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8,090,724 | 1 | 2 | 1. A method comprising: receiving an ordered collection of text-based terms; analyzing groupings of consecutive text-based terms in the ordered collection to identify occurrences of different combinations of consecutive text-based terms in the ordered collection; and maintaining frequency information representing the occurrences of the different combinations of consecutive text-based terms in the collection. | 1. A method comprising: receiving an ordered collection of text-based terms; analyzing groupings of consecutive text-based terms in the ordered collection to identify occurrences of different combinations of consecutive text-based terms in the ordered collection; and maintaining frequency information representing the occurrences of the different combinations of consecutive text-based terms in the collection. 2. The method as in claim 1 further comprising: based on the analyzing, creating a tree in which a first term in a given grouping of the groupings is defined as a parent node in the tree and a second term in the given grouping is defined as a child node of the parent node in the tree. both the first term and the second term in the given grouping being consecutive text-based terms present in the order collection. | 0.837127 |
9,293,129 | 8 | 11 | 8. A tangible computer-readable storage device storing computer-executable instructions for determining pronunciation issues, comprising: receiving text comprising sentences for a Text-To-Speech (TTS) component and a recording of the text that is used as a reference for the text; receiving synthesized speech generated by the TTS component using the text as input to the TTS component; evaluating results received by an evaluation performed at a text level by determining a similarity of the synthesized speech to the recording; evaluating results obtained from a Speech Recognition (SR) component related to different inputs to the SR component comprising the synthesized speech and the recording; evaluating results from a signal level evaluation of the text and the recording; and generating a list that includes a ranking of pronunciation issue candidates based on the evaluations. | 8. A tangible computer-readable storage device storing computer-executable instructions for determining pronunciation issues, comprising: receiving text comprising sentences for a Text-To-Speech (TTS) component and a recording of the text that is used as a reference for the text; receiving synthesized speech generated by the TTS component using the text as input to the TTS component; evaluating results received by an evaluation performed at a text level by determining a similarity of the synthesized speech to the recording; evaluating results obtained from a Speech Recognition (SR) component related to different inputs to the SR component comprising the synthesized speech and the recording; evaluating results from a signal level evaluation of the text and the recording; and generating a list that includes a ranking of pronunciation issue candidates based on the evaluations. 11. The tangible computer-readable storage device of claim 8 , further comprising performing a model level check for an acoustic model that determines a similarity of a TTS phone set and an SR phone set including determining a mapping relation between the TTS acoustic model and the SR acoustic model. | 0.686458 |
8,024,329 | 1 | 4 | 1. A method for using indexes to search a knowledge base in at least one computer system, the method executed by the computer system and comprising: accessing a knowledge base comprising a semantic network of relationships among concepts, each concept having a set of values associated with it, wherein each concept is an instance of a category and each value is an instance of an attribute and wherein categories and attributes form a knowledge base schema; receiving, from a user searching for one or more target concepts, a query represented as criteria and criteria values that specify constraints on the categories and the attributes; executing a search of the concepts and the values of the knowledge base to retrieve the one or more target concepts using indexes selected from a group consisting of: a) one or more transitive indexes that index transitive relationships from concepts in a first category through at least one second category to concepts in a third category and b) one or more transitive closure indexes that index transitive closure relationships amongst concepts within a category; and retrieving a result subset of the target concepts and the values that satisfies the criteria and criteria values. | 1. A method for using indexes to search a knowledge base in at least one computer system, the method executed by the computer system and comprising: accessing a knowledge base comprising a semantic network of relationships among concepts, each concept having a set of values associated with it, wherein each concept is an instance of a category and each value is an instance of an attribute and wherein categories and attributes form a knowledge base schema; receiving, from a user searching for one or more target concepts, a query represented as criteria and criteria values that specify constraints on the categories and the attributes; executing a search of the concepts and the values of the knowledge base to retrieve the one or more target concepts using indexes selected from a group consisting of: a) one or more transitive indexes that index transitive relationships from concepts in a first category through at least one second category to concepts in a third category and b) one or more transitive closure indexes that index transitive closure relationships amongst concepts within a category; and retrieving a result subset of the target concepts and the values that satisfies the criteria and criteria values. 4. The method of claim 1 , wherein at least one of the indexes is an attribute index of single concepts referring to a single value. | 0.890909 |
9,141,698 | 14 | 15 | 14. The non-transitory computer-readable medium of claim 13 , wherein the instructions further cause the computer processor to: associate supplemental information with the new note created in the dietary log, wherein the supplemental information comprises at least one of an image of the physical object, information derived from the image of the physical object, wirelessly received information, a machine readable code associated with the physical object, information based on the machine readable code, or contextual traits related to the physical object. | 14. The non-transitory computer-readable medium of claim 13 , wherein the instructions further cause the computer processor to: associate supplemental information with the new note created in the dietary log, wherein the supplemental information comprises at least one of an image of the physical object, information derived from the image of the physical object, wirelessly received information, a machine readable code associated with the physical object, information based on the machine readable code, or contextual traits related to the physical object. 15. The non-transitory computer-readable medium of claim 14 , wherein the contextual traits comprise at least one of a location, a place, a time, a source, a related note, a person, people, a group, a tag, an identity, sensor data, a media file, an audio file, physical data relating to the first mobile device, or derived data. | 0.738437 |
9,781,139 | 4 | 7 | 4. The method of claim 3 , further comprising: storing statistical training data calculated from the plurality of sample proxy logs and the corresponding domain names in a sample database, wherein the statistical data includes features calculated based on the domain names and flow based features; and training the classifier based on the statistical training data. | 4. The method of claim 3 , further comprising: storing statistical training data calculated from the plurality of sample proxy logs and the corresponding domain names in a sample database, wherein the statistical data includes features calculated based on the domain names and flow based features; and training the classifier based on the statistical training data. 7. The method of claim 4 , further comprising: obtaining proxy logs of the malware network communication; extracting statistical features from the proxy logs of the malware network communication; forming a second input feature vector from the statistical features extracted from the proxy logs of the malware network communication; and identifying the network communication as the malware network communication with DGA domains by applying the trained and tested classifier to the second input feature vector. | 0.793089 |
8,868,619 | 12 | 17 | 12. A method for creating a multimedia data search engine platform to allow fast search of multimedia content data elements (MMDEs), comprising: collecting MMDEs from at least an external source storing MMDEs; generating a plurality of signatures for each of the collected MMDEs; generating signature reduced clusters (SRCs) for the collected MMDEs by clustering the plurality of signatures generated for each of the collected MMDEs, wherein clustering the plurality of signatures generated further includes: generating a clustering score for each signature of an MMDE of the collected MMDEs versus all other MMDEs of the collected MMDEs, determining a size of a diagonal matrix having a size corresponding to a number of the collected MMDEs, placing the clustering score in a diagonal matrix in storage, one clustering score for each pair of MMDEs, creating a new cluster element for each two cluster elements in the diagonal matrix having a clustering score that exceeds a threshold, and repeating the process at the newly created cluster element level each time using the new cluster elements generated as the plurality of cluster elements for the subsequent sequence, until a single cluster is reached or until it is determined that a single cluster cannot be reached; and generating concept structures from the generated SRCs, wherein the concept structures generated for different SRCs are utilized to compare between different MMDEs, thereby searching for an input MMDE that matches the collected MMDEs. | 12. A method for creating a multimedia data search engine platform to allow fast search of multimedia content data elements (MMDEs), comprising: collecting MMDEs from at least an external source storing MMDEs; generating a plurality of signatures for each of the collected MMDEs; generating signature reduced clusters (SRCs) for the collected MMDEs by clustering the plurality of signatures generated for each of the collected MMDEs, wherein clustering the plurality of signatures generated further includes: generating a clustering score for each signature of an MMDE of the collected MMDEs versus all other MMDEs of the collected MMDEs, determining a size of a diagonal matrix having a size corresponding to a number of the collected MMDEs, placing the clustering score in a diagonal matrix in storage, one clustering score for each pair of MMDEs, creating a new cluster element for each two cluster elements in the diagonal matrix having a clustering score that exceeds a threshold, and repeating the process at the newly created cluster element level each time using the new cluster elements generated as the plurality of cluster elements for the subsequent sequence, until a single cluster is reached or until it is determined that a single cluster cannot be reached; and generating concept structures from the generated SRCs, wherein the concept structures generated for different SRCs are utilized to compare between different MMDEs, thereby searching for an input MMDE that matches the collected MMDEs. 17. A non-transitory computer readable medium having stored thereon instructions for causing a processor to perform a method of claim 12 . | 0.86444 |
8,265,991 | 8 | 10 | 8. The method of claim 7 , wherein: the set of rules comprises a primary set of rules and a secondary set of rules; said primary set of rules is used to determine applicability of the discount type; and said secondary set of rules is used to determine a discount value for the discount type, the secondary set of rules being called for processing if the discount type is determined to be applicable. | 8. The method of claim 7 , wherein: the set of rules comprises a primary set of rules and a secondary set of rules; said primary set of rules is used to determine applicability of the discount type; and said secondary set of rules is used to determine a discount value for the discount type, the secondary set of rules being called for processing if the discount type is determined to be applicable. 10. The method of claim 8 , wherein: a rule in the set of rules comprises an antecedent and an inference, the inference being determined if the antecedent is determined as true; an inference is a numerical value or a set of rules; and the rule engine recursively evaluates rules in the secondary set of rules to determine inferences until an inference that is a numerical value indicating a discount value for an applicable discount type is found. | 0.871773 |
6,141,011 | 1 | 11 | 1. In a computing device having a limited set of input keys, a method for assisting a user with entering user input, the method comprising: providing a terse set of physical input keys comprising navigation keys, a select key, and an edit key; at a different location on said computing device than where said physical input keys are located, displaying a user interface that requires input of information from the user; receiving user input at the navigation keys for moving a screen cursor to different regions of the user interface; with the screen cursor positioned at a particular region of the user interface, receiving user input at the edit key for invoking a context-sensitive input system; determining a set of appropriate user input entries for the device for the particular region of the user interface where the screen cursor is currently positioned; displaying at the particular region a control based on at least some of said set of appropriate user input entries; receiving user input at the navigation keys for positioning the screen cursor at a desired entry from said set of appropriate user input entries; and receiving user input at the select key for inputting the desired entry as user input for the device. | 1. In a computing device having a limited set of input keys, a method for assisting a user with entering user input, the method comprising: providing a terse set of physical input keys comprising navigation keys, a select key, and an edit key; at a different location on said computing device than where said physical input keys are located, displaying a user interface that requires input of information from the user; receiving user input at the navigation keys for moving a screen cursor to different regions of the user interface; with the screen cursor positioned at a particular region of the user interface, receiving user input at the edit key for invoking a context-sensitive input system; determining a set of appropriate user input entries for the device for the particular region of the user interface where the screen cursor is currently positioned; displaying at the particular region a control based on at least some of said set of appropriate user input entries; receiving user input at the navigation keys for positioning the screen cursor at a desired entry from said set of appropriate user input entries; and receiving user input at the select key for inputting the desired entry as user input for the device. 11. The method of claim 1, wherein said set of appropriate user input entries comprises selected ones of system default entries and user-provided entries. | 0.936782 |
10,146,813 | 1 | 4 | 1. A method comprising: receiving a query; processing a global index associated with a database with respect to the query to identify one or more identifiers within the global index that correspond to the query; based on an identification of the one or more identifiers within the global index that correspond to the query, processing, by a processing device, one or more indexes associated with one or more data items within the database with respect to the one or more identifiers; based on an identification of a presence of the one or more identifiers within a row of at least one of the one or more indexes, scanning one or more rows of the at least one of the one or more indexes to identify one or more additional rows of the at least one of the one or more indexes that also include the one or more identifiers; based on a scan of the one or more rows of the at least one of the one or more indexes, identifying one or more other identifiers within the one or more rows that are associated with the one or more identifiers; scanning one or more rows of the at least one of the one or more indexes to identify one or more additional rows of the at least one of the one or more indexes that also include the one or more other identifiers; based on the scanning of the one or more rows, identifying one or more search results in response to the query; prioritizing the one or more search results based on one or more respective priority status indicators associated with the one or more search results; and providing the one or more search results, as prioritized, in response to the query. | 1. A method comprising: receiving a query; processing a global index associated with a database with respect to the query to identify one or more identifiers within the global index that correspond to the query; based on an identification of the one or more identifiers within the global index that correspond to the query, processing, by a processing device, one or more indexes associated with one or more data items within the database with respect to the one or more identifiers; based on an identification of a presence of the one or more identifiers within a row of at least one of the one or more indexes, scanning one or more rows of the at least one of the one or more indexes to identify one or more additional rows of the at least one of the one or more indexes that also include the one or more identifiers; based on a scan of the one or more rows of the at least one of the one or more indexes, identifying one or more other identifiers within the one or more rows that are associated with the one or more identifiers; scanning one or more rows of the at least one of the one or more indexes to identify one or more additional rows of the at least one of the one or more indexes that also include the one or more other identifiers; based on the scanning of the one or more rows, identifying one or more search results in response to the query; prioritizing the one or more search results based on one or more respective priority status indicators associated with the one or more search results; and providing the one or more search results, as prioritized, in response to the query. 4. The method of claim 1 , further comprising combining a plurality of identifiers associated with a data item into a string that reflects one or more associations between the plurality of identifiers in relation to the data item. | 0.762887 |
10,042,603 | 16 | 18 | 16. A user device comprising: an input device; a random access memory; a display; and at least one microprocessor configured to: receive, by the input device, an indication associated with a first user input according to a guidance provided by the user device, the first user input being at least one of a natural language-based text input or a natural language-based speech input, in response to receiving the first user input, parse the received first user input to extract and identify a condition, an action corresponding to the condition, and a command, wherein the action is a function executable by one or more applications of the user device, define a rule including the condition and the action corresponding to the condition based on the parsed first user input, map the command to the rule in response to the defining of the rule, store the rule and the mapped command to the random access memory, receive, by the input device, an indication associated with a second user input, wherein the second user input is one of a natural language-based text input or a natural language-based speech input, and in response to receiving the second user input: determine whether the second user input corresponds to the command, activate, if the second user input corresponds to the command, the rule to detect, by a sensor of the user device, a context, control the display to display execution information if the rule is activated, and execute, if the detected context corresponds to the condition of the rule, the action corresponding to the condition, wherein the second user input is one of a natural language-based text input or a natural language-based speech input. | 16. A user device comprising: an input device; a random access memory; a display; and at least one microprocessor configured to: receive, by the input device, an indication associated with a first user input according to a guidance provided by the user device, the first user input being at least one of a natural language-based text input or a natural language-based speech input, in response to receiving the first user input, parse the received first user input to extract and identify a condition, an action corresponding to the condition, and a command, wherein the action is a function executable by one or more applications of the user device, define a rule including the condition and the action corresponding to the condition based on the parsed first user input, map the command to the rule in response to the defining of the rule, store the rule and the mapped command to the random access memory, receive, by the input device, an indication associated with a second user input, wherein the second user input is one of a natural language-based text input or a natural language-based speech input, and in response to receiving the second user input: determine whether the second user input corresponds to the command, activate, if the second user input corresponds to the command, the rule to detect, by a sensor of the user device, a context, control the display to display execution information if the rule is activated, and execute, if the detected context corresponds to the condition of the rule, the action corresponding to the condition, wherein the second user input is one of a natural language-based text input or a natural language-based speech input. 18. The user device of claim 16 , wherein the at least one microprocessor is further configured to: execute, when an event detected in the user device satisfies the condition specified in the activated rule, at least one action corresponding to the condition, and control the user device to provide feedback as an execution result. | 0.70708 |
8,049,093 | 8 | 9 | 8. A method of matching a portion of a song to a set of target songs, the method comprising the steps of: receiving the portion of the song; extracting a pitch contour from the portion of the song; creating a plurality of variable-length segments from the pitch contour; time-normalizing the plurality of variable-length segments so that each segment matches a target segment in length; key-normalizing the time-normalized segments; comparing each time-normalized and key-normalized segment to time-normalized and key-normalized portions of the target songs by comparing their wavelet coefficients; determining a plurality of locations of best matched portions of the target songs based on the comparison. | 8. A method of matching a portion of a song to a set of target songs, the method comprising the steps of: receiving the portion of the song; extracting a pitch contour from the portion of the song; creating a plurality of variable-length segments from the pitch contour; time-normalizing the plurality of variable-length segments so that each segment matches a target segment in length; key-normalizing the time-normalized segments; comparing each time-normalized and key-normalized segment to time-normalized and key-normalized portions of the target songs by comparing their wavelet coefficients; determining a plurality of locations of best matched portions of the target songs based on the comparison. 9. The method of claim 8 further comprising the steps of: determining a distance between the pitch contour from the portion of the song and a pitch contour of a target song starting at a location taken from the plurality of locations; and repeating the step of determining the distance for the plurality of locations of best matched portions, resulting in a plurality of distances. | 0.612016 |
7,725,464 | 2 | 16 | 2. The invention of claim 1 further comprising: ranking at least some of the suppliers of the search result sets compared to other suppliers using relationship based criteria not limited to current bids; and requesting search result sets related to the keyword from the suppliers in accordance with the ranking of the suppliers. | 2. The invention of claim 1 further comprising: ranking at least some of the suppliers of the search result sets compared to other suppliers using relationship based criteria not limited to current bids; and requesting search result sets related to the keyword from the suppliers in accordance with the ranking of the suppliers. 16. The invention of claim 2 further comprising: effectively repricing at least some of the ads from the matching suppliers before delivering the search result set by changing a revenue sharing arrangement with those suppliers. | 0.824031 |
9,582,608 | 14 | 15 | 14. The computer-readable medium of claim 9 , wherein presenting one or more auto-completion candidates further comprises: displaying a first portion of a first auto-completion candidate of the one or more auto-completion candidates, wherein the first portion of the first auto-completion candidate precedes or ends at a respective template word in the first auto-completion candidate; receiving a subsequent user input specifying one or more normal words corresponding to the respective template word; and in response to receiving the subsequent user input, displaying a second portion of the first auto-completion candidate succeeding the respective template word in the first auto-completion candidate. | 14. The computer-readable medium of claim 9 , wherein presenting one or more auto-completion candidates further comprises: displaying a first portion of a first auto-completion candidate of the one or more auto-completion candidates, wherein the first portion of the first auto-completion candidate precedes or ends at a respective template word in the first auto-completion candidate; receiving a subsequent user input specifying one or more normal words corresponding to the respective template word; and in response to receiving the subsequent user input, displaying a second portion of the first auto-completion candidate succeeding the respective template word in the first auto-completion candidate. 15. The computer-readable medium of claim 14 , wherein the operations further comprise: displaying one or more suggestions corresponding to the respective template word based on a user-specific vocabulary comprising at least one of a plurality of proper nouns associated with the user, wherein the subsequent user input is a selection of the one or more displayed suggestions. | 0.898488 |
8,712,317 | 15 | 16 | 15. A system in accordance with claim 13 , wherein an assessor icon is displayed, the computer further performing the step of activating the assessor icon to reveal a list of assessors. | 15. A system in accordance with claim 13 , wherein an assessor icon is displayed, the computer further performing the step of activating the assessor icon to reveal a list of assessors. 16. A system in accordance with claim 15 , wherein each assessor listed in said list of assessors has a color associated therewith, the outcome statement placed on the representation of the coursework answer appearing in said color. | 0.931483 |
9,959,324 | 2 | 3 | 2. The method of claim 1 , further comprising: clustering a plurality of common relationship clauses according to a plurality of linkages that link a plurality of data sources together; and storing the plurality of common relationship clauses and the plurality of linkages. | 2. The method of claim 1 , further comprising: clustering a plurality of common relationship clauses according to a plurality of linkages that link a plurality of data sources together; and storing the plurality of common relationship clauses and the plurality of linkages. 3. The method of claim 2 , wherein the plurality of common relationship clauses and the plurality of linkages are stored according to at least one of a class, a cluster or a syntax tree. | 0.908555 |
9,152,735 | 22 | 23 | 22. The system of claim 21 , wherein said processor is further configured to generate a traverse view query from a context transition graph prior to generating said modified view query, said traverse view query capturing traversal actions of said XSLT stylesheet on said XML document produced by said initial view query. | 22. The system of claim 21 , wherein said processor is further configured to generate a traverse view query from a context transition graph prior to generating said modified view query, said traverse view query capturing traversal actions of said XSLT stylesheet on said XML document produced by said initial view query. 23. The system of claim 22 , wherein said formatting instructions are expressed as output tag trees for each node in said traverse view query; and further comprising the step of combining said output tag trees and said traverse view query to generate said modified view query. | 0.855042 |
5,537,628 | 8 | 9 | 8. A method for handling text using a code page that is different than a native code page used in a document into which the text is pasted, comprising the steps of: (a) producing a piece table by scanning characters comprising the document to develop an array of character positions and an array of data records, said characters in the document being referenced in the array of character positions by a sequence of character position coordinates, said array of character positions being divided into a plurality of pieces, each piece comprising characters of text that are disposed adjacent to each other in the document and which have common properties; (b) including in each record of the array of data records: (i) a file number for a corresponding piece of the array of character positions, said file number indicating a file in which the characters referenced in the piece are stored; and (ii) a file position in said file where said characters are to be found; (c) producing a file control block for any file that is opened to paste text into the document, said file control block including code page identifier data indicating a default code page for the text stored in said file, and thus, for the text referenced by any of the pieces; (d) providing a data block for each file that is opened to paste text into the document, said data block including a specifier for an exception code page to be used for any run of text in the file that has a different code page than the default code page for the file in which the run of text is stored, so that the default code page for the file in which the run of text is stored and the data block for the run of text are checked to determine the code page to be applied to all of the characters in said run of text; and (e) when the code page used by any run of text to be displayed is different than the native code page, translating the code page for the characters in the run of text to be displayed to the native code page using a closest available mapping, said code page for the run of text being retained if the document is saved to a file, thereby ensuring that a reference to the code page for any text pasted into the document is not omitted from the file to which the document is saved. | 8. A method for handling text using a code page that is different than a native code page used in a document into which the text is pasted, comprising the steps of: (a) producing a piece table by scanning characters comprising the document to develop an array of character positions and an array of data records, said characters in the document being referenced in the array of character positions by a sequence of character position coordinates, said array of character positions being divided into a plurality of pieces, each piece comprising characters of text that are disposed adjacent to each other in the document and which have common properties; (b) including in each record of the array of data records: (i) a file number for a corresponding piece of the array of character positions, said file number indicating a file in which the characters referenced in the piece are stored; and (ii) a file position in said file where said characters are to be found; (c) producing a file control block for any file that is opened to paste text into the document, said file control block including code page identifier data indicating a default code page for the text stored in said file, and thus, for the text referenced by any of the pieces; (d) providing a data block for each file that is opened to paste text into the document, said data block including a specifier for an exception code page to be used for any run of text in the file that has a different code page than the default code page for the file in which the run of text is stored, so that the default code page for the file in which the run of text is stored and the data block for the run of text are checked to determine the code page to be applied to all of the characters in said run of text; and (e) when the code page used by any run of text to be displayed is different than the native code page, translating the code page for the characters in the run of text to be displayed to the native code page using a closest available mapping, said code page for the run of text being retained if the document is saved to a file, thereby ensuring that a reference to the code page for any text pasted into the document is not omitted from the file to which the document is saved. 9. The method of claim 8, further comprising the steps of determining if a run of text being saved to a file and previously identified as using an exception code page uses a code page that is the same as the default code page for said file to which the run of text is being saved; and if not, omitting the specifier for said run of text from the data block of said file so that an exception code page for the run of text is not indicated. | 0.831926 |
8,001,100 | 3 | 4 | 3. The computer implemented method of claim 1 , further comprising: responsive to determining from the metadata about the target entity that the disparate multilevel hierarchical knowledge repositories do not comprise entities related to the target entity, creating an entry in the metadata about the target entity for the problem. | 3. The computer implemented method of claim 1 , further comprising: responsive to determining from the metadata about the target entity that the disparate multilevel hierarchical knowledge repositories do not comprise entities related to the target entity, creating an entry in the metadata about the target entity for the problem. 4. The computer implemented method of claim 3 , further comprising: responsive to determining a resolution to the problem, populating the entry with the resolution to the problem. | 0.963736 |
9,218,338 | 11 | 13 | 11. A system comprising: one or more processors configured to perform operations comprising: receiving a text item input by a user to an authoring environment presented on a user device, the text item including one or more words forming a beginning portion of a sentence; determining, by operation of the system, a plurality of text strings using text included in search results received from a search engine, each text string including a matching portion and one or more suffixes, wherein the matching portion matches the text item, and wherein each respective suffix is located after the matching portion; ranking, by operation of the system, the one or more suffixes based on a credibility score calculated for each suffix and a frequency score calculated for each suffix, wherein the credibility score of a particular suffix indicates an estimated credibility of a source of the text string including the suffix, the frequency score of a particular suffix indicates an estimated frequency of appearance of the suffix; and providing one or more of the suffixes based on the ranking for display on the user device as one or more corresponding suggestions for completing the sentence begun by the user input to the authoring environment. | 11. A system comprising: one or more processors configured to perform operations comprising: receiving a text item input by a user to an authoring environment presented on a user device, the text item including one or more words forming a beginning portion of a sentence; determining, by operation of the system, a plurality of text strings using text included in search results received from a search engine, each text string including a matching portion and one or more suffixes, wherein the matching portion matches the text item, and wherein each respective suffix is located after the matching portion; ranking, by operation of the system, the one or more suffixes based on a credibility score calculated for each suffix and a frequency score calculated for each suffix, wherein the credibility score of a particular suffix indicates an estimated credibility of a source of the text string including the suffix, the frequency score of a particular suffix indicates an estimated frequency of appearance of the suffix; and providing one or more of the suffixes based on the ranking for display on the user device as one or more corresponding suggestions for completing the sentence begun by the user input to the authoring environment. 13. The system of claim 11 , configured to perform operations comprising: normalizing the received text item, including tokenizing and synonymizing the text item; and determining the text strings based on the normalized text item. | 0.728132 |
9,367,742 | 14 | 16 | 14. A method performed by an object monitoring apparatus, the method comprising: receiving at least one frame of captured images; generating an edge image by detecting edges of objects appearing in the frame; generating a reference image by detecting a part corresponding to a background in the frame to thereby define the detected part as a background edge, the reference image generated by repeatedly detecting as many as or more than a predetermined number an edge commonly appearing over a plurality of the frames; extracting a candidate object by comparing the edge image with the reference image; and determining whether the candidate object is an object-of-interest. | 14. A method performed by an object monitoring apparatus, the method comprising: receiving at least one frame of captured images; generating an edge image by detecting edges of objects appearing in the frame; generating a reference image by detecting a part corresponding to a background in the frame to thereby define the detected part as a background edge, the reference image generated by repeatedly detecting as many as or more than a predetermined number an edge commonly appearing over a plurality of the frames; extracting a candidate object by comparing the edge image with the reference image; and determining whether the candidate object is an object-of-interest. 16. The method of claim 14 , wherein the determining of whether the candidate object is the object-of-interest comprises determining the candidate object to be the object-of-interest, when the candidate object has pixels exhibiting no change in value differences for longer than a predetermined time period and has a size greater than a preset size. | 0.773964 |
7,756,341 | 5 | 6 | 5. The method according to claim 4 , further comprising: computing key-patches in images of class training sets; computing feature vectors for key-patches of the images of the class training sets; computing the general vocabulary by clustering feature vectors of the images of class training sets; computing each class' adapted vocabulary by estimating occupancy probabilities, of the feature vectors of the images of its class training set, for each class vocabulary. | 5. The method according to claim 4 , further comprising: computing key-patches in images of class training sets; computing feature vectors for key-patches of the images of the class training sets; computing the general vocabulary by clustering feature vectors of the images of class training sets; computing each class' adapted vocabulary by estimating occupancy probabilities, of the feature vectors of the images of its class training set, for each class vocabulary. 6. The method according to claim 5 , further comprising training the classifier with histograms computed for each class by estimating occupancy probabilities, of the feature vectors of images of the class trainings set, for each class vocabulary. | 0.894962 |
8,856,167 | 8 | 9 | 8. The method of claim 7 wherein the request is automatically submitted on behalf of the requesting user in response to a trigger event. | 8. The method of claim 7 wherein the request is automatically submitted on behalf of the requesting user in response to a trigger event. 9. The method of claim 8 wherein the trigger event is the expiration of a time interval. | 0.977722 |
9,741,341 | 14 | 15 | 14. One or more non-transitory computer-readable media storing executable instructions that, when executed by a processor, cause a device to: characterize a speech input based on a dynamic noise adaptation (DNA) model reflecting effects of background noise; characterize the speech input based on a null noise DNA model reflecting a null noise mismatch condition; perform Bayesian model averaging using a first weighting of the DNA model and a second weighting of the null noise DNA model; re-weight the DNA model and the null noise DNA model by adjusting the first weighting to increase a probability of the DNA model predicted by the Bayesian model averaging when the DNA model is more likely than the null noise DNA model to best characterize the speech input; and perform recognition of the speech input using the re-weighted DNA model and the re-weighted null noise DNA model. | 14. One or more non-transitory computer-readable media storing executable instructions that, when executed by a processor, cause a device to: characterize a speech input based on a dynamic noise adaptation (DNA) model reflecting effects of background noise; characterize the speech input based on a null noise DNA model reflecting a null noise mismatch condition; perform Bayesian model averaging using a first weighting of the DNA model and a second weighting of the null noise DNA model; re-weight the DNA model and the null noise DNA model by adjusting the first weighting to increase a probability of the DNA model predicted by the Bayesian model averaging when the DNA model is more likely than the null noise DNA model to best characterize the speech input; and perform recognition of the speech input using the re-weighted DNA model and the re-weighted null noise DNA model. 15. The one or more non-transitory computer-readable media of claim 14 , wherein the executable instructions, when executed by the processor, cause the device to: re-weight the DNA model and the null noise DNA model by adjusting the first weighting to decrease the probability of the DNA model predicted by the Bayesian model averaging when the DNA model is less likely than the null noise DNA model to best characterize the speech input. | 0.681223 |
9,460,214 | 3 | 8 | 3. A method comprising: receiving, through a mobile device, a product search query generated by a user of the mobile device, the product search query including a reference to a stated color wherein the reference to the stated color in the product search query is a keyword in the product search query; communicating the product search query to an online marketplace; receiving received data associated with a plurality of products identified by the online marketplace based on the product search query, the received data including an initial ranking of the plurality of products in response to identification of the reference to the stated color by comparing each term in the product search query with a listing of known color terms and in response to a determination that a cosine similarity between the product search query and an individual product title of at least a portion of the plurality of products is less than a predetermined value, the initial ranking being updated based on a plurality of similarity scores, an individual similarity score of the plurality of similarity scores indicating a color distance of a color pair between an individual reference to the stated color of a plurality of references to a product color of the at least a portion of the plurality of products, the plurality of similarity scores calculated using a color difference formula; and presenting at least a portion of the received data to the user through the mobile device wherein the portion of the received data includes a highest-ranked product based on the product search query and the reference to the stated color in the product search query, and wherein the at least a portion of the received data that is presented to the user is determined by comparing the cosine similarity to the predetermined value. | 3. A method comprising: receiving, through a mobile device, a product search query generated by a user of the mobile device, the product search query including a reference to a stated color wherein the reference to the stated color in the product search query is a keyword in the product search query; communicating the product search query to an online marketplace; receiving received data associated with a plurality of products identified by the online marketplace based on the product search query, the received data including an initial ranking of the plurality of products in response to identification of the reference to the stated color by comparing each term in the product search query with a listing of known color terms and in response to a determination that a cosine similarity between the product search query and an individual product title of at least a portion of the plurality of products is less than a predetermined value, the initial ranking being updated based on a plurality of similarity scores, an individual similarity score of the plurality of similarity scores indicating a color distance of a color pair between an individual reference to the stated color of a plurality of references to a product color of the at least a portion of the plurality of products, the plurality of similarity scores calculated using a color difference formula; and presenting at least a portion of the received data to the user through the mobile device wherein the portion of the received data includes a highest-ranked product based on the product search query and the reference to the stated color in the product search query, and wherein the at least a portion of the received data that is presented to the user is determined by comparing the cosine similarity to the predetermined value. 8. The method of claim 3 wherein the predetermined value is 0.8. | 0.977143 |
9,003,361 | 1 | 5 | 1. A method comprising: receiving user input indicating a plurality of uniform resource identifiers (URIs) for a RESTful (Representational State Transfer) web service; identifying a programming language for a RESTful web service software development kit (SDK) client; creating, by a server computer system, a plurality of methods for the plurality of URIs using programming code format of the identified programming language; creating the RESTful web service SDK client using the plurality of methods; detecting a change in the RESTful web service; identifying one of the plurality of URIs associated with the change; and updating one of the plurality of methods corresponding to the identified URI to reflect the change. | 1. A method comprising: receiving user input indicating a plurality of uniform resource identifiers (URIs) for a RESTful (Representational State Transfer) web service; identifying a programming language for a RESTful web service software development kit (SDK) client; creating, by a server computer system, a plurality of methods for the plurality of URIs using programming code format of the identified programming language; creating the RESTful web service SDK client using the plurality of methods; detecting a change in the RESTful web service; identifying one of the plurality of URIs associated with the change; and updating one of the plurality of methods corresponding to the identified URI to reflect the change. 5. The method of claim 1 , wherein updating the method comprises: creating a new method for the change in the RESTful web service. | 0.90566 |
4,090,173 | 3 | 4 | 3. The apparatus of claim 2 in which said shift register loading means includes a plurality of bit pattern producing means, each corresponding to a different message that can be sent, a different one of said bit pattern producing means enabled by said selection of a desired command. | 3. The apparatus of claim 2 in which said shift register loading means includes a plurality of bit pattern producing means, each corresponding to a different message that can be sent, a different one of said bit pattern producing means enabled by said selection of a desired command. 4. The apparatus of claim 3 in which each of said bit pattern producing means includes a coupling means coupling a selected potential to a word or complement terminal for each bit in said bit pattern, word and complement switching means responsive to said clock for alternately coupling said word or complement terminals to a different selected potential to generate a bit pattern or its complement in response to said clock at terminals of said coupling means. | 0.877067 |
9,400,974 | 8 | 11 | 8. The method of claim 1 further comprising, prior to receiving the user input for adding the electronic signature to the electronic document, generating a user interface that provides the user a plurality of options for entering the electronic signature. | 8. The method of claim 1 further comprising, prior to receiving the user input for adding the electronic signature to the electronic document, generating a user interface that provides the user a plurality of options for entering the electronic signature. 11. The method of claim 8 wherein the plurality of options for entering the electronic signature includes an option for retrieving a signature image previously associated with the user. | 0.961069 |
8,699,794 | 9 | 10 | 9. A computing apparatus comprising a processor and a memory having stored thereon instructions that when executed by the processor, configure the apparatus to perform a method for variably rendering a passage of text, the method comprising: for each glyph of a plurality of glyphs of the passage of text: obtaining a glyph representation corresponding to a current glyph, said glyph representation comprising a set of two dimensional coordinates; and varying said set of two dimensional coordinates according to a geometric transformation to obtain a varied glyph representation, said geometric transformation having been determined from statistical measurements of at least one geometric property from an ensemble of representations of said current glyph; and generating renderable output data comprising each varied glyph representation, such that when the passage of text is rendered to an output device, a given rendered representation of a given glyph subtly differs from other rendered representations of said given glyph according to said at least one geometric property. | 9. A computing apparatus comprising a processor and a memory having stored thereon instructions that when executed by the processor, configure the apparatus to perform a method for variably rendering a passage of text, the method comprising: for each glyph of a plurality of glyphs of the passage of text: obtaining a glyph representation corresponding to a current glyph, said glyph representation comprising a set of two dimensional coordinates; and varying said set of two dimensional coordinates according to a geometric transformation to obtain a varied glyph representation, said geometric transformation having been determined from statistical measurements of at least one geometric property from an ensemble of representations of said current glyph; and generating renderable output data comprising each varied glyph representation, such that when the passage of text is rendered to an output device, a given rendered representation of a given glyph subtly differs from other rendered representations of said given glyph according to said at least one geometric property. 10. The apparatus of claim 9 , wherein varying said set of two dimensional coordinates according to said geometric transformation comprises: determining at least one geometric variation function; and transforming said set of two dimensional coordinates according to said at least one geometric variation function to obtain a variant glyph representation of said current glyph that differs from said glyph representation according to said at least one geometric property. | 0.501062 |
9,996,583 | 1 | 6 | 1. 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 an original recursive expression that defines tuples belonging to an output relation, wherein the original recursive expression has a recursive aggregation construct, the recursive aggregation construct having a range and a recursive term; generating an initial delta expression from the original recursive expression; generating a final delta expression including repeatedly applying one or more differential rules to the initial delta expression, including applying an aggregates delta rule to generate a conjunction of: (i) an existential term having a subterm that is a conjunction of the range and a delta term that is the recursive term of the aggregation construct, and (ii) a gamma term having a subterm that is the aggregation construct; evaluating the original recursive expression on an initial condition to generate one or more tuples; computing an initial delta relation as a difference between the one or more tuples and the initial condition; and until the final delta expression generates no new tuples, performing operations comprising: evaluating the existential term to generate tuples related by the range and tuples in the delta relation, evaluating the aggregation construct using tuples generated by the existential term as the range of the aggregation construct, and updating the output relation including adding to the output relation any tuples newly generated by evaluating the final delta expression. | 1. 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 an original recursive expression that defines tuples belonging to an output relation, wherein the original recursive expression has a recursive aggregation construct, the recursive aggregation construct having a range and a recursive term; generating an initial delta expression from the original recursive expression; generating a final delta expression including repeatedly applying one or more differential rules to the initial delta expression, including applying an aggregates delta rule to generate a conjunction of: (i) an existential term having a subterm that is a conjunction of the range and a delta term that is the recursive term of the aggregation construct, and (ii) a gamma term having a subterm that is the aggregation construct; evaluating the original recursive expression on an initial condition to generate one or more tuples; computing an initial delta relation as a difference between the one or more tuples and the initial condition; and until the final delta expression generates no new tuples, performing operations comprising: evaluating the existential term to generate tuples related by the range and tuples in the delta relation, evaluating the aggregation construct using tuples generated by the existential term as the range of the aggregation construct, and updating the output relation including adding to the output relation any tuples newly generated by evaluating the final delta expression. 6. The system of claim 1 , wherein the original recursive expression defines a height, a depth, or a number of nodes in a tree-structured graph. | 0.850932 |
8,458,111 | 11 | 12 | 11. A computer program product for implementing a method for mapping between a declarative type and a dynamic runtime type, the computer program product comprising one or more physical storage media having stored thereon computer-executable instructions that, when executed by one or more processors of the computing system, cause the computing system to perform the method, the method comprising: an act of a customized declarative language reader accessing an activity that is defined using a declarative language, and that is configured to be executed within a continuation-based runtime, the activity including a fully modeled declarative type written in declarative markup, the declarative type including one or more members which define a data flow for the declarative type, each member being defined within a declarative tag in the declarative markup and including a name and a type of input for the member, wherein the declarative markup also includes an identification of a schema to be used to determine how the fully modeled declarative type is to be interpreted at runtime by the continuation-based runtime including how the one or more members of the declarative type are to be mapped to properties of a dynamic runtime type; an act of the customized declarative language reader creating a dynamic runtime type based on the fully modeled declarative type, creating the dynamic runtime type comprising generating, based on the schema defined in the declarative program, a type in memory without creating a common language runtime type to represent the declarative type; an act of the declarative language reader generating a mapping from the accessed declarative type to the created dynamic runtime type using the mapping schema, generating the mapping including mapping each member of the declarative type to a property of the created dynamic runtime type; and an act of interpretively executing the dynamically constructed dynamic activity type within the continuation-based runtime at a first process, such that the dynamic activity type is executed without compilation, and during execution of the dynamically constructed dynamic activity type: pausing execution of the dynamically constructed dynamic activity type at the first process; and resuming execution of the dynamically constructed dynamic activity type at a second, different process. | 11. A computer program product for implementing a method for mapping between a declarative type and a dynamic runtime type, the computer program product comprising one or more physical storage media having stored thereon computer-executable instructions that, when executed by one or more processors of the computing system, cause the computing system to perform the method, the method comprising: an act of a customized declarative language reader accessing an activity that is defined using a declarative language, and that is configured to be executed within a continuation-based runtime, the activity including a fully modeled declarative type written in declarative markup, the declarative type including one or more members which define a data flow for the declarative type, each member being defined within a declarative tag in the declarative markup and including a name and a type of input for the member, wherein the declarative markup also includes an identification of a schema to be used to determine how the fully modeled declarative type is to be interpreted at runtime by the continuation-based runtime including how the one or more members of the declarative type are to be mapped to properties of a dynamic runtime type; an act of the customized declarative language reader creating a dynamic runtime type based on the fully modeled declarative type, creating the dynamic runtime type comprising generating, based on the schema defined in the declarative program, a type in memory without creating a common language runtime type to represent the declarative type; an act of the declarative language reader generating a mapping from the accessed declarative type to the created dynamic runtime type using the mapping schema, generating the mapping including mapping each member of the declarative type to a property of the created dynamic runtime type; and an act of interpretively executing the dynamically constructed dynamic activity type within the continuation-based runtime at a first process, such that the dynamic activity type is executed without compilation, and during execution of the dynamically constructed dynamic activity type: pausing execution of the dynamically constructed dynamic activity type at the first process; and resuming execution of the dynamically constructed dynamic activity type at a second, different process. 12. The computer program product of claim 11 , wherein the schema for mapping from a declarative type to a dynamic type is swappable. | 0.930801 |
7,665,016 | 7 | 10 | 7. A method of virtually parsing an XML (Extensible Markup Language) document, the method comprising: identifying multiple segments within the document, including an initial segment and a final segment; and for each segment: if the segment is not the initial segment, loading state information saved in connection with the parsing of a previous segment; parsing the segment separately from and independent of other segments of the document; and if the segment is not the final segment, saving state information reflecting the parsing of the segment. | 7. A method of virtually parsing an XML (Extensible Markup Language) document, the method comprising: identifying multiple segments within the document, including an initial segment and a final segment; and for each segment: if the segment is not the initial segment, loading state information saved in connection with the parsing of a previous segment; parsing the segment separately from and independent of other segments of the document; and if the segment is not the final segment, saving state information reflecting the parsing of the segment. 10. The method of claim 7 , further comprising: preloading a symbol table for use during parsing of each segment. | 0.862195 |
10,146,417 | 8 | 13 | 8. In a digital medium environment in which a computing device is configured to use a document viewing application that includes a user interface to enable a user to view a document, one or more computer-readable storage media comprising instructions that are stored thereon that, responsive to execution by the computing device, perform operations comprising: receiving, via the document viewing application, a document that has been shared with multiple users; ascertaining whether crowd-sourced information exists for the document, the crowd-sourced information pertaining to one or more of settings or tools that have been used on the document by the multiple users and including device characteristics associated with devices used to interact with the document; responsive to crowd-sourced information existing for the document: receiving the crowd-sourced information including the device characteristics associated with devices used to interact with the document; ascertaining for the document at least one of the one or more settings or tools that are associated with device characteristics corresponding to the device characteristics of the computing device; and automatically applying the crowd-sourced information to the document to expose the at least one of the one or more of settings or tools. | 8. In a digital medium environment in which a computing device is configured to use a document viewing application that includes a user interface to enable a user to view a document, one or more computer-readable storage media comprising instructions that are stored thereon that, responsive to execution by the computing device, perform operations comprising: receiving, via the document viewing application, a document that has been shared with multiple users; ascertaining whether crowd-sourced information exists for the document, the crowd-sourced information pertaining to one or more of settings or tools that have been used on the document by the multiple users and including device characteristics associated with devices used to interact with the document; responsive to crowd-sourced information existing for the document: receiving the crowd-sourced information including the device characteristics associated with devices used to interact with the document; ascertaining for the document at least one of the one or more settings or tools that are associated with device characteristics corresponding to the device characteristics of the computing device; and automatically applying the crowd-sourced information to the document to expose the at least one of the one or more of settings or tools. 13. The one or more computer-readable storage media of claim 8 , wherein said ascertaining comprises ascertaining whether crowd-sourced information exists at a document level, a page level, or a content level. | 0.785421 |
7,720,883 | 1 | 17 | 1. A computer-implemented system, comprising: a key profile component configured to compute a key strength value of a data table based on a key of the data table, wherein the key of the data table comprises one or more columns of the data table, and wherein the key strength value is defined by a number of distinct values in the one or more columns as a fraction of a number of rows in the data table; and a pattern profile component configured to identify regular expression patterns in the data table as part of a data profile. | 1. A computer-implemented system, comprising: a key profile component configured to compute a key strength value of a data table based on a key of the data table, wherein the key of the data table comprises one or more columns of the data table, and wherein the key strength value is defined by a number of distinct values in the one or more columns as a fraction of a number of rows in the data table; and a pattern profile component configured to identify regular expression patterns in the data table as part of a data profile. 17. The method of claim 1 6 , further comprising: selecting column sets having a predetermined number of columns from the data table; computing a percentage based on the key strength value; and retaining column sets having corresponding key strength values above the percentage. | 0.515679 |
8,256,006 | 1 | 9 | 1. A method of minimizing the risk of theft or disclosure of personally identifiable or sensitive information comprising the steps of: identifying data from a data source in a first stage of a search mechanism performed by a computer, said first stage identifying as potentially sensitive any data from said data source that exhibits any attributes relating to sensitive information; escalating said identified data to at least a second more sensitive stage of said search mechanism, said second stage including the step of scoring said identified data based on minimal information entropy; evaluating any identified data that includes a score beyond a predetermined threshold, said evaluating step utilizing a rule table to determine whether remediation is necessary; and remediating identified data in which remediation is determined to be necessary in said evaluating step; wherein said scoring step includes the step of using an information retrieval tool from the group consisting of Vector Space Models, Latent Semantic Analysis, Latent Dirichlet Allocation and Bayesian Networks to compare attributes of said data to attributes of similar concept data files; wherein said information retrieval tool is Vector Space Models and said step of using Vector Space Models comprises the step of voting by said similar concept data files to determine a classification for said data file; wherein said concept data files include clean data file and target data file classifications; and wherein said voting step further comprises the steps of: determining the N closest concept data files to said data; calculating a value representative of how close each of said N closest concept data files is relative to said data; summing separately values calculated for clean data files and for target data files; and classifying said data as clean or target based upon the relative values of clean data files and target data files obtained in said summing step. | 1. A method of minimizing the risk of theft or disclosure of personally identifiable or sensitive information comprising the steps of: identifying data from a data source in a first stage of a search mechanism performed by a computer, said first stage identifying as potentially sensitive any data from said data source that exhibits any attributes relating to sensitive information; escalating said identified data to at least a second more sensitive stage of said search mechanism, said second stage including the step of scoring said identified data based on minimal information entropy; evaluating any identified data that includes a score beyond a predetermined threshold, said evaluating step utilizing a rule table to determine whether remediation is necessary; and remediating identified data in which remediation is determined to be necessary in said evaluating step; wherein said scoring step includes the step of using an information retrieval tool from the group consisting of Vector Space Models, Latent Semantic Analysis, Latent Dirichlet Allocation and Bayesian Networks to compare attributes of said data to attributes of similar concept data files; wherein said information retrieval tool is Vector Space Models and said step of using Vector Space Models comprises the step of voting by said similar concept data files to determine a classification for said data file; wherein said concept data files include clean data file and target data file classifications; and wherein said voting step further comprises the steps of: determining the N closest concept data files to said data; calculating a value representative of how close each of said N closest concept data files is relative to said data; summing separately values calculated for clean data files and for target data files; and classifying said data as clean or target based upon the relative values of clean data files and target data files obtained in said summing step. 9. The method as claimed in claim 1 wherein said escalating step includes the step of classifying data exhibiting certain attributes as requiring remediation irrespective of said evaluating step. | 0.743421 |
8,285,654 | 1 | 21 | 1. A computer for use in a system capable of providing a personalized performance of at least one story having a predefined timeline, the computer comprising; an input analysis unit operatively coupled to an event details records unit, said computer is configured to support at least one user interface configured to receive the one or more inputs from one or more users, said input analysis unit is configured to parse the one or more received user inputs, to recognize one or more components comprised in said inputs, thus giving rise to actual input components, and to match said actual input components to predefined input components, and said event details records unit is configured to accommodate one or more event detail records comprising at least data related to matching between actual and predefined input components and received from the input analysis unit; and wherein said computer is further configured to modify the predefined story timeline in accordance with a result of processing said one or more event detail records, to generate a performance in accordance with the modified story timeline; and to facilitate providing said generated performance via the user interface. | 1. A computer for use in a system capable of providing a personalized performance of at least one story having a predefined timeline, the computer comprising; an input analysis unit operatively coupled to an event details records unit, said computer is configured to support at least one user interface configured to receive the one or more inputs from one or more users, said input analysis unit is configured to parse the one or more received user inputs, to recognize one or more components comprised in said inputs, thus giving rise to actual input components, and to match said actual input components to predefined input components, and said event details records unit is configured to accommodate one or more event detail records comprising at least data related to matching between actual and predefined input components and received from the input analysis unit; and wherein said computer is further configured to modify the predefined story timeline in accordance with a result of processing said one or more event detail records, to generate a performance in accordance with the modified story timeline; and to facilitate providing said generated performance via the user interface. 21. The computer of claim 1 wherein the provided performance comprises at least one output selected from a group comprising: (a) text output; (b) audio output; (c) video output; (d) speech output; (e) image output. | 0.851801 |
9,460,238 | 1 | 2 | 1. A method for determining a form for a headphone part, the method comprising: receiving data representing at least one ear model; using a data processing device, orienting the at least one ear model within a coordinate system using the data, wherein orienting the at least one ear model is based at least in part on alignment with respect to at least one area of an ear; using the data processing device, determining a representative model from a plurality of oriented ear models including the at least one oriented ear model, the representative model representing a volume of space common to at least two of the oriented ear models; determining at least one of a size and shape of the headphone part based on the representative model; receiving comfort level data for the at least one ear model, wherein the comfort level data is obtainable from prototype testing and indicates a level of comfort associated with at least one location on a surface of an ear; rendering a visualization for the representative model within a computer aided design application; and overlaying the visualization with visual indicators based on the comfort level data for the oriented ear models. | 1. A method for determining a form for a headphone part, the method comprising: receiving data representing at least one ear model; using a data processing device, orienting the at least one ear model within a coordinate system using the data, wherein orienting the at least one ear model is based at least in part on alignment with respect to at least one area of an ear; using the data processing device, determining a representative model from a plurality of oriented ear models including the at least one oriented ear model, the representative model representing a volume of space common to at least two of the oriented ear models; determining at least one of a size and shape of the headphone part based on the representative model; receiving comfort level data for the at least one ear model, wherein the comfort level data is obtainable from prototype testing and indicates a level of comfort associated with at least one location on a surface of an ear; rendering a visualization for the representative model within a computer aided design application; and overlaying the visualization with visual indicators based on the comfort level data for the oriented ear models. 2. The method of claim 1 , wherein the volume of space is a volume of negative space. | 0.952987 |
8,521,718 | 7 | 8 | 7. A system, comprising: one or more computers coupled to a database of web page impressions 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: identifying a first query having first criteria, wherein the first criteria specifies one or more attributes of web page impressions; obtaining a set of web page impressions that satisfy the first query; storing, as a pre-computed response to the first query, an identifier for each web page impression in the set; after storing the pre-computed response to the first query, receiving from a client device a second query having second criteria, wherein the second criteria specifies one or more attributes of web page impressions and wherein a number of second criteria is greater than a number of first criteria; generating a plurality of sub-queries from the second query, the plurality of sub-queries comprising (i) a first sub-query having the first criteria, and (ii) one or more other sub-queries, wherein each of the second criteria is represented in at least one of the plurality of sub-queries; obtaining a response for each of the one or more other sub-queries, from the database of web page impressions, wherein each response comprises identifiers of web page impressions satisfying criteria of the associated sub-query; comparing the pre-computed response to the first query and the responses to the one or more other sub-queries; and providing an answer to the client device based at least in part on comparing the pre-computed response to the first query and the responses to the one or more other sub-queries. | 7. A system, comprising: one or more computers coupled to a database of web page impressions 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: identifying a first query having first criteria, wherein the first criteria specifies one or more attributes of web page impressions; obtaining a set of web page impressions that satisfy the first query; storing, as a pre-computed response to the first query, an identifier for each web page impression in the set; after storing the pre-computed response to the first query, receiving from a client device a second query having second criteria, wherein the second criteria specifies one or more attributes of web page impressions and wherein a number of second criteria is greater than a number of first criteria; generating a plurality of sub-queries from the second query, the plurality of sub-queries comprising (i) a first sub-query having the first criteria, and (ii) one or more other sub-queries, wherein each of the second criteria is represented in at least one of the plurality of sub-queries; obtaining a response for each of the one or more other sub-queries, from the database of web page impressions, wherein each response comprises identifiers of web page impressions satisfying criteria of the associated sub-query; comparing the pre-computed response to the first query and the responses to the one or more other sub-queries; and providing an answer to the client device based at least in part on comparing the pre-computed response to the first query and the responses to the one or more other sub-queries. 8. The system of claim 7 , further comprising identifying the second query as a complex query. | 0.678082 |
8,719,707 | 1 | 2 | 1. A computer-implemented method performed by one or more processors configured with executable instructions to perform acts comprising: receiving, from a user, a query comprising a movie quote; identifying a movie associated with the movie quote; accessing a transcript of the movie; identifying a location within the transcript of the movie that corresponds to the movie quote; and providing a movie trailer for playback in response to the query, the movie trailer comprising a portion of the movie that includes the movie quote. | 1. A computer-implemented method performed by one or more processors configured with executable instructions to perform acts comprising: receiving, from a user, a query comprising a movie quote; identifying a movie associated with the movie quote; accessing a transcript of the movie; identifying a location within the transcript of the movie that corresponds to the movie quote; and providing a movie trailer for playback in response to the query, the movie trailer comprising a portion of the movie that includes the movie quote. 2. The method of claim 1 , further comprising: identifying a first location within the movie prior to the movie quote; identifying a second location within the movie after the movie quote; and creating the movie trailer comprising a portion of the movie between the first location and the second location. | 0.680962 |
8,000,966 | 21 | 22 | 21. A program storage device readable by computer, tangibly embodying a program of instructions executable by the computer to perform a method for speech recognition, said method comprising acts of: A) receiving a spoken phrase; B) applying an acoustic model to the phrase to select proposed words for the phrase; C) determining a structure of the phrase from a beginning of the phrase to a j-th word, wherein j is a positive integer; D) based at least in part on the determined structure of the phrase up to said j-th word, identifying one or multiple partial analysis trees modifying the (j+1)th word; E) predicting said (j+1)th word from the proposed words based on said one or multiple partial analysis trees; F) obtaining a putative sentence structure for the phrase including the predicted (j+1)th word and a probability value for said putative sentence structure; G) increasing j; H) while the j-th word is not a last word of the phrase, repeating steps C-G; I) selecting as speech recognition results for the phrase a sentence structure and a word sequence obtained in steps C-H having maximum probability values; and J) returning said speech recognition results to a user. | 21. A program storage device readable by computer, tangibly embodying a program of instructions executable by the computer to perform a method for speech recognition, said method comprising acts of: A) receiving a spoken phrase; B) applying an acoustic model to the phrase to select proposed words for the phrase; C) determining a structure of the phrase from a beginning of the phrase to a j-th word, wherein j is a positive integer; D) based at least in part on the determined structure of the phrase up to said j-th word, identifying one or multiple partial analysis trees modifying the (j+1)th word; E) predicting said (j+1)th word from the proposed words based on said one or multiple partial analysis trees; F) obtaining a putative sentence structure for the phrase including the predicted (j+1)th word and a probability value for said putative sentence structure; G) increasing j; H) while the j-th word is not a last word of the phrase, repeating steps C-G; I) selecting as speech recognition results for the phrase a sentence structure and a word sequence obtained in steps C-H having maximum probability values; and J) returning said speech recognition results to a user. 22. The program storage device according to claim 21 , wherein: the act D comprises identifying one or more partial analysis trees from the determined structure of the phrase up to the j-th word, and determining which of the one or more partial analysis trees modify the (j+1)th word; and the act E comprises predicting the (j+1)th word based only on those of the one or more partial analysis trees that are determined to modify the (j+1)th word. | 0.590826 |
7,729,919 | 1 | 4 | 1. A computer readable storage medium having instructions that, when implemented on a computer cause the computer to process information, comprising: a VoiceXML module executing a form interpretation algorithm, the VoiceXML module including instructions executed by a processor of the computer in a defined order based on an execution algorithm causing the computer to establish an interactive dialog with a user to complete the form, wherein the VoiceXML module declares a first field and a second field and the instructions process dialog events associated with at least one of recognition, prompting, and messaging events, wherein the form interpretation algorithm is initialized in response to instantiation of the form and the instructions of the VoiceXML module are executed in the defined order for processing prompting events in the dialog; a SALT module having speech application language tags embedded within the VoiceXML module, the SALT module including at least one object having a temporal trigger initializing an operation associated with the instructions of the VoiceXML module during the interaction, wherein the operation initialized by the SALT module comprises at least one, but not all, of recognition, prompting, and messaging events, wherein the temporal trigger of the SALT module initializes a speech recognition event having a plurality of associated grammars, the speech recognition event obtaining a recognition result from the user having a plurality of portions, wherein the speech recognition event initialized by the SALT module associates a first portion of the recognition result with a first grammar of the plurality of grammars completing the first field declared by the VoiceXML module and associates a second portion of the recognition result with a second grammar of the plurality of grammars completing the second field declared by the VoiceXML module; and wherein the execution algorithm of the VoiceXML module automatically invokes the temporal trigger of the SALT module initializing the speech recognition event when the at least one object is encountered and automatically advances to a subsequent instruction in the defined order after completion of the speech recognition event. | 1. A computer readable storage medium having instructions that, when implemented on a computer cause the computer to process information, comprising: a VoiceXML module executing a form interpretation algorithm, the VoiceXML module including instructions executed by a processor of the computer in a defined order based on an execution algorithm causing the computer to establish an interactive dialog with a user to complete the form, wherein the VoiceXML module declares a first field and a second field and the instructions process dialog events associated with at least one of recognition, prompting, and messaging events, wherein the form interpretation algorithm is initialized in response to instantiation of the form and the instructions of the VoiceXML module are executed in the defined order for processing prompting events in the dialog; a SALT module having speech application language tags embedded within the VoiceXML module, the SALT module including at least one object having a temporal trigger initializing an operation associated with the instructions of the VoiceXML module during the interaction, wherein the operation initialized by the SALT module comprises at least one, but not all, of recognition, prompting, and messaging events, wherein the temporal trigger of the SALT module initializes a speech recognition event having a plurality of associated grammars, the speech recognition event obtaining a recognition result from the user having a plurality of portions, wherein the speech recognition event initialized by the SALT module associates a first portion of the recognition result with a first grammar of the plurality of grammars completing the first field declared by the VoiceXML module and associates a second portion of the recognition result with a second grammar of the plurality of grammars completing the second field declared by the VoiceXML module; and wherein the execution algorithm of the VoiceXML module automatically invokes the temporal trigger of the SALT module initializing the speech recognition event when the at least one object is encountered and automatically advances to a subsequent instruction in the defined order after completion of the speech recognition event. 4. The computer readable medium of claim 1 wherein the VoiceXML module declares a first field and a second field and wherein the SALT module initializes a recognition event obtaining speech input from a user and fills the first field with a first portion of the speech input and fills the second field with a second portion of the speech input. | 0.501449 |
8,706,498 | 2 | 3 | 2. The customer contact center system of claim 1 , further comprising a rules database wherein the offer engine is configured to consult the rules database in order to determine whether or not to select and deliver to an agent a script from said library of scripts, said rules database defining when a script should be selected, which script should be selected for delivery to an agent, and when a script should be modified or a new script selected. | 2. The customer contact center system of claim 1 , further comprising a rules database wherein the offer engine is configured to consult the rules database in order to determine whether or not to select and deliver to an agent a script from said library of scripts, said rules database defining when a script should be selected, which script should be selected for delivery to an agent, and when a script should be modified or a new script selected. 3. The customer contact center system of claim 2 , wherein the application server is further configured to send an alert to a supervisor that a live interaction between a customer and an agent should be monitored based upon a detection of one or more keywords, phrases, tones or combination thereof on the voice channel. | 0.903206 |
9,230,024 | 1 | 8 | 1. A computer implemented method comprising: a computer server receiving a search query from a user; the computer server identifying one or more result pages that pertain to the search query; the computer server determining, for each of the one or more result pages, a raw page ranking; the computer server determining a metric of direct evidence of user interest for at least one result page of the one or more result pages which is a result of a mathematical function which expresses how many users historically have visited the at least one result page subtracted from how many users have recently visited the at least one result page all divided by how many users historically have visited the at least one result page; the computer server adjusting the raw page ranking of the at least one result page among the one or more result pages based on the metric of direct evidence of user interest for the at least one result page to produce an adjusted page ranking for the at least one result page; and the computer server presenting, as search results, the at least one result page to the user in accordance with the adjusted page ranking; wherein: determining the metric of direct evidence of user interest for the at least one result page further comprises determining a measure of how often users traverse to or from the at least one result page while browsing. | 1. A computer implemented method comprising: a computer server receiving a search query from a user; the computer server identifying one or more result pages that pertain to the search query; the computer server determining, for each of the one or more result pages, a raw page ranking; the computer server determining a metric of direct evidence of user interest for at least one result page of the one or more result pages which is a result of a mathematical function which expresses how many users historically have visited the at least one result page subtracted from how many users have recently visited the at least one result page all divided by how many users historically have visited the at least one result page; the computer server adjusting the raw page ranking of the at least one result page among the one or more result pages based on the metric of direct evidence of user interest for the at least one result page to produce an adjusted page ranking for the at least one result page; and the computer server presenting, as search results, the at least one result page to the user in accordance with the adjusted page ranking; wherein: determining the metric of direct evidence of user interest for the at least one result page further comprises determining a measure of how often users traverse to or from the at least one result page while browsing. 8. The method of claim 1 , wherein the raw page ranking of the at least one result page is based, at least in part, on how frequently a search query keyword occurs in the at least one result page. | 0.82807 |
9,201,889 | 12 | 19 | 12. A system for searching shared files stored on a general purpose shared storage comprising: a processor; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive a search term in a native search interface of an operating system on a computing device; and perform, on the computing device, a search based on the search term including accessing a search functionality of the general purpose shared storage, wherein the search functionality of the general purpose shared storage uses indexes of the shared files stored on the shared storage and the search functionality updates the indexes of the shared files in response to a processed event stream of update events generated from the shared files, the processed event stream being generated from a stream of update events by performing event filtering, event compression and de-duplication on the stream of update events generated from the shared files of the general purpose shared storage. | 12. A system for searching shared files stored on a general purpose shared storage comprising: a processor; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive a search term in a native search interface of an operating system on a computing device; and perform, on the computing device, a search based on the search term including accessing a search functionality of the general purpose shared storage, wherein the search functionality of the general purpose shared storage uses indexes of the shared files stored on the shared storage and the search functionality updates the indexes of the shared files in response to a processed event stream of update events generated from the shared files, the processed event stream being generated from a stream of update events by performing event filtering, event compression and de-duplication on the stream of update events generated from the shared files of the general purpose shared storage. 19. The system recited in claim 12 , wherein the memory is further configured to provide the processor with instructions which when executed cause the processor to: perform, on the computing device, the search based on the search term including by accessing the search functionality of the shared storage, wherein the search functionality is further configured to update the indexes of the shared files in response to an update event stream that has been filtered to remove duplicate update events. | 0.501002 |
7,801,720 | 4 | 7 | 4. A translation requesting terminal comprising: a communications interface for communicating with a translation server via a network; a replacement rule database storing in advance a minimal semantic unit phrase having a specific property and a substitute phrase having the specific property in association with each other; a first replacing means for replacing the minimal semantic unit phrase in an original text with the substitute phrase stored in association with the minimal semantic unit phrase in the replacement rule database; a translation requesting means for sending the original text, which has been subjected to replacement by the first replacing means, to the translation server via the communications interface; a replacement table updating means for storing in a replacement table a translation of the minimal semantic unit phrase and a translation of the substitute phrase in association with each other; a searching means for searching for the translation of the substitute phrase in the translated text; and a second replacing means for replacing, on the condition that a translation text of the original text sent by the translation requesting means is received from the translation server, the translation of the substitute phrase in the translation text with the translation of the minimal semantic unit phrase which is stored in the replacement table in association with the translation of the substitute phrase, wherein the translation of the substitute phrase stored in the replacement table updating means is visually different from the substitute phrase. | 4. A translation requesting terminal comprising: a communications interface for communicating with a translation server via a network; a replacement rule database storing in advance a minimal semantic unit phrase having a specific property and a substitute phrase having the specific property in association with each other; a first replacing means for replacing the minimal semantic unit phrase in an original text with the substitute phrase stored in association with the minimal semantic unit phrase in the replacement rule database; a translation requesting means for sending the original text, which has been subjected to replacement by the first replacing means, to the translation server via the communications interface; a replacement table updating means for storing in a replacement table a translation of the minimal semantic unit phrase and a translation of the substitute phrase in association with each other; a searching means for searching for the translation of the substitute phrase in the translated text; and a second replacing means for replacing, on the condition that a translation text of the original text sent by the translation requesting means is received from the translation server, the translation of the substitute phrase in the translation text with the translation of the minimal semantic unit phrase which is stored in the replacement table in association with the translation of the substitute phrase, wherein the translation of the substitute phrase stored in the replacement table updating means is visually different from the substitute phrase. 7. The translation requesting terminal according to claim 4 , wherein: the replacement rule base stores a plurality of minimal semantic unit phrases; and the translation requesting terminal further comprises a minimal semantic unit phrase selecting means for letting a user select the specific property of minimal semantic unit phrases to be replaced by the first replacing means. | 0.501312 |
7,555,477 | 8 | 19 | 8. A computerized method for providing relevant paid content, the method comprising: receiving a search request; determining a plurality of contextual uses associated with the search request, wherein contextual uses comprise majority and minority contextual uses associated with the search request; determining type of content suitable to represent each of the determined contextual uses; and identifying at least one paid content relevant for each of the determined contextual uses. | 8. A computerized method for providing relevant paid content, the method comprising: receiving a search request; determining a plurality of contextual uses associated with the search request, wherein contextual uses comprise majority and minority contextual uses associated with the search request; determining type of content suitable to represent each of the determined contextual uses; and identifying at least one paid content relevant for each of the determined contextual uses. 19. The method of claim 8 , wherein the paid content comprises image content. | 0.951266 |
9,389,890 | 1 | 2 | 1. A management process performed by a processor for managing runtime behavior characteristics of types and type members of a computer program in an environment, the computer program having a source code which is written in at least one data-typed programming language, the process comprising the steps of: a management process executed by the processor obtaining from at least one digital storage device a directives document containing human-readable directives which are not interleaved with the computer program source code; and the management process executed by the processor inspecting the directives document for directives, which are in a human-readable format that is also parsable by software, and which include at least one of each of the following runtime behavior characteristic directives: a directive that a type T of the computer program source code is a required type, an optional type, or a prohibited type in the environment, a directive that a type member M of the computer program source code is a required type member, an optional type member, or a prohibited type member in the environment, and a directive that a degree D is enabled or disabled for a type T or a type member M in the environment. | 1. A management process performed by a processor for managing runtime behavior characteristics of types and type members of a computer program in an environment, the computer program having a source code which is written in at least one data-typed programming language, the process comprising the steps of: a management process executed by the processor obtaining from at least one digital storage device a directives document containing human-readable directives which are not interleaved with the computer program source code; and the management process executed by the processor inspecting the directives document for directives, which are in a human-readable format that is also parsable by software, and which include at least one of each of the following runtime behavior characteristic directives: a directive that a type T of the computer program source code is a required type, an optional type, or a prohibited type in the environment, a directive that a type member M of the computer program source code is a required type member, an optional type member, or a prohibited type member in the environment, and a directive that a degree D is enabled or disabled for a type T or a type member M in the environment. 2. The process of claim 1 , wherein at least one of the following occurs: the inspecting step discloses in the directives document at least three runtime behavior characteristic directives; the inspecting step discloses in the directives document at least two kinds of runtime behavior characteristic directives; the inspecting step discloses in the directives document at least one of the following param runtime behavior characteristic directives: a Parameter directive, a TypeParameter directive, or a GenericParameter directive; or the inspecting step discloses in the directives document at least one of the following group runtime behavior characteristic directives: an Application directive, a Library directive, an Assembly directive, or a Namespace directive. | 0.50065 |
9,553,832 | 9 | 11 | 9. An apparatus, comprising: a processor circuit on a device; an application support component operative on the processor circuit to generate an image representing a state of an application and to update the state of the application according to a text command; and a communication component operative on the processor circuit to transmit using a communications protocol over a first messaging channel the image to a messaging client on a client device via a messaging system as an image attachment to a first message, to receive over the first messaging channel a second message from the client device via the messaging system, to determine that a first portion of the second message comprises a text command from a set of available commands for the application and a second portion of the second message comprises text that does not comprise a text command from the set of available commands, to provide the text command of the first portion to the application support component, and to forward automatically the second portion of the message over the first messaging channel to a messaging client on a second client device via the messaging system. | 9. An apparatus, comprising: a processor circuit on a device; an application support component operative on the processor circuit to generate an image representing a state of an application and to update the state of the application according to a text command; and a communication component operative on the processor circuit to transmit using a communications protocol over a first messaging channel the image to a messaging client on a client device via a messaging system as an image attachment to a first message, to receive over the first messaging channel a second message from the client device via the messaging system, to determine that a first portion of the second message comprises a text command from a set of available commands for the application and a second portion of the second message comprises text that does not comprise a text command from the set of available commands, to provide the text command of the first portion to the application support component, and to forward automatically the second portion of the message over the first messaging channel to a messaging client on a second client device via the messaging system. 11. The apparatus of claim 9 , the messaging system comprising one of a text-messaging system, an instant-messaging system, or a social-networking messaging system. | 0.869427 |
7,984,039 | 6 | 7 | 6. A method according to claim 1 , wherein the method includes: determining whether or not to apply the merit score to the results based on a variance of merit scores across the components. | 6. A method according to claim 1 , wherein the method includes: determining whether or not to apply the merit score to the results based on a variance of merit scores across the components. 7. A method according to claim 6 , wherein the merit score is applied if the variance is above a predetermined threshold level. | 0.963124 |
4,679,951 | 13 | 15 | 13. The method of claim 12 wherein the step of selecting a desired character pair from the displayed character pairs includes manually producing by use of the keyboard an indicator for the desired character pair. | 13. The method of claim 12 wherein the step of selecting a desired character pair from the displayed character pairs includes manually producing by use of the keyboard an indicator for the desired character pair. 15. The method of claim 13, wherein the step of selecting, for each quadrant of each ideogrammatic character to be typed in which a characteristic stroke configuration appears, the single keyboard indicium which most closely identifies that stroke configuration, whereby between one and four indicia are combined to provide the identifier for each character. | 0.910634 |
7,707,162 | 9 | 10 | 9. The method of claim 1 , wherein: the plurality of ontologies are scored and the at least one ontology is selected based on the number of semantic elements in the at least one ontology that are found to be relevant to said multimedia artifact. | 9. The method of claim 1 , wherein: the plurality of ontologies are scored and the at least one ontology is selected based on the number of semantic elements in the at least one ontology that are found to be relevant to said multimedia artifact. 10. The method of claim 9 , wherein: the relevance of the plurality of ontologies is determined by respectively selecting one or more semantic elements from the plurality of ontologies, and applying corresponding classes of the one or more semantic elements to said multimedia artifact. | 0.947696 |
9,881,042 | 8 | 10 | 8. A method for determining characteristics of a plurality of people, the method comprising steps of: receiving, by a computer system, information of an individual, the information comprising qualitative data and quantitative data; analyzing, by the computer system, a quantitative data portion of the information; analyzing, by the computer system, a qualitative data portion of the information using sentiment analysis, the sentiment analysis by natural language parsing to separate the qualitative data into parts of speech; calculating, by the computer system, an initial set of scores for a popularity of the individual based on the analysis of the quantitative data and the qualitative data of the information; updating, by the computer system, a ranking for the popularity of the individual in a database based on the initial set of scores, the database configured to provide rankings of a plurality of individuals; determining, by the computer system, after waiting a predetermined amount of time, whether new data has been updated to the information on the computer system; and if new data added has been updated, calculating, by the computer system, an updated set of scores for the information based on the new data, and updating the ranking for the popularity of the individual on the database. | 8. A method for determining characteristics of a plurality of people, the method comprising steps of: receiving, by a computer system, information of an individual, the information comprising qualitative data and quantitative data; analyzing, by the computer system, a quantitative data portion of the information; analyzing, by the computer system, a qualitative data portion of the information using sentiment analysis, the sentiment analysis by natural language parsing to separate the qualitative data into parts of speech; calculating, by the computer system, an initial set of scores for a popularity of the individual based on the analysis of the quantitative data and the qualitative data of the information; updating, by the computer system, a ranking for the popularity of the individual in a database based on the initial set of scores, the database configured to provide rankings of a plurality of individuals; determining, by the computer system, after waiting a predetermined amount of time, whether new data has been updated to the information on the computer system; and if new data added has been updated, calculating, by the computer system, an updated set of scores for the information based on the new data, and updating the ranking for the popularity of the individual on the database. 10. The method of claim 8 , further comprising the steps of: recording in a log file a data retrieval attempt after each time it is determined whether new data has been updated after waiting the predetermined amount of time; and recording in the log file whether each data retrieval attempt was successful or not successful. | 0.765557 |
9,286,414 | 9 | 10 | 9. A computer-implemented data description and data delivery method, comprising: receiving, at a server computer via a network, an annotation of a data source, wherein the annotation comprises an association of a first global term with data for the data source; storing information on a data store, the information including descriptions of the data source, definitions of the first global term, and the annotation; receiving a client query to be run against the data store, the client query requesting an identification of data sources to which a respective vocabulary has been applied; determining, by the server computer, based on information stored in the data store, and in response to the client query, whether the respective vocabulary has been applied to the data source to annotate the data source in accordance with a set of global terms of the respective vocabulary; and providing, by the server computer, a second global term used for data source annotation in response to a query from a client device for global terms related to the first global term. | 9. A computer-implemented data description and data delivery method, comprising: receiving, at a server computer via a network, an annotation of a data source, wherein the annotation comprises an association of a first global term with data for the data source; storing information on a data store, the information including descriptions of the data source, definitions of the first global term, and the annotation; receiving a client query to be run against the data store, the client query requesting an identification of data sources to which a respective vocabulary has been applied; determining, by the server computer, based on information stored in the data store, and in response to the client query, whether the respective vocabulary has been applied to the data source to annotate the data source in accordance with a set of global terms of the respective vocabulary; and providing, by the server computer, a second global term used for data source annotation in response to a query from a client device for global terms related to the first global term. 10. The method of claim 9 , wherein the determining the subset of information includes receiving a third global term and determining data sources that have the third global term associated with the data thereof. | 0.785569 |
10,127,926 | 13 | 15 | 13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause a voice action server to perform operations comprising: receiving (i) audio data representing a voice command spoken by a speaker and (ii) contextual data from a client device of the speaker, the contextual data indicating a status of the client device and providing data values representing contextual signals that can authenticate the speaker without requiring the speaker to provide explicit authentication information; identifying, the speaker from the audio data representing the voice command; selecting a voice action based at least on a transcription of the audio data; selecting a third-party service provider from among a plurality of different third-party service providers, wherein the third-party service provider is selected by obtaining a mapping of voice actions to the plurality of third-party service providers, the mapping indicating that the selected third-party service provider can perform the selected voice action, the selected third-party service provider is configured to perform multiple voice actions, and wherein the selected third-party service provider requires different combinations of input data to perform authentication for at least some of the multiple voice actions; identifying one or more input authentication data types that the selected third-party service provider uses to perform authentication for the selected voice action, wherein the identified one or more input authentication data types for the selected action are different from one or more input data types that the selected third-party service provider uses to perform authentication for at least one other voice action; obtaining, without requiring the speaker to provide explicit authentication information, one or more authentication data values representing contextual signals from the received contextual data that correspond to the identified one or more input authentication data types; and providing, to the third-party service provider over a network, (i) a request to perform the selected voice action and (ii) a speaker identification result determined based on the audio data representing the voice command, and (iii) the obtained one or more authentication data values from the received contextual data, wherein the speaker identification result and the one or more obtained authentication data values enable the selected third-party service provider to authenticate the speaker and perform the selected voice action. | 13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause a voice action server to perform operations comprising: receiving (i) audio data representing a voice command spoken by a speaker and (ii) contextual data from a client device of the speaker, the contextual data indicating a status of the client device and providing data values representing contextual signals that can authenticate the speaker without requiring the speaker to provide explicit authentication information; identifying, the speaker from the audio data representing the voice command; selecting a voice action based at least on a transcription of the audio data; selecting a third-party service provider from among a plurality of different third-party service providers, wherein the third-party service provider is selected by obtaining a mapping of voice actions to the plurality of third-party service providers, the mapping indicating that the selected third-party service provider can perform the selected voice action, the selected third-party service provider is configured to perform multiple voice actions, and wherein the selected third-party service provider requires different combinations of input data to perform authentication for at least some of the multiple voice actions; identifying one or more input authentication data types that the selected third-party service provider uses to perform authentication for the selected voice action, wherein the identified one or more input authentication data types for the selected action are different from one or more input data types that the selected third-party service provider uses to perform authentication for at least one other voice action; obtaining, without requiring the speaker to provide explicit authentication information, one or more authentication data values representing contextual signals from the received contextual data that correspond to the identified one or more input authentication data types; and providing, to the third-party service provider over a network, (i) a request to perform the selected voice action and (ii) a speaker identification result determined based on the audio data representing the voice command, and (iii) the obtained one or more authentication data values from the received contextual data, wherein the speaker identification result and the one or more obtained authentication data values enable the selected third-party service provider to authenticate the speaker and perform the selected voice action. 15. The system of claim 13 , wherein selecting a voice action based at least on a transcription of the audio data comprises: obtaining a set of voice actions, wherein each voice action identifies one or more terms that correspond to that voice action; determining that one or more terms in the transcription match the one or more terms that correspond to the voice action; and in response to determining that the one or more terms in the transcription match the one or more terms that correspond to the voice action, selecting the voice action from among the set of voice actions. | 0.695378 |
9,696,877 | 1 | 4 | 1. A system comprising: one or more processors; and memory having one or more instructions stored thereon that, responsive to execution by the one or more processors, causes the one or more processors to perform operations comprising: presenting, based on a selected character and in a user interface, multiple character strings representing words or later parts of words or acronyms of which the selected character is a part, at least one of the multiple character strings being a multi-string having two or more character strings of the multiple character strings, the multi-string having or completing a long word and at least one of the two or more character strings having or completing a short word, the short word being shorter than the long word and being a constituent part of the long word, the short word and the long word being presented at the same time in the user interface; enabling selection, through the user interface and with a gesture, to select the short word or the long word through selection of one or more of the multiple character strings, wherein the selection of the multiple character string for the short word would be selecting a portion of the multiple character string for the long word; receiving selection, through the user interface, of the short word or the long word of the one of the multiple character strings through the gesture; and providing or presenting the selected short word or long word. | 1. A system comprising: one or more processors; and memory having one or more instructions stored thereon that, responsive to execution by the one or more processors, causes the one or more processors to perform operations comprising: presenting, based on a selected character and in a user interface, multiple character strings representing words or later parts of words or acronyms of which the selected character is a part, at least one of the multiple character strings being a multi-string having two or more character strings of the multiple character strings, the multi-string having or completing a long word and at least one of the two or more character strings having or completing a short word, the short word being shorter than the long word and being a constituent part of the long word, the short word and the long word being presented at the same time in the user interface; enabling selection, through the user interface and with a gesture, to select the short word or the long word through selection of one or more of the multiple character strings, wherein the selection of the multiple character string for the short word would be selecting a portion of the multiple character string for the long word; receiving selection, through the user interface, of the short word or the long word of the one of the multiple character strings through the gesture; and providing or presenting the selected short word or long word. 4. The system as recited in claim 1 , wherein enabling selection through the user interface and with the gesture enables selection through a straight line from a starting point at a key of a gesture-sensitive character-entry interface, the starting point at a tap and ending with the straight line. | 0.651054 |
7,475,017 | 3 | 5 | 3. The method of claim 2 , wherein confirming that the potential call recipient is the intended call recipient using the personal recording made by the potential call recipient further comprises prompting the caller using a combination of the personal recording in which the potential call recipient states his or her name, and the verbal prompt generated from the second source. | 3. The method of claim 2 , wherein confirming that the potential call recipient is the intended call recipient using the personal recording made by the potential call recipient further comprises prompting the caller using a combination of the personal recording in which the potential call recipient states his or her name, and the verbal prompt generated from the second source. 5. The method of claim 3 , wherein the second source is a text-to-speech generated prompt. | 0.964427 |
9,684,644 | 1 | 2 | 1. A method for managing annotations associated with a video, the method comprising: receiving from viewers of a video, a plurality of annotations for each of a plurality of intervals of the video, each interval having a start time and an end time, a content of each annotation of a plurality of the annotations including a plurality of words; forming a plurality of annotation groups by clustering the annotations based on the start times and the end times of the intervals; determining a first annotation group of the plurality of annotations groups having related annotations based at least in part on a comparison of the content of each annotation to determine that the related annotations have at least one identical or similar word; forming a first annotated clip of the video based upon the intervals in the first annotation group; and forming a synoptic annotation for the first annotated clip of the video based on the related annotations in the first annotation group, the synoptic annotation comprising one or more words selected from the related annotations in the first annotation group, the one or more words summarizing the content of the related annotations in the first annotation group. | 1. A method for managing annotations associated with a video, the method comprising: receiving from viewers of a video, a plurality of annotations for each of a plurality of intervals of the video, each interval having a start time and an end time, a content of each annotation of a plurality of the annotations including a plurality of words; forming a plurality of annotation groups by clustering the annotations based on the start times and the end times of the intervals; determining a first annotation group of the plurality of annotations groups having related annotations based at least in part on a comparison of the content of each annotation to determine that the related annotations have at least one identical or similar word; forming a first annotated clip of the video based upon the intervals in the first annotation group; and forming a synoptic annotation for the first annotated clip of the video based on the related annotations in the first annotation group, the synoptic annotation comprising one or more words selected from the related annotations in the first annotation group, the one or more words summarizing the content of the related annotations in the first annotation group. 2. The method of claim 1 , further comprising: receiving a search query including one or more search terms; responsive to receiving the search query, determining that the synoptic annotation matches the one or more search terms; and displaying the identified synoptic annotation and an identifier of the video associated with the identified synoptic annotation. | 0.67062 |
9,298,276 | 11 | 13 | 11. The computing device of claim 10 , wherein the computing device is configured to: compare the plurality of respective characters associated with the plurality of respective keys to at least one string pattern that includes the at least one metacharacter, wherein the at least one string pattern is associated with the category; and identify the category based on determining that the plurality of respective characters matches the at least one string pattern. | 11. The computing device of claim 10 , wherein the computing device is configured to: compare the plurality of respective characters associated with the plurality of respective keys to at least one string pattern that includes the at least one metacharacter, wherein the at least one string pattern is associated with the category; and identify the category based on determining that the plurality of respective characters matches the at least one string pattern. 13. The computing device of claim 11 , wherein the at least one string pattern is a regular expression. | 0.970368 |
9,544,457 | 1 | 8 | 1. An image-reading apparatus that reads an image of a document comprising a Central Processing Unit (CPU) programmed to: determine any one or both of a type of document and a shape of a document; select any one or both of an appropriate document tilt detection method and an appropriate document position detection method according to any one or both of the determined type of document and the determined shape of the document; detect any one or both of a tilt of the document and a position of the document by using the selected detection method; and when clipping is performed by using a detected rectangle, determine whether an occurring lack of a document exceeds a predetermined acceptable level. | 1. An image-reading apparatus that reads an image of a document comprising a Central Processing Unit (CPU) programmed to: determine any one or both of a type of document and a shape of a document; select any one or both of an appropriate document tilt detection method and an appropriate document position detection method according to any one or both of the determined type of document and the determined shape of the document; detect any one or both of a tilt of the document and a position of the document by using the selected detection method; and when clipping is performed by using a detected rectangle, determine whether an occurring lack of a document exceeds a predetermined acceptable level. 8. The image-reading apparatus according to claim 1 , wherein the CPU is further programmed to clip an image of a document according to any one or both of the tilt of the document and the position of the document that are detected by a document detector. | 0.566553 |
8,775,969 | 18 | 22 | 18. The mobile terminal according to claim 15 , wherein the processing apparatus is further configured to determine a sliding direction and a sliding speed in response to the first input, the selection of the first grapheme corresponding to the sliding direction and the sliding speed. | 18. The mobile terminal according to claim 15 , wherein the processing apparatus is further configured to determine a sliding direction and a sliding speed in response to the first input, the selection of the first grapheme corresponding to the sliding direction and the sliding speed. 22. The mobile terminal according to claim 18 , wherein the second grapheme is selected by sliding the second sequence of graphemes along the sliding direction using the sliding speed as an initial sliding speed, and gradually reducing the sliding speed of the second sequence of graphemes. | 0.926694 |
7,685,581 | 1 | 2 | 1. A method of type-checking a code segment written in a programming language comprising: translating the code segment from the programming language to one or more representations of a typed intermediate language, wherein the one or more representations of the typed intermediate language are capable of representing programs written in a plurality of different source languages, and wherein the one or more representations comprise a first object having a known type, and wherein the translating comprises: determining that the first object will be type-checked as an unknown type, and based on the determining, designating the first object as having the unknown type by dropping the known type of the first object and replacing the known type with the unknown type; and type-checking the one or more representations based on a rule set, wherein: the rule set comprises rules for type-checking the type designated as the unknown type, the unknown type indicates that an element of the representation is of a type that is not known, and the first object is type-checked as having an unknown type, based on the designating. | 1. A method of type-checking a code segment written in a programming language comprising: translating the code segment from the programming language to one or more representations of a typed intermediate language, wherein the one or more representations of the typed intermediate language are capable of representing programs written in a plurality of different source languages, and wherein the one or more representations comprise a first object having a known type, and wherein the translating comprises: determining that the first object will be type-checked as an unknown type, and based on the determining, designating the first object as having the unknown type by dropping the known type of the first object and replacing the known type with the unknown type; and type-checking the one or more representations based on a rule set, wherein: the rule set comprises rules for type-checking the type designated as the unknown type, the unknown type indicates that an element of the representation is of a type that is not known, and the first object is type-checked as having an unknown type, based on the designating. 2. The method of claim 1 wherein the rule set is selected from a plurality of rule sets. | 0.915222 |
10,042,846 | 14 | 15 | 14. The computer program product of claim 10 , wherein the language-specific semantic parser comprises a semantic role labeler. | 14. The computer program product of claim 10 , wherein the language-specific semantic parser comprises a semantic role labeler. 15. The computer program product of claim 14 , wherein at least one word contained within the text is identified as an action-inducing word. | 0.962121 |
8,082,264 | 13 | 15 | 13. An apparatus, comprising: a processor; and a memory to store instructions that, when executed by the processor, are operable to: receive an initial portion of a current user query, wherein the initial portion includes a particular string of text; train a model, said training comprising: continuously logging previous user queries; extracting a question from the continuously logged previous user queries; analyzing the extracted question to obtain at least one feature; assigning an intent to the extracted question; and adding an entry to the model and mapping the obtained feature for the extracted question to the assigned intent for the extracted question in the added entry of the model; guess an intent associated with the initial portion of the current user query while a remainder of the current user query is being received, wherein the guess using only the initial portion includes the following operations: extracting at least one feature from the initial portion; comparing, using the processing device, the extracted at least one feature to entries from the model; selecting, using the processing device, at least one entry from the model based on the comparison; and determining the intent for the initial portion of the current user query according to an intent included in the selected entry; wherein the intent guess obtained for the initial portion according to said extracting, said comparing, said selecting, and said determining does not include any portion of the particular text string; and respond to the initial portion of the current user query with the intent guess. | 13. An apparatus, comprising: a processor; and a memory to store instructions that, when executed by the processor, are operable to: receive an initial portion of a current user query, wherein the initial portion includes a particular string of text; train a model, said training comprising: continuously logging previous user queries; extracting a question from the continuously logged previous user queries; analyzing the extracted question to obtain at least one feature; assigning an intent to the extracted question; and adding an entry to the model and mapping the obtained feature for the extracted question to the assigned intent for the extracted question in the added entry of the model; guess an intent associated with the initial portion of the current user query while a remainder of the current user query is being received, wherein the guess using only the initial portion includes the following operations: extracting at least one feature from the initial portion; comparing, using the processing device, the extracted at least one feature to entries from the model; selecting, using the processing device, at least one entry from the model based on the comparison; and determining the intent for the initial portion of the current user query according to an intent included in the selected entry; wherein the intent guess obtained for the initial portion according to said extracting, said comparing, said selecting, and said determining does not include any portion of the particular text string; and respond to the initial portion of the current user query with the intent guess. 15. The apparatus of claim 13 , wherein the at least one feature includes at least one selected from the group comprising query tokens, query token stems, and concepts. | 0.875186 |
9,936,201 | 18 | 24 | 18. A device for coding video data, the device comprising: a memory configured to store the video data; and a video coder in communication with the memory, wherein the video coder is configured to: determine whether a coding unit (CU) depth of a current CU is smaller than a minimal CU depth of one or more neighboring CUs, or whether the CU depth of the current CU is greater than a maximum CU depth of the one or more neighboring CUs; select, as part of an entropy coding process, a context for a syntax element associated with the current CU stored in the memory based on information relating to CU depth of the one or more neighboring CUs relative to the current CU, wherein the information relating to the CU depth of the one or more neighboring CUs relative to the current CU includes whether the CU depth of the current CU is smaller than the minimal CU depth of the one or more neighboring CUs or whether the CU depth of the current CU is greater than the maximum CU depth of the one or more neighboring CUs, wherein the syntax element represents whether the current CU is split into sub-CUs; and entropy code the syntax element based on the selected context. | 18. A device for coding video data, the device comprising: a memory configured to store the video data; and a video coder in communication with the memory, wherein the video coder is configured to: determine whether a coding unit (CU) depth of a current CU is smaller than a minimal CU depth of one or more neighboring CUs, or whether the CU depth of the current CU is greater than a maximum CU depth of the one or more neighboring CUs; select, as part of an entropy coding process, a context for a syntax element associated with the current CU stored in the memory based on information relating to CU depth of the one or more neighboring CUs relative to the current CU, wherein the information relating to the CU depth of the one or more neighboring CUs relative to the current CU includes whether the CU depth of the current CU is smaller than the minimal CU depth of the one or more neighboring CUs or whether the CU depth of the current CU is greater than the maximum CU depth of the one or more neighboring CUs, wherein the syntax element represents whether the current CU is split into sub-CUs; and entropy code the syntax element based on the selected context. 24. The device of claim 18 , wherein the selected context corresponds to a probability value equal to one for the syntax element when the CU depth of the current CU is smaller than the minimal CU depth of the one or more neighboring CUs. | 0.545977 |
8,885,184 | 3 | 6 | 3. The system of claim 1 wherein: the job ticket manager is further operable to generate the first job ticket to include Advanced Function Presentation (AFP) instructions, and to generate the second job ticket to include Job Definition Format (JDF) instructions. | 3. The system of claim 1 wherein: the job ticket manager is further operable to generate the first job ticket to include Advanced Function Presentation (AFP) instructions, and to generate the second job ticket to include Job Definition Format (JDF) instructions. 6. The system of claim 3 wherein: the first job ticket comprises an AFP Form Map; and the job ticket manager is further operable to divide the second job ticket into multiple segments that each include instructions for processing a group of pages of the print data, and to wrap each segment within an Object Container structure of a Medium Map of the AFP Form Map. | 0.744741 |
9,514,223 | 15 | 16 | 15. A non-transitory, computer-readable storage device storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: selecting a hypernym from a hypernym repository; identifying a set of queries, from a query repository, that each include one or more terms that are hyponyms of the selected hypernym; determining a measure of specificity for the selected hypernym based at least on a comparison between (i) a probability distribution for co-occurrence of the one or more terms in the set of queries that are hyponyms of the selected hypernym, and (ii) a background probability distribution for the occurrence of the terms in the set of queries; determining whether the measure of specificity for the selected hypernym satisfies a threshold; and based on determining that the measure of specificity for the selected hypernym satisfies the threshold, determining whether to revise a subsequently received search query that includes one hyponym of the selected hypernym, to include another hyponym of the selected hypernym. | 15. A non-transitory, computer-readable storage device storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: selecting a hypernym from a hypernym repository; identifying a set of queries, from a query repository, that each include one or more terms that are hyponyms of the selected hypernym; determining a measure of specificity for the selected hypernym based at least on a comparison between (i) a probability distribution for co-occurrence of the one or more terms in the set of queries that are hyponyms of the selected hypernym, and (ii) a background probability distribution for the occurrence of the terms in the set of queries; determining whether the measure of specificity for the selected hypernym satisfies a threshold; and based on determining that the measure of specificity for the selected hypernym satisfies the threshold, determining whether to revise a subsequently received search query that includes one hyponym of the selected hypernym, to include another hyponym of the selected hypernym. 16. The computer-readable storage device of claim 15 , wherein determining the measure of specificity for the selected hypernym comprises: determining the probability distribution for co-occurrence of the terms in the set of queries that are hyponyms of the selected hypernym; determining the background probability distribution for the occurrence of the terms in the set of queries; calculating the measure of specificity for the selected hypernym, based on the comparing. | 0.501055 |
9,916,345 | 1 | 7 | 1. A method comprising: receiving, by one or more computing devices, a search query comprising at least one descriptor for an object, wherein the at least one descriptor comprises an image of the object and wherein the object is associated with a given category of objects; comparing, by the one or more computing devices, the at least one descriptor to contents of a three-dimensional (3D) object-data-model database, wherein the contents of the 3D object-data-model database include contents associated with the given category of objects, wherein the 3D object-data-model database further comprises a plurality of 3D object data models that describe the object, and wherein comparing the at least one descriptor to contents of the 3D object-data-model database comprises: based on a respective 3D object data model of the plurality of 3D object data models, generating a set of rendered images that correspond to the respective 3D object data model; comparing the image to the set of rendered images; and based on the comparison of the image to the set of rendered images, determining corresponding 3D object data models from the plurality of 3D object data models, and wherein the 3D object data models that describe the object comprise the corresponding 3D object data models; based on the comparison of the at least one descriptor to contents of the 3D object-data-model database, generating, by the one or more computing devices, a search query result that comprises the corresponding 3D object data models retrieved from the 3D object-data model database that describe the object and associated images that describe the object; arranging in the search query result, by the one or more computing devices, the associated images that describe the object, the corresponding 3D object data models, and the image of the object used to perform the search query, wherein the corresponding 3D object data models are arranged in the search query result in a manner such that the corresponding 3D object data models are moveable inline in the search query result; and providing, by the one or more computing devices, the search query result. | 1. A method comprising: receiving, by one or more computing devices, a search query comprising at least one descriptor for an object, wherein the at least one descriptor comprises an image of the object and wherein the object is associated with a given category of objects; comparing, by the one or more computing devices, the at least one descriptor to contents of a three-dimensional (3D) object-data-model database, wherein the contents of the 3D object-data-model database include contents associated with the given category of objects, wherein the 3D object-data-model database further comprises a plurality of 3D object data models that describe the object, and wherein comparing the at least one descriptor to contents of the 3D object-data-model database comprises: based on a respective 3D object data model of the plurality of 3D object data models, generating a set of rendered images that correspond to the respective 3D object data model; comparing the image to the set of rendered images; and based on the comparison of the image to the set of rendered images, determining corresponding 3D object data models from the plurality of 3D object data models, and wherein the 3D object data models that describe the object comprise the corresponding 3D object data models; based on the comparison of the at least one descriptor to contents of the 3D object-data-model database, generating, by the one or more computing devices, a search query result that comprises the corresponding 3D object data models retrieved from the 3D object-data model database that describe the object and associated images that describe the object; arranging in the search query result, by the one or more computing devices, the associated images that describe the object, the corresponding 3D object data models, and the image of the object used to perform the search query, wherein the corresponding 3D object data models are arranged in the search query result in a manner such that the corresponding 3D object data models are moveable inline in the search query result; and providing, by the one or more computing devices, the search query result. 7. The method of claim 1 , wherein generating the set of rendered images of the respective 3D object data model comprises: determining a number of views that are substantially evenly spaced around the respective 3D object data model; and for respective views of the number of views, generating respective rendered images that correspond to the respective 3D object data model at the respective views. | 0.785408 |
9,256,783 | 6 | 8 | 6. The method of claim 1 , wherein the imaging device comprises a mobile communication device. | 6. The method of claim 1 , wherein the imaging device comprises a mobile communication device. 8. The method of claim 6 , wherein the computing device is remotely located with respect to the mobile communication device and the image of the at least one document containing tax data is transferred to the computing device over a network. | 0.922107 |
8,165,354 | 1 | 12 | 1. A facial recognition system comprising: a face alignment module configured to locate feature points of a face in at least one image using a face alignment model; a signature extractor, implemented by one or more processor-based devices, configured to generate at least one reconstruction error and extract signature features from the face in the at least one image; and a recognizer configured to identify a person from the face in the at least one image based upon a direct combination of the extracted signature features and the at least one reconstruction error. | 1. A facial recognition system comprising: a face alignment module configured to locate feature points of a face in at least one image using a face alignment model; a signature extractor, implemented by one or more processor-based devices, configured to generate at least one reconstruction error and extract signature features from the face in the at least one image; and a recognizer configured to identify a person from the face in the at least one image based upon a direct combination of the extracted signature features and the at least one reconstruction error. 12. The system of claim 1 , wherein the recognizer is an iterative mixture recognizer. | 0.884097 |
7,657,832 | 1 | 5 | 1. A computer-implemented method for correcting an XML electronic document, the XML electronic document having a structure, the method comprising: identifying a validation error in the XML electronic document structure, the validation error being an aspect of the XML electronic document structure that fails to conform to rules of an XML document type definition or an XML schema, the rules being associated with the XML electronic document, the validation error being of a particular kind, wherein identifying the validation error includes building a deterministic finite automation from a content model defined in a document type definition of the XML electronic document and identifying the validation error using the deterministic finite automaton; selecting a suggestion template from among multiple suggestion templates according to the particular kind of the validation error, and using the selected suggestion template to suggest to a user suggested corrections that are predefined in the template for the particular kind of validation error, the selected suggestion template including logic necessary for modifying the XML electronic document structure in conformance with the rules of the XML document type definition or the XML schema, wherein modifying the XML electronic document structure comprises retagging an element in the XML electronic document structure and moving an element from a current location to a new location in the XML electronic document structure; receiving an input selecting one of the suggested corrections; and using the logic in the selected suggestion template to apply the correction selected by the input to the XML electronic document. | 1. A computer-implemented method for correcting an XML electronic document, the XML electronic document having a structure, the method comprising: identifying a validation error in the XML electronic document structure, the validation error being an aspect of the XML electronic document structure that fails to conform to rules of an XML document type definition or an XML schema, the rules being associated with the XML electronic document, the validation error being of a particular kind, wherein identifying the validation error includes building a deterministic finite automation from a content model defined in a document type definition of the XML electronic document and identifying the validation error using the deterministic finite automaton; selecting a suggestion template from among multiple suggestion templates according to the particular kind of the validation error, and using the selected suggestion template to suggest to a user suggested corrections that are predefined in the template for the particular kind of validation error, the selected suggestion template including logic necessary for modifying the XML electronic document structure in conformance with the rules of the XML document type definition or the XML schema, wherein modifying the XML electronic document structure comprises retagging an element in the XML electronic document structure and moving an element from a current location to a new location in the XML electronic document structure; receiving an input selecting one of the suggested corrections; and using the logic in the selected suggestion template to apply the correction selected by the input to the XML electronic document. 5. The method of claim 1 , wherein: identifying an aspect of the XML electronic document structure that fails to conform to rules associated with the XML electronic document includes identifying one or more structural aspects of the XML electronic document that fail to conform to the rules associated with the document; and applying the correction selected by the input includes applying the correction selected by the input to the XML electronic document, thereby bringing the entire XML electronic document into conformance with the rules. | 0.638667 |
7,797,724 | 8 | 9 | 8. A method for securely providing access to a content file, the method comprising the steps of: (a) requesting, by a user via a client device, access to a content file; (b) filtering, by a filtering mechanism, the request by applying pre-determined rules; (c) creating, by a transport mechanism executing on the client device, a document container on the client device; (d) receiving, by the document container from a server, the content file following said filtering; (e) storing, by a storage buffer on the client device, the received content file in a volatile memory element; (f) invoking, by the document container, an application program associated with the content file, the application program providing a set of menu commands for interacting with the application program; and (g) generating, by the document container, a replacement set of menu commands comprising a subset of the set of menu commands provided by the application program. | 8. A method for securely providing access to a content file, the method comprising the steps of: (a) requesting, by a user via a client device, access to a content file; (b) filtering, by a filtering mechanism, the request by applying pre-determined rules; (c) creating, by a transport mechanism executing on the client device, a document container on the client device; (d) receiving, by the document container from a server, the content file following said filtering; (e) storing, by a storage buffer on the client device, the received content file in a volatile memory element; (f) invoking, by the document container, an application program associated with the content file, the application program providing a set of menu commands for interacting with the application program; and (g) generating, by the document container, a replacement set of menu commands comprising a subset of the set of menu commands provided by the application program. 9. The method of claim 8 wherein, said rules are applied based upon a profile of a requesting user. | 0.879562 |
9,679,025 | 1 | 6 | 1. A method for providing search results for a search query, comprising: receiving a search query including an entity and entity type; parsing the entity into semantic components; generating variants based on input from auxiliary information and user configuration information for each of the semantic components; recomposing the entity in different morphological forms from different variants of the semantic components; and presenting at least one morphological form for the entity as a search result. | 1. A method for providing search results for a search query, comprising: receiving a search query including an entity and entity type; parsing the entity into semantic components; generating variants based on input from auxiliary information and user configuration information for each of the semantic components; recomposing the entity in different morphological forms from different variants of the semantic components; and presenting at least one morphological form for the entity as a search result. 6. The method of claim 1 , further comprising recomposing the entity by selectively excluding different semantic components for combining the different variants of the semantic components. | 0.869081 |
8,832,140 | 24 | 25 | 24. The method as described in claim 23 , wherein the salience measure is a normalized clarity value, and wherein the normalized clarity value is generated by accounting for a size of a measured set. | 24. The method as described in claim 23 , wherein the salience measure is a normalized clarity value, and wherein the normalized clarity value is generated by accounting for a size of a measured set. 25. The method as described in claim 24 wherein, for the set of documents S, the normalized clarity value is the number of standard deviations by which the clarity of S exceeds to expected value of the clarity of a set of documents of the same size as S. | 0.946884 |
7,521,622 | 15 | 18 | 15. The system of claim 11 , wherein the classification data processing component is operable to associate ones of the candidate harmonic segments having harmonic content levels satisfying the harmonic content predicate with respective classification records comprising an assignment to a harmonic segment class. | 15. The system of claim 11 , wherein the classification data processing component is operable to associate ones of the candidate harmonic segments having harmonic content levels satisfying the harmonic content predicate with respective classification records comprising an assignment to a harmonic segment class. 18. The system of claim 15 , wherein the classification data processing component additionally is operable to assign each of the candidate harmonic segments having harmonic content levels satisfying the harmonic content predicate to one of a speech segment class and a music segment class based on a classification predicate defining at least one condition on the estimated pitch values. | 0.788986 |
9,141,605 | 1 | 11 | 1. A method for semantic attribution of a request, said method implemented by a processor of a computer system, said method comprising: said processor receiving source data statements for the request; said processor receiving a selection of a domain for the received source data statements; said processor semantically analyzing the received source data statements, said semantically analyzing comprising matching elements in the received source data statements to respective one or more entries in an ontology associated with the selected domain, wherein the ontology comprises items and relationships that define the selected domain, and wherein each element in the received source data statements is a word or a phrase; said processor assigning the one or more entries to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries, wherein the annotation that annotates one matched element of the matched elements is a domain term that expresses that the one matched element is a noun defining a particular domain; said processor saving the annotated elements with the respective annotations; and said processor using the annotations to generate a search query for the request. | 1. A method for semantic attribution of a request, said method implemented by a processor of a computer system, said method comprising: said processor receiving source data statements for the request; said processor receiving a selection of a domain for the received source data statements; said processor semantically analyzing the received source data statements, said semantically analyzing comprising matching elements in the received source data statements to respective one or more entries in an ontology associated with the selected domain, wherein the ontology comprises items and relationships that define the selected domain, and wherein each element in the received source data statements is a word or a phrase; said processor assigning the one or more entries to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries, wherein the annotation that annotates one matched element of the matched elements is a domain term that expresses that the one matched element is a noun defining a particular domain; said processor saving the annotated elements with the respective annotations; and said processor using the annotations to generate a search query for the request. 11. The method of claim 1 , wherein the annotation that annotates one matched element of the matched elements expresses a negation of the one matched element. | 0.938329 |
8,234,114 | 9 | 10 | 9. The system as claimed in claim 8 , wherein said system constructs a forgetting formula and said forgetting formula operates with a timing counter. | 9. The system as claimed in claim 8 , wherein said system constructs a forgetting formula and said forgetting formula operates with a timing counter. 10. The system as claimed in claim 9 , wherein a value of said forgetting formula is obtained via computation of said accumulated teaching result and said difficulty level. | 0.950857 |
9,396,240 | 11 | 15 | 11. A system, comprising: at least one computer interoperably coupled with a memory storage and configured to: receive a request for an input schema to feed to a data specification language (DaSL) and a metadata outline of typed objects exposed by a database view identified in the request, the database view associated with the database selected using a graphical user interface; request extraction of the input schema and metadata outline from the database; create an instance of a DaSL compiler based upon the input schema; generate a DaSL query corresponding to objects selected from the metadata outline, the DaSL query including low-level primitive queries compiled into a computing language construct supported by the database, mapped to a specific DaSL operator, dynamically compiled at query runtime, and executed to retrieve data from the database conforming to the request; request compilation of the DaSL query; receive a calculation plan and topology cursors responsive to the compilation of the DaSL query; and initiate visualization of a dataset responsive to the execution of the calculation plan using the topology cursors. | 11. A system, comprising: at least one computer interoperably coupled with a memory storage and configured to: receive a request for an input schema to feed to a data specification language (DaSL) and a metadata outline of typed objects exposed by a database view identified in the request, the database view associated with the database selected using a graphical user interface; request extraction of the input schema and metadata outline from the database; create an instance of a DaSL compiler based upon the input schema; generate a DaSL query corresponding to objects selected from the metadata outline, the DaSL query including low-level primitive queries compiled into a computing language construct supported by the database, mapped to a specific DaSL operator, dynamically compiled at query runtime, and executed to retrieve data from the database conforming to the request; request compilation of the DaSL query; receive a calculation plan and topology cursors responsive to the compilation of the DaSL query; and initiate visualization of a dataset responsive to the execution of the calculation plan using the topology cursors. 15. The system of claim 11 , further configured to execute the calculation plan in the database. | 0.734807 |
7,624,105 | 26 | 27 | 26. The search engine of claim 21 , wherein: the regular expression further includes an exact pattern; a third of the commands comprises a check string command embodying the exact pattern; and a third of the co-processors is dedicated to execute the check string command to determine whether the input string matches the exact pattern. | 26. The search engine of claim 21 , wherein: the regular expression further includes an exact pattern; a third of the commands comprises a check string command embodying the exact pattern; and a third of the co-processors is dedicated to execute the check string command to determine whether the input string matches the exact pattern. 27. The search engine of claim 26 , wherein: the check string command includes a reference match identification (MID) value identifying the exact pattern; and the third co-processor compares the reference MID value to a plurality of result MID values provided by an external searchable database in response to an exact pattern match operation between the input string and a plurality of exact patterns stored in the searchable database. | 0.792183 |
8,768,868 | 3 | 4 | 3. The system for multi-class classifier threshold-offset estimation as set forth in claim 2 , wherein r′=r+x, where x=(t 12 , t 13 , t 14 , . . . , t 1M , . . . ), and where t denotes a threshold-offset. | 3. The system for multi-class classifier threshold-offset estimation as set forth in claim 2 , wherein r′=r+x, where x=(t 12 , t 13 , t 14 , . . . , t 1M , . . . ), and where t denotes a threshold-offset. 4. The system for multi-class classifier threshold-offset estimation as set forth in claim 3 , wherein the system further performs operation of: generating a vote designating the set of input features as belonging to one object class of each pair of the plurality of object classes M or the other to generate a set of votes; collecting the set of votes to determine which object class of the plurality of object classes M received a majority of the set of votes; classifying the set of input features as belonging to the object class receiving the majority of the set of votes. | 0.78849 |
9,194,001 | 1 | 7 | 1. A method of sequencing comprising: sequencing a plurality of cDNAs, wherein the cDNAs are obtained from a plurality of different sources, and: (a) each of the cDNAs comprises: (i) a tag that indicates from which source a cDNA is derived and (ii) separate from the tag, a binding site for a sequencing primer; (b) the sequencing is done using the sequencing primer; and (c) the cDNAs have been selected from a pooled cDNA sample; to obtain, for each of the sequenced cDNAs, the nucleotide sequence of the tag associated with the cDNA and the nucleotide sequence of at least a portion of a cDNA. | 1. A method of sequencing comprising: sequencing a plurality of cDNAs, wherein the cDNAs are obtained from a plurality of different sources, and: (a) each of the cDNAs comprises: (i) a tag that indicates from which source a cDNA is derived and (ii) separate from the tag, a binding site for a sequencing primer; (b) the sequencing is done using the sequencing primer; and (c) the cDNAs have been selected from a pooled cDNA sample; to obtain, for each of the sequenced cDNAs, the nucleotide sequence of the tag associated with the cDNA and the nucleotide sequence of at least a portion of a cDNA. 7. The method of sequencing of claim 1 , wherein the method further comprises analyzing the sequences to identify a sequence variation. | 0.794833 |
8,856,125 | 1 | 5 | 1. A method performed by data processing apparatus, the method comprising: identifying a non-text content item that is associated with each of a plurality of web pages; receiving label data that includes a set of initial labels for the non-text content item, wherein each initial label includes one or more words; grouping, for each of two or more sets of matching web pages among the plurality of web pages, initial labels that are associated with the set of matching web pages into a label group, the initial labels for different set of matching web pages being grouped to different label groups; grouping different sets of matching labels from the set of initial labels into different label groups; and selecting, as a final label for the non-text content item, an n-gram of one or more words that is included in at least a threshold number of different label groups. | 1. A method performed by data processing apparatus, the method comprising: identifying a non-text content item that is associated with each of a plurality of web pages; receiving label data that includes a set of initial labels for the non-text content item, wherein each initial label includes one or more words; grouping, for each of two or more sets of matching web pages among the plurality of web pages, initial labels that are associated with the set of matching web pages into a label group, the initial labels for different set of matching web pages being grouped to different label groups; grouping different sets of matching labels from the set of initial labels into different label groups; and selecting, as a final label for the non-text content item, an n-gram of one or more words that is included in at least a threshold number of different label groups. 5. The method of claim 1 , further comprising: identifying one or more sets of matching web pages from the plurality of web pages, each set of matching web pages being a two or more web pages that each have a characteristic that matches a characteristic of another web page in the set of matching web pages; and identifying one or more sets of matching labels from the set of initial labels, each set of matching labels including two or more initial labels having at least a threshold measure of similarity. | 0.767004 |
4,849,732 | 26 | 27 | 26. The input device according to claim 16, wherein said device includes labels disposed in close association with a corresponding key, the input values of each of said input means, said input values being viewable while the fingers are in contact with the corresponding key. | 26. The input device according to claim 16, wherein said device includes labels disposed in close association with a corresponding key, the input values of each of said input means, said input values being viewable while the fingers are in contact with the corresponding key. 27. The input device according to claim 26, wherein said labels comprise changeable display means for displaying selected input values of each corresponding input means by the use of a control key. | 0.960154 |
9,582,554 | 1 | 2 | 1. A computer-implemented method, comprising: receiving, by a processor, a table containing a plurality of entries, each entry storing plain text; receiving, by the processor, an entity database containing an entity collection, the entity collection including a plurality of entity tags that belong to a category, wherein an entity tag from the plurality of entity tags is linked with metadata information from an open access database; determining, by the processor, that a set of entries from the plurality of entries belong to the category; matching, by the processor, an entry in the set of entries to the entity tag; linking, by the processor, the entity tag to the entry; searching, by the processor, an available resource other than the open access database to link additional data related to the entry according to the entity tag; selecting the additional data from a canvas overlying the available resource; and enriching, by the processor, the table to include the additional data in a new column. | 1. A computer-implemented method, comprising: receiving, by a processor, a table containing a plurality of entries, each entry storing plain text; receiving, by the processor, an entity database containing an entity collection, the entity collection including a plurality of entity tags that belong to a category, wherein an entity tag from the plurality of entity tags is linked with metadata information from an open access database; determining, by the processor, that a set of entries from the plurality of entries belong to the category; matching, by the processor, an entry in the set of entries to the entity tag; linking, by the processor, the entity tag to the entry; searching, by the processor, an available resource other than the open access database to link additional data related to the entry according to the entity tag; selecting the additional data from a canvas overlying the available resource; and enriching, by the processor, the table to include the additional data in a new column. 2. The computer-implemented method of claim 1 , further comprising: enriching, by the processor, the table with the information from the open access database according to the entity tag. | 0.75718 |
9,779,162 | 8 | 10 | 8. A system comprising: a computer processor; and a non-transitory computer readable medium storing instructions that, when executed by the computer processor, are configured to: receive a request from a user to create a first event in a calendar; create the first event in the calendar; associate one or more types of metadata with the user and the first event; aggregate the one or more types of metadata for the first event to create aggregated metadata; determine an action based on the aggregated metadata; execute the action in a second event subsequent to the first event; responsive to executing the action, receiving a feedback of the user on the second event; determine an effect of executing the action on a goal associated with the user based on the feedback of the user on the second event; responsive to determining the effect of executing the action, determine a suggestion for the user based on the effect of executing the action; and provide the suggestion to the user. | 8. A system comprising: a computer processor; and a non-transitory computer readable medium storing instructions that, when executed by the computer processor, are configured to: receive a request from a user to create a first event in a calendar; create the first event in the calendar; associate one or more types of metadata with the user and the first event; aggregate the one or more types of metadata for the first event to create aggregated metadata; determine an action based on the aggregated metadata; execute the action in a second event subsequent to the first event; responsive to executing the action, receiving a feedback of the user on the second event; determine an effect of executing the action on a goal associated with the user based on the feedback of the user on the second event; responsive to determining the effect of executing the action, determine a suggestion for the user based on the effect of executing the action; and provide the suggestion to the user. 10. The computer-implemented method of claim 8 , wherein the instructions that, when executed by the computer processor, are further configured to receive a custom metadata tag for the first event from the user, the custom metadata tag corresponding to the one or more types of metadata. | 0.687364 |
7,805,397 | 1 | 12 | 1. A fuzzy logic method for reasoning about data, comprising the steps of: (i) accessing the data; (ii) determining a type of the data from a group consisting of numeric, linguistic and a hybrid combination thereof; (iii) selecting a rule for firing based on the determined type of the data; (iv) obtaining fuzzy membership grades; (v) aggregating the fuzzy membership grades by invoking a parametric formulation; (vi) applying a compositional rule of inference parametrically to extract a consequent to obtain a fuzzy output; and (vii) defuzifying the fuzzy output. | 1. A fuzzy logic method for reasoning about data, comprising the steps of: (i) accessing the data; (ii) determining a type of the data from a group consisting of numeric, linguistic and a hybrid combination thereof; (iii) selecting a rule for firing based on the determined type of the data; (iv) obtaining fuzzy membership grades; (v) aggregating the fuzzy membership grades by invoking a parametric formulation; (vi) applying a compositional rule of inference parametrically to extract a consequent to obtain a fuzzy output; and (vii) defuzifying the fuzzy output. 12. The method according to claim 1 , wherein the data is medical data. | 0.898571 |
8,010,367 | 1 | 7 | 1. A method for authenticating a user, comprising: prompting a user for a free-form password in a password establishment dialog; receiving a user utterance; processing the utterance through a speech recognition engine to generate an acoustic baseform; associating the user with the acoustic baseform in a speaker-dependent password recognition grammar; matching, in a password usage dialog, user utterances against the acoustic baseform in the speaker-dependent password recognition grammar associated with the user, the matching thereby verifying both the free-form password and the user that provided the user utterance; and using results from the matching to determine whether to grant the user access to a secure resource. | 1. A method for authenticating a user, comprising: prompting a user for a free-form password in a password establishment dialog; receiving a user utterance; processing the utterance through a speech recognition engine to generate an acoustic baseform; associating the user with the acoustic baseform in a speaker-dependent password recognition grammar; matching, in a password usage dialog, user utterances against the acoustic baseform in the speaker-dependent password recognition grammar associated with the user, the matching thereby verifying both the free-form password and the user that provided the user utterance; and using results from the matching to determine whether to grant the user access to a secure resource. 7. The method of claim 1 , further comprising: determining whether the received utterance is acoustically similar to entries in a pre-existing speech recognition grammar; and when the received utterance is acoustically similar, presenting a notification to that effect to the user and re-prompting the user for a different user utterance. | 0.661323 |
8,849,732 | 1 | 10 | 1. A method for adaptive remote maintenance of rolling stocks, the method comprising: receiving diagnostic information for rolling stock operation; identifying a plurality of events based on a plurality of current rules applied to the diagnostic information, the current rules and corresponding events being for maintenance incidents of the rolling stock; receiving, by a processor, dispensation information showing dispensation of the events relative to the respective current rules, the dispensation corresponding to event validation and event discarding; applying, by the processor, supervised learning to the diagnostic information with the event validation and event discard as ground truth information; and outputting a new rule from the applying of the supervised learning, the new rule being different than any of the current rules. | 1. A method for adaptive remote maintenance of rolling stocks, the method comprising: receiving diagnostic information for rolling stock operation; identifying a plurality of events based on a plurality of current rules applied to the diagnostic information, the current rules and corresponding events being for maintenance incidents of the rolling stock; receiving, by a processor, dispensation information showing dispensation of the events relative to the respective current rules, the dispensation corresponding to event validation and event discarding; applying, by the processor, supervised learning to the diagnostic information with the event validation and event discard as ground truth information; and outputting a new rule from the applying of the supervised learning, the new rule being different than any of the current rules. 10. The method of claim 1 further comprising: performing the identifying for one of the rules before another of the rules based, at least in part, on a relative number of events for the one and the other of the rules. | 0.635906 |
7,750,891 | 17 | 18 | 17. The process of claim 1 , further comprising the step of: providing feedback to a user. | 17. The process of claim 1 , further comprising the step of: providing feedback to a user. 18. The process of claim 17 , wherein the feedback comprises any of visual feedback and audio feedback. | 0.969581 |
9,940,923 | 1 | 2 | 1. An apparatus for wireless communications, said apparatus comprising: a module configured to, when a mobile communications device has been set to a first mode in which said mobile communications device accepts text input instead of speech input, receive text that has been entered by a user of said mobile communications device and to convert the received text to a synthesized speech signal during a call in which a second communications device is configured to receive speech packets, wherein said mobile communications device is settable to a second mode in which said mobile communications device accepts speech input instead of text input; a vocoder configured to encode the synthesized speech signal to produce a plurality of corresponding speech packets; and a transceiver configured to transmit the plurality of corresponding speech packets over a wireless communications link to said second communications device, wherein said module includes a voice synthesizer configured to store characteristics of a voice of the user and to use said stored characteristics to produce the synthesized speech signal, wherein said apparatus is configured to transmit, via said transceiver, an audio notification informing said second communications device that speech from said mobile communications device following said audio notification will be converted from text, and wherein said apparatus is configured to transmit said audio notification prior to transmitting said plurality of corresponding speech packets. | 1. An apparatus for wireless communications, said apparatus comprising: a module configured to, when a mobile communications device has been set to a first mode in which said mobile communications device accepts text input instead of speech input, receive text that has been entered by a user of said mobile communications device and to convert the received text to a synthesized speech signal during a call in which a second communications device is configured to receive speech packets, wherein said mobile communications device is settable to a second mode in which said mobile communications device accepts speech input instead of text input; a vocoder configured to encode the synthesized speech signal to produce a plurality of corresponding speech packets; and a transceiver configured to transmit the plurality of corresponding speech packets over a wireless communications link to said second communications device, wherein said module includes a voice synthesizer configured to store characteristics of a voice of the user and to use said stored characteristics to produce the synthesized speech signal, wherein said apparatus is configured to transmit, via said transceiver, an audio notification informing said second communications device that speech from said mobile communications device following said audio notification will be converted from text, and wherein said apparatus is configured to transmit said audio notification prior to transmitting said plurality of corresponding speech packets. 2. The apparatus according to claim 1 , wherein said module includes a text-to-speech conversion engine configured to convert said received text to a speech signal, and wherein said voice synthesizer is arranged to produce the synthesized speech signal from said speech signal. | 0.760381 |
8,374,850 | 1 | 2 | 1. An apparatus comprising a processor and a memory storing a computer program, the memory and computer program being configured to, with the processor, cause the apparatus to at least: receive text input data; cause the text input data to be displayed; cause a precursor to be defined as one or more words; reference a dictionary containing a plurality of entries, each said entry including an index, and a candidate word; select a list of n-number of candidate words from said dictionary whose index matches the precursor, where n≧1; either: in an instance in which m>n and the precursor comprises two or more words: cause n-number of candidate words from said list of candidate words to be displayed, cause the precursor to be shortened by causing one or more words to be deleted from the precursor, select a supplemental list of candidate words from said dictionary whose index matches the shortened precursor, and cause m−n number or less of said supplemental candidate words to be displayed; or, in an instance in which n>m: cause the precursor to be lengthened by causing one or more words to be added to the precursor, select an alternate list of candidate words from said dictionary whose index matches the lengthened precursor, and cause m-number or less of candidate words from the alternate list to be displayed; and cause a prompt to be displayed, the prompt enabling a user to either select one of the displayed candidate words or enter a desired word; wherein m comprises a maximum number of candidate words capable of being caused to be displayed. | 1. An apparatus comprising a processor and a memory storing a computer program, the memory and computer program being configured to, with the processor, cause the apparatus to at least: receive text input data; cause the text input data to be displayed; cause a precursor to be defined as one or more words; reference a dictionary containing a plurality of entries, each said entry including an index, and a candidate word; select a list of n-number of candidate words from said dictionary whose index matches the precursor, where n≧1; either: in an instance in which m>n and the precursor comprises two or more words: cause n-number of candidate words from said list of candidate words to be displayed, cause the precursor to be shortened by causing one or more words to be deleted from the precursor, select a supplemental list of candidate words from said dictionary whose index matches the shortened precursor, and cause m−n number or less of said supplemental candidate words to be displayed; or, in an instance in which n>m: cause the precursor to be lengthened by causing one or more words to be added to the precursor, select an alternate list of candidate words from said dictionary whose index matches the lengthened precursor, and cause m-number or less of candidate words from the alternate list to be displayed; and cause a prompt to be displayed, the prompt enabling a user to either select one of the displayed candidate words or enter a desired word; wherein m comprises a maximum number of candidate words capable of being caused to be displayed. 2. The apparatus according to claim 1 , wherein said apparatus is caused to, in an initial state, before receiving any text entry, causing the precursor to be initialized by defining the precursor as a predefined word. | 0.883047 |
8,972,434 | 14 | 32 | 14. A computer-implemented method for executing search requests, the method comprising: receiving from a user a search request for travel reservation information, the search request including at least one first constraint to be met by results returned by a search; selecting at least one additional constraint not included in the search request; constructing a first query based on the at least one first constraint and the at least one additional constraint such that fewer search results are obtained in response to executing the first query than would be obtained in response to executing a query constructed without the at least one additional constraint; constructing a second query based on the at least one first search constraint without the at least one additional constraint; wherein the select at least one additional constraint is performed based on an estimated execution time of the first query with the at least one additional constraint; and executing the first query to obtain first phase query results and the second query to obtain second phase query results, wherein the first phase query results and the second phase query results are non-intersecting. | 14. A computer-implemented method for executing search requests, the method comprising: receiving from a user a search request for travel reservation information, the search request including at least one first constraint to be met by results returned by a search; selecting at least one additional constraint not included in the search request; constructing a first query based on the at least one first constraint and the at least one additional constraint such that fewer search results are obtained in response to executing the first query than would be obtained in response to executing a query constructed without the at least one additional constraint; constructing a second query based on the at least one first search constraint without the at least one additional constraint; wherein the select at least one additional constraint is performed based on an estimated execution time of the first query with the at least one additional constraint; and executing the first query to obtain first phase query results and the second query to obtain second phase query results, wherein the first phase query results and the second phase query results are non-intersecting. 32. The computer-implemented method of claim 14 , wherein the executing comprises executing the first query on a first travel reservation information source and executing the second query on the first travel reservation information source. | 0.863584 |
9,990,436 | 1 | 5 | 1. A computer-implemented method for presenting a personalized trends module, comprising: determining first trending topics associated with a user; receiving, via a first network communication, an in-stream feed of second trending topics based on on-line activity, of the user, comprising at least one of a page view, a query, or a click; augmenting a social timeline associated with the user with at least one of the second trending topics to produce an interim list of third trending topics, wherein the social timeline is produced by logging content, retrieved via a second network communication, posted on one or more accounts of the user on one or more social media sites, wherein recently posted content on the social timeline corresponds to a summary of the first trending topics; ranking the third trending topics by source category using a frequency index; selecting a subset of highest ranked third trending topics from a first source category; and controlling a graphical user interface on a computer display to display a personalized trends module highlighting at least some of the subset of the highest ranked third trending topics to distinguish at least some of the subset of the highest ranked third trending topics from one or more other topics by allocating one or more positions to at least some of the subset of the highest ranked third trending topics to customize an online experience of the user with customized trending topics, at least some of the method implemented via a processor device comprising hardware. | 1. A computer-implemented method for presenting a personalized trends module, comprising: determining first trending topics associated with a user; receiving, via a first network communication, an in-stream feed of second trending topics based on on-line activity, of the user, comprising at least one of a page view, a query, or a click; augmenting a social timeline associated with the user with at least one of the second trending topics to produce an interim list of third trending topics, wherein the social timeline is produced by logging content, retrieved via a second network communication, posted on one or more accounts of the user on one or more social media sites, wherein recently posted content on the social timeline corresponds to a summary of the first trending topics; ranking the third trending topics by source category using a frequency index; selecting a subset of highest ranked third trending topics from a first source category; and controlling a graphical user interface on a computer display to display a personalized trends module highlighting at least some of the subset of the highest ranked third trending topics to distinguish at least some of the subset of the highest ranked third trending topics from one or more other topics by allocating one or more positions to at least some of the subset of the highest ranked third trending topics to customize an online experience of the user with customized trending topics, at least some of the method implemented via a processor device comprising hardware. 5. The computer-implemented method of claim 1 further comprising: performing at least one of the receiving, the augmenting, the ranking, the selecting, or the controlling at one or more periodic intervals. | 0.734456 |
7,689,245 | 4 | 5 | 4. A method of multi-modal interaction with a first user and a second user through a wireless device having a language translation application, the method comprising: displaying at the wireless device a list of prioritized target languages associated with a location of the wireless device received via wireless connection, the location detected by a location detection system, when a translation services application is activated on the wireless device; receiving at the wireless device a first message in a first language; providing at the wireless device a first message text in the first language in a first window; upon the first user approval of the first message text, translating at a translation device in a network the first message text into a second language and providing at the wireless device the first message text in a second window in the second language; receiving at the wireless device a second message in the second language; providing at the wireless device a second message text in the second window in the second language; and upon the second user approval of the second message text, translating at the translation device in a wireless network the second message text into the first language and providing the second message text in the first window in the first language, wherein the second language is selectable from the list of prioritized target languages associated with the location of the wireless device. | 4. A method of multi-modal interaction with a first user and a second user through a wireless device having a language translation application, the method comprising: displaying at the wireless device a list of prioritized target languages associated with a location of the wireless device received via wireless connection, the location detected by a location detection system, when a translation services application is activated on the wireless device; receiving at the wireless device a first message in a first language; providing at the wireless device a first message text in the first language in a first window; upon the first user approval of the first message text, translating at a translation device in a network the first message text into a second language and providing at the wireless device the first message text in a second window in the second language; receiving at the wireless device a second message in the second language; providing at the wireless device a second message text in the second window in the second language; and upon the second user approval of the second message text, translating at the translation device in a wireless network the second message text into the first language and providing the second message text in the first window in the first language, wherein the second language is selectable from the list of prioritized target languages associated with the location of the wireless device. 5. The method of multi-modal interaction with a first of claim 4 , wherein the second language is preselected according user and a second user through a wireless device having a language translation application to the location of the device. | 0.502066 |
8,301,995 | 1 | 14 | 1. A method of operating a digital content acquisition device, comprising: a user selects a first annotation stored in the acquisition device that identifies some aspect of at least a first content item to be captured, capture at least the first content item and one or more subsequently captured content items in the acquisition device, associate, within the acquisition device and without user intervention, the first annotation with the first content item, automatically associate, within the acquisition device and without user intervention, the first annotation with any other of the subsequently captured content items until a second annotation stored within the acquisition device that identifies some aspect of at least a second content item to be captured is selected by the user, capture the second content item in the acquisition device, thereafter associate, within the acquisition device and without user intervention, the second annotation with at least the second content item, store data of the captured content items along with the associated first and second annotations and record linking references of the associated annotations into headers of the captured content items; when the acquisition device is turned on, determine whether the acquisition device had been turned off for more than a predetermined time period before the acquisition device being turned on; and if the acquisition device had been turned off for more than the predetermined time period before the acquisition device being turned on, automatically generate an alert of whether to associate a previous annotation with a next content item to be captured, wherein the previous annotation is associated with a last content item captured in the acquisition device before the acquisition device was turned off. | 1. A method of operating a digital content acquisition device, comprising: a user selects a first annotation stored in the acquisition device that identifies some aspect of at least a first content item to be captured, capture at least the first content item and one or more subsequently captured content items in the acquisition device, associate, within the acquisition device and without user intervention, the first annotation with the first content item, automatically associate, within the acquisition device and without user intervention, the first annotation with any other of the subsequently captured content items until a second annotation stored within the acquisition device that identifies some aspect of at least a second content item to be captured is selected by the user, capture the second content item in the acquisition device, thereafter associate, within the acquisition device and without user intervention, the second annotation with at least the second content item, store data of the captured content items along with the associated first and second annotations and record linking references of the associated annotations into headers of the captured content items; when the acquisition device is turned on, determine whether the acquisition device had been turned off for more than a predetermined time period before the acquisition device being turned on; and if the acquisition device had been turned off for more than the predetermined time period before the acquisition device being turned on, automatically generate an alert of whether to associate a previous annotation with a next content item to be captured, wherein the previous annotation is associated with a last content item captured in the acquisition device before the acquisition device was turned off. 14. The method of claim 1 , wherein at least one of the first and second annotations identifies a date at which the respective first or second content items are to be captured. | 0.833017 |
9,959,318 | 1 | 13 | 1. A method comprising, by a computing system: receiving, from a client system of a first user of an online social network, an indication of the first user accessing a query field associated with a currently accessed page of the online social network, the online social network being associated with a plurality of entities, wherein the currently accessed page is a unique profile page of a particular entity of the plurality of entities; identifying the particular entity of the plurality of entities corresponding to the profile page generating one or more structured queries based on the particular entity corresponding to the profile page, each structured query comprising a reference to the particular entity corresponding to the profile page and one or more additional query tokens; and sending, to the client system of the first user, responsive to the user accessing the query field, instructions for displaying one or more suggested queries on the page, wherein the one or more suggested queries correspond to one or more of the structured queries, respectively, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results corresponding to the selected query. | 1. A method comprising, by a computing system: receiving, from a client system of a first user of an online social network, an indication of the first user accessing a query field associated with a currently accessed page of the online social network, the online social network being associated with a plurality of entities, wherein the currently accessed page is a unique profile page of a particular entity of the plurality of entities; identifying the particular entity of the plurality of entities corresponding to the profile page generating one or more structured queries based on the particular entity corresponding to the profile page, each structured query comprising a reference to the particular entity corresponding to the profile page and one or more additional query tokens; and sending, to the client system of the first user, responsive to the user accessing the query field, instructions for displaying one or more suggested queries on the page, wherein the one or more suggested queries correspond to one or more of the structured queries, respectively, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results corresponding to the selected query. 13. The method of claim 1 , further comprising: determining a rank for each structured query; and wherein sending one or more of the structured queries comprises sending each structured query having a rank greater than a threshold rank. | 0.807818 |
9,047,612 | 1 | 5 | 1. A computer-implemented method for managing, via a brand management system (BMS) having a processor and a memory, a plurality of brand item profiles associated with a marketer to be displayed in connection with one or more social media system (SMS) accounts to a plurality of members of one or more SMSs, comprising the steps of: receiving, from a developer via an interface of the BMS, content information to be integrated into a brand item profile of the plurality of brand item profiles associated with the marketer if the content information satisfies a set of predetermined rules, wherein the BMS is different from the one or more SMSs, and wherein the BMS manages content corresponding to multiple SMSs; updating the brand item profile with the content information; using the processor, integrating the brand item profile into a global SMS account, based at least in part upon one or more predetermined content display regions on one or more pages corresponding to the global SMS account, wherein the predetermined content display regions comprise at least one content display region for standardized marketer content and one or more content display regions for brand item profile content; and providing information corresponding to the global SMS account to the respective SMS, such that the one or more pages of the global SMS account, when displayed in response to a request of a member of the respective SMS via a portal of the respective SMS, comprises the standardized marketer content displayed in the at least one content display region for standardized marketer content and the content information associated with the brand item profile displayed in the one or more content display regions for the brand item profile content. | 1. A computer-implemented method for managing, via a brand management system (BMS) having a processor and a memory, a plurality of brand item profiles associated with a marketer to be displayed in connection with one or more social media system (SMS) accounts to a plurality of members of one or more SMSs, comprising the steps of: receiving, from a developer via an interface of the BMS, content information to be integrated into a brand item profile of the plurality of brand item profiles associated with the marketer if the content information satisfies a set of predetermined rules, wherein the BMS is different from the one or more SMSs, and wherein the BMS manages content corresponding to multiple SMSs; updating the brand item profile with the content information; using the processor, integrating the brand item profile into a global SMS account, based at least in part upon one or more predetermined content display regions on one or more pages corresponding to the global SMS account, wherein the predetermined content display regions comprise at least one content display region for standardized marketer content and one or more content display regions for brand item profile content; and providing information corresponding to the global SMS account to the respective SMS, such that the one or more pages of the global SMS account, when displayed in response to a request of a member of the respective SMS via a portal of the respective SMS, comprises the standardized marketer content displayed in the at least one content display region for standardized marketer content and the content information associated with the brand item profile displayed in the one or more content display regions for the brand item profile content. 5. The method of claim 1 , wherein a developer is selected from the group consisting of: an employee of the marketer, an employee of a marketer location, an employee of a third party marketing firm associated with the marketer, a content administrator. | 0.786802 |
8,650,141 | 1 | 4 | 1. An emotional profiling server comprising a non-transitory computer-readable storage medium encoded with databases and modules configured to cause a Central Processor Unit (CPU) to execute predetermined steps, wherein said databases and modules further comprise: a) a media survey module configured to deliver at least one multi-media survey form to a plurality of users and to collect at least one answer from each user; said answer reflecting the emotional reflex of the user; b) a survey result database to store a plurality of survey results, each of said survey result comprising said at least one answer; c) a cluster analysis module configured to perform cluster analysis on said survey result database and produce at least one cluster; d) an emotional profile database that stores at least one emotional profile record wherein said media survey module collects and aggregates a plurality of answers from a plurality of users and stores said answers as survey results to said survey result database; wherein said cluster analysis module: i) performs cluster analysis on said aggregated answer to segregate said plurality of users into clusters, each cluster being a user segment, ii assigns an emotional code to said cluster, and iii)) stores said emotional code and other relevant cluster information as an emotional profile record in said emotional profile database. | 1. An emotional profiling server comprising a non-transitory computer-readable storage medium encoded with databases and modules configured to cause a Central Processor Unit (CPU) to execute predetermined steps, wherein said databases and modules further comprise: a) a media survey module configured to deliver at least one multi-media survey form to a plurality of users and to collect at least one answer from each user; said answer reflecting the emotional reflex of the user; b) a survey result database to store a plurality of survey results, each of said survey result comprising said at least one answer; c) a cluster analysis module configured to perform cluster analysis on said survey result database and produce at least one cluster; d) an emotional profile database that stores at least one emotional profile record wherein said media survey module collects and aggregates a plurality of answers from a plurality of users and stores said answers as survey results to said survey result database; wherein said cluster analysis module: i) performs cluster analysis on said aggregated answer to segregate said plurality of users into clusters, each cluster being a user segment, ii assigns an emotional code to said cluster, and iii)) stores said emotional code and other relevant cluster information as an emotional profile record in said emotional profile database. 4. The server according to claim 1 wherein said multi-media object further comprises non-textual objects, check boxes, radio buttons or any combination thereof; said non-textual objects comprising images, photographs, video clips, audio files, or any combination thereof. | 0.748609 |
8,538,704 | 1 | 2 | 1. A method, implemented by a computing device, in a healthcare information technology system for providing inferred genetic findings for a person, the method comprising: receiving a request issued by a user for genetic test results for a subject gene for a person; incident to receiving the request, accessing a first data store to discover whether there exists the genetic test results for the person; and when the genetic test results of the person are undiscovered, automatically inferring, at the computing device, one or more genetic findings, wherein the process of inferring comprises: (a) accessing an inference table that associates genes with a plurality of modes of inheritance; (b) identifying a mode of inheritance associated with the subject gene by querying the inference table with the subject gene; (c) determining a traversal pattern of the subject gene within a family of the person as a function of the identified mode of inheritance; (d) employing the traversal pattern to target at least one member of the family of the person that potentially carries the subject gene; (e) accessing a second data store to discover whether there exists genetic test results for the at least one targeted member of the person's family; and (f) when the genetic test results of the at least one targeted member of the person's family are discovered, calculating a probability that the person exhibits a mutated form of the subject gene using the genetic test results of the at least one targeted member of the person's family. | 1. A method, implemented by a computing device, in a healthcare information technology system for providing inferred genetic findings for a person, the method comprising: receiving a request issued by a user for genetic test results for a subject gene for a person; incident to receiving the request, accessing a first data store to discover whether there exists the genetic test results for the person; and when the genetic test results of the person are undiscovered, automatically inferring, at the computing device, one or more genetic findings, wherein the process of inferring comprises: (a) accessing an inference table that associates genes with a plurality of modes of inheritance; (b) identifying a mode of inheritance associated with the subject gene by querying the inference table with the subject gene; (c) determining a traversal pattern of the subject gene within a family of the person as a function of the identified mode of inheritance; (d) employing the traversal pattern to target at least one member of the family of the person that potentially carries the subject gene; (e) accessing a second data store to discover whether there exists genetic test results for the at least one targeted member of the person's family; and (f) when the genetic test results of the at least one targeted member of the person's family are discovered, calculating a probability that the person exhibits a mutated form of the subject gene using the genetic test results of the at least one targeted member of the person's family. 2. The method of claim 1 , wherein discovering whether there exists the genetic test results for the person comprises searching an electronic medical record (EMR) developed for the person. | 0.811623 |
8,588,825 | 16 | 17 | 16. The user device of claim 10 , wherein the instructions comprise instructions to: receive, via the communication interface, a text message; determine whether the received text message includes metadata, wherein the metadata indicates that the received text message includes text enhancements; interpret a meaning of the received text message when the received text message does not include the metadata; display, via the display, the text message with text enhancements based on the meaning of the received text message. | 16. The user device of claim 10 , wherein the instructions comprise instructions to: receive, via the communication interface, a text message; determine whether the received text message includes metadata, wherein the metadata indicates that the received text message includes text enhancements; interpret a meaning of the received text message when the received text message does not include the metadata; display, via the display, the text message with text enhancements based on the meaning of the received text message. 17. The user device of claim 16 , wherein the instructions comprise instructions to: select a classification for the received text message based on the meaning of the received text message; and select text enhancements based on the classification of the received text message. | 0.873857 |
7,827,177 | 1 | 5 | 1. A computer implemented method comprising: accessing compound document declarations that specify how to section a given XML document into subdocuments of a compound document; one or more computing devices generating a compound document that includes a parent document and a plurality of subdocuments of said parent document; wherein content of said parent document includes for each subdocument of said plurality of subdocuments, a link to said each subdocument; and wherein generating said compound document includes applying said compound document declarations to a source XML document to generate said parent document and said plurality of subdocuments of said parent document. | 1. A computer implemented method comprising: accessing compound document declarations that specify how to section a given XML document into subdocuments of a compound document; one or more computing devices generating a compound document that includes a parent document and a plurality of subdocuments of said parent document; wherein content of said parent document includes for each subdocument of said plurality of subdocuments, a link to said each subdocument; and wherein generating said compound document includes applying said compound document declarations to a source XML document to generate said parent document and said plurality of subdocuments of said parent document. 5. The computer-implemented method of claim 1 , wherein said compound document declarations include a certain instruction that specifies how to generate at least one of a subdocument name or subdocument resource path. | 0.843434 |
7,548,848 | 1 | 3 | 1. A method for evaluating contents of a message, comprising: characterizing a message segment, wherein the message segment further comprises a packet in a packet-switched network; scanning the message segment to define a stream of tokens associated with the message segment; associating the message segment with a meta session through the stream of tokens, wherein the meta session is made persistent across message transactions and different HTTP sessions by storing data generated by the meta session on a persistent storage medium; parsing the token stream to extract substructures according to a grammar; determining rules associated with the tokens, the rules when executed defining actions for intrusion detection and prevention; executing the actions associated with the message segment; and queuing the message segment for transmission to a destination, wherein each of the operations in the method is executed by an integrated circuit. | 1. A method for evaluating contents of a message, comprising: characterizing a message segment, wherein the message segment further comprises a packet in a packet-switched network; scanning the message segment to define a stream of tokens associated with the message segment; associating the message segment with a meta session through the stream of tokens, wherein the meta session is made persistent across message transactions and different HTTP sessions by storing data generated by the meta session on a persistent storage medium; parsing the token stream to extract substructures according to a grammar; determining rules associated with the tokens, the rules when executed defining actions for intrusion detection and prevention; executing the actions associated with the message segment; and queuing the message segment for transmission to a destination, wherein each of the operations in the method is executed by an integrated circuit. 3. The method of claim 1 , wherein the message segment is received from a sender, the sender using a network to send a message associated with the message segment, and the message associated with the message segment is identified as a suspect message which is quarantined. | 0.797619 |
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