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1. A method of operating a computer to present a user interface, the method comprising creating an integrated User Interface (UI) language preference list (“the List”) in a computer system having multiple UI language settings including an application UI language preference list (“APL”), a user UI language preference list (“UPL”), and an ultimate fallback UI language (“original UI language”), the method comprising merging one or more of the multiple UI language settings to the List, the merging one or more of the multiple UI language settings to the List including merging the UPL to the List, the merging the UPL, comprising: with a processor of the computer: (a) adding a language in the UPL, to the List if the language is not already in the List; (b) merging a parent language of the added language to the List if the added language is a Language Interface Pack (LIP) language, wherein the LIP language is a software application added on to a language installed on the computer system upon verifying that the language installed on the computer system is a valid parent language of the LIP language; and (c) merging a base language of the added language to the List if the added language is a partially localized language, wherein the base language is a language in which a majority of user interface resources is displayed to a user, and the partially localized language is a language in which a remainder of the user interface resources is displayed to the user; and the method further comprising: selecting from among one or more language resources available on the computer in an order established by the List; and rendering a display using the selected language resource.
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1. A method of operating a computer to present a user interface, the method comprising creating an integrated User Interface (UI) language preference list (“the List”) in a computer system having multiple UI language settings including an application UI language preference list (“APL”), a user UI language preference list (“UPL”), and an ultimate fallback UI language (“original UI language”), the method comprising merging one or more of the multiple UI language settings to the List, the merging one or more of the multiple UI language settings to the List including merging the UPL to the List, the merging the UPL, comprising: with a processor of the computer: (a) adding a language in the UPL, to the List if the language is not already in the List; (b) merging a parent language of the added language to the List if the added language is a Language Interface Pack (LIP) language, wherein the LIP language is a software application added on to a language installed on the computer system upon verifying that the language installed on the computer system is a valid parent language of the LIP language; and (c) merging a base language of the added language to the List if the added language is a partially localized language, wherein the base language is a language in which a majority of user interface resources is displayed to a user, and the partially localized language is a language in which a remainder of the user interface resources is displayed to the user; and the method further comprising: selecting from among one or more language resources available on the computer in an order established by the List; and rendering a display using the selected language resource. 8. The computer method of claim 1 , further comprising providing an application programming interface, the application programming interface including separate commands to request services related to setting and retrieving UI language settings through the List.
| 0.573694 |
7. A method comprising: performing a link analysis of related metadata items to which a collection of related data objects conform; calculating metadata scores for the related metadata items based upon the link analysis; identifying search results for a set of query terms, each result of the search results being a subset of related data objects within the collection, the subset comprising, for each particular term of the set of query terms, at least one data object that matches the particular term; wherein identifying the search results comprises: identifying groups of initial data objects to investigate for the search results, the groups including at least a first group matching a first query term and a second group matching a second query term; identifying particular subsets of related data objects within the collection by, in an order at least partially based on the metadata scores, expanding networks of the related data objects from the initial data objects; determining which of the particular subsets qualify as the search results.
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7. A method comprising: performing a link analysis of related metadata items to which a collection of related data objects conform; calculating metadata scores for the related metadata items based upon the link analysis; identifying search results for a set of query terms, each result of the search results being a subset of related data objects within the collection, the subset comprising, for each particular term of the set of query terms, at least one data object that matches the particular term; wherein identifying the search results comprises: identifying groups of initial data objects to investigate for the search results, the groups including at least a first group matching a first query term and a second group matching a second query term; identifying particular subsets of related data objects within the collection by, in an order at least partially based on the metadata scores, expanding networks of the related data objects from the initial data objects; determining which of the particular subsets qualify as the search results. 11. The method of claim 7 , further comprising identifying particular subsets of related data objects and determining which of the particular subsets qualify as the search results by: populating a candidate set of data objects from the initial data objects; ordering at least the data objects in the candidate set, the ordering comprising, for each particular data object in the candidate set, identifying a priority score based at least partially upon a particular metadata score that has been assigned to a particular metadata item to which the particular data object conforms; based on the ordering, identifying a first data object within the candidate set to investigate; determining whether the first data object is a search result by determining whether the first data object is or comprises a subset of related data objects such that, for each particular term of the query terms, at least one data object that matches the particular term; when the first data object is not a search result, identifying one or more new data objects to investigate by adding, to the candidate set, one or more ancestor objects that are related to the first data object; iteratively repeating at least the identifying a first data object to investigate, determining whether the first data object is a search result, and identifying one or more new data objects to investigate, with respect to different data objects within the candidate set, until the search results have been identified.
| 0.571429 |
5. A computer-implemented method, comprising: detecting character input in an interface of a computing device; analyzing the character input to determine a plurality of suggestions, the plurality of suggestions are based at least in part upon the character input, the suggestions having respective confidence scores, wherein a first suggestion of the plurality of suggestions is designated as one of a correction type, a common base portion type, or a completion type, the common base portion type including at least a root word, the completion type including at least a corresponding completing word; determining a two-dimensional spatial layout of at least a portion of the plurality of suggestions, a location of a suggestion of the portion being determined based, at least in part, upon the respective confidence score of the suggestion, wherein first suggestions that share a same completion type are grouped together in a first group, second suggestions that share a same correction type are grouped together in a second group, and third suggestions that share a same common base portion type are grouped together in a third group; providing for display the at least the portion of the plurality of suggestions arranged according to the spatial layout, wherein the first suggestions that form the first group, the second suggestions that form the second group and the third suggestions that form the third group are displayed proximate to one another in the spatial layout; detecting a user selection of a specified selection of the plurality of suggestions displayed according to the spatial layout; and determining a modified character input based at least in part on the specified selection.
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5. A computer-implemented method, comprising: detecting character input in an interface of a computing device; analyzing the character input to determine a plurality of suggestions, the plurality of suggestions are based at least in part upon the character input, the suggestions having respective confidence scores, wherein a first suggestion of the plurality of suggestions is designated as one of a correction type, a common base portion type, or a completion type, the common base portion type including at least a root word, the completion type including at least a corresponding completing word; determining a two-dimensional spatial layout of at least a portion of the plurality of suggestions, a location of a suggestion of the portion being determined based, at least in part, upon the respective confidence score of the suggestion, wherein first suggestions that share a same completion type are grouped together in a first group, second suggestions that share a same correction type are grouped together in a second group, and third suggestions that share a same common base portion type are grouped together in a third group; providing for display the at least the portion of the plurality of suggestions arranged according to the spatial layout, wherein the first suggestions that form the first group, the second suggestions that form the second group and the third suggestions that form the third group are displayed proximate to one another in the spatial layout; detecting a user selection of a specified selection of the plurality of suggestions displayed according to the spatial layout; and determining a modified character input based at least in part on the specified selection. 15. The computer-implemented method of claim 5 , wherein a font size of the suggestions is proportional to the respective confidence score.
| 0.608832 |
18. The computer program product of claim 15 wherein the information handling system performs additional actions comprising: selecting a set of relevant connecting verbs, from the plurality of connecting verbs, based upon an amount of each of the plurality of connecting verbs and their relevance; and performing the collection of the plurality of document segments based upon the set of relevant connecting verbs.
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18. The computer program product of claim 15 wherein the information handling system performs additional actions comprising: selecting a set of relevant connecting verbs, from the plurality of connecting verbs, based upon an amount of each of the plurality of connecting verbs and their relevance; and performing the collection of the plurality of document segments based upon the set of relevant connecting verbs. 19. The computer program product of claim 18 wherein each of the plurality of connecting verbs form a subject-verb-object (SVO) relation with the first entity and the second entity.
| 0.921274 |
10. A computer readable storage medium having stored thereon a program, the program being executable by a processor for performing a method, the method comprising: assigning a part of speech identifier to each word in a source string, the source string in a first language; detecting a first sequence of syntactic chunks in the source string, the syntactic chunks each comprising at least one of the words; assigning a syntactic chunk label to each of the detected syntactic chunks in the source string; defining connections between each of the detected syntactic chunks in the source string and at least one syntactic chunk of a sequence of syntactic chunks in a target string, the target string being a parallel translation in a second language of the source string, said defining comprising determining connections based on a chunk mapping table, the chunk mapping table using pre-defined connections based on the assigned syntactic chunk label; mapping each word in the detected syntactic chunks in the source string to each word in the syntactic chunks in the target string, said mapping based on a word mapping table and the part of speech identifier; and translating by a computer an input string in the first language into a translation in the second language based on the chunk mapping table and the word mapping table.
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10. A computer readable storage medium having stored thereon a program, the program being executable by a processor for performing a method, the method comprising: assigning a part of speech identifier to each word in a source string, the source string in a first language; detecting a first sequence of syntactic chunks in the source string, the syntactic chunks each comprising at least one of the words; assigning a syntactic chunk label to each of the detected syntactic chunks in the source string; defining connections between each of the detected syntactic chunks in the source string and at least one syntactic chunk of a sequence of syntactic chunks in a target string, the target string being a parallel translation in a second language of the source string, said defining comprising determining connections based on a chunk mapping table, the chunk mapping table using pre-defined connections based on the assigned syntactic chunk label; mapping each word in the detected syntactic chunks in the source string to each word in the syntactic chunks in the target string, said mapping based on a word mapping table and the part of speech identifier; and translating by a computer an input string in the first language into a translation in the second language based on the chunk mapping table and the word mapping table. 11. The computer readable medium of claim 10 , wherein assigning the syntactic chunk label further comprises assigning the syntactic chunk label based on the assigned part of speech identifier of the at least one of the words in the source string.
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1. A method of providing contextual information to a user, comprising: receiving context data describing the user's current context; identifying a plurality of information items corresponding to the user's current context; applying a personalized user behavior model for the user to determine, for each of the plurality of information items, a likelihood that the information item will be of value to the user, the user behavior model including a routine model describing correlations between contexts, the routine model comprising a plurality of transition rules; selecting an information item from among the plurality of information items based on the corresponding likelihood; providing the selected information item for presentation to the user; receiving feedback indicating the user found value in presentation of the selected information item; identifying a contributing transition rule from among the plurality of transition rules based on the contributing transition rule having contributed to selection of the selected information item, the contributing transition rule comprising a source context and a destination context; and storing an indication that the user found value in presentation of the selected information item in conjunction with the contributing transition rule such that information items associated with the destination context are in future determined to have a higher likelihood when the user is associated with the source context.
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1. A method of providing contextual information to a user, comprising: receiving context data describing the user's current context; identifying a plurality of information items corresponding to the user's current context; applying a personalized user behavior model for the user to determine, for each of the plurality of information items, a likelihood that the information item will be of value to the user, the user behavior model including a routine model describing correlations between contexts, the routine model comprising a plurality of transition rules; selecting an information item from among the plurality of information items based on the corresponding likelihood; providing the selected information item for presentation to the user; receiving feedback indicating the user found value in presentation of the selected information item; identifying a contributing transition rule from among the plurality of transition rules based on the contributing transition rule having contributed to selection of the selected information item, the contributing transition rule comprising a source context and a destination context; and storing an indication that the user found value in presentation of the selected information item in conjunction with the contributing transition rule such that information items associated with the destination context are in future determined to have a higher likelihood when the user is associated with the source context. 9. The method of claim 1 , wherein the user behavior model comprises a personality model comprising a plurality of metrics indicating the user's affinity with a corresponding plurality of personality traits, the method further comprising: identifying one or more contributing personality traits from among the plurality of personality traits based on the contributing personality traits having contributed to selection of the selected information item; and increasing the user's affinity with the contributing personality traits in the personality model.
| 0.634868 |
6. A computer-implemented method for enhancing search result listings, comprising: employing a processor executing computer executable instructions stored on a computer readable storage medium to implement the following acts: obtaining a search result list from an object oriented search engine sorted by rank; sorting the search result list by attribute value as a primary sort and rank as a secondary sort; calculating the attribute value's rank for each attribute value; resorting the search result list based on, at least in part, the attribute value rank as a primary sort, attribute value as a secondary sort, and search result rank as a tertiary sort to obtain attribute value based grouped search results; and displaying the resorted search result list to a user on a search result page in groups associated with an attribute value, wherein the search result list references a plurality of information pages each comprising an object block representing an object classified as an object type having attributes for which the object block contains elements identified as attribute values, wherein the attribute pertains to a source of a respective information page.
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6. A computer-implemented method for enhancing search result listings, comprising: employing a processor executing computer executable instructions stored on a computer readable storage medium to implement the following acts: obtaining a search result list from an object oriented search engine sorted by rank; sorting the search result list by attribute value as a primary sort and rank as a secondary sort; calculating the attribute value's rank for each attribute value; resorting the search result list based on, at least in part, the attribute value rank as a primary sort, attribute value as a secondary sort, and search result rank as a tertiary sort to obtain attribute value based grouped search results; and displaying the resorted search result list to a user on a search result page in groups associated with an attribute value, wherein the search result list references a plurality of information pages each comprising an object block representing an object classified as an object type having attributes for which the object block contains elements identified as attribute values, wherein the attribute pertains to a source of a respective information page. 24. The method of claim 6 , wherein calculating the attribute value's rank comprises utilizing an object ranking algorithm.
| 0.615101 |
6. The method of claim 1 , wherein generating the one or more candidate words comprises generating the one more candidate words based on a first vocabulary set of words stored on the electronic device and a second vocabulary set of words stored on a remote server device.
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6. The method of claim 1 , wherein generating the one or more candidate words comprises generating the one more candidate words based on a first vocabulary set of words stored on the electronic device and a second vocabulary set of words stored on a remote server device. 7. The method of claim 6 , wherein generating the one or more candidate words based on the second vocabulary set of words comprises receiving a portion of the one or more candidate words from the remote server device.
| 0.938497 |
11. A system for collecting and transmitting contextual information relating to a conversation on a communication channel between a first client and a second client, comprising: a processor; and a computer readable memory having computer executable instructions, which when executed by the processor, perform the method of: obtaining caller contextual information from a caller that is exchanged using a voice communication channel; wherein the voice communication channel is used to transmit contextual data packets and conversational data packets during the conversation; wherein the caller contextual information is based on a caller rule used in determining the caller contextual information to be transmitted between the caller and a callee; obtaining callee contextual information based on a callee rule used in determining the callee contextual information to be transmitted between the callee and the caller; determining a first scope of the callee contextual information; determining a second scope of the caller contextual information; determining whether to change the first scope of the callee contextual information based on the second scope of the caller contextual information; and updating the callee contextual information based on the determined the second scope of the caller contextual information; and transmitting the callee contextual information.
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11. A system for collecting and transmitting contextual information relating to a conversation on a communication channel between a first client and a second client, comprising: a processor; and a computer readable memory having computer executable instructions, which when executed by the processor, perform the method of: obtaining caller contextual information from a caller that is exchanged using a voice communication channel; wherein the voice communication channel is used to transmit contextual data packets and conversational data packets during the conversation; wherein the caller contextual information is based on a caller rule used in determining the caller contextual information to be transmitted between the caller and a callee; obtaining callee contextual information based on a callee rule used in determining the callee contextual information to be transmitted between the callee and the caller; determining a first scope of the callee contextual information; determining a second scope of the caller contextual information; determining whether to change the first scope of the callee contextual information based on the second scope of the caller contextual information; and updating the callee contextual information based on the determined the second scope of the caller contextual information; and transmitting the callee contextual information. 20. The computer readable memory device of claim 11 , wherein updating the callee contextual information includes identifying information to be deleted from the callee contextual information, storing the identified information in storage, and deleting the identified information from the callee contextual information.
| 0.5 |
8. A system for synthesizing multi-person speech into an aggregate voice, the system comprising: a crowd-sourcing module configured to crowd-source a data message including a textual passage; a collecting module configured to collect, from a plurality of speakers, a set of vocal data for the textual passage, wherein the set of vocal data includes a first set of enunciation data corresponding to a first portion of the textual passage, a second set of enunciation data corresponding to a second portion of the textual passage, and a third set of enunciation data corresponding to both the first and second portions of the textual passage; a mapping module configured to map a source voice profile to a subset of the set of vocal data to synthesize the aggregate voice, wherein mapping the source voice profile to a subset of the set of vocal data to synthesize the aggregate voice includes: an extracting module configured to extract phonological data from the set of vocal data, wherein the phonological data includes pronunciation tags, intonation tags, and syllable rates; a converting module configured to convert, based on the phonological data including pronunciation tags, intonation tags and syllable rates, the set of vocal data into a set of phoneme strings; and an applying module configured to apply, to the set of phoneme strings, the source voice profile; an assigning module configured to assign, based on evaluating the phonological data from the set of vocal data, a first quality score to the first set of enunciation data; and a transmitting module configured to transmit, in response to determining that the first quality score is greater than a first quality threshold, bonus credits to a first speaker of the first set of enunciation data.
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8. A system for synthesizing multi-person speech into an aggregate voice, the system comprising: a crowd-sourcing module configured to crowd-source a data message including a textual passage; a collecting module configured to collect, from a plurality of speakers, a set of vocal data for the textual passage, wherein the set of vocal data includes a first set of enunciation data corresponding to a first portion of the textual passage, a second set of enunciation data corresponding to a second portion of the textual passage, and a third set of enunciation data corresponding to both the first and second portions of the textual passage; a mapping module configured to map a source voice profile to a subset of the set of vocal data to synthesize the aggregate voice, wherein mapping the source voice profile to a subset of the set of vocal data to synthesize the aggregate voice includes: an extracting module configured to extract phonological data from the set of vocal data, wherein the phonological data includes pronunciation tags, intonation tags, and syllable rates; a converting module configured to convert, based on the phonological data including pronunciation tags, intonation tags and syllable rates, the set of vocal data into a set of phoneme strings; and an applying module configured to apply, to the set of phoneme strings, the source voice profile; an assigning module configured to assign, based on evaluating the phonological data from the set of vocal data, a first quality score to the first set of enunciation data; and a transmitting module configured to transmit, in response to determining that the first quality score is greater than a first quality threshold, bonus credits to a first speaker of the first set of enunciation data. 9. The system of claim 8 , wherein the source voice profile includes a predetermined set of phonological and prosodic characteristics corresponding to a voice of a first individual.
| 0.582386 |
19. The computer-readable medium as in claim 18 , wherein switching between the first view of the collaborative document resident on the server device and the second view of the portable document resident on the client device is based on a received user selection via the graphical user interface.
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19. The computer-readable medium as in claim 18 , wherein switching between the first view of the collaborative document resident on the server device and the second view of the portable document resident on the client device is based on a received user selection via the graphical user interface. 20. The computer-readable medium of claim 19 , further comprising: providing for display a document identification portion indicating whether a currently displayed document is editable on the client device when the client device is disconnected from the server device.
| 0.90531 |
4. The system of claim 1 , wherein applying the first level of complexity of the machine learning model to the input value by applying at least one biased first level of complexity to the input value to generate at least one class label comprises: applying a negatively biased first level of complexity to the input value to generate a first class label; and applying a positively biased first level of complexity to the input value to generate a second class label.
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4. The system of claim 1 , wherein applying the first level of complexity of the machine learning model to the input value by applying at least one biased first level of complexity to the input value to generate at least one class label comprises: applying a negatively biased first level of complexity to the input value to generate a first class label; and applying a positively biased first level of complexity to the input value to generate a second class label. 5. The system of claim 4 , wherein determining whether the first level of complexity is able to classify the input value comprises: comparing the first class label to the second class label; and determining whether a consensus exists between the negatively biased first level of complexity and the positively biased first level of complexity based, at least in part, on the comparing.
| 0.761693 |
1. A system for detecting a three-way call in a monitored telephone conversation, the system comprising: a speech recognition module configured to extract at least one characteristic of the monitored telephone conversation; a database that stores a representation of the monitored telephone conversation in correspondence with the extracted at least one characteristic; a three-way call detection module configured to analyze the at least one characteristic of the monitored telephone conversation so as to detect a presence or absence of the three-way call in the monitored telephone conversation; and a tagging module configured to determine a starting point of the three-way call in the monitored telephone conversation, wherein the database further stores the determined starting point in correspondence with the representation of the monitored telephone conversation.
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1. A system for detecting a three-way call in a monitored telephone conversation, the system comprising: a speech recognition module configured to extract at least one characteristic of the monitored telephone conversation; a database that stores a representation of the monitored telephone conversation in correspondence with the extracted at least one characteristic; a three-way call detection module configured to analyze the at least one characteristic of the monitored telephone conversation so as to detect a presence or absence of the three-way call in the monitored telephone conversation; and a tagging module configured to determine a starting point of the three-way call in the monitored telephone conversation, wherein the database further stores the determined starting point in correspondence with the representation of the monitored telephone conversation. 9. The system of claim 1 , further comprising a playback module configured to begin playback of the monitored telephone conversation from the determined starting point.
| 0.552952 |
12. An apparatus according to claim 9 in which surface structure elements associated with each element of said syntactic structure or relation are transferred as labels for said corresponding meta-model elements or relationships.
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12. An apparatus according to claim 9 in which surface structure elements associated with each element of said syntactic structure or relation are transferred as labels for said corresponding meta-model elements or relationships. 13. An apparatus according to claim 12 in which said extraction of said at least one semantic element comprises a variability leveling process for resolving semantic synonymy.
| 0.956227 |
2. A continuous speech recognition system for recognizing an input speech composed of a plurality of continuously spoken words comprising: a speech analyzing means for analyzing an input signal at every given frame time point m and outputting an input pattern expressed in a time series of a feature vector comprising a predetermined number of feature parameters; an input pattern memory to store said input pattern; a reference pattern memory to store a reference pattern comprising a feature vector in the same format as said input pattern for each of a plurality (V) of predetermined words to be recognized; a distance calculating means to calculate the distance between the feature vector of said input pattern at a time point m and the feature vector of the reference pattern of the v-th word at a time point n at every time point n under a predetermined distance formula by changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v while changing the reference pattern V from the first word to end word V for each time point to end point M; an asymptotic calculating means to calculate a similarity measure D(l, v, n) given by the cumulative sum of said distances on the l-th digit at said time points n and a path information F(l, v, n) indicating a time point of the input pattern at the start point of said v-th reference pattern on a path through which said similarity measure D(l, v, n) has been obtained by a predetermined asymptotic expression according to a dynamic programming process while changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v, while changing digit number l from one to L, and while changing the reference pattern v from the first word to the end word V for each time point m of the input pattern, said time point m changing from the start point to end point M; a digit similarity measure and digit path information calculating means to select a minimum similarity measure from among the similarity measures at the end time points of the reference patterns of all the words on the l-th digit obtained through said asymptotic calculating means, and to provide said minimum similarity measure as a digit similarity measure DB(l, m), a category to which the word corresponding to said minimum similarity measure belongs as a digit recognition category W(l, m)=v, and path information corresponding to said minimum similarity measure as a digit path information FB(l, m) on said digit l at said time point m while changing digit number l from one to L for each time point m of the input pattern, said each time point m changing from the start point to end point M; an initializing means to give said digit similarity measure DB (l-1, m-1) as an initial value of said similarity measure at a time point (m-1) and to give time point (m-1) as an initial value of said path information at a time point m while changing the line point m of the input pattern from the start point to end point M; a decision means to obtain a final digit from said similarity measure DB(l, m), to obtain a recognized result at said final digit from said digit recognition category W(l, M), at the end point M of said input pattern, to obtain an end point of said input pattern on the digit previous to the final digit by one from said digit path information at the end point M, to obtain a recognized result of the digit prior to said final digit by one from said digit recognition category at the end point, and to obtain a recognized result at each digit sequentially toward the start point of said input pattern.
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2. A continuous speech recognition system for recognizing an input speech composed of a plurality of continuously spoken words comprising: a speech analyzing means for analyzing an input signal at every given frame time point m and outputting an input pattern expressed in a time series of a feature vector comprising a predetermined number of feature parameters; an input pattern memory to store said input pattern; a reference pattern memory to store a reference pattern comprising a feature vector in the same format as said input pattern for each of a plurality (V) of predetermined words to be recognized; a distance calculating means to calculate the distance between the feature vector of said input pattern at a time point m and the feature vector of the reference pattern of the v-th word at a time point n at every time point n under a predetermined distance formula by changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v while changing the reference pattern V from the first word to end word V for each time point to end point M; an asymptotic calculating means to calculate a similarity measure D(l, v, n) given by the cumulative sum of said distances on the l-th digit at said time points n and a path information F(l, v, n) indicating a time point of the input pattern at the start point of said v-th reference pattern on a path through which said similarity measure D(l, v, n) has been obtained by a predetermined asymptotic expression according to a dynamic programming process while changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v, while changing digit number l from one to L, and while changing the reference pattern v from the first word to the end word V for each time point m of the input pattern, said time point m changing from the start point to end point M; a digit similarity measure and digit path information calculating means to select a minimum similarity measure from among the similarity measures at the end time points of the reference patterns of all the words on the l-th digit obtained through said asymptotic calculating means, and to provide said minimum similarity measure as a digit similarity measure DB(l, m), a category to which the word corresponding to said minimum similarity measure belongs as a digit recognition category W(l, m)=v, and path information corresponding to said minimum similarity measure as a digit path information FB(l, m) on said digit l at said time point m while changing digit number l from one to L for each time point m of the input pattern, said each time point m changing from the start point to end point M; an initializing means to give said digit similarity measure DB (l-1, m-1) as an initial value of said similarity measure at a time point (m-1) and to give time point (m-1) as an initial value of said path information at a time point m while changing the line point m of the input pattern from the start point to end point M; a decision means to obtain a final digit from said similarity measure DB(l, m), to obtain a recognized result at said final digit from said digit recognition category W(l, M), at the end point M of said input pattern, to obtain an end point of said input pattern on the digit previous to the final digit by one from said digit path information at the end point M, to obtain a recognized result of the digit prior to said final digit by one from said digit recognition category at the end point, and to obtain a recognized result at each digit sequentially toward the start point of said input pattern. 19. A continuous speech recognition system according to claim 2, wherein said asymptotic expression is ##EQU14##
| 0.884781 |
8. A method of encoding and displaying text on an electro-mechanical Braille display, said text having characters with video attributes and being formatted for a visual presentation in which the characters have a predetermined relative spatial relationship with each other, said method comprising steps of: A. hierarchically ordering a description of each character into a plurality of frames of information, said plurality of frames having a top frame and a bottom frame; B. displaying said top frame of the description of the character when said character is first caused to be displayed on said display; C. individually on the Braille display replacing the displayed frame of said character with a succeeding frame of said plurality of frames; and D. repeating step C until all of the frames of the description of the character have been displayed, whereby the formatting and relative spatial relationship of the characters in the displayed text are substantially preserved when said text is displayed on said Braille display and the description of each character can be fully communicated by first displaying said top frames and then individually displaying successive frames until all frames have been displayed.
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8. A method of encoding and displaying text on an electro-mechanical Braille display, said text having characters with video attributes and being formatted for a visual presentation in which the characters have a predetermined relative spatial relationship with each other, said method comprising steps of: A. hierarchically ordering a description of each character into a plurality of frames of information, said plurality of frames having a top frame and a bottom frame; B. displaying said top frame of the description of the character when said character is first caused to be displayed on said display; C. individually on the Braille display replacing the displayed frame of said character with a succeeding frame of said plurality of frames; and D. repeating step C until all of the frames of the description of the character have been displayed, whereby the formatting and relative spatial relationship of the characters in the displayed text are substantially preserved when said text is displayed on said Braille display and the description of each character can be fully communicated by first displaying said top frames and then individually displaying successive frames until all frames have been displayed. 13. The method of claim 8 wherein the plurality of frames consists of four frames wherein the top frame is a first frame and the bottom frame is a fourth frame.
| 0.616756 |
9. A speech processing apparatus for processing an input utterance and registering an unknown word contained in the input utterance into a database on the basis of the processing result, comprising: recognition means for recognizing the input utterance based on both an acoustic score matching a duration of the input utterance for a known word and an acoustic score for a duration of the utterance for an unknown word; unknown word determination means for determining whether the recognition result of the input utterance obtained by the recognition means contains the unknown word on the basis of an acoustic model representing acoustic features of individual phonemes and syllables of a language; recognition result rejection means for determining whether the recognition result determined by the unknown word determination means to contain an unknown word is rejected or not for acquisition and for registering into the database; and word extracting means for storing pronunciation of a word corresponding to the unknown word contained in the recognition result determined not to be rejected by the recognition result rejection means, wherein the acquired pronunciation of the word is used for subsequent speech recognition, and wherein the recognition result rejection means determines whether the recognition result is rejected or not on the basis of a confidence measure for a known word immediately before the unknown word and for a known word immediately after the unknown word contained in the recognition result.
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9. A speech processing apparatus for processing an input utterance and registering an unknown word contained in the input utterance into a database on the basis of the processing result, comprising: recognition means for recognizing the input utterance based on both an acoustic score matching a duration of the input utterance for a known word and an acoustic score for a duration of the utterance for an unknown word; unknown word determination means for determining whether the recognition result of the input utterance obtained by the recognition means contains the unknown word on the basis of an acoustic model representing acoustic features of individual phonemes and syllables of a language; recognition result rejection means for determining whether the recognition result determined by the unknown word determination means to contain an unknown word is rejected or not for acquisition and for registering into the database; and word extracting means for storing pronunciation of a word corresponding to the unknown word contained in the recognition result determined not to be rejected by the recognition result rejection means, wherein the acquired pronunciation of the word is used for subsequent speech recognition, and wherein the recognition result rejection means determines whether the recognition result is rejected or not on the basis of a confidence measure for a known word immediately before the unknown word and for a known word immediately after the unknown word contained in the recognition result. 10. The speech processing apparatus according to claim 9 , wherein the recognition result rejection means determines whether the recognition result is rejected or not on the basis of an unknown-word language model for a sentence containing an unknown word.
| 0.5 |
8. The method of claim 1 , wherein summarizing content of the received electronic message includes replacing one or more words found in the received electronic message with the selected canonical equivalent.
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8. The method of claim 1 , wherein summarizing content of the received electronic message includes replacing one or more words found in the received electronic message with the selected canonical equivalent. 9. The method of claim 8 , wherein the replacing of one or more words includes replacing a combination of two or more words with the selected canonical equivalent.
| 0.930326 |
1. An apparatus comprising: a processor to: receive a user selection of an audit data set including a plurality of exceptions, wherein each exception of the plurality of exceptions represents an instance of misbilling associated with the audit data set, wherein the audit data set is selected from a plurality of billing data sets, each billing data set of the plurality billing data sets including corresponding billing data that has been extracted by the processor from a database; apply a first audit rule to audit the audit data set and produce first audit rule results, wherein the first audit rule results identify a first subset of exceptions of the plurality of exceptions within the audit data set; apply a second audit rule, distinct from the first audit rule, to audit the audit data set and produce second audit rule results, wherein the second audit rule results identify a second subset of exceptions of the plurality of exceptions within the audit data set; present the first subset of exceptions and the second subset of exceptions to a user via a results user interface; and receive a selection of a particular audit rule, wherein the particular audit rule is one of the first audit rule and the second audit rule, and wherein the particular audit rule is selected based on the first audit rule results and the second audit rule results.
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1. An apparatus comprising: a processor to: receive a user selection of an audit data set including a plurality of exceptions, wherein each exception of the plurality of exceptions represents an instance of misbilling associated with the audit data set, wherein the audit data set is selected from a plurality of billing data sets, each billing data set of the plurality billing data sets including corresponding billing data that has been extracted by the processor from a database; apply a first audit rule to audit the audit data set and produce first audit rule results, wherein the first audit rule results identify a first subset of exceptions of the plurality of exceptions within the audit data set; apply a second audit rule, distinct from the first audit rule, to audit the audit data set and produce second audit rule results, wherein the second audit rule results identify a second subset of exceptions of the plurality of exceptions within the audit data set; present the first subset of exceptions and the second subset of exceptions to a user via a results user interface; and receive a selection of a particular audit rule, wherein the particular audit rule is one of the first audit rule and the second audit rule, and wherein the particular audit rule is selected based on the first audit rule results and the second audit rule results. 6. The apparatus of claim 1 , wherein each exception of the plurality of exceptions is based on an attribute of the audit data set.
| 0.621526 |
17. A computerized method for the indexing and retrieval of classified documents comprising: retrieving a document(s) from a document collection, said document(s) having been classified according to a predefined classification scheme, said predefined classification scheme comprising classification codes, said classification codes comprising title(s) and definition(s), said document(s) further comprising at least one retrieval key, wherein said retrieval key corresponds with at least one term of at least one of said classification code title(s) or said classification code definition(s), wherein said retrieving is in response to a request from a search engine, retrieving from a database at least one keyword derived from at least one of said classification code title(s) or classification code definition(s); inserting said term into said document(s) to create a tagged document; and transmitting said tagged document to said search engine.
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17. A computerized method for the indexing and retrieval of classified documents comprising: retrieving a document(s) from a document collection, said document(s) having been classified according to a predefined classification scheme, said predefined classification scheme comprising classification codes, said classification codes comprising title(s) and definition(s), said document(s) further comprising at least one retrieval key, wherein said retrieval key corresponds with at least one term of at least one of said classification code title(s) or said classification code definition(s), wherein said retrieving is in response to a request from a search engine, retrieving from a database at least one keyword derived from at least one of said classification code title(s) or classification code definition(s); inserting said term into said document(s) to create a tagged document; and transmitting said tagged document to said search engine. 20. The computerized method for the indexing and retrieval of classified documents of claim 17 , wherein the document collection contains at least one patent document.
| 0.706019 |
18. A system including memory and one or more processors operable to execute instructions, stored in the memory, comprising instructions to perform the operations of: identifying a respective ordered list of search result documents for each query in a plurality of queries; identifying: a given query in the plurality of queries; a first and second grouping in the ordered list for the given query; and a first and second grouping in the ordered list for each of the remaining queries in the plurality of queries; determining non-overlap scores between the given query and each of the remaining queries in the plurality of queries, wherein the non-overlap scores measure dissimilarities between the search result documents within the first grouping in the ordered list for the given query and the first grouping in the ordered list for each of the remaining queries in the plurality of queries; selecting one or more candidate queries from the remaining queries in the plurality of queries based on the non-overlap scores; determining overlap scores between the given query and each of the candidate queries, wherein the overlap scores measure similarities between the search result documents within the second grouping in the ordered list for the given query and the second grouping in the ordered list for each of the candidate queries; selecting one or more related queries from the candidate queries based on the overlap scores; and storing data associating the related queries with the given query.
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18. A system including memory and one or more processors operable to execute instructions, stored in the memory, comprising instructions to perform the operations of: identifying a respective ordered list of search result documents for each query in a plurality of queries; identifying: a given query in the plurality of queries; a first and second grouping in the ordered list for the given query; and a first and second grouping in the ordered list for each of the remaining queries in the plurality of queries; determining non-overlap scores between the given query and each of the remaining queries in the plurality of queries, wherein the non-overlap scores measure dissimilarities between the search result documents within the first grouping in the ordered list for the given query and the first grouping in the ordered list for each of the remaining queries in the plurality of queries; selecting one or more candidate queries from the remaining queries in the plurality of queries based on the non-overlap scores; determining overlap scores between the given query and each of the candidate queries, wherein the overlap scores measure similarities between the search result documents within the second grouping in the ordered list for the given query and the second grouping in the ordered list for each of the candidate queries; selecting one or more related queries from the candidate queries based on the overlap scores; and storing data associating the related queries with the given query. 25. The system of claim 18 , wherein: the search results documents in the second grouping in the ordered list for the given query have the same ordering as the respective search result documents in the second grouping in the ordered list for each of the candidate queries.
| 0.526643 |
86. An apparatus comprising: establishing an account for each of a plurality of users, wherein each account is associated with storage space to store one or more documents; storing a first document in the server computer system in a first account, the first document capable of being modified by a plurality of authorized users; enabling access to the first document via a browser-controlled window executing on a client computer by one or more authorized users; associating a set of restrictions with the first document, the restrictions including an ability to modify the first document in one or more permitted ways by one of a first group of users, the first group of users being users whose identities are known to the server computer system; receiving a request to access the first document from a first user, wherein the first user is a member of the first group of users, wherein the request to access accompanies the first user's identification information and authorization information; verifying the identity of the first user; if the first user is authorized to access the first document, then permitting the first user to access the first document via a first browser-controlled window executing on a client computer; and if the first user is authorized to modify the first document, (a) applying one or more modifications to the first document, the one or more modifications having been received from the first user; (b) electronically notifying one or more of a second group of users that the first user modified the first document, the second group of users being users whose identities are known to the server computer system; and (c) enabling a second user to approve or disapprove the one or more modifications made to the first document by the first user, wherein the second user is a member of the second group of users who are notified of the one or more modifications made by the first user to the first document, and wherein the second user is not the same as the first user.
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86. An apparatus comprising: establishing an account for each of a plurality of users, wherein each account is associated with storage space to store one or more documents; storing a first document in the server computer system in a first account, the first document capable of being modified by a plurality of authorized users; enabling access to the first document via a browser-controlled window executing on a client computer by one or more authorized users; associating a set of restrictions with the first document, the restrictions including an ability to modify the first document in one or more permitted ways by one of a first group of users, the first group of users being users whose identities are known to the server computer system; receiving a request to access the first document from a first user, wherein the first user is a member of the first group of users, wherein the request to access accompanies the first user's identification information and authorization information; verifying the identity of the first user; if the first user is authorized to access the first document, then permitting the first user to access the first document via a first browser-controlled window executing on a client computer; and if the first user is authorized to modify the first document, (a) applying one or more modifications to the first document, the one or more modifications having been received from the first user; (b) electronically notifying one or more of a second group of users that the first user modified the first document, the second group of users being users whose identities are known to the server computer system; and (c) enabling a second user to approve or disapprove the one or more modifications made to the first document by the first user, wherein the second user is a member of the second group of users who are notified of the one or more modifications made by the first user to the first document, and wherein the second user is not the same as the first user. 88. The apparatus of claim 86 , wherein the processor executable instructions include instructions to cause the server computer system to store an indication that a notification has been sent to one or more of the second group of users that the first document is modified.
| 0.676143 |
1. A method comprising: obtaining an utterance vector that is derived from an utterance; determining hash values for the utterance vector according to multiple different hash functions; determining a set of speaker vectors from a plurality of hash tables using the hash values, each speaker vector being derived from one or more utterances of a respective speaker; comparing the speaker vectors in the set with the utterance vector; selecting a speaker vector based on comparing the speaker vectors in the set with the utterance vector; determining a speaker identity corresponding to the selected speaker vector; and outputting data indicating the speaker identity.
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1. A method comprising: obtaining an utterance vector that is derived from an utterance; determining hash values for the utterance vector according to multiple different hash functions; determining a set of speaker vectors from a plurality of hash tables using the hash values, each speaker vector being derived from one or more utterances of a respective speaker; comparing the speaker vectors in the set with the utterance vector; selecting a speaker vector based on comparing the speaker vectors in the set with the utterance vector; determining a speaker identity corresponding to the selected speaker vector; and outputting data indicating the speaker identity. 5. The method of claim 1 , further comprising: determining that the selected speaker vector corresponds to a particular user; and based at least in part on the determining that the selected speaker vector corresponds to a particular user identity, authenticating the particular user.
| 0.68411 |
23. A non-transitory computer readable medium including computer program code for characterizing unregistered domain names, the computer readable medium comprising: code for obtaining a list of a plurality of resolution requests for a plurality of unregistered domain names, wherein each resolution request includes a timestamp field, a requesting-machine identifier field, and an unregistered domain name field; code for determining a number of occurrences of resolution requests for each of the unregistered domain names; code for computing a plurality of groupings based on the number of occurrences; and code for associating a score with each of the unregistered domain names.
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23. A non-transitory computer readable medium including computer program code for characterizing unregistered domain names, the computer readable medium comprising: code for obtaining a list of a plurality of resolution requests for a plurality of unregistered domain names, wherein each resolution request includes a timestamp field, a requesting-machine identifier field, and an unregistered domain name field; code for determining a number of occurrences of resolution requests for each of the unregistered domain names; code for computing a plurality of groupings based on the number of occurrences; and code for associating a score with each of the unregistered domain names. 27. The computer readable medium of claim 23 further comprising: code for determining a number of the plurality of resolution requests associated with a particular IP address; and code for reducing the number of the plurality of resolution requests associated with the particular IP address.
| 0.601808 |
1. A computer system for generating a video edit decision list comprising a formatted list of computer instructions for an edit controller for assembling a video program, wherein each instruction defines source material and a destination of a video editing event, the computer system comprising: input means for receiving a representation of the video program as a sequence of edit events produced by a digital video editing system, selecting means, connected to the input means, for selecting one of a plurality of video edit decision list format specifiers, wherein each format specifier specifies a syntax of a video edit decision list of a different machine, generating means for generating, according to the sequence of edit events, the formatted list of computer instructions in the syntax specified by the selected video edit decision list format specifier, and output means, connected to the selecting means, for outputting the formatted list as the video edit decision list for use by the edit controller for assembling the video program.
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1. A computer system for generating a video edit decision list comprising a formatted list of computer instructions for an edit controller for assembling a video program, wherein each instruction defines source material and a destination of a video editing event, the computer system comprising: input means for receiving a representation of the video program as a sequence of edit events produced by a digital video editing system, selecting means, connected to the input means, for selecting one of a plurality of video edit decision list format specifiers, wherein each format specifier specifies a syntax of a video edit decision list of a different machine, generating means for generating, according to the sequence of edit events, the formatted list of computer instructions in the syntax specified by the selected video edit decision list format specifier, and output means, connected to the selecting means, for outputting the formatted list as the video edit decision list for use by the edit controller for assembling the video program. 9. The system according to claim 1, wherein each of said format specifiers includes at least one model for specifying a video editing event in the corresponding format.
| 0.652655 |
15. The system of claim 9 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising: testing the finite state machine prior to the generating of the test dialogs associated with the call flow.
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15. The system of claim 9 , the computer-readable storage medium having additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising: testing the finite state machine prior to the generating of the test dialogs associated with the call flow. 16. The system of claim 15 , wherein the testing of the finite state machine is performed using stored real-call records.
| 0.820623 |
1. A method of editing delimited ambiguous inputs on a handheld electronic device, comprising: indicating, on the handheld electronic device, an unintended language object corresponding to a first delimited ambiguous input, wherein the first delimited ambiguous input corresponds to at least one other language object, and wherein the indicating of the unintended language object is based on a frequency difference between a first frequency value associated with the unintended language object and a second frequency value associated with the other language object, wherein at least two predetermined ranges are maintained, such that if the frequency difference falls within one predetermined range a first non-default text style will be applied to the unintended language object and if the frequency difference falls within a second predetermined range a second non-default text style will be applied to the unintended language object; detecting, on the handheld electronic device, a selection of the unintended language object generated from the first delimited ambiguous input; and outputting, on the handheld electronic device, the other language object and at least one of an edit option or a delete option in response to the selection of the unintended language object.
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1. A method of editing delimited ambiguous inputs on a handheld electronic device, comprising: indicating, on the handheld electronic device, an unintended language object corresponding to a first delimited ambiguous input, wherein the first delimited ambiguous input corresponds to at least one other language object, and wherein the indicating of the unintended language object is based on a frequency difference between a first frequency value associated with the unintended language object and a second frequency value associated with the other language object, wherein at least two predetermined ranges are maintained, such that if the frequency difference falls within one predetermined range a first non-default text style will be applied to the unintended language object and if the frequency difference falls within a second predetermined range a second non-default text style will be applied to the unintended language object; detecting, on the handheld electronic device, a selection of the unintended language object generated from the first delimited ambiguous input; and outputting, on the handheld electronic device, the other language object and at least one of an edit option or a delete option in response to the selection of the unintended language object. 10. The method of claim 1 , further comprising: providing a delete option; and detecting a selection of the delete option.
| 0.629597 |
3. The method of claim 1 wherein, extracting at least some concepts correspondingly associated with the plurality of the software design artifacts comprises: applying parsing methods to textual forms of the plurality of the software design artifacts to decompose at least some of the plurality of the software design artifacts into text-based document objects; and based at least in part on different predefined templates corresponding to different concept types, classifying at least some of the text-based document objects as concept descriptions of the different concept types.
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3. The method of claim 1 wherein, extracting at least some concepts correspondingly associated with the plurality of the software design artifacts comprises: applying parsing methods to textual forms of the plurality of the software design artifacts to decompose at least some of the plurality of the software design artifacts into text-based document objects; and based at least in part on different predefined templates corresponding to different concept types, classifying at least some of the text-based document objects as concept descriptions of the different concept types. 4. The method of claim 3 wherein, extracting the at least some key terms correspondingly associated with the at least some extracted concepts comprises: parsing at least some of the extracted concepts to decompose the concept descriptions into words and phrases; storing the decomposed words and phrases as key terms in a key terms database; comparing the decomposed words and phrases to a stop list; and deleting from the key terms database those key terms that correspond to words and phrases also present in the stop list.
| 0.838889 |
1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user.
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1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user. 63. The method of claim 1 , wherein receiving at least one query includes receiving at least one query for at least one tenure report that lists performance data pertaining to a plurality of agents, wherein the at least one tenure report is organized by a plurality of tenure periods of the agents.
| 0.513964 |
1. A method for expanding a query, comprising the steps of: storing a bipartite representation; wherein the bipartite representation comprises a first set of nodes; wherein each node in the first set of nodes represents a linguistic word; wherein the bipartite representation comprises a second set of nodes; wherein each node in the second set of nodes represents visual content; receiving the query; for at least one query term of the query, performing the steps of: determining whether the at least one query term is associated with one or more other query terms through visual content; wherein determining whether the at least one query term is associated with one or more other query terms through visual content comprises: determining, based on the bipartite representation, an association score between (a) a first node of the bipartite representation, which represents a linguistic word associated with the at least one query term, and (b) a second node of the bipartite representation, which represents one or more other linguistic words associated with one or more other query terms; determining, based on the association score, that the at least one query term is associated with the one or more other query terms through visual content; in response to determining that the at least one query term is associated with one or more other query terms through visual content, creating an expanded query by adding at least one of the one or more other query terms to the query; wherein the method is performed by one or more computing devices.
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1. A method for expanding a query, comprising the steps of: storing a bipartite representation; wherein the bipartite representation comprises a first set of nodes; wherein each node in the first set of nodes represents a linguistic word; wherein the bipartite representation comprises a second set of nodes; wherein each node in the second set of nodes represents visual content; receiving the query; for at least one query term of the query, performing the steps of: determining whether the at least one query term is associated with one or more other query terms through visual content; wherein determining whether the at least one query term is associated with one or more other query terms through visual content comprises: determining, based on the bipartite representation, an association score between (a) a first node of the bipartite representation, which represents a linguistic word associated with the at least one query term, and (b) a second node of the bipartite representation, which represents one or more other linguistic words associated with one or more other query terms; determining, based on the association score, that the at least one query term is associated with the one or more other query terms through visual content; in response to determining that the at least one query term is associated with one or more other query terms through visual content, creating an expanded query by adding at least one of the one or more other query terms to the query; wherein the method is performed by one or more computing devices. 11. The method of claim 1 , wherein adding at least one of the one or more other query terms to the query comprises substituting the at least one query term of the query with at least one of the one or more other query terms to the query.
| 0.674279 |
17. The website editor of claim 1 , wherein the editor display component displays an editor interface comprising a media library interface.
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17. The website editor of claim 1 , wherein the editor display component displays an editor interface comprising a media library interface. 18. The website editor of claim 17 , wherein the media library interface displays media items available for inclusion on the website.
| 0.948853 |
8. A device, comprising: a processor; an input device coupled to the processor; an output device coupled to the processor; and a non-transitory computer readable storage medium coupled to the processor, wherein the non-transitory computer readable storage medium comprises code executable by the processor for implementing a method comprising: obtaining a first image comprising a plurality of pixels representing an at least one symbol and a plurality of pixels representing a background area; defining a first and a second boundary in the first image, wherein the first and the second boundaries are each a path comprising a plurality of pixels that minimizes a cost associated with change in color for the path and each of the paths are positioned on opposite sides of the at least one symbol; generating a plurality of pixels representing an at least one translated symbol of the at least one symbol; generating a plurality of pixels representing an augmented version of the background area, by interpolating a plurality of background pixel values between the first and the second boundaries; and constructing a second image comprising the plurality of pixels representing the at least one translated symbol and the plurality of pixels representing the augmented version of the background area.
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8. A device, comprising: a processor; an input device coupled to the processor; an output device coupled to the processor; and a non-transitory computer readable storage medium coupled to the processor, wherein the non-transitory computer readable storage medium comprises code executable by the processor for implementing a method comprising: obtaining a first image comprising a plurality of pixels representing an at least one symbol and a plurality of pixels representing a background area; defining a first and a second boundary in the first image, wherein the first and the second boundaries are each a path comprising a plurality of pixels that minimizes a cost associated with change in color for the path and each of the paths are positioned on opposite sides of the at least one symbol; generating a plurality of pixels representing an at least one translated symbol of the at least one symbol; generating a plurality of pixels representing an augmented version of the background area, by interpolating a plurality of background pixel values between the first and the second boundaries; and constructing a second image comprising the plurality of pixels representing the at least one translated symbol and the plurality of pixels representing the augmented version of the background area. 13. The device of claim 8 , wherein interpolating background pixel values utilizes non-linear interpolation.
| 0.799107 |
17. The non-transitory computer readable storage medium of claim 12 , wherein determining the co-occurrence measure for the first input sentence comprises: grouping second input sentences that are determined to be similar to each other; grouping, from the identified pairs of first and second input sentences that include a second input sentence belonging to the group of second input sentences, first input sentences that are determined to be similar to each other; and determining that a cardinality of the group of first input sentences meets a threshold cardinality.
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17. The non-transitory computer readable storage medium of claim 12 , wherein determining the co-occurrence measure for the first input sentence comprises: grouping second input sentences that are determined to be similar to each other; grouping, from the identified pairs of first and second input sentences that include a second input sentence belonging to the group of second input sentences, first input sentences that are determined to be similar to each other; and determining that a cardinality of the group of first input sentences meets a threshold cardinality. 18. The non-transitory computer readable storage medium of claim 17 , wherein grouping second input sentences that are determined to be similar to each other comprises grouping second input sentences that are successfully parsed by a same rule.
| 0.93679 |
9. An apparatus comprising: a processor; and a memory storing machine-readable instructions that, when executed, cause the processor to implement: an editor useable to create a first script defining a physical topology and control of a process control system including multiple process controllers and process control devices, the first script including tokens that have a type and value to define attributes of the multiple process controllers and process control devices, the topology representing physical communicative couplings between the multiple process controllers and the process control devices, the first script comprising an interpretable system-level vendor-independent schema; and a compiler including: a parser to identify one or more first expressions based on grammatical relationships between the tokens contained in the first script; and an interpreter to: retrieve vendor-specific information associated with the process control system from a device database associated with the process control system; and form a second script based on the identified one or more first expressions and the retrieved vendor-specific information, the second script to configure the multiple process controllers and process control devices and structured in accordance with a first vendor-specific configuration language associated with the process control system.
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9. An apparatus comprising: a processor; and a memory storing machine-readable instructions that, when executed, cause the processor to implement: an editor useable to create a first script defining a physical topology and control of a process control system including multiple process controllers and process control devices, the first script including tokens that have a type and value to define attributes of the multiple process controllers and process control devices, the topology representing physical communicative couplings between the multiple process controllers and the process control devices, the first script comprising an interpretable system-level vendor-independent schema; and a compiler including: a parser to identify one or more first expressions based on grammatical relationships between the tokens contained in the first script; and an interpreter to: retrieve vendor-specific information associated with the process control system from a device database associated with the process control system; and form a second script based on the identified one or more first expressions and the retrieved vendor-specific information, the second script to configure the multiple process controllers and process control devices and structured in accordance with a first vendor-specific configuration language associated with the process control system. 10. The apparatus as defined in claim 9 , wherein the first script is to be compiled to form a third script, the third script structured in accordance with a second vendor-specific configuration language associated with a second process control system.
| 0.665761 |
8. A system comprising: at least a memory and a processor to implement a language detection service, the language detection service configured to: determine which human writing system is associated with a string of text characters based on numerical values representing the text characters in the string; when the numerical values are associated with more than one human language, compare the string with a targeted dictionary, including a plurality of strings, in which individual said strings in the targeted dictionary are associated with a corresponding said human language, to identify the corresponding said human language associated with the string; and designate which linguistic services are available for use by an application based on the corresponding said human language associated with the string and based on a service property of the linguistic services, the service property corresponding to a text property of the string of text characters.
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8. A system comprising: at least a memory and a processor to implement a language detection service, the language detection service configured to: determine which human writing system is associated with a string of text characters based on numerical values representing the text characters in the string; when the numerical values are associated with more than one human language, compare the string with a targeted dictionary, including a plurality of strings, in which individual said strings in the targeted dictionary are associated with a corresponding said human language, to identify the corresponding said human language associated with the string; and designate which linguistic services are available for use by an application based on the corresponding said human language associated with the string and based on a service property of the linguistic services, the service property corresponding to a text property of the string of text characters. 11. The system of claim 8 , wherein the language detection service is further configured to receive a request from the application specifying which service properties are relevant to the application.
| 0.617647 |
1. A computer implemented method for indexing and retrieving documents in a database, comprising the steps of: constructing a set of particles and a simultaneously optimized particle-based language model using training documents, and in which a perplexity of the particle-based language model is at least ten times lower than the perplexity of a word-based language model constructed from the same training documents, wherein the set of particles applies expectation maximization to an objective function, and where the objective function considers any combination of: a size of the set of particles; errors in representing all documents in a document training set and a query training set; a retrieval accuracy of using the set of particles; an entropy of a statistical models that represent the set of particles; and a particle-level language model derived from the documents and the queries in the training sets; converting each document in a collection of documents to a document particle graph, the document particle graph including particles selected from the set of the particles; extracting, for each document, a set of document keys from the corresponding particle graph; storing the document keys for each document in an index to a database storing the collection of documents; converting a query to a query particle graph including a set of query particles, the query graph including particles selected from the set of the particles; extracting a set of query keys from the query particle graph; retrieving relevant documents from the database according to the query keys and the document keys stored in the index; and outputting the relevant documents to a user.
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1. A computer implemented method for indexing and retrieving documents in a database, comprising the steps of: constructing a set of particles and a simultaneously optimized particle-based language model using training documents, and in which a perplexity of the particle-based language model is at least ten times lower than the perplexity of a word-based language model constructed from the same training documents, wherein the set of particles applies expectation maximization to an objective function, and where the objective function considers any combination of: a size of the set of particles; errors in representing all documents in a document training set and a query training set; a retrieval accuracy of using the set of particles; an entropy of a statistical models that represent the set of particles; and a particle-level language model derived from the documents and the queries in the training sets; converting each document in a collection of documents to a document particle graph, the document particle graph including particles selected from the set of the particles; extracting, for each document, a set of document keys from the corresponding particle graph; storing the document keys for each document in an index to a database storing the collection of documents; converting a query to a query particle graph including a set of query particles, the query graph including particles selected from the set of the particles; extracting a set of query keys from the query particle graph; retrieving relevant documents from the database according to the query keys and the document keys stored in the index; and outputting the relevant documents to a user. 13. The method of claim 1 , in which the particles in the set of particles are acoustically distinct and self-contained.
| 0.747917 |
1. A computer-implemented system for review and export of a clinical content structure, the system comprising: a server configured to provide a first authoring environment that operates on a first set of one or more programmed computers associated with a first protocol and a second authoring environment that operates on a second set of one or more programmed computers associated with a second protocol, wherein the first set of one or more programmed computers and the second set of one or more programmed computers are communicatively coupled to a server via a network, the first protocol and the second protocol are different, and the clinical content structure comprises a set of one or more evidence-based options that are selectable by a clinician during patient care; a server configured to display, at the first authoring environment and the second authoring environment, a default clinical content structure; a server configured to receive first modification data from the one or more users of the first authoring environment and second modification data from one or more users of the second authoring environment; a server configured to modify the default clinical content structure based on the first modification data and the second modification data to create a modified clinical content structure; a server configured to store a first plurality of data translation rules associated with the first authoring environment, wherein each data translation rule of the first plurality of data translation rules maps at least one term associated with the first authoring environment to one or more terms of one or more standard term libraries; a server configured to store a second plurality of data translation rules associated with the second authoring environment, wherein each data translation rule of the second plurality of data translation rules maps at least one term associated with the second authoring environment to one or more terms of the one or more standard term libraries; a server configured to automatically translate the modified clinical content structure into a first standard structure using the first plurality of data translation rules; a server configured to automatically translate the modified clinical content structure into a second standard structure using the second plurality of data translation rules; a server configured to convert the first standard structure into a first export structure that is executable by the first protocol of the first set of one or more programmed computers; a server configured to convert the second standard structure into a second export structure that is executable by the second protocol of the second set of one or more programmed computers; and a server configured to transmit the first export structure to the first set of one or more programmed computers and the second export structure to the second set of one or more programmed computers.
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1. A computer-implemented system for review and export of a clinical content structure, the system comprising: a server configured to provide a first authoring environment that operates on a first set of one or more programmed computers associated with a first protocol and a second authoring environment that operates on a second set of one or more programmed computers associated with a second protocol, wherein the first set of one or more programmed computers and the second set of one or more programmed computers are communicatively coupled to a server via a network, the first protocol and the second protocol are different, and the clinical content structure comprises a set of one or more evidence-based options that are selectable by a clinician during patient care; a server configured to display, at the first authoring environment and the second authoring environment, a default clinical content structure; a server configured to receive first modification data from the one or more users of the first authoring environment and second modification data from one or more users of the second authoring environment; a server configured to modify the default clinical content structure based on the first modification data and the second modification data to create a modified clinical content structure; a server configured to store a first plurality of data translation rules associated with the first authoring environment, wherein each data translation rule of the first plurality of data translation rules maps at least one term associated with the first authoring environment to one or more terms of one or more standard term libraries; a server configured to store a second plurality of data translation rules associated with the second authoring environment, wherein each data translation rule of the second plurality of data translation rules maps at least one term associated with the second authoring environment to one or more terms of the one or more standard term libraries; a server configured to automatically translate the modified clinical content structure into a first standard structure using the first plurality of data translation rules; a server configured to automatically translate the modified clinical content structure into a second standard structure using the second plurality of data translation rules; a server configured to convert the first standard structure into a first export structure that is executable by the first protocol of the first set of one or more programmed computers; a server configured to convert the second standard structure into a second export structure that is executable by the second protocol of the second set of one or more programmed computers; and a server configured to transmit the first export structure to the first set of one or more programmed computers and the second export structure to the second set of one or more programmed computers. 9. The computer-implemented system of claim 1 wherein the clinical content structure comprises an order set.
| 0.529258 |
15. A system, comprising: a processor; and a memory hosting an application, which, when executed on the processor, performs an operation for encrypting a first application data file, the operation comprising: determining a file format of the first application data file, encrypting the first application data file, selecting a second application data file template having a file format matching the file format of the first application data file, wherein a placeholder image is embedded in the second application data file template, storing the first application data file as encrypted content in an image file container, wherein storing the first application data file as the encrypted content in the image file container comprises: generating the image file container having a first image format; and embedding the encrypted content, as image data, in the image file container; replacing the placeholder image in the second application data file template with the image file container storing the first application data file as encrypted content, embedding, in the second application data file template, textual instructions for accessing the encrypted content, and generating a second application data file from the second application data file template, wherein the textual instructions are presented to users when accessing the second application data file.
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15. A system, comprising: a processor; and a memory hosting an application, which, when executed on the processor, performs an operation for encrypting a first application data file, the operation comprising: determining a file format of the first application data file, encrypting the first application data file, selecting a second application data file template having a file format matching the file format of the first application data file, wherein a placeholder image is embedded in the second application data file template, storing the first application data file as encrypted content in an image file container, wherein storing the first application data file as the encrypted content in the image file container comprises: generating the image file container having a first image format; and embedding the encrypted content, as image data, in the image file container; replacing the placeholder image in the second application data file template with the image file container storing the first application data file as encrypted content, embedding, in the second application data file template, textual instructions for accessing the encrypted content, and generating a second application data file from the second application data file template, wherein the textual instructions are presented to users when accessing the second application data file. 21. The system of claim 15 , wherein the file format of the first application data file comprises one of a word processor format, a spreadsheet format, presentation slide format, and a portable document format (PDF).
| 0.651549 |
24. An electronic device, comprising: a touch-sensitive surface; one or more processors; and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for: displaying one or more views of a plurality of views, wherein: a first view of the one or more displayed views includes a plurality of gesture recognizers; the plurality of gesture recognizers in the first view includes one or more proxy gesture recognizers and one or more non-proxy gesture recognizers; each gesture recognizer indicates one of a plurality of predefined states; and a first proxy gesture recognizer in the first view has a state that corresponds to a state of a respective non-proxy gesture recognizer that is not in the first view, wherein the state of the first proxy gesture recognizer and the corresponding state of the respective non-proxy gesture recognizer are both selected from a same set of predefined states; detecting a sequence of one or more sub-events; delivering a respective sub-event to the respective non-proxy gesture recognizer that is not in the first view and at least a subset of the one or more non-proxy gesture recognizers in the first view; and processing the respective sub-event with at least one of the one or more non-proxy gesture recognizers in the first view in accordance with states of the first proxy gesture recognizer and at least the subset of the one or more non-proxy gesture recognizers in the first view.
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24. An electronic device, comprising: a touch-sensitive surface; one or more processors; and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for: displaying one or more views of a plurality of views, wherein: a first view of the one or more displayed views includes a plurality of gesture recognizers; the plurality of gesture recognizers in the first view includes one or more proxy gesture recognizers and one or more non-proxy gesture recognizers; each gesture recognizer indicates one of a plurality of predefined states; and a first proxy gesture recognizer in the first view has a state that corresponds to a state of a respective non-proxy gesture recognizer that is not in the first view, wherein the state of the first proxy gesture recognizer and the corresponding state of the respective non-proxy gesture recognizer are both selected from a same set of predefined states; detecting a sequence of one or more sub-events; delivering a respective sub-event to the respective non-proxy gesture recognizer that is not in the first view and at least a subset of the one or more non-proxy gesture recognizers in the first view; and processing the respective sub-event with at least one of the one or more non-proxy gesture recognizers in the first view in accordance with states of the first proxy gesture recognizer and at least the subset of the one or more non-proxy gesture recognizers in the first view. 30. The device of claim 24 , wherein: at least a second non-proxy gesture recognizer of the one or more non-proxy gesture recognizers in the first view is adapted to delay delivering one or more sub-events of the sequence of one or more sub-events to the first view until after the second non-proxy gesture recognizer fails to recognize a gesture that corresponds to the sequence of one or more sub-events.
| 0.506822 |
52. A data processing system according to claim 51 wherein said memory processor is further programmable such that the processor may receive a block of data from the memory, said memory processor formatting the block of data as the block of data is sequentially transferred.
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52. A data processing system according to claim 51 wherein said memory processor is further programmable such that the processor may receive a block of data from the memory, said memory processor formatting the block of data as the block of data is sequentially transferred. 53. A data processing system according to claim 52 wherein said memory processor is further programmable such that the memory may send a block of data from the memory to said memory processor, said memory processor formatting the block of data and sending the block of data back to the memory.
| 0.879319 |
1. A method for searching a database of Objects, in which each Object is associated with a plurality of Attributes, each Attribute is associated with a Kind, and each Kind is associated with a plurality of Attributes, comprising: performing processing associated with receiving, utilizing a computer, search criteria from a user, the search criteria comprising an Attribute; performing processing associated with creating, utilizing the computer, a Nonceattribute using the search criteria performing processing associated with inputting, utilizing the computer, a search utilizing the Nonceattribute; performing processing associated with identifying, utilizing the computer, all Objects having the Nonceattribute; performing processing associated with identifying, utilizing the computer, all Attributes associated with the Objects; performing processing associated with identifying, utilizing the computer, all Kinds associated with the Attributes; and performing processing associated with displaying, utilizing the computer, at least a portion of the Kinds and at least a portion of the Attributes in a search result display, the search result display presented in a mutable hierarchical format independent of a location of an object in a default hierarchical structure.
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1. A method for searching a database of Objects, in which each Object is associated with a plurality of Attributes, each Attribute is associated with a Kind, and each Kind is associated with a plurality of Attributes, comprising: performing processing associated with receiving, utilizing a computer, search criteria from a user, the search criteria comprising an Attribute; performing processing associated with creating, utilizing the computer, a Nonceattribute using the search criteria performing processing associated with inputting, utilizing the computer, a search utilizing the Nonceattribute; performing processing associated with identifying, utilizing the computer, all Objects having the Nonceattribute; performing processing associated with identifying, utilizing the computer, all Attributes associated with the Objects; performing processing associated with identifying, utilizing the computer, all Kinds associated with the Attributes; and performing processing associated with displaying, utilizing the computer, at least a portion of the Kinds and at least a portion of the Attributes in a search result display, the search result display presented in a mutable hierarchical format independent of a location of an object in a default hierarchical structure. 9. The method of claim 1 , wherein the Nonceattribute comprises a word, or a search phrase, or any combination thereof.
| 0.739686 |
1. A non-transitory computer-readable memory having contents configured to cause at least one computer having a processor to perform a method, the method comprising: providing a language model for a selected language to various computing devices of multiple users of the selected language, wherein the language model is accessible and modifiable via a language recognition system, and wherein the language model includes a dynamic portion; causing display of an interface for user input to delete a word from the dynamic portion of the language model; receiving, via the interface, a user's input to delete a word from the dynamic portion of the language model; in response to the input to delete a word from the language model, prompting, via the interface, the user to provide a reason for the deletion; in response to the prompting, receiving input identifying one or more reasons for the deletion; collecting, from the various computing devices, the received input identifying the reasons for the multiple users' deletions of words in the selected language; aggregating the collected input from the various computing devices about the deletions; generating updates to the dynamic portion of the language model based on the aggregated input about the deletions; and transmitting the generated language model updates to the various computing devices.
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1. A non-transitory computer-readable memory having contents configured to cause at least one computer having a processor to perform a method, the method comprising: providing a language model for a selected language to various computing devices of multiple users of the selected language, wherein the language model is accessible and modifiable via a language recognition system, and wherein the language model includes a dynamic portion; causing display of an interface for user input to delete a word from the dynamic portion of the language model; receiving, via the interface, a user's input to delete a word from the dynamic portion of the language model; in response to the input to delete a word from the language model, prompting, via the interface, the user to provide a reason for the deletion; in response to the prompting, receiving input identifying one or more reasons for the deletion; collecting, from the various computing devices, the received input identifying the reasons for the multiple users' deletions of words in the selected language; aggregating the collected input from the various computing devices about the deletions; generating updates to the dynamic portion of the language model based on the aggregated input about the deletions; and transmitting the generated language model updates to the various computing devices. 4. The computer-readable memory of claim 1 wherein prompting the user to provide information about the deletion includes prompting the user to classify the deleted word.
| 0.762821 |
1. A computer implemented method, comprising: identifying a plurality of classification terms indicative of a classification; identifying a corpus of communications from one or more databases, the corpus of communications including a plurality of communications that are not labeled with an association to the classification; determining a cluster of the communications based on occurrence of one or more of the classification terms in the communications of the cluster; subsequent to determining the cluster, determining a feature set based on the communications of the cluster, wherein determining the feature set comprises: determining one or more features that are based on content that appears in a plurality of the communications of the cluster, wherein the content is in addition to the classification terms used in determining the cluster, and wherein determining the features based on the content that is in addition to the classification terms comprises determining the features based on the content appearing in the plurality of the communications of the cluster; assigning the feature set to an indication of the classification; and using the assigned feature set to classify an additional communication with the classification or using the assigned feature set to select a data extraction parser, for the classification, for the additional communication.
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1. A computer implemented method, comprising: identifying a plurality of classification terms indicative of a classification; identifying a corpus of communications from one or more databases, the corpus of communications including a plurality of communications that are not labeled with an association to the classification; determining a cluster of the communications based on occurrence of one or more of the classification terms in the communications of the cluster; subsequent to determining the cluster, determining a feature set based on the communications of the cluster, wherein determining the feature set comprises: determining one or more features that are based on content that appears in a plurality of the communications of the cluster, wherein the content is in addition to the classification terms used in determining the cluster, and wherein determining the features based on the content that is in addition to the classification terms comprises determining the features based on the content appearing in the plurality of the communications of the cluster; assigning the feature set to an indication of the classification; and using the assigned feature set to classify an additional communication with the classification or using the assigned feature set to select a data extraction parser, for the classification, for the additional communication. 17. The computer implemented method of claim 1 , wherein the communications of the cluster include structured communications, and wherein determining the cluster of the communications is further based on hierarchical structure of structural paths of the structured communications of the cluster, the structural paths being structural paths of eXtensible Markup Language or Hypertext Markup Language.
| 0.619604 |
8. A computer program product for transforming historical data collected in response to one or more triggering events, in order to classify textual values, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to access a plurality of textual values from historical transaction data; computer readable program code configured to remove undesired characters from the plurality of textual values; computer readable program code configured to implement a clustering algorithm to the plurality of textual values to identify one or more distinct patterns within the plurality of textual values, wherein the clustering algorithm comprises: a primary process coding the plurality of textual values into one or more phonetic components, thereby reducing the plurality of textual values into a combination of consonant sounds, wherein identifying the one or more distinct patterns within the plurality of textual values comprises comparing pronunciations and phonetics of the plurality of textual values; and a secondary process for identifying and classifying, based on an Internet search, one or more of the plurality of textual values unable to be classified by the primary process; computer readable program code configured to create one or more clusters by grouping the plurality of textual values based, respectively, on the one or more distinct patterns output by the primary process and the Internet search of the secondary process; computer readable program code configured to apply a similarity gauge to the textual values of each of the clusters to determine similarity or dissimilarity among the textual values of each cluster; computer readable program code configured to filter the textual values of each cluster to determine which textual values belong in each cluster and which textual values do not belong in each cluster, wherein the textual values that belong are cluster values; computer readable program code configured to pass the cluster values for each cluster to a reference table; computer readable program code configured to store the cluster values for each cluster in the reference table for future access; and computer readable program code configured to, in response to a need for classification of a future set of textual values, access the reference table and lookup the future set of textual values in the reference table to determine whether any of the future set of textual values are cluster values.
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8. A computer program product for transforming historical data collected in response to one or more triggering events, in order to classify textual values, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to access a plurality of textual values from historical transaction data; computer readable program code configured to remove undesired characters from the plurality of textual values; computer readable program code configured to implement a clustering algorithm to the plurality of textual values to identify one or more distinct patterns within the plurality of textual values, wherein the clustering algorithm comprises: a primary process coding the plurality of textual values into one or more phonetic components, thereby reducing the plurality of textual values into a combination of consonant sounds, wherein identifying the one or more distinct patterns within the plurality of textual values comprises comparing pronunciations and phonetics of the plurality of textual values; and a secondary process for identifying and classifying, based on an Internet search, one or more of the plurality of textual values unable to be classified by the primary process; computer readable program code configured to create one or more clusters by grouping the plurality of textual values based, respectively, on the one or more distinct patterns output by the primary process and the Internet search of the secondary process; computer readable program code configured to apply a similarity gauge to the textual values of each of the clusters to determine similarity or dissimilarity among the textual values of each cluster; computer readable program code configured to filter the textual values of each cluster to determine which textual values belong in each cluster and which textual values do not belong in each cluster, wherein the textual values that belong are cluster values; computer readable program code configured to pass the cluster values for each cluster to a reference table; computer readable program code configured to store the cluster values for each cluster in the reference table for future access; and computer readable program code configured to, in response to a need for classification of a future set of textual values, access the reference table and lookup the future set of textual values in the reference table to determine whether any of the future set of textual values are cluster values. 10. The computer program product of claim 8 , wherein applying a similarity gauge to the textual values comprises: determining a Jaccard distance score among the textual values of each cluster.
| 0.542948 |
19. A non-transitory computer-readable medium comprising computer program instructions, wherein the computer program instructions are executable by a computer processor to perform a method comprising: (A) obtaining, from a user, first data representing a first part of a sentence, wherein the first part of the sentence comprises a first one of a subject, a predicate, and an object; (B) obtaining, from the user, second data representing a second part of the sentence, wherein the second part of the sentence comprises a second one of the subject, the predicate, and the object; (C) identifying a synonym of the first part of the sentence; (D) identifying a synonym of the second part of the sentence; (E) forming a first query from the synonym of the first part of the sentence and the synonym of the second part of the sentence, comprising: (E)(1) selecting a first form for the first query, wherein the first form specifies a first one of the following sequences: subject, predicate, object; subject, predicate; subject, object; predicate, object; (E)(2) forming the first query in the first form the forming comprising: (E)(2)(a) if the first form specifies the sequence subject, predicate, object, then forming the first query to include a subject followed by a predicate followed by an object, wherein the subject, predicate, and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; (E)(2)(b) if the first form specifies the sequence subject, predicate, then forming the first query to include a subject followed by a predicate, wherein the subject and predicate are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; (E)(2)(c) if the first form specifies the sequence subject, object, then forming the first query to include a subject followed by an object, wherein the subject and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; and (E)(2)(d) if the first form specifies the sequence predicate, object, then forming the first query to include a predicate followed by an object, wherein the predicate and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; and (F) searching a dataset in memory using the first query to identify a first subset of the dataset; (G) providing, to the user, executed by the computer processor, output representing the subset of the dataset wherein the sentence differs from the first query.
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19. A non-transitory computer-readable medium comprising computer program instructions, wherein the computer program instructions are executable by a computer processor to perform a method comprising: (A) obtaining, from a user, first data representing a first part of a sentence, wherein the first part of the sentence comprises a first one of a subject, a predicate, and an object; (B) obtaining, from the user, second data representing a second part of the sentence, wherein the second part of the sentence comprises a second one of the subject, the predicate, and the object; (C) identifying a synonym of the first part of the sentence; (D) identifying a synonym of the second part of the sentence; (E) forming a first query from the synonym of the first part of the sentence and the synonym of the second part of the sentence, comprising: (E)(1) selecting a first form for the first query, wherein the first form specifies a first one of the following sequences: subject, predicate, object; subject, predicate; subject, object; predicate, object; (E)(2) forming the first query in the first form the forming comprising: (E)(2)(a) if the first form specifies the sequence subject, predicate, object, then forming the first query to include a subject followed by a predicate followed by an object, wherein the subject, predicate, and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; (E)(2)(b) if the first form specifies the sequence subject, predicate, then forming the first query to include a subject followed by a predicate, wherein the subject and predicate are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; (E)(2)(c) if the first form specifies the sequence subject, object, then forming the first query to include a subject followed by an object, wherein the subject and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; and (E)(2)(d) if the first form specifies the sequence predicate, object, then forming the first query to include a predicate followed by an object, wherein the predicate and object are selected from the first part of the sentence, the second part of the sentence, the synonym of the first part of the sentence, and the synonym of the second part of the sentence; and (F) searching a dataset in memory using the first query to identify a first subset of the dataset; (G) providing, to the user, executed by the computer processor, output representing the subset of the dataset wherein the sentence differs from the first query. 30. The non-transitory computer-readable medium of claim 19 , wherein the first part of the sentence comprises the subject, and wherein the second part of the sentence comprises the object.
| 0.57017 |
2. The method of claim 1 , wherein the querying further comprises: marking the item type if the querying returns zero instances of the item type and if no other item type is marked.
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2. The method of claim 1 , wherein the querying further comprises: marking the item type if the querying returns zero instances of the item type and if no other item type is marked. 3. The method of claim 2 , further comprising: ceasing the querying and the associating if the item type is already marked.
| 0.934183 |
9. The method of claim 1 , wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device.
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9. The method of claim 1 , wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device. 10. The method of claim 9 , wherein the input constrained device has a plurality of overloaded keys, each of the overloaded keys representing two or more characters.
| 0.962289 |
1. A method in a computer system for, in a representation of one or more dictionaries comprising a plurality of text segments, characterizing the sense of an occurrence of a polysemous word, the method comprising the steps of: selecting a plurality of dictionary text segments each containing a first word; identifying among the selected dictionary text segments a first occurrence of a second word, the first occurrence of the second word having no word sense characterization; identifying among the selected dictionary text segments a second occurrence of the second word, the second occurrence of the second word having a word sense characterization; and attributing to the first occurrence of the second word the word sense characterization of the second occurrence of the second word.
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1. A method in a computer system for, in a representation of one or more dictionaries comprising a plurality of text segments, characterizing the sense of an occurrence of a polysemous word, the method comprising the steps of: selecting a plurality of dictionary text segments each containing a first word; identifying among the selected dictionary text segments a first occurrence of a second word, the first occurrence of the second word having no word sense characterization; identifying among the selected dictionary text segments a second occurrence of the second word, the second occurrence of the second word having a word sense characterization; and attributing to the first occurrence of the second word the word sense characterization of the second occurrence of the second word. 6. The method of claim 1 wherein the attributing step is only performed where the identified occurrences of the second word share the same part of speech.
| 0.745655 |
18. An apparatus for assessing reputability of email, comprising: a memory configured to store at least some hierarchical domains that include a first domain level and a second sub-domain level of the first domain level, wherein at least some of the first and second domain levels of the same hierarchical domains have different associated reputability values; and a processing device configured to access the memory to derive a first lower reputability value for a domain when a reputability value for a sub-domain level of the domain is not found in the memory and to derive a second higher reputability value for the domain when a reputability value for the sub-domain level of the domain is found in the memory, wherein the processing device is configured to: determine whether the first domain level in one of the hierarchical domains matches a domain for assessment; use a first reputability value associated with the first domain level for deriving a reputability score when the first domain level matches the domain; determine whether a second sub-domain level of the first domain level matches the domain; and use a second reputability value associated with the second sub-domain level associated with a higher reputability than the first reputability value for deriving the reputability score when the second sub-domain level matches the domain for assessment.
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18. An apparatus for assessing reputability of email, comprising: a memory configured to store at least some hierarchical domains that include a first domain level and a second sub-domain level of the first domain level, wherein at least some of the first and second domain levels of the same hierarchical domains have different associated reputability values; and a processing device configured to access the memory to derive a first lower reputability value for a domain when a reputability value for a sub-domain level of the domain is not found in the memory and to derive a second higher reputability value for the domain when a reputability value for the sub-domain level of the domain is found in the memory, wherein the processing device is configured to: determine whether the first domain level in one of the hierarchical domains matches a domain for assessment; use a first reputability value associated with the first domain level for deriving a reputability score when the first domain level matches the domain; determine whether a second sub-domain level of the first domain level matches the domain; and use a second reputability value associated with the second sub-domain level associated with a higher reputability than the first reputability value for deriving the reputability score when the second sub-domain level matches the domain for assessment. 20. The apparatus according to claim 18 , wherein the processing device is configured, for at least some of the hierarchical domains, to increase the reputability score for each additional sub-domain level for the same hierarchical domains found in the memory.
| 0.635342 |
19. A method for analyzing electronic customer communication data, generating behavioral assessment data and generating a responsive communication, which method comprises: receiving, by a server, electronic customer communication data of two or more types, wherein the server is configured to provide a user interface comprising a web site, web portal, or virtual portal, and wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; identifying a customer associated with the electronic customer communication data received by the server; aggregating electronic customer communication data from one or more sources based on identification of the customer from the electronic customer communication data; analyzing the aggregated electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; generating behavioral assessment data by the contact center based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; generating a responsive communication based on the generated behavioral assessment data; and providing the responsive communication via the user interface.
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19. A method for analyzing electronic customer communication data, generating behavioral assessment data and generating a responsive communication, which method comprises: receiving, by a server, electronic customer communication data of two or more types, wherein the server is configured to provide a user interface comprising a web site, web portal, or virtual portal, and wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; identifying a customer associated with the electronic customer communication data received by the server; aggregating electronic customer communication data from one or more sources based on identification of the customer from the electronic customer communication data; analyzing the aggregated electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; generating behavioral assessment data by the contact center based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; generating a responsive communication based on the generated behavioral assessment data; and providing the responsive communication via the user interface. 20. The method of claim 19 , wherein the server is a third-party server configured to send and receive communications.
| 0.713602 |
20. The system of claim 18 , wherein the at least one processor is further caused to: identify a plurality of views of the application based on the traversed view hierarchy, wherein each of the plurality of views contains at least one of the plurality of components of the application; generate at least one component reference table for the application, the at least one component reference table including, for each of the plurality of views, the at least one component of the application contained in the view; and store the at least one component reference table generated for the application.
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20. The system of claim 18 , wherein the at least one processor is further caused to: identify a plurality of views of the application based on the traversed view hierarchy, wherein each of the plurality of views contains at least one of the plurality of components of the application; generate at least one component reference table for the application, the at least one component reference table including, for each of the plurality of views, the at least one component of the application contained in the view; and store the at least one component reference table generated for the application. 21. The system of claim 20 , wherein the at least one processor is further caused to: map the at least one component contained in each of the plurality of views included in the at least one component reference table to the application running on the user device.
| 0.844773 |
1. A method comprising, by a computing device: receiving, from a client device of a first user of an online social network, an unstructured text query comprising an ambiguous n-gram, the online social network being associated with a plurality of objects; identifying one or more objects corresponding to the ambiguous n-gram based on a calculated probability that the n-gram correspond to the identified objects; generating a first set of structured queries, each structured query from the first set of structured queries corresponding to an identified object, the structured query comprising a reference to the corresponding identified object; receiving, from the client device of the first user, a selection of a structured query corresponding to a first object of the identified objects; and generating a second set of structured queries, each structured query of the second set of structured queries comprising a reference to the first object.
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1. A method comprising, by a computing device: receiving, from a client device of a first user of an online social network, an unstructured text query comprising an ambiguous n-gram, the online social network being associated with a plurality of objects; identifying one or more objects corresponding to the ambiguous n-gram based on a calculated probability that the n-gram correspond to the identified objects; generating a first set of structured queries, each structured query from the first set of structured queries corresponding to an identified object, the structured query comprising a reference to the corresponding identified object; receiving, from the client device of the first user, a selection of a structured query corresponding to a first object of the identified objects; and generating a second set of structured queries, each structured query of the second set of structured queries comprising a reference to the first object. 13. The method of claim 1 , further comprising receiving from the first user a selection of a second structured query from the second set of structured queries.
| 0.618665 |
6. The system of claim 1 , wherein the user comment information includes targeted comment information conveying one or more targeted comments for the panoramic segment, the targeted comment information including a targeted time indication that identifies a point in time in the segment duration of the panoramic content segment associated with a targeted comment and a targeted location indication that identifies a viewing angle within the panorama of the panoramic content segment associated with the targeted comment.
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6. The system of claim 1 , wherein the user comment information includes targeted comment information conveying one or more targeted comments for the panoramic segment, the targeted comment information including a targeted time indication that identifies a point in time in the segment duration of the panoramic content segment associated with a targeted comment and a targeted location indication that identifies a viewing angle within the panorama of the panoramic content segment associated with the targeted comment. 7. The system of claim 6 , wherein the one or more processors are further configured by machine readable instructions to: identify the targeted comment from the user comments conveyed by the user comment information, wherein the targeted comment is identified based on a represented source of the targeted comment and/or content included in the targeted comment; determine, for a target window of time, whether the viewing angle associated with the targeted comment is located within or outside the one or more visible ranges of viewing angles selected by the user; and generate, responsive to a determination that, for the target window of time, the viewing angle associated with the targeted comment is located outside the one or more visible ranges of viewing angles selected by the user during the target window of time, the alert information indicating the targeted comment is located outside the current field of view selected by the user such that the notification is based on the alert information indicating the targeted comment is outside the current field of view.
| 0.808928 |
27. A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by at least a processor of a computing device, perform the method comprising: receiving, over a network, a user context query from a user, wherein the user context query is formatted as a parameter of a uniform resource locator (URL) and comprises at least one user context criteria; formulating a network data query based on the at least one user context criteria, said formulating comprises configuring the network data query based on user data relating to the querying user corresponding to a context of most interest to the user; identifying at least one entry from a plurality of entries in a context query bid database that relates to the at least one user context criteria based on the formulated network data query, wherein each of the plurality of entries comprises at least one bid context criteria, a bid amount, an identification of an advertiser, and an identification of at least one advertisement; selecting one of the identified at least one of the plurality of entries on the context query bid database, wherein the selected one of the plurality of entries on the context query bid database has the highest bid amount; retrieving, over the network, at least one entry from an advertisement database such that an identification of an advertiser and an identification of an advertisement on the at least one entry from the advertisement database matches the identification of the advertiser and the identification of the at least one advertisement on the selected one of the plurality of entries on the context query bid database, wherein each entry on the advertisement database comprises an identification of an advertiser, an identification of an advertisement, and at least one advertisement data object; and generating a dynamic webpage having content relating to the user context query.
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27. A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by at least a processor of a computing device, perform the method comprising: receiving, over a network, a user context query from a user, wherein the user context query is formatted as a parameter of a uniform resource locator (URL) and comprises at least one user context criteria; formulating a network data query based on the at least one user context criteria, said formulating comprises configuring the network data query based on user data relating to the querying user corresponding to a context of most interest to the user; identifying at least one entry from a plurality of entries in a context query bid database that relates to the at least one user context criteria based on the formulated network data query, wherein each of the plurality of entries comprises at least one bid context criteria, a bid amount, an identification of an advertiser, and an identification of at least one advertisement; selecting one of the identified at least one of the plurality of entries on the context query bid database, wherein the selected one of the plurality of entries on the context query bid database has the highest bid amount; retrieving, over the network, at least one entry from an advertisement database such that an identification of an advertiser and an identification of an advertisement on the at least one entry from the advertisement database matches the identification of the advertiser and the identification of the at least one advertisement on the selected one of the plurality of entries on the context query bid database, wherein each entry on the advertisement database comprises an identification of an advertiser, an identification of an advertisement, and at least one advertisement data object; and generating a dynamic webpage having content relating to the user context query. 39. The non-transitory computer-readable storage medium of claim 27 , wherein said formulating the network data query based on the at least one user context criteria so as to identify at least one entry in a context query bid database that relates to the at least one user context criteria comprises: searching for user profile data, social network data, spatial data, temporal data, topical data and context query bid data that is available via the network and relates to the context.
| 0.664283 |
9. The method of claim 1 , wherein calculating the word spacing associated with each column comprises: creating a histogram of spaces between consecutive components of the plurality of components associated with each column; identifying a frequently occurring space from the histogram, wherein the frequently occurring space is within a threshold range determined by the line height; and computing the word spacing based on the frequently occurring space.
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9. The method of claim 1 , wherein calculating the word spacing associated with each column comprises: creating a histogram of spaces between consecutive components of the plurality of components associated with each column; identifying a frequently occurring space from the histogram, wherein the frequently occurring space is within a threshold range determined by the line height; and computing the word spacing based on the frequently occurring space. 10. The method of claim 9 , wherein the consecutive components comprise at least one of vertically overlapping components and components separated by a predefined distance, wherein the vertically overlapping components share at least one coordinate along a vertical axis.
| 0.922686 |
17. A translation system comprising: a device; an automatic translator module executable and stored on the device and configured to automatically convert a capitalized source text to lower case text and translate the lower case text to a target text; an aligner configured to determine an alignment between one or more phrases in the capitalized source text and one or more respective phrases in the target text of a capitalization configuration; and a capitalization module configured to recover a capitalized text from the target text according to capitalization information in the capitalized source text and the target text and the alignment determined by the aligner, and to capitalize the target text, the capitalization of the target text including: generating a plurality of capitalization configurations for the target text; for each capitalization configuration, computing a feature probability for each of a plurality of capitalization model feature functions; associating a feature weight with each capitalization model feature function; applying the associated feature weight to the respective computed feature probability for each of the plurality of capitalization model feature functions; for each capitalization configuration, calculating a capitalization configuration probability based on a weighted sum of the computed feature probabilities and applied feature weights, and based on the alignment between the one or more phrases in the capitalized source text and the one or more phrases in the target text or between the capitalized source text and the capitalization configuration; assigning the calculated capitalization configuration probability to each respective capitalization configuration; and selecting the best capitalization configuration from the plurality of capitalization configurations based on the highest calculated capitalization configuration probability.
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17. A translation system comprising: a device; an automatic translator module executable and stored on the device and configured to automatically convert a capitalized source text to lower case text and translate the lower case text to a target text; an aligner configured to determine an alignment between one or more phrases in the capitalized source text and one or more respective phrases in the target text of a capitalization configuration; and a capitalization module configured to recover a capitalized text from the target text according to capitalization information in the capitalized source text and the target text and the alignment determined by the aligner, and to capitalize the target text, the capitalization of the target text including: generating a plurality of capitalization configurations for the target text; for each capitalization configuration, computing a feature probability for each of a plurality of capitalization model feature functions; associating a feature weight with each capitalization model feature function; applying the associated feature weight to the respective computed feature probability for each of the plurality of capitalization model feature functions; for each capitalization configuration, calculating a capitalization configuration probability based on a weighted sum of the computed feature probabilities and applied feature weights, and based on the alignment between the one or more phrases in the capitalized source text and the one or more phrases in the target text or between the capitalized source text and the capitalization configuration; assigning the calculated capitalization configuration probability to each respective capitalization configuration; and selecting the best capitalization configuration from the plurality of capitalization configurations based on the highest calculated capitalization configuration probability. 22. The translation system of claim 17 wherein the capitalization module further includes an initial position model feature function.
| 0.501732 |
1. A computer method comprises: receiving a query from a user system; generating a query string that substantially matches characters of the query; searching a plurality of data objects of a first type for data objects of the first type that substantially match the query wherein i) each data object of the first type is associated with at least one data object of a second type, ii) each data object of the first type includes a query, and iii) each data object of the second type includes an answer to a query; generating a first-relevance score for each data object of the second type that is associated with at least one of the data objects of the first type that was identified in the searching step; searching a plurality of data objects of the second type for data objects of the second type that substantially match the query string; generating a second-relevance score for each data object of the second type that substantially matches the query; generating a list of data objects of the second type that are identified in the search of the data objects of the first type and that are identified in the search of the data objects of the second type; ranking the data objects of the second type in the list of data objects based on the first and second relevance scores; and transferring the list of data objects to the user system.
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1. A computer method comprises: receiving a query from a user system; generating a query string that substantially matches characters of the query; searching a plurality of data objects of a first type for data objects of the first type that substantially match the query wherein i) each data object of the first type is associated with at least one data object of a second type, ii) each data object of the first type includes a query, and iii) each data object of the second type includes an answer to a query; generating a first-relevance score for each data object of the second type that is associated with at least one of the data objects of the first type that was identified in the searching step; searching a plurality of data objects of the second type for data objects of the second type that substantially match the query string; generating a second-relevance score for each data object of the second type that substantially matches the query; generating a list of data objects of the second type that are identified in the search of the data objects of the first type and that are identified in the search of the data objects of the second type; ranking the data objects of the second type in the list of data objects based on the first and second relevance scores; and transferring the list of data objects to the user system. 2. The method of claim 1 , wherein the data objects of the first type are case objects.
| 0.612875 |
1. A method comprising: under control of one or more computing devices comprising one or more processors, classifying, by a VAD module, a plurality of frames of a media file into one or more speech frames and one or more non-speech frames; receiving feedback associated with the one or more speech frames and the one or more non-speech frames, the feedback including a determination of accuracy of classifying one or more frames of the media file that are located at a predetermined time before the plurality of frames of the media file or that are selected based on a predetermined condition, the feedback being generated by a speech recognizer, the VAD module and the speech recognizer processing the media file asynchronously; and utilizing the feedback to update a model to be used for voice activity detection (VAD) of a plurality of frames of the media file yet to be processed.
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1. A method comprising: under control of one or more computing devices comprising one or more processors, classifying, by a VAD module, a plurality of frames of a media file into one or more speech frames and one or more non-speech frames; receiving feedback associated with the one or more speech frames and the one or more non-speech frames, the feedback including a determination of accuracy of classifying one or more frames of the media file that are located at a predetermined time before the plurality of frames of the media file or that are selected based on a predetermined condition, the feedback being generated by a speech recognizer, the VAD module and the speech recognizer processing the media file asynchronously; and utilizing the feedback to update a model to be used for voice activity detection (VAD) of a plurality of frames of the media file yet to be processed. 2. A method as recited in claim 1 , wherein the classifying includes identifying whether each of the plurality of frames of the media file includes speech or non-speech.
| 0.523176 |
1. A computer-executed method for displaying social interest in television programs, the method comprising: storing a plurality of social media content items received from an external social networking system; selecting a plurality of television programs, each television program associated with one of a series of chronological time segments of television; for each selected television program: determining that a subset of the social media content items is relevant to the television program, storing the subset of the social media content items relevant to the television program, and determining a level of social interest in the television program based on the subset of the social media content items determined to be relevant to the television program; for each of the time segments, determining a level of social interest in the time segment based upon an aggregate level of social interest in the television programs associated with the time segment; and graphically displaying at least one time segment and the determined level of social interest for each displayed time segment.
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1. A computer-executed method for displaying social interest in television programs, the method comprising: storing a plurality of social media content items received from an external social networking system; selecting a plurality of television programs, each television program associated with one of a series of chronological time segments of television; for each selected television program: determining that a subset of the social media content items is relevant to the television program, storing the subset of the social media content items relevant to the television program, and determining a level of social interest in the television program based on the subset of the social media content items determined to be relevant to the television program; for each of the time segments, determining a level of social interest in the time segment based upon an aggregate level of social interest in the television programs associated with the time segment; and graphically displaying at least one time segment and the determined level of social interest for each displayed time segment. 9. The computer-executed method of claim 1 , wherein graphically displaying at least one time segment comprises displaying a first portion of the time segment corresponding to positive sentiment that is visually distinguished from a second portion of the time segment corresponding to negative sentiment.
| 0.730275 |
19. A computer-implemented method of establishing an interaction language for a user interface of a display, comprising: providing, on the user interface, non-language elements prompting the user to provide a first response; determining a language for the user based on the first response provided by the user; prompting, in the determined language, the user to provide a second response; determining a sub-language of the determined language based on the second response provided by the user.
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19. A computer-implemented method of establishing an interaction language for a user interface of a display, comprising: providing, on the user interface, non-language elements prompting the user to provide a first response; determining a language for the user based on the first response provided by the user; prompting, in the determined language, the user to provide a second response; determining a sub-language of the determined language based on the second response provided by the user. 21. The method of claim 19 , wherein the prompting the user to provide the second response includes prompting the user to say a specific word and the second response received from the user includes the specific word as a speech input, and wherein the determining the sub-language includes determining a regional variant of the determined language based on a pronunciation of the specified word as the speech input.
| 0.5 |
24. An apparatus for reproducing text subtitle streams, the apparatus comprising: a decoder configured to decode the at least one text subtitle stream received from an external source, each text subtitle stream including text data to be displayed within a region of a display screen, first information specifying a global style of the region, and second information specifying a local style for a portion of the text data; and a controller configured to read a playlist including at least one playitem and first and second subplayitems, the playitem specifying a time based playing interval from an in-time until an out-time associated with at least one audio/video stream, the first subplayitem specifying a time based playing interval from an in-time until an out-time associated with the at least one text subtitle stream, the first subplayitem for a reproducing of the text subtitle stream being synchronized with the playitem, the second subplayitem for a reproduction of browsable slideshow being not synchronized with the playitem and to control the decoder to decode the text subtitle stream using the first information and the second information.
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24. An apparatus for reproducing text subtitle streams, the apparatus comprising: a decoder configured to decode the at least one text subtitle stream received from an external source, each text subtitle stream including text data to be displayed within a region of a display screen, first information specifying a global style of the region, and second information specifying a local style for a portion of the text data; and a controller configured to read a playlist including at least one playitem and first and second subplayitems, the playitem specifying a time based playing interval from an in-time until an out-time associated with at least one audio/video stream, the first subplayitem specifying a time based playing interval from an in-time until an out-time associated with the at least one text subtitle stream, the first subplayitem for a reproducing of the text subtitle stream being synchronized with the playitem, the second subplayitem for a reproduction of browsable slideshow being not synchronized with the playitem and to control the decoder to decode the text subtitle stream using the first information and the second information. 25. The apparatus of claim 24 , wherein the global style comprises a plurality of display properties including font-related display properties required for displaying the text data, and the local style comprises at least one of the font-related display properties applied for the portion of the text data.
| 0.517765 |
11. A non-transitory computer-readable medium storing computer software instructions executable by a computer system including one or more computers to perform operations comprising: obtaining a first set of test values, a second set of test values, and a third set of test values; receiving text comprising characters represented as code point values, the characters identified as being in a first encoding format, each code point value representing one character in the text; and making a determination that the text likely includes characters incorrectly converted from a second encoding format to the first encoding format, wherein making the determination includes (i) determining for a sequence of code point values consisting of a first code point value followed by a second code point value that the first code point value is in the first set of test values and that the second code point value is in the second set of test values, or (ii) determining for a sequence of code point values consisting of a first code point value followed by a second code point value followed by a third code point value that the first code point value is in the third set of test values, that the second code point value is in the second set of test values, and that the third code point value is in the second set of test values.
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11. A non-transitory computer-readable medium storing computer software instructions executable by a computer system including one or more computers to perform operations comprising: obtaining a first set of test values, a second set of test values, and a third set of test values; receiving text comprising characters represented as code point values, the characters identified as being in a first encoding format, each code point value representing one character in the text; and making a determination that the text likely includes characters incorrectly converted from a second encoding format to the first encoding format, wherein making the determination includes (i) determining for a sequence of code point values consisting of a first code point value followed by a second code point value that the first code point value is in the first set of test values and that the second code point value is in the second set of test values, or (ii) determining for a sequence of code point values consisting of a first code point value followed by a second code point value followed by a third code point value that the first code point value is in the third set of test values, that the second code point value is in the second set of test values, and that the third code point value is in the second set of test values. 16. The non-transitory computer-readable medium of claim 11 , wherein the second set of test values matches a bit mask having a format 10xx xxxx, and includes hexadecimal values in Win-1252 encoding format, wherein hexadecimal values 8, 9, A, or B matches a first half-byte of the bit mask and one of hexadecimal values 0-F matches a second half-byte of the bit mask.
| 0.503911 |
1. A system, comprising: a processor configured to: determine a topic based on a user demand, wherein determining the topic comprises: determine frequencies of phrases based on an analysis of a search query log from a web site, a search query log from a search engine, or a combination thereof; compare the frequencies of the phrases to a predetermined threshold; determine at least one theme based on phrases having frequencies exceeding the predetermined threshold; sort the at least one theme based on common words in the phrases; cluster the at least one theme; and determine the topic based on the clustered at least one theme; automatically generate content for the topic, wherein the content is configured or organized differently than on other web pages of the web site; and select the content that is contextually relevant for display within a corpus of content, wherein the corpus of content includes a web site, a user's social networking web page, content customized for mobile devices, content customized based on location awareness, or an electronic mail message; and a memory coupled to the processor and configured to provide the processor with instructions.
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1. A system, comprising: a processor configured to: determine a topic based on a user demand, wherein determining the topic comprises: determine frequencies of phrases based on an analysis of a search query log from a web site, a search query log from a search engine, or a combination thereof; compare the frequencies of the phrases to a predetermined threshold; determine at least one theme based on phrases having frequencies exceeding the predetermined threshold; sort the at least one theme based on common words in the phrases; cluster the at least one theme; and determine the topic based on the clustered at least one theme; automatically generate content for the topic, wherein the content is configured or organized differently than on other web pages of the web site; and select the content that is contextually relevant for display within a corpus of content, wherein the corpus of content includes a web site, a user's social networking web page, content customized for mobile devices, content customized based on location awareness, or an electronic mail message; and a memory coupled to the processor and configured to provide the processor with instructions. 2. The system recited in claim 1 , wherein the content is optimized for the topic.
| 0.922139 |
8. A method, comprising: at an electronic device with a display and a touch-sensitive surface: concurrently displaying on the display a first text entry area, and an integrated input area, the integrated input area including: a left portion with a left side of a split keyboard with a first set of characters; a right portion with a right side of the split keyboard with a second set of characters; and a center portion in between the left portion and the right portion; detecting a first input on the touch-sensitive surface; in response to detecting the first input, entering a reconfiguration mode for the integrated input area; and, while in the reconfiguration mode for the integrated input area: detecting a second input by a first thumb and/or a second thumb; in response to detecting the second input, adjusting the size of at least one of the left side and the right side of the split keyboard in the integrated input area, maintaining the first set of characters in the left side of the split keyboard, and maintaining the second set of characters in the right side of the split keyboard; detecting a third input; and, in response to detecting the third input, exiting the reconfiguration mode for the integrated input area.
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8. A method, comprising: at an electronic device with a display and a touch-sensitive surface: concurrently displaying on the display a first text entry area, and an integrated input area, the integrated input area including: a left portion with a left side of a split keyboard with a first set of characters; a right portion with a right side of the split keyboard with a second set of characters; and a center portion in between the left portion and the right portion; detecting a first input on the touch-sensitive surface; in response to detecting the first input, entering a reconfiguration mode for the integrated input area; and, while in the reconfiguration mode for the integrated input area: detecting a second input by a first thumb and/or a second thumb; in response to detecting the second input, adjusting the size of at least one of the left side and the right side of the split keyboard in the integrated input area, maintaining the first set of characters in the left side of the split keyboard, and maintaining the second set of characters in the right side of the split keyboard; detecting a third input; and, in response to detecting the third input, exiting the reconfiguration mode for the integrated input area. 14. The method of claim 8 , wherein the second input includes a horizontal movement of the first thumb away from a vertical side of the display closest to the first thumb; and the method includes: in response to detecting the horizontal movement of the first thumb away from the vertical side of the display closest to the first thumb, increasing the size of the left side and the right side of the split keyboard.
| 0.682722 |
1. An apparatus for inputting characters/numerals for a communication terminal provided with a touch screen keyboard on a touch part, through which designation of coordinates or selection of characters can be performed using a finger or a tool for communications with an outside or data storage, the apparatus comprising: a block body positioned in the touch screen keyboard for generating a manipulation signal of a stationary block in accordance with a block manipulation of a user who desires a character/numeral input or a moving manipulation in at least four directions based on a center of a user, the block body including a plurality of blocks and a plurality of closed sectors of the stationary block positioned in at least four directions, in which the block body is moved, being allocated with consonants, vowels, numerals, symbols, and function keys by languages including Hangeul, Roman characters, and Japanese; a character storage unit storing character data by languages used in the character input apparatus; a program memory storing an inner operating program of the communication terminal; a code storage unit storing code data corresponding to the blocks provided on the block body and the stationary block positioned on an outside of the block body; a block manipulation recognition unit detecting a touch manipulation state of each block provided on the block body; a stationary block recognition unit detecting a manipulation state of the stationary block in accordance with a moving manipulation of the block body in at least four directions; a microprocessor judging of which language a user inputs a phoneme with reference to the character data stored in the character storage unit in accordance with the operating program stored in the program memory when a touch manipulation state detection signal is inputted through the block or stationary block manipulation recognition unit, and generating and outputting a display control signal for displaying phonemes of the corresponding language inputted by the user with reference to the code data stored in the code storage unit; a display drive unit outputting a drive control signal for displaying the character and numeral selected by the user through manipulation of the stationary block in accordance with the moving manipulation of the block body or the block on the block body, in accordance with the display control signal outputted from the microprocessor; and a display unit displaying the character and the numeral in accordance with the drive control signal outputted from the display drive unit; wherein the stationary block and the block body are logically implemented and are displayed on the touch part of the touch screen.
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1. An apparatus for inputting characters/numerals for a communication terminal provided with a touch screen keyboard on a touch part, through which designation of coordinates or selection of characters can be performed using a finger or a tool for communications with an outside or data storage, the apparatus comprising: a block body positioned in the touch screen keyboard for generating a manipulation signal of a stationary block in accordance with a block manipulation of a user who desires a character/numeral input or a moving manipulation in at least four directions based on a center of a user, the block body including a plurality of blocks and a plurality of closed sectors of the stationary block positioned in at least four directions, in which the block body is moved, being allocated with consonants, vowels, numerals, symbols, and function keys by languages including Hangeul, Roman characters, and Japanese; a character storage unit storing character data by languages used in the character input apparatus; a program memory storing an inner operating program of the communication terminal; a code storage unit storing code data corresponding to the blocks provided on the block body and the stationary block positioned on an outside of the block body; a block manipulation recognition unit detecting a touch manipulation state of each block provided on the block body; a stationary block recognition unit detecting a manipulation state of the stationary block in accordance with a moving manipulation of the block body in at least four directions; a microprocessor judging of which language a user inputs a phoneme with reference to the character data stored in the character storage unit in accordance with the operating program stored in the program memory when a touch manipulation state detection signal is inputted through the block or stationary block manipulation recognition unit, and generating and outputting a display control signal for displaying phonemes of the corresponding language inputted by the user with reference to the code data stored in the code storage unit; a display drive unit outputting a drive control signal for displaying the character and numeral selected by the user through manipulation of the stationary block in accordance with the moving manipulation of the block body or the block on the block body, in accordance with the display control signal outputted from the microprocessor; and a display unit displaying the character and the numeral in accordance with the drive control signal outputted from the display drive unit; wherein the stationary block and the block body are logically implemented and are displayed on the touch part of the touch screen. 12. The apparatus of claim 1 , wherein if the block body is a Japanese block body, -dan characters of each gyo of Japanese are allocated to each block provided on the block body, and characters dan, dan, dan, dan and a conversion function symbol are allocated to the stationary block in at least four directions, in which the block body is movable.
| 0.792545 |
11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving data specifying a new voice action submitted by an application developer, the data identifying (i) an application, and (ii) a voice command trigger term; validating the received data; generating a data structure instance that specifies (i) the application, (ii) the voice command trigger term, and (iii) one or more alternate voice command trigger terms that are each determined based at least on the voice command trigger term; after generating the data structure instance enabling triggering of the new voice action by a spoken utterance based at least on storing the data structure instance at a database that comprises one or more other data structure instances, wherein one or more of the other data structure instances specify (i) an application, and (ii) one or more voice command trigger terms that includes at least one voice command trigger term that is determined based at least on another voice command trigger term in the same data structure instance; after enabling triggering of the new voice action by a spoken utterance and based at least on determining that a transcription of a spoken utterance includes a particular one of the alternate voice command trigger terms that are each determined based at least on the voice command trigger term, selecting a particular data structure instance from the database that specifies the particular one of the alternate voice command trigger terms that are each determined based at least on the voice command trigger term; and identifying a particular application that is specified by the particular data structure instance.
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11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving data specifying a new voice action submitted by an application developer, the data identifying (i) an application, and (ii) a voice command trigger term; validating the received data; generating a data structure instance that specifies (i) the application, (ii) the voice command trigger term, and (iii) one or more alternate voice command trigger terms that are each determined based at least on the voice command trigger term; after generating the data structure instance enabling triggering of the new voice action by a spoken utterance based at least on storing the data structure instance at a database that comprises one or more other data structure instances, wherein one or more of the other data structure instances specify (i) an application, and (ii) one or more voice command trigger terms that includes at least one voice command trigger term that is determined based at least on another voice command trigger term in the same data structure instance; after enabling triggering of the new voice action by a spoken utterance and based at least on determining that a transcription of a spoken utterance includes a particular one of the alternate voice command trigger terms that are each determined based at least on the voice command trigger term, selecting a particular data structure instance from the database that specifies the particular one of the alternate voice command trigger terms that are each determined based at least on the voice command trigger term; and identifying a particular application that is specified by the particular data structure instance. 13. The system of claim 11 , wherein generating the data structure instance that specifies (i) the application, (ii) the voice command trigger term, and (iii) the one or more alternate voice command trigger terms that are each determined based at least on the voice command trigger term comprises: translating the received data to a different data format.
| 0.631794 |
6. The method of claim 1 , further comprising: receiving a second query that includes a second date-qualified query term; inspecting the second query to determine that the second query includes a date; and in response to determining that the second query includes a date, establishing the second query as not being a date-qualified query.
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6. The method of claim 1 , further comprising: receiving a second query that includes a second date-qualified query term; inspecting the second query to determine that the second query includes a date; and in response to determining that the second query includes a date, establishing the second query as not being a date-qualified query. 7. The method of claim 6 further comprising generating results for the second query without regard to dates contained in queries, which included the second date-qualified query term, that were previously received by the search engine.
| 0.856339 |
31. A non-transitory computer-readable medium having stored thereon instructions which, when executed by a device with a touch-sensitive surface and a display, cause the device to: display text of an electronic document on the display; display an insertion marker at a first position in the text of the electronic document, the text around the first position having a visual appearance; detecting a first input at a location on the touch-sensitive surface, the location on the touch-sensitive surface corresponding to a location on the display where the text of the electronic document is displayed other than the first position in the text and a second position in the text, wherein the first input is an input in a first direction; and in response to detecting the first input: in accordance with a determination that the first input in the first direction at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a first set of one or more predefined conditions: translate the electronic document on the display, and maintain the insertion marker at the first position in the text; and, in accordance with a determination that the first input in the first direction at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a second set of one or more predefined conditions that is distinct from the first set of one or more predefined conditions, the second set of one or more predefined conditions including a condition that the first input has a speed greater than a predefined threshold velocity: move the insertion marker in the text from the first position to the second position in the text, and maintain the visual appearance of the text around the first position in the text.
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31. A non-transitory computer-readable medium having stored thereon instructions which, when executed by a device with a touch-sensitive surface and a display, cause the device to: display text of an electronic document on the display; display an insertion marker at a first position in the text of the electronic document, the text around the first position having a visual appearance; detecting a first input at a location on the touch-sensitive surface, the location on the touch-sensitive surface corresponding to a location on the display where the text of the electronic document is displayed other than the first position in the text and a second position in the text, wherein the first input is an input in a first direction; and in response to detecting the first input: in accordance with a determination that the first input in the first direction at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a first set of one or more predefined conditions: translate the electronic document on the display, and maintain the insertion marker at the first position in the text; and, in accordance with a determination that the first input in the first direction at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a second set of one or more predefined conditions that is distinct from the first set of one or more predefined conditions, the second set of one or more predefined conditions including a condition that the first input has a speed greater than a predefined threshold velocity: move the insertion marker in the text from the first position to the second position in the text, and maintain the visual appearance of the text around the first position in the text. 36. The non-transitory computer-readable medium of claim 31 , wherein the first set of one or more predefined conditions comprises that the first input comprises movement of a contact in a first predefined direction.
| 0.771074 |
1. A computer-implemented method for addressing spelling errors comprising: establishing a phonetic database having a plurality of phonetically equivalent formulas stored therein, each of the phonetically equivalent formulas being associated with at least one respective pronounceable unit; receiving an initial search string from a user through a search interface; wherein the initial search string is in a particular language of the user's preference; determining, from the phonetic database, an alternative pronounceable unit that is specified, by a phonetically equivalent formula of the plurality of phonetically equivalent formulas from the phonetic database, to be phonetically similar to a particular pronounceable unit that is represented within the initial search string; generating an alternative search string, in the particular language, based at least in part on the initial search string and the alternative pronounceable unit; and performing at least one of: (a) searching a data set for data items that are associated with the alternative search string, and displaying at least one search result that was obtained through the searching, or (b) outputting the alternative search string; wherein generating the alternative search string comprises generating a search string that contains the initial search string but in which at least one instance of the particular pronounceable unit has been replaced in the initial search string by the alternative pronounceable unit; wherein the method is performed by one or more self improving phonetic search engines.
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1. A computer-implemented method for addressing spelling errors comprising: establishing a phonetic database having a plurality of phonetically equivalent formulas stored therein, each of the phonetically equivalent formulas being associated with at least one respective pronounceable unit; receiving an initial search string from a user through a search interface; wherein the initial search string is in a particular language of the user's preference; determining, from the phonetic database, an alternative pronounceable unit that is specified, by a phonetically equivalent formula of the plurality of phonetically equivalent formulas from the phonetic database, to be phonetically similar to a particular pronounceable unit that is represented within the initial search string; generating an alternative search string, in the particular language, based at least in part on the initial search string and the alternative pronounceable unit; and performing at least one of: (a) searching a data set for data items that are associated with the alternative search string, and displaying at least one search result that was obtained through the searching, or (b) outputting the alternative search string; wherein generating the alternative search string comprises generating a search string that contains the initial search string but in which at least one instance of the particular pronounceable unit has been replaced in the initial search string by the alternative pronounceable unit; wherein the method is performed by one or more self improving phonetic search engines. 8. The method of claim 1 , wherein determining the alternative pronounceable unit comprises (a) parsing the initial search string into one or more pronounceable units and (b) applying the plurality of phonetically equivalent formulas to the one or more pronounceable units to produce one or more alternative pronounceable units.
| 0.625114 |
9. The speech recognition system of claim 8 , wherein tuning the speech module comprises feeding a collection of utterances of the utterance type to the speech module.
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9. The speech recognition system of claim 8 , wherein tuning the speech module comprises feeding a collection of utterances of the utterance type to the speech module. 10. The speech recognition system of claim 9 , wherein the collection of utterances includes one or more pre-recorded utterances stored in a repository of recordings of utterances.
| 0.803541 |
1. A computing system comprising: a processor; and computer storage memory having computer-executable instructions stored thereon which, when executed by the processor, configure the computing system to facilitate presentation of search result items having varied prominence, the processor being operable, when executing the instructions, to: reference a search result item to be presented within a search results page in response to a search query; determine that a size prominence of the search result item is to be modified based on a click-through rate associated with the search result item exceeding a threshold value compared to click-through rates associated with one or more other search result items within the search results page, each of the search result item and the one or more other search result items being a different set of components displayed as a group adjacent to one another on the search results page; select a modified size prominence to which the size prominence is to be adjusted; and adjust the size of the search result item to the modified size prominence in accordance with the determination that the size prominence of the search result item is to be modified, the adjusting comprising increasing the vertical space allocation and a number of components of the search result item.
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1. A computing system comprising: a processor; and computer storage memory having computer-executable instructions stored thereon which, when executed by the processor, configure the computing system to facilitate presentation of search result items having varied prominence, the processor being operable, when executing the instructions, to: reference a search result item to be presented within a search results page in response to a search query; determine that a size prominence of the search result item is to be modified based on a click-through rate associated with the search result item exceeding a threshold value compared to click-through rates associated with one or more other search result items within the search results page, each of the search result item and the one or more other search result items being a different set of components displayed as a group adjacent to one another on the search results page; select a modified size prominence to which the size prominence is to be adjusted; and adjust the size of the search result item to the modified size prominence in accordance with the determination that the size prominence of the search result item is to be modified, the adjusting comprising increasing the vertical space allocation and a number of components of the search result item. 6. The system of claim 1 , wherein the determination to modify the size prominence dynamically occurs, without user intervention, upon submission of a search query.
| 0.876526 |
1. A method for encoding an audio signal, the method comprising: determining a spectral representation of the audio signal, the determining a spectral representation comprising determining modified discrete cosine transform, MDCT, coefficients; encoding the audio signal using the determined spectral representation; determining a pseudo spectrum from the MDCT coefficients, wherein determining the pseudo spectrum comprises, for a particular MDCT coefficient X m in a particular frequency bin m, determining a corresponding coefficient Y m of the pseudo spectrum as Y m = ( X m 2 + ( X m - 1 - X m + 1 ) 2 ) 1 2 , wherein X m−1 and X m+1 are MDCT coefficients in frequency bins m−1 and m+1, respectively, adjacent to the particular frequency bin m; classifying parts of the audio signal to be speech parts or non-speech parts based at least in part on the determined pseudo spectrum; and determining a loudness measure for the audio signal based on the speech parts.
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1. A method for encoding an audio signal, the method comprising: determining a spectral representation of the audio signal, the determining a spectral representation comprising determining modified discrete cosine transform, MDCT, coefficients; encoding the audio signal using the determined spectral representation; determining a pseudo spectrum from the MDCT coefficients, wherein determining the pseudo spectrum comprises, for a particular MDCT coefficient X m in a particular frequency bin m, determining a corresponding coefficient Y m of the pseudo spectrum as Y m = ( X m 2 + ( X m - 1 - X m + 1 ) 2 ) 1 2 , wherein X m−1 and X m+1 are MDCT coefficients in frequency bins m−1 and m+1, respectively, adjacent to the particular frequency bin m; classifying parts of the audio signal to be speech parts or non-speech parts based at least in part on the determined pseudo spectrum; and determining a loudness measure for the audio signal based on the speech parts. 4. The method of claim 1 , wherein the audio signal is a multi-channel signal, the method further comprising: downmixing the multi-channel audio signal and performing the classification step on the downmixed signal.
| 0.730673 |
1. A computer-system-implemented method for requesting desired information from a graph database, the method comprising: executing a query against the graph database storing a graph by providing, by a computer system separate from the graph database, the query and a first query header to a first shard of the graph database, wherein: the graph comprises nodes, edges between the nodes, and predicates to represent data; the query includes a subject, a predicate, and an object; and the first query header specifies the first shard; receiving first results and a first result header from the first shard in response to the query, wherein the first result header specifies that the first results are first partial results; and receiving second results and a second result header from a second shard of the graph database in response to the query, wherein the second result header specifies that the second results are second partial results, and wherein the second results and the second result header are received from the second shard without the computer system providing a corresponding query to the second shard; and wherein a combination of the first partial results and the second partial results provides a total result to the query that includes a subset of the graph.
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1. A computer-system-implemented method for requesting desired information from a graph database, the method comprising: executing a query against the graph database storing a graph by providing, by a computer system separate from the graph database, the query and a first query header to a first shard of the graph database, wherein: the graph comprises nodes, edges between the nodes, and predicates to represent data; the query includes a subject, a predicate, and an object; and the first query header specifies the first shard; receiving first results and a first result header from the first shard in response to the query, wherein the first result header specifies that the first results are first partial results; and receiving second results and a second result header from a second shard of the graph database in response to the query, wherein the second result header specifies that the second results are second partial results, and wherein the second results and the second result header are received from the second shard without the computer system providing a corresponding query to the second shard; and wherein a combination of the first partial results and the second partial results provides a total result to the query that includes a subset of the graph. 2. The method of claim 1 , wherein the method further comprises combining the first partial results and the second partial results to obtain the total result.
| 0.614848 |
1. A method for querying a distributed database system, the method comprising: parsing, by one or more processors, a query request; generating, by one or more processors, an access plan for the query request, wherein the access plan specifies therein a database table related to the query request, and wherein a copy of the database table is stored in multiple database devices; selecting, by one or more processors and based on status information of each copy of the database table, one copy of the database table from a plurality of copies of the database table as a target database table, wherein the status information of each of the plurality of copies of the database table comprises: consistent status information indicating whether a particular copy of the database table is consistent with other copies of the database table; availability status information indicating an availability of a particular copy of the database table; and load status information indicating workload of a database device in which a particular copy of the database table is stored; executing, by one or more processors, a query operation on the target database table according to the access plan; checking, by one or more processors, a consistent requirement of the query request; selecting, by one or more processors and based on the consistent status information of each of the plurality of copies, at least one copy of the database table whose consistent status information indicates that said at least one copy is consistent with other copies of the database table to form a first candidate copy set, wherein the first candidate copy set is selected in response to the consistent requirement of the query request being determined as having a consistency level that exceeds a first predefined level; selecting, by one or more processors, the plurality of copies to form a first candidate copy set without considering the consistent status information if the consistent requirement of the query request has a consistency level that is below a second predefined level; selecting from the first candidate copy set, by one or more processors and based on the availability status information of each copy of the database table in the first candidate copy set, at least one copy of the database table whose availability status information indicates that said at least one copy of the database table is available to form a second candidate copy set; and selecting from the second candidate copy set, by one or more processors and based on the load status information of each copy in the second candidate copy set, a copy of the database table, whose load status information indicates that the database device that stores the copy has a lowest workload compared to other database devices that are soring the copy of the database table, as the target database table.
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1. A method for querying a distributed database system, the method comprising: parsing, by one or more processors, a query request; generating, by one or more processors, an access plan for the query request, wherein the access plan specifies therein a database table related to the query request, and wherein a copy of the database table is stored in multiple database devices; selecting, by one or more processors and based on status information of each copy of the database table, one copy of the database table from a plurality of copies of the database table as a target database table, wherein the status information of each of the plurality of copies of the database table comprises: consistent status information indicating whether a particular copy of the database table is consistent with other copies of the database table; availability status information indicating an availability of a particular copy of the database table; and load status information indicating workload of a database device in which a particular copy of the database table is stored; executing, by one or more processors, a query operation on the target database table according to the access plan; checking, by one or more processors, a consistent requirement of the query request; selecting, by one or more processors and based on the consistent status information of each of the plurality of copies, at least one copy of the database table whose consistent status information indicates that said at least one copy is consistent with other copies of the database table to form a first candidate copy set, wherein the first candidate copy set is selected in response to the consistent requirement of the query request being determined as having a consistency level that exceeds a first predefined level; selecting, by one or more processors, the plurality of copies to form a first candidate copy set without considering the consistent status information if the consistent requirement of the query request has a consistency level that is below a second predefined level; selecting from the first candidate copy set, by one or more processors and based on the availability status information of each copy of the database table in the first candidate copy set, at least one copy of the database table whose availability status information indicates that said at least one copy of the database table is available to form a second candidate copy set; and selecting from the second candidate copy set, by one or more processors and based on the load status information of each copy in the second candidate copy set, a copy of the database table, whose load status information indicates that the database device that stores the copy has a lowest workload compared to other database devices that are soring the copy of the database table, as the target database table. 7. The method of claim 1 , wherein the distributed database system is a federation database system.
| 0.642691 |
21. The method of claim 15, wherein the secondary address specification is automatically built by replacing a secondary address prefix for a primary address prefix in the primary document address specification.
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21. The method of claim 15, wherein the secondary address specification is automatically built by replacing a secondary address prefix for a primary address prefix in the primary document address specification. 22. The method of claim 21, further comprising: (a) obtaining a URL from a transaction log; (b) parsing the URL into a URL prefix and URL suffix; (c) providing an address map containing a plurality of primary address prefixes and corresponding secondary address prefixes; (d) determining if the URL prefix is included in the address map as a primary address prefix; (i) if the URL prefix is included in the address map as a primary address prefix, combining a secondary address prefix that corresponds to the primary address prefix with the URL suffix to build the secondary address specification; and (ii) if the URL prefix is not included in the address map as a primary address prefix, changing the parsing of the URL to incrementally reduce the URL prefix and increase the URL suffix and then repeating this paragraph (d).
| 0.732578 |
9. The method of claim 1 , wherein step (a) comprises: a.1) creating a pronunciation dictionary that defines a sequence of phonemes for each of the predetermined keywords; a.2) creating an acoustic model that statistically models a relation between textual properties of the phonemes for each of the predetermined keywords and spoken properties of the phonemes for each of the predetermined keywords; and a.3) concatenating acoustic models for the sequence of phonemes for each of the predetermined keywords.
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9. The method of claim 1 , wherein step (a) comprises: a.1) creating a pronunciation dictionary that defines a sequence of phonemes for each of the predetermined keywords; a.2) creating an acoustic model that statistically models a relation between textual properties of the phonemes for each of the predetermined keywords and spoken properties of the phonemes for each of the predetermined keywords; and a.3) concatenating acoustic models for the sequence of phonemes for each of the predetermined keywords. 11. The method of claim 9 , wherein step (a.2) comprises creating the acoustic model selected from the group consisting of: context-independent model, context-dependent model, and triphone model.
| 0.842708 |
1. A method comprising: dividing a first version of a document into one or more sections; generating a condensed version of the document that includes a linkcorresponding to at least one of the one or more sections; transmitting the condensed version of the document to a mobile device for display; receiving a modified version of the document from the mobile device, the modified version including one or more edits to one or more of the sections; and re-aggregating the modified one or more sections with unmodified sections to form a revised document.
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1. A method comprising: dividing a first version of a document into one or more sections; generating a condensed version of the document that includes a linkcorresponding to at least one of the one or more sections; transmitting the condensed version of the document to a mobile device for display; receiving a modified version of the document from the mobile device, the modified version including one or more edits to one or more of the sections; and re-aggregating the modified one or more sections with unmodified sections to form a revised document. 11. The method of claim 1 , wherein the one or more links includes a link to a graph.
| 0.711618 |
9. A non-transitory computer-readable storage medium storing one or more sequences of instructions, wherein execution of the one or more sequences of instructions by one or more processors causes the one or more processors to perform the steps of: receiving, at a search engine, a phonetically-spelled string; wherein the phonetically-spelled string is the result of transforming an audio input into the phonetically-spelled string that has not been converted into any predetermined set of correctly-spelled words; identifying one or more previously-submitted phonetically-spelled query strings from a plurality of other users based on the phonetically-spelled string; and generating a set of query results based, at least in part, on the phonetically-spelled string and on the one ore more previously-submitted phonetically-spelled query strings; wherein the steps of the method are performed by one or more computing devices.
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9. A non-transitory computer-readable storage medium storing one or more sequences of instructions, wherein execution of the one or more sequences of instructions by one or more processors causes the one or more processors to perform the steps of: receiving, at a search engine, a phonetically-spelled string; wherein the phonetically-spelled string is the result of transforming an audio input into the phonetically-spelled string that has not been converted into any predetermined set of correctly-spelled words; identifying one or more previously-submitted phonetically-spelled query strings from a plurality of other users based on the phonetically-spelled string; and generating a set of query results based, at least in part, on the phonetically-spelled string and on the one ore more previously-submitted phonetically-spelled query strings; wherein the steps of the method are performed by one or more computing devices. 12. The non-transitory computer-readable storage medium of claim 9 , wherein execution of the one or more sequences of instructions by the one or more processors causes the one or more processors to further perform the step of: recording one or more addresses of pages visited by a user, wherein each page was provided to the user in one or more previous search results.
| 0.5 |
12. The method according to claim 9 , further comprising the step of: identifying a subset of the respective modified criteria that reference a single, respective table and for which an index is to be created.
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12. The method according to claim 9 , further comprising the step of: identifying a subset of the respective modified criteria that reference a single, respective table and for which an index is to be created. 13. The method according to claim 12 , further comprising the step of: running the query according to a join order, the join order determined by selecting one of the subset of respective modified criteria.
| 0.886254 |
11. An apparatus for controlling a vehicle, comprising: an input arranged to receive one or more instructions issued as speech; a memory arranged to store the received speech; a speech recognition module arranged to analyze the speech to provide a sequence of words and a word confidence measure for each word recognized; a natural language understanding module arranged to receive the sequence of words and the word confidence measures, and analyze the sequence of words to identify a semantic concept corresponding to an instruction based on the analysis and a semantic confidence level for the identified semantic concept derived at least in part with reference to the word confidence measures of the words associated with the semantic concept; a response generation module arranged to provide a spoken confirmation of the identified semantic concept based on the semantic confidence level and an indicated verbosity level; and a command generation module arranged to use the identified semantic concept to provide a control input for the vehicle; wherein the response generation module is arranged to provide the spoken confirmation of the identified semantic concept to indicate that the instruction was not understood when the semantic confidence level is below a threshold, or the command generation module is arranged to use the identified semantic concept to provide a control input for the vehicle when the semantic confidence level exceeds the threshold, and the response generation module is arranged to provide the spoken confirmation of the identified semantic concept with at least one of a speaking rate or a pitch that is increased as the indicated verbosity level decreases.
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11. An apparatus for controlling a vehicle, comprising: an input arranged to receive one or more instructions issued as speech; a memory arranged to store the received speech; a speech recognition module arranged to analyze the speech to provide a sequence of words and a word confidence measure for each word recognized; a natural language understanding module arranged to receive the sequence of words and the word confidence measures, and analyze the sequence of words to identify a semantic concept corresponding to an instruction based on the analysis and a semantic confidence level for the identified semantic concept derived at least in part with reference to the word confidence measures of the words associated with the semantic concept; a response generation module arranged to provide a spoken confirmation of the identified semantic concept based on the semantic confidence level and an indicated verbosity level; and a command generation module arranged to use the identified semantic concept to provide a control input for the vehicle; wherein the response generation module is arranged to provide the spoken confirmation of the identified semantic concept to indicate that the instruction was not understood when the semantic confidence level is below a threshold, or the command generation module is arranged to use the identified semantic concept to provide a control input for the vehicle when the semantic confidence level exceeds the threshold, and the response generation module is arranged to provide the spoken confirmation of the identified semantic concept with at least one of a speaking rate or a pitch that is increased as the indicated verbosity level decreases. 17. The apparatus of claim 11 , wherein the natural language understanding module is arranged to analyze the sequence of words to identify the semantic concept using a bottom-up approach starting with an analysis of each word identified individually and then extending the analysis to neighboring words.
| 0.514317 |
2. The method of claim 1 , wherein computing a score for the second term comprises: computing respective changes in co-occurrence frequency between corresponding elements of the first vector and the second vector; generating an order of co-occurring terms according to the corresponding computed changes in co-occurrence frequency; and computing a measure of importance of a top number of co-occurring terms in the order.
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2. The method of claim 1 , wherein computing a score for the second term comprises: computing respective changes in co-occurrence frequency between corresponding elements of the first vector and the second vector; generating an order of co-occurring terms according to the corresponding computed changes in co-occurrence frequency; and computing a measure of importance of a top number of co-occurring terms in the order. 4. The method of claim 2 , wherein computing a score for the second term comprises: computing a weighted sum of the changes in co-occurrence frequencies for the top number of co-occurring terms in the order, wherein each change in co-occurrence frequency is weighted by the measure of importance of the corresponding co-occurring term.
| 0.799056 |
2. The method of claim 1 , wherein parsing the XPATH input expression to produce a plurality of sub-expressions, comprises: parsing the XPATH input expression to identify expression nodes, step nodes, function nodes, and predicates to the step nodes; and, arranging the nodes in an XPATH traversal tree (XTT) model.
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2. The method of claim 1 , wherein parsing the XPATH input expression to produce a plurality of sub-expressions, comprises: parsing the XPATH input expression to identify expression nodes, step nodes, function nodes, and predicates to the step nodes; and, arranging the nodes in an XPATH traversal tree (XTT) model. 3. The method of claim 2 , wherein parsing the XPATH input expression to identify expression nodes, step nodes, function nodes, and predicates to the step nodes, further comprises identifying parenthesis nodes for the XPATH input expression.
| 0.885805 |
8. At least one non-transitory computer-readable medium encoded with instructions that, when executed by a server comprising at least one hardware computer processor, perform a method of facilitating a search for content via the Internet, the method comprising: receiving a first search query from a client device; identifying at least one search engine to be queried; generating at least one second search query, wherein the at least one second search query is generated based, at least in part, on the content of the first search query, and wherein the at least one second search query comprises at least one formatted search query that is formatted for the at least one search engine; and sending, to the client device, the at least one second search query, including the at least one formatted search query, and information specifying the identified at least one search engine to be used by the client device in performing an Internet search using the at least one second search query and the information specifying the identified at least one search engine; wherein the first search query is in audio form, and wherein generating the at least one second search query further comprises generating the at least one second search query, at least in part, by performing speech recognition on the first search query using a first language model associated with the identified at least one search engine; and wherein the identified at least one search engine is a site-specific search engine.
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8. At least one non-transitory computer-readable medium encoded with instructions that, when executed by a server comprising at least one hardware computer processor, perform a method of facilitating a search for content via the Internet, the method comprising: receiving a first search query from a client device; identifying at least one search engine to be queried; generating at least one second search query, wherein the at least one second search query is generated based, at least in part, on the content of the first search query, and wherein the at least one second search query comprises at least one formatted search query that is formatted for the at least one search engine; and sending, to the client device, the at least one second search query, including the at least one formatted search query, and information specifying the identified at least one search engine to be used by the client device in performing an Internet search using the at least one second search query and the information specifying the identified at least one search engine; wherein the first search query is in audio form, and wherein generating the at least one second search query further comprises generating the at least one second search query, at least in part, by performing speech recognition on the first search query using a first language model associated with the identified at least one search engine; and wherein the identified at least one search engine is a site-specific search engine. 13. The at least one non-transitory computer-readable medium of claim 8 , wherein the identifying the at least one search engine to be queried is based on the content of the first search query.
| 0.55768 |
1. A computer-implemented method of searching for information, comprising: at a server system: receiving from a client system a fill-the-blank query comprising one or more term segments and one or more missing term identifiers signifying missing information sought by a user; converting the fill-the-blank query into a corresponding search pattern, wherein the search pattern includes: one or more missing content identifiers corresponding to the one or more missing term identifiers, and a set of one or more query expressions corresponding to each term segment; identifying a set of documents matching the search pattern; identifying content in the set of documents corresponding to the search pattern, the identified content including one or more potential answers corresponding to the one or more missing term identifiers; and responding to the query by providing to the client system at least one of the one or more potential answers.
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1. A computer-implemented method of searching for information, comprising: at a server system: receiving from a client system a fill-the-blank query comprising one or more term segments and one or more missing term identifiers signifying missing information sought by a user; converting the fill-the-blank query into a corresponding search pattern, wherein the search pattern includes: one or more missing content identifiers corresponding to the one or more missing term identifiers, and a set of one or more query expressions corresponding to each term segment; identifying a set of documents matching the search pattern; identifying content in the set of documents corresponding to the search pattern, the identified content including one or more potential answers corresponding to the one or more missing term identifiers; and responding to the query by providing to the client system at least one of the one or more potential answers. 2. The method of claim 1 , including determining match scores for one or more matches between the search pattern and documents in the set of documents; wherein responding to the query includes providing a ranked set of information items containing the identified content in accordance with the match scores.
| 0.610828 |
16. A computing device, comprising: a device processor; a display screen; and a memory device including instructions operable to be executed by the processor to perform a set of actions, enabling the computing device to: maintain communication data associated with a contact type based at least in part upon past communications between a user and one or more contacts associated with the contact type, the communication data including: a type of communication sent to the one or more contacts of the contact type by the user in a context, the context being associated with at least one behavioral pattern of the user; and a dialog pattern associated with the type of communication in the context, the dialog pattern including at least one of words or phrases associated with one or more past communications between the user and the one or more contacts associated with the contact type; generate a dialog profile for the contact type based at least in part upon the dialog patterns; identify a current context as being related to the context; adjust the dialog profile associated with the one or more contacts to include dialog patterns associated with the context; and generate a communication for the current context based at least in part upon the dialog patterns associated with the dialog profile and the context.
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16. A computing device, comprising: a device processor; a display screen; and a memory device including instructions operable to be executed by the processor to perform a set of actions, enabling the computing device to: maintain communication data associated with a contact type based at least in part upon past communications between a user and one or more contacts associated with the contact type, the communication data including: a type of communication sent to the one or more contacts of the contact type by the user in a context, the context being associated with at least one behavioral pattern of the user; and a dialog pattern associated with the type of communication in the context, the dialog pattern including at least one of words or phrases associated with one or more past communications between the user and the one or more contacts associated with the contact type; generate a dialog profile for the contact type based at least in part upon the dialog patterns; identify a current context as being related to the context; adjust the dialog profile associated with the one or more contacts to include dialog patterns associated with the context; and generate a communication for the current context based at least in part upon the dialog patterns associated with the dialog profile and the context. 17. The computing device of claim 16 , further comprising: prompt the user for an input to at least one of generate the communication or send the communication.
| 0.553184 |
9. A method comprising: receiving a span of text from a document; receiving a phrase vector for the span, the phrase vector having a quantity of features and representing a context for the span; determining, using at least one silicon-based hardware processor, a quantity of candidate entities from a knowledge base for an ambiguous entity mention included in the span; for each of the quantity of candidate entities: determining, using the at least one silicon-based hardware processor, a support score for the candidate entity for each feature in the phrase vector, combining, using the at least one silicon-based hardware processor, the support scores additively, and computing, using the combined support scores, a probability that the span resolves to the candidate entity given the context; and resolving, using the at least one silicon-based hardware processor, the span to a candidate entity with a highest probability.
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9. A method comprising: receiving a span of text from a document; receiving a phrase vector for the span, the phrase vector having a quantity of features and representing a context for the span; determining, using at least one silicon-based hardware processor, a quantity of candidate entities from a knowledge base for an ambiguous entity mention included in the span; for each of the quantity of candidate entities: determining, using the at least one silicon-based hardware processor, a support score for the candidate entity for each feature in the phrase vector, combining, using the at least one silicon-based hardware processor, the support scores additively, and computing, using the combined support scores, a probability that the span resolves to the candidate entity given the context; and resolving, using the at least one silicon-based hardware processor, the span to a candidate entity with a highest probability. 14. The method of claim 9 , wherein combining the support scores additively comprises: computing a sum of the support scores for the candidate entity; and dividing the sum by the quantity of features.
| 0.723478 |
19. The computer-readable medium of claim 12 , wherein deriving the one or more negative keywords from the subset of off-topic search criteria comprises: identifying subsets of words in each of the off-topic search criteria; associating each subset of words with an importance metric; and summing the associated importance metric for each occurrence of the subset of words in the off-topic search criteria.
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19. The computer-readable medium of claim 12 , wherein deriving the one or more negative keywords from the subset of off-topic search criteria comprises: identifying subsets of words in each of the off-topic search criteria; associating each subset of words with an importance metric; and summing the associated importance metric for each occurrence of the subset of words in the off-topic search criteria. 22. The computer-readable medium of claim 19 , wherein deriving the one or more negative keywords from the subset of off-topic search criteria further comprises: assigning the subset of words with the highest summed importance metric as negative keywords.
| 0.840223 |
13. The computer implemented method of claim 9 further comprising determining whether combinations associated with a query have been parsed prior to receiving the query.
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13. The computer implemented method of claim 9 further comprising determining whether combinations associated with a query have been parsed prior to receiving the query. 14. The computer implemented method of claim 13 further comprising executing the query.
| 0.916748 |
1. A method comprising: detecting insertion of a connector into an accessory port of a computing device based on detection pin signals conveyed via a plurality of detection pins in the connector; ascertaining an orientation of the connector inserted in the accessory port based on the detection pin signals; determining, based on logic states of the detection pin signals, whether an accessory device connected via the connector is a one-wire type device or a two-wire type device; and configuring a switching mechanism of the computing device to route signals to pins of the accessory port according to the ascertained orientation and the determined type of the accessory device connected.
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1. A method comprising: detecting insertion of a connector into an accessory port of a computing device based on detection pin signals conveyed via a plurality of detection pins in the connector; ascertaining an orientation of the connector inserted in the accessory port based on the detection pin signals; determining, based on logic states of the detection pin signals, whether an accessory device connected via the connector is a one-wire type device or a two-wire type device; and configuring a switching mechanism of the computing device to route signals to pins of the accessory port according to the ascertained orientation and the determined type of the accessory device connected. 5. The method of claim 1 , wherein configuring the switching mechanism comprises directing switches or multiplexers of the computing device to route signal path connections to pins of the accessory port.
| 0.755485 |
53. The method of claim 52 , further comprising: controlling display of information, stored in association with the plurality of symbol sequences in the interactive dictionary database in memory, useable to view and set at least a subset of the plurality of symbol sequences to at least one of an active and an inactive status.
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53. The method of claim 52 , further comprising: controlling display of information, stored in association with the plurality of symbol sequences in the interactive dictionary database in memory, useable to view and set at least a subset of the plurality of symbol sequences to at least one of an active and an inactive status. 54. The method of claim 53 , wherein a status indicator of at least one single symbol sequence, including a symbol displayed on the initial electronic screen overlay, is automatically initially set to be inactive upon a status indicator of at least one multi-symbol sequence, including the displayed symbol beginning the at least one multi-symbol sequence, being set to an active status.
| 0.87763 |
7. Image processing circuitry for modifying bits of an input pixel data word, comprising: an embedded data engine configured to output at least one bit of embedded data; decatenation circuitry that is coupled to the embedded data engine and that is configured to separate the input pixel data word into first and second subsets of bits; arithmetic circuitry that modifies bits of the first subset of bits based on whether the at least one bit of embedded data is the same as at least one corresponding bit of the second subset of bits; and concatenation circuitry that is coupled to the decatenation circuitry and that is configured to produce an output data word including the at least one bit of embedded data.
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7. Image processing circuitry for modifying bits of an input pixel data word, comprising: an embedded data engine configured to output at least one bit of embedded data; decatenation circuitry that is coupled to the embedded data engine and that is configured to separate the input pixel data word into first and second subsets of bits; arithmetic circuitry that modifies bits of the first subset of bits based on whether the at least one bit of embedded data is the same as at least one corresponding bit of the second subset of bits; and concatenation circuitry that is coupled to the decatenation circuitry and that is configured to produce an output data word including the at least one bit of embedded data. 13. The image processing circuitry defined in claim 7 , wherein the at least one bit of embedded data corresponds to a bit of data selected from the group consisting of: coordinate data, compressed data, and encrypted data.
| 0.632841 |
17. A system comprising: a computer processor to read a portion of a data word, wherein the data word includes a plurality of syllables, and the read portion of the data word includes at least one of: 1) a first syllable of the plurality of syllables and 2) a second syllable of the plurality of syllables; a first memory to store the first syllable; and a second memory to store the second syllable, wherein bits of the second syllable are less critical than bits of the first syllable, and the second memory is distinct from the first memory based on at least a physical attribute.
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17. A system comprising: a computer processor to read a portion of a data word, wherein the data word includes a plurality of syllables, and the read portion of the data word includes at least one of: 1) a first syllable of the plurality of syllables and 2) a second syllable of the plurality of syllables; a first memory to store the first syllable; and a second memory to store the second syllable, wherein bits of the second syllable are less critical than bits of the first syllable, and the second memory is distinct from the first memory based on at least a physical attribute. 22. The system of claim 17 , wherein the processor is further configured to process the first syllable, and read the second syllable if the processor determines that the second syllable should be read based on the processing of the first syllable.
| 0.680736 |
5. The system of claim 1 , wherein the predictive language model is configured to weight the grammar such that probabilities of individual potential matching symbols that are included in relatively more occurrences in the dataset are higher than probabilities of other individual potential matching symbols that are included in relatively fewer occurrences in the dataset.
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5. The system of claim 1 , wherein the predictive language model is configured to weight the grammar such that probabilities of individual potential matching symbols that are included in relatively more occurrences in the dataset are higher than probabilities of other individual potential matching symbols that are included in relatively fewer occurrences in the dataset. 6. The system of claim 5 , wherein the predictive language model is further configured to update the grammar as further user entries are received.
| 0.865086 |
1. A computing device for detecting events based on query-page relationships, comprising: a query-page store identifying occurrences of query-page pairs, each occurrence of a query-page pair indicating that a user selected that page from a search result for that query, each occurrence of a query-page pair having a time associated with the user selection; a generate dual graph component that generates a dual graph having vertices corresponding to distinct query-page pairs of the query-page store and edges between vertices that have a common query or a common page, each vertex having a time period vector with an element for each time period, each element having a value derived from occurrences of the query-page pair of the vertex with a time within the time period; an identify semantic cluster component that identifies clusters of vertices of the dual graph, each cluster having vertices whose query-page pairs are semantically similar; and an identify time pattern cluster component that identifies time pattern clusters of a semantic cluster, a time pattern cluster having vertices representing semantically related query-page pairs that have similar patterns of associated times, wherein an identified time pattern cluster represents an event relating to the query-page pairs of the vertices within the identified time pattern cluster, and wherein query-page pairs are semantically similar based on the following: S S ( a , b ) = C N ( a ) N ( b ) ∑ i = 1 N ( a ) ∑ j = 1 N ( b ) S S ( N i ( a ) , N j ( b ) ) where S s (a, b) represents the semantic similarity between vertex a and vertex b, N(k) represents the neighboring vertices of vertex k , N i (k) represents the i th neighbor vertex of vertex k, and C represents a decay factor between 0 and 1 that indicates the contribution of the neighbors to the similarity of a pair of vertices wherein the components are implemented as instructions stored in memory of the computing device for execution by a processor of the computing device.
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1. A computing device for detecting events based on query-page relationships, comprising: a query-page store identifying occurrences of query-page pairs, each occurrence of a query-page pair indicating that a user selected that page from a search result for that query, each occurrence of a query-page pair having a time associated with the user selection; a generate dual graph component that generates a dual graph having vertices corresponding to distinct query-page pairs of the query-page store and edges between vertices that have a common query or a common page, each vertex having a time period vector with an element for each time period, each element having a value derived from occurrences of the query-page pair of the vertex with a time within the time period; an identify semantic cluster component that identifies clusters of vertices of the dual graph, each cluster having vertices whose query-page pairs are semantically similar; and an identify time pattern cluster component that identifies time pattern clusters of a semantic cluster, a time pattern cluster having vertices representing semantically related query-page pairs that have similar patterns of associated times, wherein an identified time pattern cluster represents an event relating to the query-page pairs of the vertices within the identified time pattern cluster, and wherein query-page pairs are semantically similar based on the following: S S ( a , b ) = C N ( a ) N ( b ) ∑ i = 1 N ( a ) ∑ j = 1 N ( b ) S S ( N i ( a ) , N j ( b ) ) where S s (a, b) represents the semantic similarity between vertex a and vertex b, N(k) represents the neighboring vertices of vertex k , N i (k) represents the i th neighbor vertex of vertex k, and C represents a decay factor between 0 and 1 that indicates the contribution of the neighbors to the similarity of a pair of vertices wherein the components are implemented as instructions stored in memory of the computing device for execution by a processor of the computing device. 4. The computing device of claim 1 wherein the semantic similarity between query-page pairs is based on similarity between neighbors of the query-page pairs.
| 0.558583 |
17. The apparatus of claim 16 , wherein the processor configured to filter and normalize is further configured to: process the obtained records to remove records related to restricted content.
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17. The apparatus of claim 16 , wherein the processor configured to filter and normalize is further configured to: process the obtained records to remove records related to restricted content. 18. The apparatus of claim 17 , wherein the restricted content comprises search queries and URLs associated with one or more of classified content or adult content.
| 0.943553 |
11. A system, comprising: one or more processors; memory; and one or more programming modules stored on the memory and executable by the one or more processors to: receive a plurality of code script samples; transform the plurality of code script samples into a plurality of tokenized samples, the transform based on syntactical elements of the plurality of code script samples; receive from a cluster engine identification of a cluster of samples, the cluster of samples including at least a first tokenized sample of the plurality of tokenized samples and a second tokenized sample of the plurality of tokenized samples, the cluster being identified at least in part based on similarities of the first tokenized sample and the second tokenized sample; identify the first tokenized sample as a representative sample of the cluster of samples; identify a known malicious code sample that has at least a threshold similarity to the representative sample by de-obfuscation of the representative sample of the cluster of samples to produce a de-obfuscated representative sample and comparison of the de-obfuscated representative sample to a plurality of known malicious code sample; based on the identified known malicious code, label the cluster of samples as malicious, wherein the label of cluster of samples as malicious is unscored; and generate, based at least on the unscored labeled samples in the cluster of samples, a generalized code signature that identifies the first tokenized sample and the second tokenized sample.
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11. A system, comprising: one or more processors; memory; and one or more programming modules stored on the memory and executable by the one or more processors to: receive a plurality of code script samples; transform the plurality of code script samples into a plurality of tokenized samples, the transform based on syntactical elements of the plurality of code script samples; receive from a cluster engine identification of a cluster of samples, the cluster of samples including at least a first tokenized sample of the plurality of tokenized samples and a second tokenized sample of the plurality of tokenized samples, the cluster being identified at least in part based on similarities of the first tokenized sample and the second tokenized sample; identify the first tokenized sample as a representative sample of the cluster of samples; identify a known malicious code sample that has at least a threshold similarity to the representative sample by de-obfuscation of the representative sample of the cluster of samples to produce a de-obfuscated representative sample and comparison of the de-obfuscated representative sample to a plurality of known malicious code sample; based on the identified known malicious code, label the cluster of samples as malicious, wherein the label of cluster of samples as malicious is unscored; and generate, based at least on the unscored labeled samples in the cluster of samples, a generalized code signature that identifies the first tokenized sample and the second tokenized sample. 12. The system of claim 11 , wherein at least some of the plurality of script code samples are obfuscated code samples, and the one or more programming modules are further executable by the one or more processors to transform the obfuscated code samples into the tokenized samples.
| 0.66609 |
27. The program product of claim 26 , wherein the merging includes mapping a first object in a first intermediate model to a second object in a second intermediate model.
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27. The program product of claim 26 , wherein the merging includes mapping a first object in a first intermediate model to a second object in a second intermediate model. 30. The program product of claim 27 , wherein the mapping includes semantically matching objects using an ontology of a domain for the business entity.
| 0.95625 |
1. A method for indexing a suffix tree in a social network, the method comprising: scanning, by a computing device, an input string and dividing the string into partitions each having a common prefix; performing no-merge suffix tree indexing on the divided partitions, wherein a suffix tree is built without performing a process of merging sub-trees having a common prefix in the no-merge suffix tree indexing; storing information on the partitions on which no-merge suffix tree indexing is performed; storing suffix nodes of the no-merge suffix tree; and establishing a prefix tree.
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1. A method for indexing a suffix tree in a social network, the method comprising: scanning, by a computing device, an input string and dividing the string into partitions each having a common prefix; performing no-merge suffix tree indexing on the divided partitions, wherein a suffix tree is built without performing a process of merging sub-trees having a common prefix in the no-merge suffix tree indexing; storing information on the partitions on which no-merge suffix tree indexing is performed; storing suffix nodes of the no-merge suffix tree; and establishing a prefix tree. 2. The method of claim 1 , wherein said performing no-merge suffix tree indexing includes: generating a set of suffixes having the common prefix in the input string; generating a suffix set from the set of suffixes and storing the suffix set; and building the suffix set as a sub-tree.
| 0.54823 |
6. The method of claim 1 , wherein determining whether the characters associated with the second sequence of one or more keys are included in the first candidate word comprises: determining, by the computing device, a first candidate string in which the characters associated with the second sequence of one or more keys are included in the first candidate word; determining, by the computing device, a second candidate string in which the characters associated with the second sequence of one or more keys are included in the second candidate word; and comparing, by the computing device, a cost value associated with the first candidate string and a cost value associated with the second candidate string, wherein the first and second cost values are determined based at least in part on the lexicon.
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6. The method of claim 1 , wherein determining whether the characters associated with the second sequence of one or more keys are included in the first candidate word comprises: determining, by the computing device, a first candidate string in which the characters associated with the second sequence of one or more keys are included in the first candidate word; determining, by the computing device, a second candidate string in which the characters associated with the second sequence of one or more keys are included in the second candidate word; and comparing, by the computing device, a cost value associated with the first candidate string and a cost value associated with the second candidate string, wherein the first and second cost values are determined based at least in part on the lexicon. 7. The method of claim 6 , wherein the first candidate word comprises a predicted word that is based at least in part on the set of candidate strings.
| 0.854945 |
1. A method for registering a domain, comprising: receiving a request to register an Internationalized Domain Name (IDN) at a registry server; determining a language category of the request; identifying corresponding code points of language variants within the language category for one or more code points in the request; converting each of the one or more code points into a representative code point chosen from among the corresponding code points by applying a deterministic algorithm to a value of each of the corresponding code points; determining, by a computer processor, a generalized variant of the IDN based on the converted code points; comparing a portion of the generalized variant to a stored database of registered IDNs; if the portion of the generalized variant matches a portion of a registered IDN, comparing another portion of the generalized variant to the stored database of registered IDNs; if all portions of the generalized variant match a registered IDN, blocking the registration; and if at least one portion of the generalized variant does not match a portion of a registered IDN, registering the IDN and storing the generalized variant in the database.
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1. A method for registering a domain, comprising: receiving a request to register an Internationalized Domain Name (IDN) at a registry server; determining a language category of the request; identifying corresponding code points of language variants within the language category for one or more code points in the request; converting each of the one or more code points into a representative code point chosen from among the corresponding code points by applying a deterministic algorithm to a value of each of the corresponding code points; determining, by a computer processor, a generalized variant of the IDN based on the converted code points; comparing a portion of the generalized variant to a stored database of registered IDNs; if the portion of the generalized variant matches a portion of a registered IDN, comparing another portion of the generalized variant to the stored database of registered IDNs; if all portions of the generalized variant match a registered IDN, blocking the registration; and if at least one portion of the generalized variant does not match a portion of a registered IDN, registering the IDN and storing the generalized variant in the database. 7. The method of claim 1 , wherein the language category is Chinese and the language variants include traditional Chinese and simplified Chinese.
| 0.526316 |
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