a plurality of speech delivery analysis criteria; receive from the user a selection of at least one of the speech delivery analysis criteria for analyzing the speech delivery of the user; receive from the user a text version of a speech prior to delivery of the speech by the user; transmitting the text version of the speech to an analysis engine for analysis based on the selected at least one of the speech delivery analysis criteria prior to delivery of the speech by the user; receive from at least one sensing device, speech data captured by the at least one sensing device during the delivery of the speech by the user; transmit the speech data and the selected at least one of the speech delivery analysis criteria to the analysis engine for analysis based on the selected at least one of the speech delivery analysis criteria, the selected at least one of the speech delivery analysis criteria comprising a comparison of the delivery of the speech by the user as captured by the speech data to the text version of the speech received prior to delivery of the speech by the user; receive from the analysis engine an analysis report for the speech data, the analysis report comprising an analysis of the speech data performed by the analysis engine based on the selected at least one of the speech delivery analysis criteria; and present, to the user, via the graphical user interface, the analysis report. | 18. A non-transitory computer readable medium comprising instructions for analyzing the speech delivery of a user that, when executed by at least one processor, configure the at least one processor to: present to the user, via a graphical user interface on a display of a computing device, a plurality of speech delivery analysis criteria; receive from the user a selection of at least one of the speech delivery analysis criteria for analyzing the speech delivery of the user; receive from the user a text version of a speech prior to delivery of the speech by the user; transmitting the text version of the speech to an analysis engine for analysis based on the selected at least one of the speech delivery analysis criteria prior to delivery of the speech by the user; receive from at least one sensing device, speech data captured by the at least one sensing device during the delivery of the speech by the user; transmit the speech data and the selected at least one of the speech delivery analysis criteria to the analysis engine for analysis based on the selected at least one of the speech delivery analysis criteria, the selected at least one of the speech delivery analysis criteria comprising a comparison of the delivery of the speech by the user as captured by the speech data to the text version of the speech received prior to delivery of the speech by the user; receive from the analysis engine an analysis report for the speech data, the analysis report comprising an analysis of the speech data performed by the analysis engine based on the selected at least one of the speech delivery analysis criteria; and present, to the user, via the graphical user interface, the analysis report. 20. The non-transitory computer readable medium of claim 18 , wherein the instructions further configure the at least one processor to: receive from the analysis engine an analysis report for the text version of the speech, the analysis report for the text version of the speech comprising an analysis of the text version of the speech performed by the analysis engine based on the selected at least one of the speech delivery analysis criteria; and present, to the user, via the graphical user interface, the analysis report for the text version of the speech prior to the delivery of the speech by the user. | 0.5 |
8,983,955 | 1 | 20 | 1. A computer readable medium for managing electronic information, comprising: a plurality of predefined portions of text-based data with at least one of said plurality of predefined portions of text-based data being stored; at least one modified predefined portion of text-based data, said at least one modified predefined portion of text-based data being created based at least in part on modifications to at least one of said plurality of predefined portions of text-based data; and said at least one modified predefined portion of text-based data being stored; a plurality of links comprising at least one of code or a markup language, at least one of said plurality of predefined portions of said text-based data and said at least one modified predefined portion of text-based data being associated with at least one of said plurality of links; and a plurality of attributes for organizing at least one of said plurality of predefined portions of text-based data and said at least one modified predefined portion of text-based data, at least one of said plurality of attributes defining a point in a multidimensional space. | 1. A computer readable medium for managing electronic information, comprising: a plurality of predefined portions of text-based data with at least one of said plurality of predefined portions of text-based data being stored; at least one modified predefined portion of text-based data, said at least one modified predefined portion of text-based data being created based at least in part on modifications to at least one of said plurality of predefined portions of text-based data; and said at least one modified predefined portion of text-based data being stored; a plurality of links comprising at least one of code or a markup language, at least one of said plurality of predefined portions of said text-based data and said at least one modified predefined portion of text-based data being associated with at least one of said plurality of links; and a plurality of attributes for organizing at least one of said plurality of predefined portions of text-based data and said at least one modified predefined portion of text-based data, at least one of said plurality of attributes defining a point in a multidimensional space. 20. The computer readable medium according to claim 1 , wherein said multidimensional space is configured to permit point-to-point movement within said multidimensional space. | 0.845133 |
10,083,227 | 1 | 9 | 1. A computer system comprising one or more processing units and at least one memory coupled to the one or more processing units, the computer system programmed to perform operations comprising: receiving, through a graphical user interface, input from a user for a search area for a database search, the input for the search area including a search area string received from user input and comprising one or more key words; converting the search area string into first query language operations, stored in the at least one memory, when executed by the one or more processing units, the first query language operations configured to identify one or more database tables of plural available database tables of a database, the plural available database tables associated with one or more respective data objects, stored in the at least one memory, storing description information for respective database tables, the identified database tables having one or more data objects storing description information matching at least a portion of the search area string; executing the first query language operations, the executing comprising: accessing the description information for the plural available database tables through respective data objects, the description information comprising, and stored in the respective one or more data objects, one or more of; (1) names of the plural available database tables, (2) text descriptions of the plural available database tables, and (3) data definitions for fields of the plural available database tables; determining the one or more of the plural available database tables that have description information matching the at least a portion of the search area string by comparing, using the one or more processing units, the search area string, according to operations specified by the first query language operations, with the one or more data objects stored in the at least one memory, wherein identifying information for tables determined to have matching description information is appended to first query execution results; generating first query execution results comprising the identifying information, retrieved from at least a portion of the one or more data objects stored in the at least one memory, of the determined one or more of the plural available tables; receiving, through the graphical user interface, input, comprising one or more keywords, from the user for a search string to be executed only against at least a portion of the determined one or more of the plural available tables of the first query execution results, the at least a portion of the determined one or more of the plural available tables of the first query execution results being all of the one or more of the plural available tables of the first query execution results or a portion of the plural available tables of the first query execution results selected by a user through user input received through the graphical user interface; converting the search string into second query language operations, stored in the at least one memory, when executed by the one or more processing units, the second query language operations configured to identify data stored in the at least a portion of the determined one or more of the plurality of available tables of the first query execution results having a relationship with the search string specified by at least a portion of the second query language operations; executing the second query language operations to generate second query results the executing comprising: for each table of the at least a portion of the first query execution results, each table having a plurality of fields, analyzing each field of the respective table to determine whether it can be searched to determine if values of the field have the specified relationship with the search string; for fields that can be searched, searching the table for records having the specified relationship for the respective field; and adding at least a portion of records having the specified relationship to the second query results; and returning the second query results to the user. | 1. A computer system comprising one or more processing units and at least one memory coupled to the one or more processing units, the computer system programmed to perform operations comprising: receiving, through a graphical user interface, input from a user for a search area for a database search, the input for the search area including a search area string received from user input and comprising one or more key words; converting the search area string into first query language operations, stored in the at least one memory, when executed by the one or more processing units, the first query language operations configured to identify one or more database tables of plural available database tables of a database, the plural available database tables associated with one or more respective data objects, stored in the at least one memory, storing description information for respective database tables, the identified database tables having one or more data objects storing description information matching at least a portion of the search area string; executing the first query language operations, the executing comprising: accessing the description information for the plural available database tables through respective data objects, the description information comprising, and stored in the respective one or more data objects, one or more of; (1) names of the plural available database tables, (2) text descriptions of the plural available database tables, and (3) data definitions for fields of the plural available database tables; determining the one or more of the plural available database tables that have description information matching the at least a portion of the search area string by comparing, using the one or more processing units, the search area string, according to operations specified by the first query language operations, with the one or more data objects stored in the at least one memory, wherein identifying information for tables determined to have matching description information is appended to first query execution results; generating first query execution results comprising the identifying information, retrieved from at least a portion of the one or more data objects stored in the at least one memory, of the determined one or more of the plural available tables; receiving, through the graphical user interface, input, comprising one or more keywords, from the user for a search string to be executed only against at least a portion of the determined one or more of the plural available tables of the first query execution results, the at least a portion of the determined one or more of the plural available tables of the first query execution results being all of the one or more of the plural available tables of the first query execution results or a portion of the plural available tables of the first query execution results selected by a user through user input received through the graphical user interface; converting the search string into second query language operations, stored in the at least one memory, when executed by the one or more processing units, the second query language operations configured to identify data stored in the at least a portion of the determined one or more of the plurality of available tables of the first query execution results having a relationship with the search string specified by at least a portion of the second query language operations; executing the second query language operations to generate second query results the executing comprising: for each table of the at least a portion of the first query execution results, each table having a plurality of fields, analyzing each field of the respective table to determine whether it can be searched to determine if values of the field have the specified relationship with the search string; for fields that can be searched, searching the table for records having the specified relationship for the respective field; and adding at least a portion of records having the specified relationship to the second query results; and returning the second query results to the user. 9. The computer system of claim 1 , wherein results of the database search indicate real-time status of the database. | 0.929603 |
8,719,007 | 1 | 11 | 1. A method for determining offer terms from text, comprising: mapping keywords from a procurement event to a domain of the procurement event; receiving, to a computing device, an offer text associated with the procurement event; identifying, by the computing device, event-specific entities in the offer text; determining, by the computing device, the domain of the procurement event from the identified event-specific entities; and using the mapped keywords corresponding to the determined domain: determining, by the computing device, offer components from the offer text; extracting, by the computing device, offer parameters from the offer text; and constructing, by a computing device, an offer structure using the identified event-specific entities, derived offer components, and extracted offer parameters. | 1. A method for determining offer terms from text, comprising: mapping keywords from a procurement event to a domain of the procurement event; receiving, to a computing device, an offer text associated with the procurement event; identifying, by the computing device, event-specific entities in the offer text; determining, by the computing device, the domain of the procurement event from the identified event-specific entities; and using the mapped keywords corresponding to the determined domain: determining, by the computing device, offer components from the offer text; extracting, by the computing device, offer parameters from the offer text; and constructing, by a computing device, an offer structure using the identified event-specific entities, derived offer components, and extracted offer parameters. 11. The method of claim 1 , wherein determining the offer components includes deriving from the offer text a condition metric, condition scope, threshold value, a threshold comparison operator, and at least one item to which the condition metric, condition scope, threshold value, and threshold comparison operator apply. | 0.518018 |
6,163,775 | 37 | 38 | 37. The method of claim 31 wherein at least one of said attribute sets defines cells that include a plurality of pointers to other attribute sets within the same record, said pointers indicating those attribute sets within the same record that contain defined values. | 37. The method of claim 31 wherein at least one of said attribute sets defines cells that include a plurality of pointers to other attribute sets within the same record, said pointers indicating those attribute sets within the same record that contain defined values. 38. The method of claim 37 wherein at least one of said records is a folder type record, said folder type record including at least one cell that contains data and a plurality of pointers to a plurality of other records included within said folder. | 0.5 |
7,664,325 | 1 | 12 | 1. A computer-readable medium storing computer-executable instructions that, when executed, cause one or more processors to perform steps comprising: (a) forming a primitive structure from a handwritten document, the primitive structure being associated with a set of component objects; (b) detecting a logical structure of a candidate handwritten object from the set of component objects; (c) determining a classifier for the candidate handwritten object; and (d) validating the candidate handwritten object from the classifier to obtain a validated handwritten object. | 1. A computer-readable medium storing computer-executable instructions that, when executed, cause one or more processors to perform steps comprising: (a) forming a primitive structure from a handwritten document, the primitive structure being associated with a set of component objects; (b) detecting a logical structure of a candidate handwritten object from the set of component objects; (c) determining a classifier for the candidate handwritten object; and (d) validating the candidate handwritten object from the classifier to obtain a validated handwritten object. 12. The computer-readable medium of claim 1 , wherein the computer-executable instructions, when executed, cause the one or more processors to detect the logical structure of the candidate handwritten object further include: normalizing a component object by replacing the component object with a structurally consistent component object. | 0.555263 |
9,037,580 | 14 | 15 | 14. The method according to claim 13 , wherein the applying a logical synthesis component includes determining from the input query a procedure for synthesizing the resultant candidate answer for the input query from said at least one of the candidate answers to each of the subqueries. | 14. The method according to claim 13 , wherein the applying a logical synthesis component includes determining from the input query a procedure for synthesizing the resultant candidate answer for the input query from said at least one of the candidate answers to each of the subqueries. 15. The method according to claim 14 , wherein the determining the procedure for synthesizing the candidate answers includes using said natural language processing, when decomposing said at least one of the input queries, to determine said procedure. | 0.5 |
8,892,417 | 3 | 34 | 3. The computer program product of claim 1 wherein the plurality of instructions are further configured for (1) receiving source data relating to a subject, (2) computing a plurality of derived features based at least in part on the received source data, wherein the processed data comprises the source data and the derived features, and (3) generating an evaluation indicator indicative of whether a narrative story relating to the processed data that incorporates a story angle of the angle set data structure whose applicability conditions were satisfied by the processed data is to be generated. | 3. The computer program product of claim 1 wherein the plurality of instructions are further configured for (1) receiving source data relating to a subject, (2) computing a plurality of derived features based at least in part on the received source data, wherein the processed data comprises the source data and the derived features, and (3) generating an evaluation indicator indicative of whether a narrative story relating to the processed data that incorporates a story angle of the angle set data structure whose applicability conditions were satisfied by the processed data is to be generated. 34. The computer program product of claim 3 wherein the plurality of instructions are further configured for execution by a first processor and a second processor, wherein the instructions configured for performing the receiving operation, the derived features computation operation, the processing operation, and the generation operation are for execution by the first processor, wherein the plurality of instructions are further configured for execution by the first processor to communicate the evaluation indicator to the second processor, and wherein the instructions further comprising a plurality of additional instructions for execution by the second processor, the additional instructions configured for automatically generating a narrative story in response to the communicated evaluation indicator indicating that the narrative story is to be generated. | 0.5 |
6,154,720 | 2 | 24 | 2. The conversational sentence translation apparatus according to claim 1, wherein said semantic searcher selects a plurality of conversational sentence examples having highest degrees of semantic coincidence in the order of decreasing degree of semantic coincidence; said apparatus further comprises a selector for selecting, through a dialogue with a user, a conversational sentence example semantically closer to the input conversational sentence than any other, from among the plurality of conversational sentence examples selected by the semantic searcher; and said display means displays the conversational sentence example selected by the selector and the translation thereof. | 2. The conversational sentence translation apparatus according to claim 1, wherein said semantic searcher selects a plurality of conversational sentence examples having highest degrees of semantic coincidence in the order of decreasing degree of semantic coincidence; said apparatus further comprises a selector for selecting, through a dialogue with a user, a conversational sentence example semantically closer to the input conversational sentence than any other, from among the plurality of conversational sentence examples selected by the semantic searcher; and said display means displays the conversational sentence example selected by the selector and the translation thereof. 24. The conversational sentence translation apparatus according to claim 2, wherein the selector comprises a correction deciding means for presenting a plurality of conversational sentence examples selected by the semantic searcher prior to the selection of a conversational sentence example to decide through a dialogue with the user whether or not a correction to the conversational sentence entered through the input means is necessary, and for, if deciding that a correction is necessary, transmitting a control signal to the input means and the analyzer; the input means, upon receiving the control signal from the correction deciding means, permits an input of an additional sentence to be added to the last input conversational sentence; and the analyzer comprises a conversational sentence retaining means for retaining an input conversational sentence, so that upon receiving the control signal from the correction deciding means, the analyzer extracts the semantic features from an input conversational sentence generated by adding the additional sentence, entered through the input means, to the input conversational sentence retained in the conversational sentence retaining means. | 0.5 |
7,899,810 | 9 | 12 | 9. A hardware computer storage device with computer executable instructions for accessing a database, comprising executable instructions to: present a user at a client computer with a set of business objects, wherein the business objects include familiar terms corresponding to information about the structure of the database; receive a plurality of selected business objects; generate a SQL query from the selected business objects, wherein the SQL query includes a SELECT clause and a FROM clause, wherein the FROM clause includes a list of tables associated with selected business objects; receive a selection of a context from several contexts applicable to the SQL query; wherein the selected context includes a list of joins between tables that give meaning to the selected business objects; receive a condition used to restrict the scope of values returned from the database; translate the condition into a WHERE clause in the SQL query; and transmit the SQL query to the database. | 9. A hardware computer storage device with computer executable instructions for accessing a database, comprising executable instructions to: present a user at a client computer with a set of business objects, wherein the business objects include familiar terms corresponding to information about the structure of the database; receive a plurality of selected business objects; generate a SQL query from the selected business objects, wherein the SQL query includes a SELECT clause and a FROM clause, wherein the FROM clause includes a list of tables associated with selected business objects; receive a selection of a context from several contexts applicable to the SQL query; wherein the selected context includes a list of joins between tables that give meaning to the selected business objects; receive a condition used to restrict the scope of values returned from the database; translate the condition into a WHERE clause in the SQL query; and transmit the SQL query to the database. 12. The hardware computer storage device of claim 9 further comprising executable instructions to receive a tabular result set. | 0.917639 |
7,542,979 | 3 | 4 | 3. A computer system in accordance with claim 2 , wherein the variable rule comprises a condition, a parsedescriptor, and the value clause. | 3. A computer system in accordance with claim 2 , wherein the variable rule comprises a condition, a parsedescriptor, and the value clause. 4. A computer system in accordance with claim 3 , wherein the variable rule includes an endcondition. | 0.504902 |
8,708,960 | 1 | 14 | 1. An infusion pump assembly comprising: a reservoir assembly configured to contain an infusible fluid; a motor assembly configured to act upon the reservoir assembly and dispense at least a portion of the infusible fluid contained within the reservoir assembly; processing logic configured to control the motor assembly; wherein the processing logic includes: a primary microprocessor configured to execute one or more primary applications written in a first computer language; and a safety microprocessor configured to execute one or more safety applications written in a second computer language that is different than the first computer language; and a computer program product residing on a computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: receiving, on the primary microprocessor executing one or more applications written in a first computer language, an initial command processable by the one or more applications written in the first computer language; converting the initial command into a modified command processable by one or more applications written in a second computer language; and providing the modified command to the safety microprocessor executing the one or more applications written in the second computer language. | 1. An infusion pump assembly comprising: a reservoir assembly configured to contain an infusible fluid; a motor assembly configured to act upon the reservoir assembly and dispense at least a portion of the infusible fluid contained within the reservoir assembly; processing logic configured to control the motor assembly; wherein the processing logic includes: a primary microprocessor configured to execute one or more primary applications written in a first computer language; and a safety microprocessor configured to execute one or more safety applications written in a second computer language that is different than the first computer language; and a computer program product residing on a computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: receiving, on the primary microprocessor executing one or more applications written in a first computer language, an initial command processable by the one or more applications written in the first computer language; converting the initial command into a modified command processable by one or more applications written in a second computer language; and providing the modified command to the safety microprocessor executing the one or more applications written in the second computer language. 14. The infusion pump assembly of claim 1 wherein the first computer language is chosen from the group consisting of Ada, Basic, Cobol, C, C++, C#, Fortran, Visual Assembler, Visual Basic, Visual J++, Java, and Java Script. | 0.747738 |
10,102,277 | 34 | 35 | 34. A non-transitory computer-readable storage medium impressed with computer program instructions to provide user identification of a desired document, the instructions, when executed on a processor, implement a method comprising: providing, accessibly to a computer system, a database identifying a catalog of documents in an embedding space; calculating a Prior probability score for each document of a candidate list including at least a portion of the documents of the embedding space, the Prior probability score indicating a preliminary probability, for each particular document of the candidate list, that the particular document is the desired document; a computer system identifying toward the user an initial (i=0) collection of N0>1 candidate documents from the candidate list in dependence on the calculated Prior probability scores for the documents in the candidate list, the initial collection of candidate documents having fewer documents than the candidate list; and for each i'th iteration in a plurality of iterations, beginning with a first iteration (i=1) and in response to user selection of an i'th selected document from the (i−1)'th collection of candidate documents, identifying toward the user an i'th collection of Ni>1 candidate documents from the candidate list in dependence on Posterior probability scores for at least a portion of the documents in the candidate list, Ni being smaller than the number of documents in the candidate list, the Posterior probability score for each given document D being given by P(C|D)P(D), where C is the sequence of documents c 1 , . . . , c i selected by the user up through the i'th iteration, where P(C|D) is the system's view of the probability of C if the desired document is D and where P(D) is the calculated Prior probability score for document D. | 34. A non-transitory computer-readable storage medium impressed with computer program instructions to provide user identification of a desired document, the instructions, when executed on a processor, implement a method comprising: providing, accessibly to a computer system, a database identifying a catalog of documents in an embedding space; calculating a Prior probability score for each document of a candidate list including at least a portion of the documents of the embedding space, the Prior probability score indicating a preliminary probability, for each particular document of the candidate list, that the particular document is the desired document; a computer system identifying toward the user an initial (i=0) collection of N0>1 candidate documents from the candidate list in dependence on the calculated Prior probability scores for the documents in the candidate list, the initial collection of candidate documents having fewer documents than the candidate list; and for each i'th iteration in a plurality of iterations, beginning with a first iteration (i=1) and in response to user selection of an i'th selected document from the (i−1)'th collection of candidate documents, identifying toward the user an i'th collection of Ni>1 candidate documents from the candidate list in dependence on Posterior probability scores for at least a portion of the documents in the candidate list, Ni being smaller than the number of documents in the candidate list, the Posterior probability score for each given document D being given by P(C|D)P(D), where C is the sequence of documents c 1 , . . . , c i selected by the user up through the i'th iteration, where P(C|D) is the system's view of the probability of C if the desired document is D and where P(D) is the calculated Prior probability score for document D. 35. The non-transitory computer-readable recording medium of claim 34 , wherein the method further comprises, for each i'th iteration in the plurality of iterations, calculating the Posterior probability score for each document of the candidate list in dependence on the user selection of the i'th document from the (i−1)'th collection of candidate documents. | 0.87552 |
4,695,975 | 11 | 12 | 11. The visual communications device as claimed in claim 3, wherein said control means includes means for recognizing a predetermined set of control words interspersed in the selected natural language words received by said input means, and upon recognizing said control words executing said control words to override specified ones of the display rules. | 11. The visual communications device as claimed in claim 3, wherein said control means includes means for recognizing a predetermined set of control words interspersed in the selected natural language words received by said input means, and upon recognizing said control words executing said control words to override specified ones of the display rules. 12. The visual communications device as claimed in claim 11, wherein said predetermined set of control words includes control words for inhibiting the display of a specified image and displaying a specified image. | 0.5 |
9,542,927 | 23 | 27 | 23. An article of manufacture including a non-transitory computer-readable storage medium having stored thereon program instructions that, upon execution by one or more processors of a system, cause the system to perform operations comprising: extracting speech features from a plurality of recorded reference speech utterances of a reference speaker to generate a reference set of reference-speaker vectors; for each respective plurality of recorded colloquial speech utterances of a respective colloquial speaker of multiple colloquial speakers, extracting speech features from the recorded colloquial speech utterances of the respective colloquial speaker to generate a respective set of colloquial-speaker vectors; for each respective set of colloquial-speaker vectors, replacing each colloquial-speaker vector of the respective set of colloquial-speaker vectors with a respective, optimally-matched reference-speaker vector from among the reference set of reference-speaker vectors, wherein the respective, optimally-matched reference-speaker vector is identified by matching under a transform that compensates for differences in speech between the reference speaker and the respective colloquial speaker; aggregating the replaced colloquial-speaker vectors of all the respective sets of colloquial-speaker vectors into an aggregate set of conditioned speaker vectors; providing the aggregate set of conditioned speaker vectors to a text-to-speech (TTS) system implemented on one or more computing devices; and training the TTS system using the provided aggregate set of conditioned speaker vectors. | 23. An article of manufacture including a non-transitory computer-readable storage medium having stored thereon program instructions that, upon execution by one or more processors of a system, cause the system to perform operations comprising: extracting speech features from a plurality of recorded reference speech utterances of a reference speaker to generate a reference set of reference-speaker vectors; for each respective plurality of recorded colloquial speech utterances of a respective colloquial speaker of multiple colloquial speakers, extracting speech features from the recorded colloquial speech utterances of the respective colloquial speaker to generate a respective set of colloquial-speaker vectors; for each respective set of colloquial-speaker vectors, replacing each colloquial-speaker vector of the respective set of colloquial-speaker vectors with a respective, optimally-matched reference-speaker vector from among the reference set of reference-speaker vectors, wherein the respective, optimally-matched reference-speaker vector is identified by matching under a transform that compensates for differences in speech between the reference speaker and the respective colloquial speaker; aggregating the replaced colloquial-speaker vectors of all the respective sets of colloquial-speaker vectors into an aggregate set of conditioned speaker vectors; providing the aggregate set of conditioned speaker vectors to a text-to-speech (TTS) system implemented on one or more computing devices; and training the TTS system using the provided aggregate set of conditioned speaker vectors. 27. The article of manufacture of claim 23 , wherein extracting speech features from the plurality of recorded reference speech utterances of the reference speaker comprises decomposing the recorded reference speech utterances of the reference speaker into reference temporal frames of parameterized reference speech units, wherein each reference temporal frame corresponds to a respective reference-speaker vector of speech features that include at least one of spectral envelope parameters, aperiodicity envelope parameters, fundamental frequencies, or voicing, of a respective reference speech unit, and wherein extracting speech features from the recorded colloquial speech utterances of the respective colloquial speaker comprises decomposing the recorded colloquial speech utterances of the respective colloquial speaker into colloquial temporal frames of parameterized colloquial speech units, wherein each colloquial temporal frame corresponds to a respective colloquial-speaker vector of speech features that include at least one of spectral envelope parameters, aperiodicity envelope parameters, fundamental frequencies, or voicing, of a respective colloquial speech unit. | 0.5 |
9,705,998 | 19 | 24 | 19. A mobile client configured to display information, comprising: means for receiving a plurality of sets of one or more first keywords on a mobile client, each set of first keywords associated with one or more respective first messages, the means for receiving further configured to receive a set of target keywords associated with a target message; means for monitoring user interaction of the respective first messages on the mobile client; means for performing learning operations on the mobile client with the first keywords based on monitored user interaction to estimate a set of keyword interest weights; means for receiving the target message over a wireless link if the estimated set of keyword interest weights indicate a desirability of the target message; and means for displaying the target message on the mobile client based on the estimated set of keyword interest weights. | 19. A mobile client configured to display information, comprising: means for receiving a plurality of sets of one or more first keywords on a mobile client, each set of first keywords associated with one or more respective first messages, the means for receiving further configured to receive a set of target keywords associated with a target message; means for monitoring user interaction of the respective first messages on the mobile client; means for performing learning operations on the mobile client with the first keywords based on monitored user interaction to estimate a set of keyword interest weights; means for receiving the target message over a wireless link if the estimated set of keyword interest weights indicate a desirability of the target message; and means for displaying the target message on the mobile client based on the estimated set of keyword interest weights. 24. The mobile client according to claim 19 , wherein the means for performing incorporates random or pseudo-random noise in the learning operations. | 0.815594 |
7,685,507 | 41 | 42 | 41. The computer program product of claim 40 , wherein code that displays the pre-formatted form calculation includes: displaying a second hyperlink for a second element in the form calculation, the form calculation including a mathematical equation, displaying the second hyperlink to indicate to a user that a control is available for the second element, the second hyperlink including at least one second hyperlink target, the second hyperlink target identified by a second link to a choice satisfying the second element on the form calculation, the second hyperlink providing a link from the form calculation to a second another location, wherein the second another location is identified by a reference to a list of valid operators in the form calculation; responsive to selection of the second hyperlink by the user, presenting the control for user interaction, the control displaying the list of valid operators for the mathematical 6 quation, each operator for selection in the list being presented without a hyperlink; receiving a selection of a valid operator from the list of valid operators; and upon completion of user interaction with the control and in response to receiving the selection of a valid operator, replacing the second element with a second new element corresponding to the selection of the valid operator, displaying the second hyperlink for the second new element in the form calculation and causing the presented control to disappear. | 41. The computer program product of claim 40 , wherein code that displays the pre-formatted form calculation includes: displaying a second hyperlink for a second element in the form calculation, the form calculation including a mathematical equation, displaying the second hyperlink to indicate to a user that a control is available for the second element, the second hyperlink including at least one second hyperlink target, the second hyperlink target identified by a second link to a choice satisfying the second element on the form calculation, the second hyperlink providing a link from the form calculation to a second another location, wherein the second another location is identified by a reference to a list of valid operators in the form calculation; responsive to selection of the second hyperlink by the user, presenting the control for user interaction, the control displaying the list of valid operators for the mathematical 6 quation, each operator for selection in the list being presented without a hyperlink; receiving a selection of a valid operator from the list of valid operators; and upon completion of user interaction with the control and in response to receiving the selection of a valid operator, replacing the second element with a second new element corresponding to the selection of the valid operator, displaying the second hyperlink for the second new element in the form calculation and causing the presented control to disappear. 42. The computer program product of claim 41 , wherein program code which presents the control for user interaction includes program code which selects the control from the group consisting of a dialog box, a list, and a text entry field. | 0.5 |
9,069,853 | 23 | 28 | 23. A computer-readable storage device embodying instructions that, when executed by a processor, cause the processor to: receive an input corresponding to one of a company name and a patent document identifier and an identifier related to a selected one of a plurality of pre-defined goal oriented searches, each of the plurality of pre-defined goal oriented searches comprising multiple criteria, the plurality of pre-defined goal oriented searches including a patent invalidity search; retrieve a first document based on the input, the first document comprising a patent document corresponding to the patent document identifier; extract data from the first document using an extraction module, the extracted data including a priority date, an issue date, owner data, and a list of cited references; insert at least some of the extracted data from the first document into the selected one of the plurality of pre-defined goal oriented searches provided by a server to produce a goal-oriented query constructed to identify one or more documents that satisfy the multiple criteria; search one or more data sources using the goal-oriented query to retrieve search results; apply a rule derived from explicit user interactions and implicit user interactions to produce a matrix including highest probability keywords identified from the search results; identify a plurality of search results using a greedy algorithm; retrieve ancillary information from a secondary search of at least one other data source using a query that is related to data from the plurality of search results, the ancillary information including associative data that is not included within the search results; correlate the search results with the ancillary information to identify associations between search results to produce augmented search results; refine the rule based on the data; and apply the refined rule to filter the search results according to some of the extracted data to produce filtered search results including prior art not cited in the patent document when the identifier corresponds to the patent invalidity search. | 23. A computer-readable storage device embodying instructions that, when executed by a processor, cause the processor to: receive an input corresponding to one of a company name and a patent document identifier and an identifier related to a selected one of a plurality of pre-defined goal oriented searches, each of the plurality of pre-defined goal oriented searches comprising multiple criteria, the plurality of pre-defined goal oriented searches including a patent invalidity search; retrieve a first document based on the input, the first document comprising a patent document corresponding to the patent document identifier; extract data from the first document using an extraction module, the extracted data including a priority date, an issue date, owner data, and a list of cited references; insert at least some of the extracted data from the first document into the selected one of the plurality of pre-defined goal oriented searches provided by a server to produce a goal-oriented query constructed to identify one or more documents that satisfy the multiple criteria; search one or more data sources using the goal-oriented query to retrieve search results; apply a rule derived from explicit user interactions and implicit user interactions to produce a matrix including highest probability keywords identified from the search results; identify a plurality of search results using a greedy algorithm; retrieve ancillary information from a secondary search of at least one other data source using a query that is related to data from the plurality of search results, the ancillary information including associative data that is not included within the search results; correlate the search results with the ancillary information to identify associations between search results to produce augmented search results; refine the rule based on the data; and apply the refined rule to filter the search results according to some of the extracted data to produce filtered search results including prior art not cited in the patent document when the identifier corresponds to the patent invalidity search. 28. The computer-readable storage device of claim 23 , wherein: the plurality of pre-defined goal oriented searches further includes an asset search; and when the identifier corresponds to the asset search, further comprising instructions that, when executed, cause the processor to generate an asset report to identify data related to a potentially valuable asset from a plurality of assets based on search results from the pre-defined query. | 0.724845 |
8,255,383 | 1 | 13 | 1. A method, comprising: ranking a plurality of categories of a keyword detected in a query submitted by a user; ranking a category based on a frequency of selection by human search assistants; choosing a human search assistant based on association of the human search assistant with the category and the keyword; providing content identifying the query, the keyword and the category to the human search assistant when determining that the category is ranked highest; and qualifying the query based on the category and an action received when the human search assistant is performing a search for a response to the query. | 1. A method, comprising: ranking a plurality of categories of a keyword detected in a query submitted by a user; ranking a category based on a frequency of selection by human search assistants; choosing a human search assistant based on association of the human search assistant with the category and the keyword; providing content identifying the query, the keyword and the category to the human search assistant when determining that the category is ranked highest; and qualifying the query based on the category and an action received when the human search assistant is performing a search for a response to the query. 13. The method according to claim 1 , wherein the category of the keyword is supplied by an external source. | 0.850416 |
9,535,908 | 15 | 16 | 15. A computing device comprising: a processing unit and addressable memory; the processing unit configured to: execute workflow instance based on stored data associated only with the workflow instance; receive, as input into a document set of the workflow instance, one or more documents from an input activity of the workflow instance, the input comprising: document metadata associated with the one or more documents, the document metadata comprising a type and a source of the document, wherein the input activity generates the one or more documents for use by workflow activities downstream; select, by an output activity of the workflow instance, the one or more documents from the document set for input by designating the document metadata corresponding to the one or more documents and perform operations according to a set of instructions associated with the workflow instance, wherein the selection is based on a query to return one or more documents of the document set that match the document metadata; and select, by a processing activity of the workflow instance, the one or more documents from the document set to input by designating the corresponding document metadata, wherein the selection by the processing activity is based on to specify the type of the document to input and an activity name that is the source of the document; wherein the selecting of the one or more documents across workflow activities of the workflow instance is done at runtime and without a workflow instance activity having prior knowledge of another workflow instance activity. | 15. A computing device comprising: a processing unit and addressable memory; the processing unit configured to: execute workflow instance based on stored data associated only with the workflow instance; receive, as input into a document set of the workflow instance, one or more documents from an input activity of the workflow instance, the input comprising: document metadata associated with the one or more documents, the document metadata comprising a type and a source of the document, wherein the input activity generates the one or more documents for use by workflow activities downstream; select, by an output activity of the workflow instance, the one or more documents from the document set for input by designating the document metadata corresponding to the one or more documents and perform operations according to a set of instructions associated with the workflow instance, wherein the selection is based on a query to return one or more documents of the document set that match the document metadata; and select, by a processing activity of the workflow instance, the one or more documents from the document set to input by designating the corresponding document metadata, wherein the selection by the processing activity is based on to specify the type of the document to input and an activity name that is the source of the document; wherein the selecting of the one or more documents across workflow activities of the workflow instance is done at runtime and without a workflow instance activity having prior knowledge of another workflow instance activity. 16. The processing unit of the computing device of claim 15 further configured to designate a store location or a storage container for the workflow instance. | 0.5 |
10,068,024 | 1 | 10 | 1. A method for generating data to provide situational awareness or decision-making assistance to a user in relation to a physical environment, the method comprising, with a computer system: processing input data comprising at least data associated with the physical environment; and when a need for situational awareness or decision-making assistance is detected based on the input data, generating response data, the response data derived from multimodal data from a plurality of electronic data streams comprising audio, visual and textual information, the data streams received from a plurality of data sources, wherein generating the response data comprises: determining a characteristic of the need for situational awareness or decision-making assistance; extracting semantic information from the audio, visual and textual information; correlating the extracted semantic information in accordance with the characteristic; selecting a subset of the audio, visual and textual information based on the correlation of the extracted semantic information with the characteristic; and outputting at least a portion of the selected subset as the response data. | 1. A method for generating data to provide situational awareness or decision-making assistance to a user in relation to a physical environment, the method comprising, with a computer system: processing input data comprising at least data associated with the physical environment; and when a need for situational awareness or decision-making assistance is detected based on the input data, generating response data, the response data derived from multimodal data from a plurality of electronic data streams comprising audio, visual and textual information, the data streams received from a plurality of data sources, wherein generating the response data comprises: determining a characteristic of the need for situational awareness or decision-making assistance; extracting semantic information from the audio, visual and textual information; correlating the extracted semantic information in accordance with the characteristic; selecting a subset of the audio, visual and textual information based on the correlation of the extracted semantic information with the characteristic; and outputting at least a portion of the selected subset as the response data. 10. The method of claim 1 , wherein the input comprises a natural language query. | 0.904028 |
9,355,150 | 9 | 16 | 9. A system for producing a-solution documents, the system comprising: a memory resource to store instructions; one or more processors; and a content manager engine to use the one or more processors and the instructions stored in the memory resource for: receiving, from a client system, at least one selection for specifying an issue or query regarding a computer system; selecting a first solution mapping from a plurality of solution mappings based on the at least one received selection, the first solution mapping specifying a plurality of document mappings, wherein (1) each of the plurality of solution mappings is associated with at least one document mapping and a set of content fragments, and (2) at least some of the plurality of solution mappings are associated with existing solution documents; retrieving one or more content fragments associated with each of the plurality of document mappings from a content database, wherein (1) the plurality of document mappings refers to at least a first document encoded in a first format and a second document encoded in a second format, and (2) at least one of the first and second formats is incompatible with the client system; producing a solution document in a format compatible with the client system, the solution document including at least the one or more content fragments; providing the solution document to the client system, the solution document comprising at least some modifiable content pertaining to the selected issue or query; receiving, from the client system, modifications to at least one content fragment in the solution document; updating the at least one modified content fragment in the content database; and producing new solution documents to replace the existing solution documents for each of the plurality of solution mappings with one of the modified content fragments in its set of content fragments. | 9. A system for producing a-solution documents, the system comprising: a memory resource to store instructions; one or more processors; and a content manager engine to use the one or more processors and the instructions stored in the memory resource for: receiving, from a client system, at least one selection for specifying an issue or query regarding a computer system; selecting a first solution mapping from a plurality of solution mappings based on the at least one received selection, the first solution mapping specifying a plurality of document mappings, wherein (1) each of the plurality of solution mappings is associated with at least one document mapping and a set of content fragments, and (2) at least some of the plurality of solution mappings are associated with existing solution documents; retrieving one or more content fragments associated with each of the plurality of document mappings from a content database, wherein (1) the plurality of document mappings refers to at least a first document encoded in a first format and a second document encoded in a second format, and (2) at least one of the first and second formats is incompatible with the client system; producing a solution document in a format compatible with the client system, the solution document including at least the one or more content fragments; providing the solution document to the client system, the solution document comprising at least some modifiable content pertaining to the selected issue or query; receiving, from the client system, modifications to at least one content fragment in the solution document; updating the at least one modified content fragment in the content database; and producing new solution documents to replace the existing solution documents for each of the plurality of solution mappings with one of the modified content fragments in its set of content fragments. 16. The system of claim 9 , wherein the content manager engine uses further instructions for: producing at least one automated selection based on the at least one received selection, wherein the first solution mapping is further selected based on the at least one automated selection. | 0.759322 |
8,272,009 | 30 | 34 | 30. A system that delivers content to users of a broadcast network, said broadcast network primarily involving synchronized distribution of content to multiple users, said system comprising: a first platform for providing an interface for receiving textual constraints from asset providers, such that each asset is associated with at least one textual constraint received via the interface and is further associated with at least one targeting constraint selected from the group consisting of temporal constraints, demographic constraints, or network constraints; and a processor operative to: compare said textual constraints of said assets with textual information associated with the programming to determine a goodness of fit value for each of the subset of assets; and identify a subset of the assets for presentation in conjunction with the programming according to the respective goodness of fit values; and deliver said subset of assets along with their respective textual constraints to a downstream second platform in association with an asset delivery spot in such a way that one of the subset of assets is selected by the second platform according to the respective textual constraints for presentation to at least one user of the broadcast network during the asset delivery spot. | 30. A system that delivers content to users of a broadcast network, said broadcast network primarily involving synchronized distribution of content to multiple users, said system comprising: a first platform for providing an interface for receiving textual constraints from asset providers, such that each asset is associated with at least one textual constraint received via the interface and is further associated with at least one targeting constraint selected from the group consisting of temporal constraints, demographic constraints, or network constraints; and a processor operative to: compare said textual constraints of said assets with textual information associated with the programming to determine a goodness of fit value for each of the subset of assets; and identify a subset of the assets for presentation in conjunction with the programming according to the respective goodness of fit values; and deliver said subset of assets along with their respective textual constraints to a downstream second platform in association with an asset delivery spot in such a way that one of the subset of assets is selected by the second platform according to the respective textual constraints for presentation to at least one user of the broadcast network during the asset delivery spot. 34. The system of claim 30 , further comprising: an asset database, wherein said asset database includes a plurality of assets of a plurality of asset providers. | 0.668724 |
9,055,509 | 13 | 16 | 13. The method according to claim 1 , further including generating a status update for the user corresponding to the distraction level of the user for transmission to other users via a wireless link. | 13. The method according to claim 1 , further including generating a status update for the user corresponding to the distraction level of the user for transmission to other users via a wireless link. 16. The method according to claim 13 , further including postponing messages for the status for other messaging parties based upon driver conditions for the user. | 0.5 |
6,105,036 | 14 | 23 | 14. A computer system configured to display a source code file to a user, the source file including an ordered arrangement of a plurality of object definitions that define a plurality of multimedia objects, the computer system comprising: (a) a computer display; and (b) a processor, coupled to the computer display, the processor configured to display at least a portion of the plurality of object definitions in first representations on the computer display; and in response to user input, to selectively display on the computer display, in place of the first representation of a selected object definition, an inlined multimedia representation of the selected object definition disposed at a relative location of the selected object definition in the ordered arrangement. | 14. A computer system configured to display a source code file to a user, the source file including an ordered arrangement of a plurality of object definitions that define a plurality of multimedia objects, the computer system comprising: (a) a computer display; and (b) a processor, coupled to the computer display, the processor configured to display at least a portion of the plurality of object definitions in first representations on the computer display; and in response to user input, to selectively display on the computer display, in place of the first representation of a selected object definition, an inlined multimedia representation of the selected object definition disposed at a relative location of the selected object definition in the ordered arrangement. 23. The computer system of claim 14, wherein the processor includes a browser configured to parse the source code file to form a parse tree including a plurality of nodes, each node associated with one of the plurality of object definitions, and each node including a display indicator indicating whether to display the object definition associated therewith or the inlined multimedia representation therefor, wherein the processor is configured to access the display indicator for each node when selectively displaying the inlined multimedia representation. | 0.5 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.