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8,843,490 | 9 | 10 | 9. The method of claim 8 , further comprising extending a constraint language for constraint clustering, wherein constraints for the constraint clustering are defined in a form of must-link or cannot-link pairs. | 9. The method of claim 8 , further comprising extending a constraint language for constraint clustering, wherein constraints for the constraint clustering are defined in a form of must-link or cannot-link pairs. 10. The method of claim 9 , further comprising extending the constraint language so that the constraints are assigned confidence scores. | 0.5 |
8,126,712 | 1 | 16 | 1. An information communication terminal configured to exchange at least speech information with a plurality of information communication terminals, comprising: a speech recognition module configured to recognize the speech information to identify a plurality of words based on the recognized speech information; a storage medium configured to store keyword extraction condition setting data in which conditions for extracting keywords are set; a keyword extraction module configured to read the keyword extraction condition setting data to extract a plurality of keywords from the plurality of words; a subject extraction processing module configured to: associate the plurality of words read by the keyword extraction module with knowledge network data in which the plurality of keywords and a route among the plurality of keywords are described in a network form, generate a plurality of word pairs in a predetermined order from the plurality of keywords, extract the shortest route connecting words in each word pair from the knowledge network data, give point values to each word on each of the shortest routes, count the point values given to the respective words, and extract a word having a relatively high point value as a subject word; a related information acquisition module configured to acquire related information related to the plurality of keywords; and a related information output module configured to provide the related information to a monitor. | 1. An information communication terminal configured to exchange at least speech information with a plurality of information communication terminals, comprising: a speech recognition module configured to recognize the speech information to identify a plurality of words based on the recognized speech information; a storage medium configured to store keyword extraction condition setting data in which conditions for extracting keywords are set; a keyword extraction module configured to read the keyword extraction condition setting data to extract a plurality of keywords from the plurality of words; a subject extraction processing module configured to: associate the plurality of words read by the keyword extraction module with knowledge network data in which the plurality of keywords and a route among the plurality of keywords are described in a network form, generate a plurality of word pairs in a predetermined order from the plurality of keywords, extract the shortest route connecting words in each word pair from the knowledge network data, give point values to each word on each of the shortest routes, count the point values given to the respective words, and extract a word having a relatively high point value as a subject word; a related information acquisition module configured to acquire related information related to the plurality of keywords; and a related information output module configured to provide the related information to a monitor. 16. The information communication terminal according to claim 1 , wherein the subject extraction processing module reads a previously set threshold value to extract a word having the point equal to or higher than a threshold value. | 0.838008 |
9,918,745 | 1 | 6 | 1. A medical implant assembly for securing an elongate rod to a bone, the medical implant assembly comprising: a shank with a lower body portion for fixation to the bone and an integral upper portion having a top radiused surface above a hemisphere thereof and a capture structure thereon; a receiver having a base and a pair of upright arms extending upward from the base with opposed interior surfaces that define an open channel for receiving the elongate rod, the arm interior surfaces having a closure top mating feature formed thereon, the base defining a chamber in communication with the open channel and having an upper capture region, a lower locking region, and a lower opening in communication with a bottom surface of the receiver, the receiver including an interference engagement surface between the lower opening and the closure top mating feature; an insert positioned within the receiver prior to the shank and configured to engage the elongate rod when the elongate rod is received within the open channel, the insert being positioned in the receiver entirely above the receiver chamber upper capture region and initially being prevented from moving downwardly within the receiver by the interference engagement surface, the insert having a central opening: a retainer positioned in the receiver chamber prior to the shank, the retainer capturing the shank upper portion capture structure within the receiver chamber upper capture region when the shank is uploaded through the receiver lower opening, wherein after the shank upper portion is captured by the retainer, the insert is forced downwardly within the receiver by a tool into engagement with the interference engagement surface so as to prevent the insert from moving back up within the receiver, and wherein the shank has pivotal motion in only one plane with respect to the receiver prior to locking of the medical implant assembly. | 1. A medical implant assembly for securing an elongate rod to a bone, the medical implant assembly comprising: a shank with a lower body portion for fixation to the bone and an integral upper portion having a top radiused surface above a hemisphere thereof and a capture structure thereon; a receiver having a base and a pair of upright arms extending upward from the base with opposed interior surfaces that define an open channel for receiving the elongate rod, the arm interior surfaces having a closure top mating feature formed thereon, the base defining a chamber in communication with the open channel and having an upper capture region, a lower locking region, and a lower opening in communication with a bottom surface of the receiver, the receiver including an interference engagement surface between the lower opening and the closure top mating feature; an insert positioned within the receiver prior to the shank and configured to engage the elongate rod when the elongate rod is received within the open channel, the insert being positioned in the receiver entirely above the receiver chamber upper capture region and initially being prevented from moving downwardly within the receiver by the interference engagement surface, the insert having a central opening: a retainer positioned in the receiver chamber prior to the shank, the retainer capturing the shank upper portion capture structure within the receiver chamber upper capture region when the shank is uploaded through the receiver lower opening, wherein after the shank upper portion is captured by the retainer, the insert is forced downwardly within the receiver by a tool into engagement with the interference engagement surface so as to prevent the insert from moving back up within the receiver, and wherein the shank has pivotal motion in only one plane with respect to the receiver prior to locking of the medical implant assembly. 6. The medical implant assembly of claim 1 , wherein the receiver has an internal frusto-conical surface above the lower opening so as to create a temporary friction fit between the receiver and the shank prior to locking of the medical implant assembly. | 0.73922 |
8,078,638 | 15 | 16 | 15. A tangible non-transitory machine-readable medium having information stored thereon, wherein the information, when read by a machine, causes the machine to perform the following: access a first table corresponding to a first set of data, wherein the first set of data contains a first plurality of name-value pairs organized in a multi-level nested structure and represented using a first format with a first syntax, the first table has at least one row and each row has at least one field, and the first table corresponds to a name-value pair from the first set of data that is located at two levels outside an innermost level, each row of the first table corresponds to a name-value pair nested immediately within the name-value pair corresponding to the first table, and each field of a row corresponds to a name-value pair nested immediately within the name-value pair corresponding to the row; access at least a second table corresponding to a second set of data, wherein the second set of data contains a second plurality of name-value pairs organized in a multi-level nested structure and represented using a second format with a second syntax, the second table has at least one row and each row has at least one field, and the second table corresponds to a name-value pair from the second set of data that is located at two levels outside the innermost level, each row of the second table corresponds to a name-value pair nested immediately within the name-value pair corresponding to the second table, and each field of a row corresponds to a name-value pair nested immediately within the name-value pair corresponding to the row; join at least the first table and the second table according to a join predicate to obtain a third table, such that a row from the first table and a row from the second table are combined to form a row in the third table if the row from the first table and the row from the second table both satisfy the join predicate; and automatically resolve any namespace conflict when joining the first table and the second table, such that if a field from a first row from the first table and a field from a second row from the second table have the same name and the first row and the second row are to be combined, then the field from the first row is automatically qualified with a name of the first table and the field from the second row is automatically qualified with a name of the second table. | 15. A tangible non-transitory machine-readable medium having information stored thereon, wherein the information, when read by a machine, causes the machine to perform the following: access a first table corresponding to a first set of data, wherein the first set of data contains a first plurality of name-value pairs organized in a multi-level nested structure and represented using a first format with a first syntax, the first table has at least one row and each row has at least one field, and the first table corresponds to a name-value pair from the first set of data that is located at two levels outside an innermost level, each row of the first table corresponds to a name-value pair nested immediately within the name-value pair corresponding to the first table, and each field of a row corresponds to a name-value pair nested immediately within the name-value pair corresponding to the row; access at least a second table corresponding to a second set of data, wherein the second set of data contains a second plurality of name-value pairs organized in a multi-level nested structure and represented using a second format with a second syntax, the second table has at least one row and each row has at least one field, and the second table corresponds to a name-value pair from the second set of data that is located at two levels outside the innermost level, each row of the second table corresponds to a name-value pair nested immediately within the name-value pair corresponding to the second table, and each field of a row corresponds to a name-value pair nested immediately within the name-value pair corresponding to the row; join at least the first table and the second table according to a join predicate to obtain a third table, such that a row from the first table and a row from the second table are combined to form a row in the third table if the row from the first table and the row from the second table both satisfy the join predicate; and automatically resolve any namespace conflict when joining the first table and the second table, such that if a field from a first row from the first table and a field from a second row from the second table have the same name and the first row and the second row are to be combined, then the field from the first row is automatically qualified with a name of the first table and the field from the second row is automatically qualified with a name of the second table. 16. The medium of claim 15 , wherein the information, when read by the machine, causes the machine to further perform the following: convert the first set of data into the first table; and convert the second set of data into the second table, wherein the first set of data and the second set of data are converted into the first table and the second table respectively without relying on any schema for the first syntax and the second syntax. | 0.5 |
8,458,208 | 7 | 8 | 7. The method of claim 1 , further comprising: forwarding the database query comprising the logical database table identifier, the data element, and the at least one data source assurance indicator to at least one additional distributed database device within the distributed network of databases; receiving at least one distributed query response comprising a distributed database device node identifier and an additional encrypted data element associated with data returned from each distributed database device that processed the database query; and determining authenticity of each distributed database device that processed the database query based upon the additional encrypted data element and the distributed database device node identifier associated with each distributed database device that processed the database query. | 7. The method of claim 1 , further comprising: forwarding the database query comprising the logical database table identifier, the data element, and the at least one data source assurance indicator to at least one additional distributed database device within the distributed network of databases; receiving at least one distributed query response comprising a distributed database device node identifier and an additional encrypted data element associated with data returned from each distributed database device that processed the database query; and determining authenticity of each distributed database device that processed the database query based upon the additional encrypted data element and the distributed database device node identifier associated with each distributed database device that processed the database query. 8. The method of claim 7 , where determining the authenticity of each distributed database device that processed the database query comprises selecting a public encryption key using the associated distributed database device node identifier for each distributed database device that processed the database query and decrypting the associated additional encrypted data element using the selected public encryption key for each distributed database device that processed the database query. | 0.720504 |
8,494,850 | 1 | 3 | 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 speech data and data indicating a candidate transcription for the speech data; accessing a phonetic representation for the candidate transcription; extracting, from the phonetic representation, multiple test sequences for a particular phone in the phonetic representation, each of the multiple test sequences including a different set of contextual phones surrounding the particular phone; receiving data indicating that an acoustic model includes data corresponding to one or more of the multiple test sequences; selecting, from among the one or more test sequences for which the acoustic model includes data, the test sequence that includes the highest number of contextual phones, the selected test sequence including fewer than a predetermined maximum number of contextual phones; accessing data from the acoustic model corresponding to the selected test sequence; and generating a score for the candidate transcription based on the accessed data from the acoustic model that corresponds to the selected test sequence, wherein generating the score comprises: determining a penalty based on the selected test sequence including fewer than the predetermined maximum number of contextual phones; and adjusting a first score for the candidate transcription based on the penalty to generate an adjusted score, the adjusted score indicating a lower likelihood than the first score that the candidate transcription is an accurate transcription for the speech data. | 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 speech data and data indicating a candidate transcription for the speech data; accessing a phonetic representation for the candidate transcription; extracting, from the phonetic representation, multiple test sequences for a particular phone in the phonetic representation, each of the multiple test sequences including a different set of contextual phones surrounding the particular phone; receiving data indicating that an acoustic model includes data corresponding to one or more of the multiple test sequences; selecting, from among the one or more test sequences for which the acoustic model includes data, the test sequence that includes the highest number of contextual phones, the selected test sequence including fewer than a predetermined maximum number of contextual phones; accessing data from the acoustic model corresponding to the selected test sequence; and generating a score for the candidate transcription based on the accessed data from the acoustic model that corresponds to the selected test sequence, wherein generating the score comprises: determining a penalty based on the selected test sequence including fewer than the predetermined maximum number of contextual phones; and adjusting a first score for the candidate transcription based on the penalty to generate an adjusted score, the adjusted score indicating a lower likelihood than the first score that the candidate transcription is an accurate transcription for the speech data. 3. The system of claim 1 , wherein extracting multiple test sequences for the particular phone comprises extracting one or more asymmetric test sequences that include asymmetric numbers of contextual phones before and after the particular phone. | 0.873971 |
7,983,478 | 1 | 3 | 1. A method for handwritten character generation, implemented at least in part by a computing device, the method comprising: receiving a character; and generating a corresponding handwritten character using Hidden Markov Models trained to generate handwritten characters, the generating including using a Multi-Space Probability Distribution technique that includes a probability for determining whether a stroke is real or imaginary. | 1. A method for handwritten character generation, implemented at least in part by a computing device, the method comprising: receiving a character; and generating a corresponding handwritten character using Hidden Markov Models trained to generate handwritten characters, the generating including using a Multi-Space Probability Distribution technique that includes a probability for determining whether a stroke is real or imaginary. 3. The method of claim 1 , wherein the Hidden Markov Models comprise Hidden Markov Models trained using slope, curvature and imaginary stroke features. | 0.724453 |
9,613,030 | 7 | 13 | 7. A method for translating between languages, comprising: receiving, by a user device using a microphone, an audible phrase spoken in a first language; performing, by the user device, a voice recognition process to convert the audible phrase into a plurality of text in the first language; providing for display, by the user device on a display device when the user device is in a first orientation, the plurality of text in the first language and in a first directional reading format; detecting, by the user device using an orientation detection device, a reorientation of the user device from the first orientation to a predefined orientation of the user device that is rotated relative to the first orientation; translating, by the user device in response to the detecting of the reorientation to the predefined orientation, the plurality of text from the first language to a second language; and providing for display, by the user device on the display device in response to the detecting of the reorientation to the predefined orientation, the plurality of text in the second language and a second directional reading format that is different than the first directional reading format. | 7. A method for translating between languages, comprising: receiving, by a user device using a microphone, an audible phrase spoken in a first language; performing, by the user device, a voice recognition process to convert the audible phrase into a plurality of text in the first language; providing for display, by the user device on a display device when the user device is in a first orientation, the plurality of text in the first language and in a first directional reading format; detecting, by the user device using an orientation detection device, a reorientation of the user device from the first orientation to a predefined orientation of the user device that is rotated relative to the first orientation; translating, by the user device in response to the detecting of the reorientation to the predefined orientation, the plurality of text from the first language to a second language; and providing for display, by the user device on the display device in response to the detecting of the reorientation to the predefined orientation, the plurality of text in the second language and a second directional reading format that is different than the first directional reading format. 13. The method of claim 7 , further comprising: providing, by the user device for display on the display device, a graphical user interface that includes the plurality of text in the second language, and a virtual keyboard in the second language. | 0.677165 |
9,606,986 | 10 | 19 | 10. A method for processing discourse input comprising: at an electronic device with a processor and memory storing one or more programs for execution by the processor: receiving a discourse input from a user; determining a text string corresponding to the discourse input, wherein determining the text string comprises: determining, using a first language model, a conditional probability of a candidate word in the discourse input given one or more words in the discourse input; and applying a weight to the conditional probability of the candidate word given the one or more words to obtain a weighted conditional probability of the candidate word given the one or more words, wherein the weight is based on a conditional probability of the candidate word given one or more classes associated with the one or more words, and wherein the text string is based on the weighted conditional probability of the candidate word; and generating an output based on the text string. | 10. A method for processing discourse input comprising: at an electronic device with a processor and memory storing one or more programs for execution by the processor: receiving a discourse input from a user; determining a text string corresponding to the discourse input, wherein determining the text string comprises: determining, using a first language model, a conditional probability of a candidate word in the discourse input given one or more words in the discourse input; and applying a weight to the conditional probability of the candidate word given the one or more words to obtain a weighted conditional probability of the candidate word given the one or more words, wherein the weight is based on a conditional probability of the candidate word given one or more classes associated with the one or more words, and wherein the text string is based on the weighted conditional probability of the candidate word; and generating an output based on the text string. 19. The method of claim 10 , wherein the weighted conditional probability of the candidate word is proportional to the conditional probability of the candidate word given the one or more words. | 0.770784 |
8,355,903 | 29 | 30 | 29. The computer program product as recited in claim 19 , wherein the instructions are further configured to (1) identify a plurality of the angle data structures for the narrative story based at least in part on a plurality of the angle data structures that are associated with the applicability conditions deemed applicable to the received domain related data and information, (2) prioritize the plurality of identified angle data structures, and (3) automatically render a narrative story that is descriptive of the at least one member as influenced by the thematic natures of the identified angle data structures and in accordance with the prioritization of those identified angle data structures. | 29. The computer program product as recited in claim 19 , wherein the instructions are further configured to (1) identify a plurality of the angle data structures for the narrative story based at least in part on a plurality of the angle data structures that are associated with the applicability conditions deemed applicable to the received domain related data and information, (2) prioritize the plurality of identified angle data structures, and (3) automatically render a narrative story that is descriptive of the at least one member as influenced by the thematic natures of the identified angle data structures and in accordance with the prioritization of those identified angle data structures. 30. The computer program product as recited in claim 29 , wherein each of the angle data structures are further associated with an importance value, and wherein the instructions are further configured to prioritize the plurality of identified angle data structures based at least in part on their associated importance values. | 0.5 |
9,818,450 | 8 | 9 | 8. A subtitle generating apparatus, comprising: one or more computer processors, adapted to: obtain an audio file of dialogue in a first language; obtain a file of script text corresponding to the dialogue in the audio file in the same first language; determine a timing correspondence between dialogue in the audio file and words in the script text; detect at least a first pause during performance of the dialogue in the audio file; define a respective breakable point in the script text corresponding to the or each detected pause; divide the script text out into a sequence of subtitle lines of text responsive to the location of one or more of the defined breakable points; obtain a file of script text corresponding to the dialogue in the audio file in a different second language; obtain the sequence of subtitle lines of text divided out of the script text of the first language, the sequence comprising a characteristic number of lines; detect corresponding features of the text between both languages; divide the script text in the second language into a sequence of subtitle lines of text having the same characteristic number of lines, the points of division being responsive to the correspondence of features of the text between both languages output the sequence of subtitle lines of text for presentation on a display device. | 8. A subtitle generating apparatus, comprising: one or more computer processors, adapted to: obtain an audio file of dialogue in a first language; obtain a file of script text corresponding to the dialogue in the audio file in the same first language; determine a timing correspondence between dialogue in the audio file and words in the script text; detect at least a first pause during performance of the dialogue in the audio file; define a respective breakable point in the script text corresponding to the or each detected pause; divide the script text out into a sequence of subtitle lines of text responsive to the location of one or more of the defined breakable points; obtain a file of script text corresponding to the dialogue in the audio file in a different second language; obtain the sequence of subtitle lines of text divided out of the script text of the first language, the sequence comprising a characteristic number of lines; detect corresponding features of the text between both languages; divide the script text in the second language into a sequence of subtitle lines of text having the same characteristic number of lines, the points of division being responsive to the correspondence of features of the text between both languages output the sequence of subtitle lines of text for presentation on a display device. 9. The subtitle generating apparatus of claim 8 , in which one or more of said computer processors is adapted to: set a maximum length for a line of subtitle text; and divide the remaining script text at the last breakable point in the remaining script text whose position precedes the position in the remaining script text equal to the maximum length of line of subtitle text. | 0.60148 |
9,626,523 | 1 | 2 | 1. A method preventing incorporation of data entries by a third party to a user's own user profile, including: maintaining at least one trust object linked to fields of a user profile on an online social network, wherein the trust object holds audit trail fields that identify how data became incorporated in at least some fields of the user profile including names of data sources, interface categories of the data sources, and origins that identify geographic locations of the data sources; and access control fields that specify field-by-field and party-by-party control over third party data incorporation to the user profile fields including identifying a user's engagement preferences, a connection type of the user with a third party, statuses of data streams from third parties and information identifying the third parties; providing a privacy controller, wherein the privacy controller provides user access to information in the audit trail fields for user's own user profile; and provides user control on a field-by-field and party-by-party basis over third party data incorporation to the user profile fields; receiving instructions that set user's preferences for field-by-field and party-by-party control over the third party data incorporation to the user's own user profile; and updating the trust object responsive to the received instructions and using the updated trust object to automatically prevent incorporation of data entries by a third party to the user's own user profile of the online social network according to one or more of a source, a type, and an origin of the third party identified from the information. | 1. A method preventing incorporation of data entries by a third party to a user's own user profile, including: maintaining at least one trust object linked to fields of a user profile on an online social network, wherein the trust object holds audit trail fields that identify how data became incorporated in at least some fields of the user profile including names of data sources, interface categories of the data sources, and origins that identify geographic locations of the data sources; and access control fields that specify field-by-field and party-by-party control over third party data incorporation to the user profile fields including identifying a user's engagement preferences, a connection type of the user with a third party, statuses of data streams from third parties and information identifying the third parties; providing a privacy controller, wherein the privacy controller provides user access to information in the audit trail fields for user's own user profile; and provides user control on a field-by-field and party-by-party basis over third party data incorporation to the user profile fields; receiving instructions that set user's preferences for field-by-field and party-by-party control over the third party data incorporation to the user's own user profile; and updating the trust object responsive to the received instructions and using the updated trust object to automatically prevent incorporation of data entries by a third party to the user's own user profile of the online social network according to one or more of a source, a type, and an origin of the third party identified from the information. 2. The method of claim 1 , wherein the privacy controller enables the user to opt out of any use of a selected data source to populate the fields of the user profile. | 0.666667 |
9,514,118 | 1 | 3 | 1. A method for database implementation of electronic checklists, the method comprising implementing using at least one processor, the steps of: displaying at a user interface, a first electronic checklist template within a template editor; defining a modified electronic checklist template, wherein defining the modified electronic checklist template comprises modifying the first electronic checklist template based on inputs received at the template editor; and generating a database implemented electronic checklist template, the database implemented electronic checklist template comprising: a markup language encoding of the modified electronic checklist template; and at least one system controlled column, wherein data input within data fields of the at least one system controlled column is determined by: one or more system information parameters; and one or more predefined rules of system behaviour associated with the at least one system controlled column. | 1. A method for database implementation of electronic checklists, the method comprising implementing using at least one processor, the steps of: displaying at a user interface, a first electronic checklist template within a template editor; defining a modified electronic checklist template, wherein defining the modified electronic checklist template comprises modifying the first electronic checklist template based on inputs received at the template editor; and generating a database implemented electronic checklist template, the database implemented electronic checklist template comprising: a markup language encoding of the modified electronic checklist template; and at least one system controlled column, wherein data input within data fields of the at least one system controlled column is determined by: one or more system information parameters; and one or more predefined rules of system behaviour associated with the at least one system controlled column. 3. The method according to claim 1 , wherein defining the modified electronic checklist template includes selecting for inclusion within the modified electronic checklist template, a system controlled column within the first electronic checklist template, said system controlled column having one or more predefined rules of system behaviour associated therewith. | 0.791619 |
9,015,648 | 5 | 8 | 5. The method of claim 1 wherein performing an attribute level merge comprises: comparing conditions of each switch branch in the second version of the first BPEL implementation with those of the IT-side modified version of the first BPEL implementation. | 5. The method of claim 1 wherein performing an attribute level merge comprises: comparing conditions of each switch branch in the second version of the first BPEL implementation with those of the IT-side modified version of the first BPEL implementation. 8. The method of claim 5 wherein comparing the conditions comprises comparing code segments. | 0.847682 |
7,890,533 | 17 | 18 | 17. The method of claim 7 , further comprising: receiving a color specified by the user for each of the visual elements; and adding the specified colors to the visual elements. | 17. The method of claim 7 , further comprising: receiving a color specified by the user for each of the visual elements; and adding the specified colors to the visual elements. 18. The method of claim 17 , further comprising: displaying the information related to the concept corresponding to the selected visual element using the specified colors for each of the visual elements. | 0.5 |
7,568,171 | 17 | 22 | 17. A method for posing a computer-animated three-dimensional model in a three-dimensional scene space, the model including a plurality of elements, the method comprising: receiving a stroke drawn in a two-dimensional screen space by a user, the stroke having a starting point, an ending point, and a direction; associating the stroke with an element of the model, wherein the element has a first and second reference point; defining a first projection line in scene space which extends from a camera position and passes through the starting point of the stroke; defining a second projection line in scene space which extends from the camera position and passes through the ending point of the stroke; moving the element in the scene space based on the stroke, wherein the amount of the movement of the element in the scene space is determined by a three dimensional transformation which positions the first and second reference points as coinicident with the first and second projection lines, respectively; and displaying the moved element in a three-dimensional scene space. | 17. A method for posing a computer-animated three-dimensional model in a three-dimensional scene space, the model including a plurality of elements, the method comprising: receiving a stroke drawn in a two-dimensional screen space by a user, the stroke having a starting point, an ending point, and a direction; associating the stroke with an element of the model, wherein the element has a first and second reference point; defining a first projection line in scene space which extends from a camera position and passes through the starting point of the stroke; defining a second projection line in scene space which extends from the camera position and passes through the ending point of the stroke; moving the element in the scene space based on the stroke, wherein the amount of the movement of the element in the scene space is determined by a three dimensional transformation which positions the first and second reference points as coinicident with the first and second projection lines, respectively; and displaying the moved element in a three-dimensional scene space. 22. The method of claim 17 , wherein moving the element is based at least in part on whether the stroke intersects itself. | 0.628049 |
9,387,014 | 29 | 31 | 29. A method for decompressing a spinal canal, comprising: moving a posterior element of a vertebra that is separated from a first portion of a lateral mass of the vertebra away from the first portion of the lateral mass to expand a spinal canal disposed between the posterior element and the first portion of the lateral mass; implanting a first bone anchor into the first portion of the lateral mass, the bone anchor including a head having opposed arms that each have a proximal terminal end surface; coupling a first end of a first connecting plate to the first bone anchor by positioning a distal surface of the first connecting plate on the proximal terminal end surfaces of each of the opposed arms of the head of the bone anchor; and coupling a second end of the first connecting plate to the posterior element to maintain the posterior element in a fixed position with respect to the first portion of the lateral mass. | 29. A method for decompressing a spinal canal, comprising: moving a posterior element of a vertebra that is separated from a first portion of a lateral mass of the vertebra away from the first portion of the lateral mass to expand a spinal canal disposed between the posterior element and the first portion of the lateral mass; implanting a first bone anchor into the first portion of the lateral mass, the bone anchor including a head having opposed arms that each have a proximal terminal end surface; coupling a first end of a first connecting plate to the first bone anchor by positioning a distal surface of the first connecting plate on the proximal terminal end surfaces of each of the opposed arms of the head of the bone anchor; and coupling a second end of the first connecting plate to the posterior element to maintain the posterior element in a fixed position with respect to the first portion of the lateral mass. 31. The method of claim 29 , further comprising: moving the posterior element of a vertebra that is separated from a second portion of the lateral mass of the vertebra away from the second portion of the lateral mass to expand a spinal canal disposed between the posterior element and the second portion of the lateral mass, the second portion of the lateral mass being on a contralateral side of the vertebra than the first portion of the lateral mass; implanting a second bone anchor into the second portion of the lateral mass; coupling a first end of a second connecting plate to the second bone anchor; and coupling a second end of the second connecting plate to the posterior element to maintain the posterior element in a fixed position with respect to the second portion of the lateral mass. | 0.5 |
9,437,186 | 5 | 7 | 5. A system comprising: at least one processor coupled to a memory, the memory including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor: to receive audio input data, including a speech utterance; to perform automatic speech recognition (ASR) processing on the audio input data to generate ASR output; to determine a first ending of the utterance in the audio input data; to generate a first speech recognition output including a first portion of the ASR output that corresponds to the audio input data from a beginning of the audio input data up to the first ending; to process the first speech recognition output to obtain a first speech processing result; and: (1) if the audio input data after the first ending does not include speech, to initiate a first action to be executed on a first device based at least in part on the first speech processing result, and (2) if the audio input data after the first ending includes speech: to discard the first speech processing result, to determine a second ending of the utterance in the audio input data after the first ending, to generate a second speech recognition output including a second portion of the ASR output that corresponds to the audio input data from the beginning of the audio input data up to the second ending, to process the second speech recognition output to obtain a second speech processing result, and to initiate a second action that is different from the first action to be executed on the first device based at least in part on the second speech processing result. | 5. A system comprising: at least one processor coupled to a memory, the memory including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor: to receive audio input data, including a speech utterance; to perform automatic speech recognition (ASR) processing on the audio input data to generate ASR output; to determine a first ending of the utterance in the audio input data; to generate a first speech recognition output including a first portion of the ASR output that corresponds to the audio input data from a beginning of the audio input data up to the first ending; to process the first speech recognition output to obtain a first speech processing result; and: (1) if the audio input data after the first ending does not include speech, to initiate a first action to be executed on a first device based at least in part on the first speech processing result, and (2) if the audio input data after the first ending includes speech: to discard the first speech processing result, to determine a second ending of the utterance in the audio input data after the first ending, to generate a second speech recognition output including a second portion of the ASR output that corresponds to the audio input data from the beginning of the audio input data up to the second ending, to process the second speech recognition output to obtain a second speech processing result, and to initiate a second action that is different from the first action to be executed on the first device based at least in part on the second speech processing result. 7. The system of claim 5 , wherein the at least one processor is further configured to determine if the audio input data after the first ending includes speech by: determining the second ending of the utterance in the audio input data; generating the second speech recognition output; and comparing the first speech recognition output to the second speech recognition output. | 0.5 |
7,809,695 | 34 | 35 | 34. An information-retrieval system comprising: a plurality of databases; and a server for providing users access to one or more of the databases, the server including: means for defining and processing a query to generate results comprising documents that include content duplicative of content within one or more other documents within the results; duplicate-determination means for determining whether one or more documents within the results of the query include content duplicative of content within one or more other documents within the results, wherein the duplicate-determination means includes: first means for comparing a first document signature for a first one of the documents within the results to a second document signature for a second one of the documents within the results, with each signature based on a plurality of terms and their corresponding positions within its corresponding document; second means for comparing, respectively, first and second lengths and first and second temporal features of the first and second documents; and third means for comparing a set of features common to the first and second documents, the set of features comprising features selected based on a corresponding inverse-document-frequency (idf) value, wherein the first and second documents have at least a threshold number of features in common with each other; wherein the duplicate-determination means is adapted to determine whether the first and second documents are duplicates in response to the results of the third comparing means; means for controlling display of results of the query with at least one of the displayed results indicated as including content duplicative of content in one or more other documents within the results; and means for controlling output of results of the query to a printer or email transmission device, based on user selected options related to output of documents that include content duplicative of content of one or more other documents within the results. | 34. An information-retrieval system comprising: a plurality of databases; and a server for providing users access to one or more of the databases, the server including: means for defining and processing a query to generate results comprising documents that include content duplicative of content within one or more other documents within the results; duplicate-determination means for determining whether one or more documents within the results of the query include content duplicative of content within one or more other documents within the results, wherein the duplicate-determination means includes: first means for comparing a first document signature for a first one of the documents within the results to a second document signature for a second one of the documents within the results, with each signature based on a plurality of terms and their corresponding positions within its corresponding document; second means for comparing, respectively, first and second lengths and first and second temporal features of the first and second documents; and third means for comparing a set of features common to the first and second documents, the set of features comprising features selected based on a corresponding inverse-document-frequency (idf) value, wherein the first and second documents have at least a threshold number of features in common with each other; wherein the duplicate-determination means is adapted to determine whether the first and second documents are duplicates in response to the results of the third comparing means; means for controlling display of results of the query with at least one of the displayed results indicated as including content duplicative of content in one or more other documents within the results; and means for controlling output of results of the query to a printer or email transmission device, based on user selected options related to output of documents that include content duplicative of content of one or more other documents within the results. 35. The system of claim 34 , wherein the means for comparing a set of features is executed in response to the results of the means for comparing first and second lengths and respective first and second temporal features of respective first and second documents. | 0.5 |
8,620,947 | 9 | 12 | 9. A computer-implemented method for destination selection with a navigation system, comprising: receiving information regarding a destination comprising a broad place name and a narrow place name; querying a relation table that associates search terms to inverted indexes; determining whether the broad place name of the destination information is a frequently used search term associated with an inverted index; identifying that the frequently used search term is not listed in the inverted index, wherein the inverted index includes documents associated with the broad place name of the destination; searching for document identifiers in inverted indexes that are not associated with the broad place name of the destination information; generating a document set for each searched inverted index, wherein the document set includes a list of document identifiers associated with documents that include the narrow place name of the destination information; comparing the document sets to identify what document identifiers are located in all document sets; and providing a result set of document identifiers that are located in all document sets. | 9. A computer-implemented method for destination selection with a navigation system, comprising: receiving information regarding a destination comprising a broad place name and a narrow place name; querying a relation table that associates search terms to inverted indexes; determining whether the broad place name of the destination information is a frequently used search term associated with an inverted index; identifying that the frequently used search term is not listed in the inverted index, wherein the inverted index includes documents associated with the broad place name of the destination; searching for document identifiers in inverted indexes that are not associated with the broad place name of the destination information; generating a document set for each searched inverted index, wherein the document set includes a list of document identifiers associated with documents that include the narrow place name of the destination information; comparing the document sets to identify what document identifiers are located in all document sets; and providing a result set of document identifiers that are located in all document sets. 12. The method of claim 9 , wherein the destination information includes a point of interest name. | 0.639706 |
8,364,509 | 1 | 47 | 1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user. | 1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user. 47. The method of claim 1 , wherein receiving at least one query includes receiving at least one query for at least one report identifying at least one agent whose performance falls below at least one minimum threshold. | 0.704054 |
9,710,471 | 15 | 16 | 15. The contents management apparatus of claim 14 , wherein: the touch screen is further configured to: display keyword regions based on at least one of the selection and the input drag; and the at least one processor is further configured to: receive information corresponding to a detected touch event associated with a keyword region of the keyword regions; and filter the displayed graphical user interface objects based on a keyword mapped to the keyword region. | 15. The contents management apparatus of claim 14 , wherein: the touch screen is further configured to: display keyword regions based on at least one of the selection and the input drag; and the at least one processor is further configured to: receive information corresponding to a detected touch event associated with a keyword region of the keyword regions; and filter the displayed graphical user interface objects based on a keyword mapped to the keyword region. 16. The contents management apparatus of claim 15 , wherein the at least one processor is further configured to: determine a strength of the touch event based on the information; and filter the displayed graphical user interface objects based on the strength. | 0.5 |
9,754,187 | 16 | 17 | 16. A system comprising: a processor device to: acquire an electronic image of a document with a fixed structure, wherein the fixed structure comprises field names and field values corresponding to the field names, and wherein the field names and the field values are located at set locations in the document; recognize key words in the electronic image of the document, wherein the key words comprise the field names and the field values; match one or more templates from a plurality of templates with the document, wherein the one or more templates comprise reference objects that specify areas in the electronic image of the document where permitted field values corresponding to field names are to be extracted, and wherein, to match the one or more templates, the processor device is further to match the field names and the permitted field values from the one or more templates with the identified field names and the field values from the recognized key words; select a template from the one or more templates based on a quality of a match between the field names and the permitted field values from the template with the identified field names and the field values from the recognized key words; and extract the field values from the electronic image of the document using the selected template. | 16. A system comprising: a processor device to: acquire an electronic image of a document with a fixed structure, wherein the fixed structure comprises field names and field values corresponding to the field names, and wherein the field names and the field values are located at set locations in the document; recognize key words in the electronic image of the document, wherein the key words comprise the field names and the field values; match one or more templates from a plurality of templates with the document, wherein the one or more templates comprise reference objects that specify areas in the electronic image of the document where permitted field values corresponding to field names are to be extracted, and wherein, to match the one or more templates, the processor device is further to match the field names and the permitted field values from the one or more templates with the identified field names and the field values from the recognized key words; select a template from the one or more templates based on a quality of a match between the field names and the permitted field values from the template with the identified field names and the field values from the recognized key words; and extract the field values from the electronic image of the document using the selected template. 17. The system of claim 16 , wherein the processor device is further to perform a distortion correction of the electronic image of the document. | 0.843478 |
9,043,319 | 21 | 22 | 21. The system of claim 20 , wherein determining whether real-time search results should be included in a response to the search query includes: receiving data for the search query; generating one or more scores from the data; and determining that each of the one or more scores satisfies a respective threshold. | 21. The system of claim 20 , wherein determining whether real-time search results should be included in a response to the search query includes: receiving data for the search query; generating one or more scores from the data; and determining that each of the one or more scores satisfies a respective threshold. 22. The system of claim 21 , wherein the data includes a rate with which new documents responsive to the query are identified. | 0.585526 |
8,176,049 | 1 | 10 | 1. A method to be executed by a processor in an electronic environment, comprising: receiving an object in a network environment; receiving a search query that includes a first regular expression, wherein the first regular expression comprises a string according to one or more syntax rules; mapping the first regular expression to a first attribute, wherein the first attribute is included amongst a plurality of attributes provided in an attribute map, and wherein the plurality of attributes each represent respective regular expressions; and parsing only the regular expressions related to attributes that have not been found in the object, wherein if a parsing activity identifies a match for the first regular expression in the object, then other regular expressions that contain the first attribute are not searched for the search query. | 1. A method to be executed by a processor in an electronic environment, comprising: receiving an object in a network environment; receiving a search query that includes a first regular expression, wherein the first regular expression comprises a string according to one or more syntax rules; mapping the first regular expression to a first attribute, wherein the first attribute is included amongst a plurality of attributes provided in an attribute map, and wherein the plurality of attributes each represent respective regular expressions; and parsing only the regular expressions related to attributes that have not been found in the object, wherein if a parsing activity identifies a match for the first regular expression in the object, then other regular expressions that contain the first attribute are not searched for the search query. 10. The method of claim 1 , further comprising: determining a content type of the object; and inserting the content type into a content field associated with a tag for the object. | 0.818089 |
8,655,913 | 15 | 16 | 15. A system for locating an element in a document object model (DOM) tree structure based on fuzzy matching of attributes of the element and relative positioning of other elements in the DOM tree structure, the system comprising: one or more processors; memory accessible by the one or more processors; one or more modules stored in the memory and configured for execution by the one or more processors, the one or more modules comprising: a DOM attributes module configured to receive a plurality of attributes for searching an element in a DOM tree structure, wherein the DOM tree structure includes one or more nodes respectively representing different elements in a web page; a DOM attributes search module configured to determine a location of an element in a DOM tree structure based on the plurality of attributes, wherein the location of the element corresponds to a respective node in the DOM tree structure; and a relative location module configured to: if the location of the element is not successfully determined based on the plurality of attributes, search the DOM tree structure based at least in part on one of: a prefix search query, a suffix search query, and a wildcard matching criteria; and determine a relative location of the element in the DOM tree structure, wherein the determination of the relative location of the element is based on fuzzy matching according to a predetermined percentage of one or more matching attributes and based on respective positions of one or more elements in the DOM tree structure. | 15. A system for locating an element in a document object model (DOM) tree structure based on fuzzy matching of attributes of the element and relative positioning of other elements in the DOM tree structure, the system comprising: one or more processors; memory accessible by the one or more processors; one or more modules stored in the memory and configured for execution by the one or more processors, the one or more modules comprising: a DOM attributes module configured to receive a plurality of attributes for searching an element in a DOM tree structure, wherein the DOM tree structure includes one or more nodes respectively representing different elements in a web page; a DOM attributes search module configured to determine a location of an element in a DOM tree structure based on the plurality of attributes, wherein the location of the element corresponds to a respective node in the DOM tree structure; and a relative location module configured to: if the location of the element is not successfully determined based on the plurality of attributes, search the DOM tree structure based at least in part on one of: a prefix search query, a suffix search query, and a wildcard matching criteria; and determine a relative location of the element in the DOM tree structure, wherein the determination of the relative location of the element is based on fuzzy matching according to a predetermined percentage of one or more matching attributes and based on respective positions of one or more elements in the DOM tree structure. 16. The system of claim 15 , wherein the DOM attributes search module is further configured to: determine if there is an exact match of at least one attribute among the plurality of attributes corresponding to at least one element in the DOM tree structure. | 0.5 |
8,364,487 | 8 | 9 | 8. The method of claim 1 , said spoken search request being an audio file received over a network. | 8. The method of claim 1 , said spoken search request being an audio file received over a network. 9. The method of claim 8 , said audio file being created by a mobile device. | 0.5 |
8,997,220 | 1 | 11 | 1. A method comprising: identifying a plurality of suspicious websites from among a plurality of websites; extracting a set of lexical features for each website among from the plurality of suspicious websites; clustering each website from among the plurality of suspicious websites into a plurality of groups based on the set of lexical features extracted for each website; performing group analysis on each group from among the plurality of groups to identify at least one suspicious group that provides confirmation of at least one search engine optimization (SEO) attack; and using the identified at least one suspicious group to identify a corresponding group of compromised servers targeted by the SEO attack, wherein the corresponding group of compromised servers comprises a subset of servers that exhibit a change in behavior, indicative of the SEO attack. | 1. A method comprising: identifying a plurality of suspicious websites from among a plurality of websites; extracting a set of lexical features for each website among from the plurality of suspicious websites; clustering each website from among the plurality of suspicious websites into a plurality of groups based on the set of lexical features extracted for each website; performing group analysis on each group from among the plurality of groups to identify at least one suspicious group that provides confirmation of at least one search engine optimization (SEO) attack; and using the identified at least one suspicious group to identify a corresponding group of compromised servers targeted by the SEO attack, wherein the corresponding group of compromised servers comprises a subset of servers that exhibit a change in behavior, indicative of the SEO attack. 11. The method of claim 1 , further comprising generating at least one derived regular expression and using the derived regular expression to evaluate at least one link returned by a search engine. | 0.75 |
8,538,911 | 1 | 6 | 1. An event analysis system comprising: an information database; a memory comprising: an event model comprising an event type and event attributes of the event type; an event detection engine configured to detect events that correspond to the event model; an event implication engine configured to determine implications of events detected by the event detection engine; an environment model comprising a first model entity and a focus entity, and a focus relationship between the focus entity to the first model entity; and a processor coupled to the memory which is operable to: initiate execution of the event detection engine on articles published on a network to: parse a markup language of the articles and extract text from the articles published on the network; store the extracted text; based on the extracted text, detect an event involving the first model entity represented in the articles; and apply the event model to generate an event object for the detected event according to a common event structure; initiate execution of the event implication engine on the event object to: recognize that the focus relationship exists between the focus entity and the first model entity; determine an inferred event involving the focus entity based on the recognition that the focus relationship exists between the focus entity and the first model entity and the detection of the event involving the first model entity, the inferred event having an event type that is different than an event type of the event involving the first model entity; and create a new event object from the inferred event. | 1. An event analysis system comprising: an information database; a memory comprising: an event model comprising an event type and event attributes of the event type; an event detection engine configured to detect events that correspond to the event model; an event implication engine configured to determine implications of events detected by the event detection engine; an environment model comprising a first model entity and a focus entity, and a focus relationship between the focus entity to the first model entity; and a processor coupled to the memory which is operable to: initiate execution of the event detection engine on articles published on a network to: parse a markup language of the articles and extract text from the articles published on the network; store the extracted text; based on the extracted text, detect an event involving the first model entity represented in the articles; and apply the event model to generate an event object for the detected event according to a common event structure; initiate execution of the event implication engine on the event object to: recognize that the focus relationship exists between the focus entity and the first model entity; determine an inferred event involving the focus entity based on the recognition that the focus relationship exists between the focus entity and the first model entity and the detection of the event involving the first model entity, the inferred event having an event type that is different than an event type of the event involving the first model entity; and create a new event object from the inferred event. 6. The event analysis system of claim 1 , where the processor is further operable to: apply the event implication engine to the new event object. | 0.908805 |
7,661,060 | 19 | 26 | 19. A mobile communication terminal for controlling reproduction of media information, comprising: an analyzer that identifies a plurality of media items specified in a Synchronized Multimedia Integration Language (SMIL) document at the mobile communication terminal; a generator that generates a table that associates each of the plurality of media items with a time, the table comprising a reproduction control table that lists times when each of a plurality of first ones of the media items are to be reproduced and a stop control table that lists times when reproduction of each of a plurality of second ones of the media items are to be stopped, and wherein each media item in the table has a connection structure of a linked list; and a controller that controls reproduction of the plurality of media items on the mobile communication terminal based on the table, wherein when there are a plurality of media items to be reproduced, the media items are aligned according to a z-index alignment method and the media items are reproduced starting from a media item having a lowest order under control of the controller, wherein the stop control table and the reproduction control table are separately operated, and wherein the controller arbitrarily adjusts a stop time of media being reproduced according to a user's input. | 19. A mobile communication terminal for controlling reproduction of media information, comprising: an analyzer that identifies a plurality of media items specified in a Synchronized Multimedia Integration Language (SMIL) document at the mobile communication terminal; a generator that generates a table that associates each of the plurality of media items with a time, the table comprising a reproduction control table that lists times when each of a plurality of first ones of the media items are to be reproduced and a stop control table that lists times when reproduction of each of a plurality of second ones of the media items are to be stopped, and wherein each media item in the table has a connection structure of a linked list; and a controller that controls reproduction of the plurality of media items on the mobile communication terminal based on the table, wherein when there are a plurality of media items to be reproduced, the media items are aligned according to a z-index alignment method and the media items are reproduced starting from a media item having a lowest order under control of the controller, wherein the stop control table and the reproduction control table are separately operated, and wherein the controller arbitrarily adjusts a stop time of media being reproduced according to a user's input. 26. The terminal of claim 19 , wherein said time indicates a time when reproduction of an associated one of the media items is to be stopped. | 0.53 |
9,805,006 | 1 | 2 | 1. A method of loading a web page, comprising: providing, via a computer network and to a computing device having one or more processors, a script configured for loading with a web page, the web page configured for display on the computing device, the script having a plurality of function definitions and configured for asynchronous loading such that the web page is operable while the script is loaded; receiving an indication of a user interaction with the web page prior to complete loading of the plurality of function definitions on the web page; determining that the user interaction corresponds to a function definition of the plurality of function definitions that has not been loaded; subsequent to determining that the user interaction corresponds to the function definition that has not been loaded: instructing, using a variable, the computing device to queue a command string corresponding to the function definition; determining that the function has been loaded and instructing the computing device to retrieve the command string from the variable; and instructing the computing device to execute the function definition corresponding to the command string. | 1. A method of loading a web page, comprising: providing, via a computer network and to a computing device having one or more processors, a script configured for loading with a web page, the web page configured for display on the computing device, the script having a plurality of function definitions and configured for asynchronous loading such that the web page is operable while the script is loaded; receiving an indication of a user interaction with the web page prior to complete loading of the plurality of function definitions on the web page; determining that the user interaction corresponds to a function definition of the plurality of function definitions that has not been loaded; subsequent to determining that the user interaction corresponds to the function definition that has not been loaded: instructing, using a variable, the computing device to queue a command string corresponding to the function definition; determining that the function has been loaded and instructing the computing device to retrieve the command string from the variable; and instructing the computing device to execute the function definition corresponding to the command string. 2. The method of claim 1 , further comprising: instantiating the variable as a global variable. | 0.755155 |
8,195,669 | 17 | 18 | 17. The non-transitory computer-readable storage media of claim 14 , wherein the process of maximizing a likelihood includes the use of a specific function that processes data describing parent-child relationships between the documents. | 17. The non-transitory computer-readable storage media of claim 14 , wherein the process of maximizing a likelihood includes the use of a specific function that processes data describing parent-child relationships between the documents. 18. The non-transitory computer-readable storage media of claim 17 , wherein the specific function utilizes:
g ( y i ,y j ,x )= R i,j ( y i −y i ), where R i,j denotes the parent-child relation: R i,j =1 if document i is the parent of j, and R i,j =0 for other cases. | 0.5 |
8,666,226 | 13 | 17 | 13. A system for converting script code of a three dimensional (3D) video having relative dynamic descriptors of objects orientation into 3D video with absolute descriptors orientation for object in the video, said system comprised of: a parsing module for identifying exchangeable dynamic objects in the video; an optimization module for parsing each frame script code of the video for analyzing dynamic descriptors of objects for determining absolute values for each descriptors including the absolute orientation values for each object in each frame; and a template generation module for creating a video template which supports the creation of customized videos by altering or exchanging dynamic objects. | 13. A system for converting script code of a three dimensional (3D) video having relative dynamic descriptors of objects orientation into 3D video with absolute descriptors orientation for object in the video, said system comprised of: a parsing module for identifying exchangeable dynamic objects in the video; an optimization module for parsing each frame script code of the video for analyzing dynamic descriptors of objects for determining absolute values for each descriptors including the absolute orientation values for each object in each frame; and a template generation module for creating a video template which supports the creation of customized videos by altering or exchanging dynamic objects. 17. The system of claim 13 , wherein the identification of dynamic object is performed by identifying name convention of objects. | 0.704128 |
8,869,049 | 11 | 19 | 11. A computer program product that comprises a non-transient computer readable storage medium containing computer executable instructions for assisting a user to design a user interface (UI), comprising: instructions to process a command to automatically generate a design for an incomplete UI design, the incomplete UI design comprising a user-selected UI component; instructions to identify a design example comprising a corresponding UI component similar to the user-selected UI component and a recommended UI component; and instructions to provide the recommended UI component for display in the incomplete UI design. | 11. A computer program product that comprises a non-transient computer readable storage medium containing computer executable instructions for assisting a user to design a user interface (UI), comprising: instructions to process a command to automatically generate a design for an incomplete UI design, the incomplete UI design comprising a user-selected UI component; instructions to identify a design example comprising a corresponding UI component similar to the user-selected UI component and a recommended UI component; and instructions to provide the recommended UI component for display in the incomplete UI design. 19. The computer program product of claim 11 , wherein the design example is among a plurality of design examples in a plurality of layout groups, each layout group comprising one or more design examples with similar layouts to the incomplete UI design, the instructions further comprising: instructions to receive a user command identifying a selected layout group and provide user choices from within the selected layout group. | 0.5 |
8,200,617 | 4 | 11 | 4. The method of claim 1 , further comprising, collecting the metadata from, one or more of, a plurality of content sources hosted by host servers and the object itself; wherein, each of the plurality of content sources includes at least a portion of the object or a reference to the object associated with the location identifier. | 4. The method of claim 1 , further comprising, collecting the metadata from, one or more of, a plurality of content sources hosted by host servers and the object itself; wherein, each of the plurality of content sources includes at least a portion of the object or a reference to the object associated with the location identifier. 11. The method of claim 4 , further comprising, analyzing multiple tags identified from the plurality of content sources; selecting a subset of the multiple tags for use in identifying a set of semantic types with which the object or the content embodied therein has a semantic relationship. | 0.5 |
9,645,999 | 11 | 13 | 11. The method of claim 1 , wherein adjusting edge weights comprises: obtaining a feature vector representation of each document, each feature vector indicating an amount of occurrences of respective n-grams in the respective document with respective cardinal values; and for each of at least some of the feature vectors, selecting cardinal values of the respective feature vector correspond to n-grams in the adjustment n-gram set and adjusting the selected cardinal values. | 11. The method of claim 1 , wherein adjusting edge weights comprises: obtaining a feature vector representation of each document, each feature vector indicating an amount of occurrences of respective n-grams in the respective document with respective cardinal values; and for each of at least some of the feature vectors, selecting cardinal values of the respective feature vector correspond to n-grams in the adjustment n-gram set and adjusting the selected cardinal values. 13. The method of claim 11 , wherein adjusting edge weights comprises: steps for determining similarity of feature vectors. | 0.62037 |
9,002,873 | 8 | 12 | 8. A non-transitory computer readable storage medium having a plurality of instructions stored thereon that, when executed by one or more processors, cause the one or more processors to execute a method of filtering a corpus of documents, comprising: identifying a corpus of documents relevant to a litigation to be filtered; generating a first modifiable query, wherein the first modifiable query comprises desired characteristics of the documents in the corpus; filtering the corpus of documents in accordance with the first modifiable query into a first result set; naming the first result set of the first modifiable query with a first name that identifies the first result set; generating a second modifiable query; filtering the first result set in accordance with the second modifiable query to generate a second result set based on the first modifiable query and the second modifiable query, the filtering the first result set further comprising: applying the second modifiable query to the first result set by using the first result set, specified by the first name that identifies the first result set, as a source of documents for the applying the second modifiable query; naming the second result set with a second name that identifies the second result set; labeling elements of the second result set with the second name that identifies the second result set, wherein the labeling presents the first and second modifiable queries upon a user selection; determining a change in either the first modifiable query or second modifiable query; and automatically updating the second result set, without additional user involvement, to reflect the change in either the first modifiable query or the second modifiable query. | 8. A non-transitory computer readable storage medium having a plurality of instructions stored thereon that, when executed by one or more processors, cause the one or more processors to execute a method of filtering a corpus of documents, comprising: identifying a corpus of documents relevant to a litigation to be filtered; generating a first modifiable query, wherein the first modifiable query comprises desired characteristics of the documents in the corpus; filtering the corpus of documents in accordance with the first modifiable query into a first result set; naming the first result set of the first modifiable query with a first name that identifies the first result set; generating a second modifiable query; filtering the first result set in accordance with the second modifiable query to generate a second result set based on the first modifiable query and the second modifiable query, the filtering the first result set further comprising: applying the second modifiable query to the first result set by using the first result set, specified by the first name that identifies the first result set, as a source of documents for the applying the second modifiable query; naming the second result set with a second name that identifies the second result set; labeling elements of the second result set with the second name that identifies the second result set, wherein the labeling presents the first and second modifiable queries upon a user selection; determining a change in either the first modifiable query or second modifiable query; and automatically updating the second result set, without additional user involvement, to reflect the change in either the first modifiable query or the second modifiable query. 12. The computer readable storage medium of claim 8 , further comprising instructions that, when executed by the one or more processors, cause the one or more processors to use each modifiable query on separate document sets. | 0.581784 |
8,387,024 | 1 | 3 | 1. A software product testing system, comprising: a knowledge base stored on a non-transitory computer readable medium comprising a data set that includes a plurality of testing parameters, possible actions associated with each testing parameter and, for each action, a plurality of language-specific format rules for inputs and outputs associated with the action; and a computing device operably connected to the non-transitory computer readable medium and configured to run: a test case generator that selects a test case in a target language for a software product based upon a testing parameter associated with the software product, wherein the testing parameter is an attribute of the test case that denotes which type of test is to be performed, the test case comprising: a selected action to be taken by a software product, wherein the selected action is selected from the possible actions stored in the knowledge base and based upon the testing parameter associated with the software product, an input to prompt the action, and an expected output that corresponds to the selected action and the input, wherein the expected output has a format corresponding to a language-specific format rule for the selected action in the target language and is determined by the selected action and the input to prompt the action, and a test verifier that determines whether an output generated by an application of the test case for the software product matches the expected output as defined by the testing parameter associated with the software product. | 1. A software product testing system, comprising: a knowledge base stored on a non-transitory computer readable medium comprising a data set that includes a plurality of testing parameters, possible actions associated with each testing parameter and, for each action, a plurality of language-specific format rules for inputs and outputs associated with the action; and a computing device operably connected to the non-transitory computer readable medium and configured to run: a test case generator that selects a test case in a target language for a software product based upon a testing parameter associated with the software product, wherein the testing parameter is an attribute of the test case that denotes which type of test is to be performed, the test case comprising: a selected action to be taken by a software product, wherein the selected action is selected from the possible actions stored in the knowledge base and based upon the testing parameter associated with the software product, an input to prompt the action, and an expected output that corresponds to the selected action and the input, wherein the expected output has a format corresponding to a language-specific format rule for the selected action in the target language and is determined by the selected action and the input to prompt the action, and a test verifier that determines whether an output generated by an application of the test case for the software product matches the expected output as defined by the testing parameter associated with the software product. 3. The software product testing system of claim 1 , wherein the test case generator is configured to receive an input of the testing parameter, and the testing parameter prompts selection of the selected action. | 0.5 |
8,977,584 | 15 | 16 | 15. The method of claim 14 , wherein the dialogue parameters comprises a number of dialogue actions in the dialogue pathway and an amount of time take for each dialogue action. | 15. The method of claim 14 , wherein the dialogue parameters comprises a number of dialogue actions in the dialogue pathway and an amount of time take for each dialogue action. 16. The method of claim 15 , further comprising aggregating dialogue pathways from a plurality of individual targets. | 0.5 |
8,166,027 | 1 | 10 | 1. A method for testing a web site, said method comprising the steps of: a website test server for testing a web site; said web site test server being programmed to identify web pages of the web site that include a first web page, a second web page, and other web pages, the second web page being a web page which has received a greatest number of feedback responses from previous users of the web site; said web site test server being further programmed to measure an ease of navigation from the first web page to the second web page by counting hyperlinks on the first web page and determining how many intervening hyperlinks are required to navigate between the first web page and the second web page; said web site test server being further programmed to determine a shortest number of the intervening hyperlinks required to navigate from the first web page of the web site to the second web page of the web site, wherein the shortest number of intervening hyperlinks is determined by: reading HTML of the first web page, identifying each hyperlink on the first web page, reading HTML of the web pages associated with each hyperlink and identifying further hyperlinks until reaching the second web page; and said website test server generates a score for ease of navigation though said web site based at least in part on said shortest number, such that a lower number correlates to easier navigation through said web site. | 1. A method for testing a web site, said method comprising the steps of: a website test server for testing a web site; said web site test server being programmed to identify web pages of the web site that include a first web page, a second web page, and other web pages, the second web page being a web page which has received a greatest number of feedback responses from previous users of the web site; said web site test server being further programmed to measure an ease of navigation from the first web page to the second web page by counting hyperlinks on the first web page and determining how many intervening hyperlinks are required to navigate between the first web page and the second web page; said web site test server being further programmed to determine a shortest number of the intervening hyperlinks required to navigate from the first web page of the web site to the second web page of the web site, wherein the shortest number of intervening hyperlinks is determined by: reading HTML of the first web page, identifying each hyperlink on the first web page, reading HTML of the web pages associated with each hyperlink and identifying further hyperlinks until reaching the second web page; and said website test server generates a score for ease of navigation though said web site based at least in part on said shortest number, such that a lower number correlates to easier navigation through said web site. 10. The method of claim 1 , further comprising: sending an agent program to the web site under test; conducting a number of predefined searches based on at least one predefined search query; and recording a time for receiving a response from the number of predefined searches. | 0.810959 |
9,146,993 | 1 | 3 | 1. A method comprising: identifying a first video content item and one or more additional content items that were displayed in association with the first video content item, the one or more additional content items forming a first set; compiling user interaction statistics for the one or more additional content items in the first set, at least some of the one or more additional content items being associated with one or more keywords, wherein the user interaction statistics are used to determine one or more top rated ones of the one or more additional content items based on a number of user interactions with a respective one of the one or more additional content items, wherein the user interactions are selected from the group comprising click through or conversion after presentation and click through; based on the interaction statistics, associating the first video content item with at least some of the keywords associated with one or more top rated content items based at least on the compiling, wherein the associating includes storing an association between the first video content item and the some of the keywords; identifying a second different video content item; determining one or more attributes associated with the first video content item, wherein an attribute is selected from the group comprising a respective source of the first video content item, a respective content channel of the first video content item, a respective search query associated in a search system with the first video content item, or a respective media document topic of the first video content item, wherein the media document topic is identified based on non-textual content of the first video content item and non-textual content of the second different video content item; determining one or more attributes associated with the second different video content item, wherein an attribute is selected from the group comprising a respective source of the second different video content item, a respective content channel of the second different video content item, a respective search query associated in a search system with the second different video content item, or a respective media document topic of the second different video content item; comparing the first and second different video content items including identifying one or more common attributes of the first video content item and the second different video content item based at least in part on the determining one or more attributes of both the first and second different video content items, wherein the one or more common attributes of the first and second different video content items include one or more of a respective source of the first and second different video content items, a respective content channel of the first and second different video content items, a respective search query associated in a search system with the first and second different video content item, or a respective media document topic of the first and second different video content item; based on the identified one or more common attributes of the first video content item and the second different video content item, using at least some of the keywords assigned to the first video content item as keywords for the second different video content item, wherein the first video content item and the second different video content item will include one or more keywords in common; and providing additional content when displaying the second different video content based on the one or more keywords in common. | 1. A method comprising: identifying a first video content item and one or more additional content items that were displayed in association with the first video content item, the one or more additional content items forming a first set; compiling user interaction statistics for the one or more additional content items in the first set, at least some of the one or more additional content items being associated with one or more keywords, wherein the user interaction statistics are used to determine one or more top rated ones of the one or more additional content items based on a number of user interactions with a respective one of the one or more additional content items, wherein the user interactions are selected from the group comprising click through or conversion after presentation and click through; based on the interaction statistics, associating the first video content item with at least some of the keywords associated with one or more top rated content items based at least on the compiling, wherein the associating includes storing an association between the first video content item and the some of the keywords; identifying a second different video content item; determining one or more attributes associated with the first video content item, wherein an attribute is selected from the group comprising a respective source of the first video content item, a respective content channel of the first video content item, a respective search query associated in a search system with the first video content item, or a respective media document topic of the first video content item, wherein the media document topic is identified based on non-textual content of the first video content item and non-textual content of the second different video content item; determining one or more attributes associated with the second different video content item, wherein an attribute is selected from the group comprising a respective source of the second different video content item, a respective content channel of the second different video content item, a respective search query associated in a search system with the second different video content item, or a respective media document topic of the second different video content item; comparing the first and second different video content items including identifying one or more common attributes of the first video content item and the second different video content item based at least in part on the determining one or more attributes of both the first and second different video content items, wherein the one or more common attributes of the first and second different video content items include one or more of a respective source of the first and second different video content items, a respective content channel of the first and second different video content items, a respective search query associated in a search system with the first and second different video content item, or a respective media document topic of the first and second different video content item; based on the identified one or more common attributes of the first video content item and the second different video content item, using at least some of the keywords assigned to the first video content item as keywords for the second different video content item, wherein the first video content item and the second different video content item will include one or more keywords in common; and providing additional content when displaying the second different video content based on the one or more keywords in common. 3. The method of claim 1 wherein the user interaction statistics comprise at least one of a click-through rate of a particular one of the one or more additional content items when the particular one of the one or more additional content items is displayed in association with the first video content item and a conversion rate of the content item when the particular one of the one or more additional content items is displayed in association with the first video content item. | 0.5 |
7,747,984 | 9 | 13 | 9. One or more computer readable storage media having computer executable components comprising: a graphics design application for manipulating graphics data; a tester for receiving a target document containing target graphics data, the target graphics data including at least one of pixel data or vector object data, the tester including: a document reader for determining the target graphics data of the target document; and an action generator for automatically generating user device actions based on the target graphics data for a test case for generating test graphics data substantially similar to the target graphics data; the document reader being configured to determine one or more graphics data attributes of selected graphics data of the target graphics data, and the action generator being configured to generate an input device action for selecting an appropriate graphics data attribute through a user interface control of the graphics design application. | 9. One or more computer readable storage media having computer executable components comprising: a graphics design application for manipulating graphics data; a tester for receiving a target document containing target graphics data, the target graphics data including at least one of pixel data or vector object data, the tester including: a document reader for determining the target graphics data of the target document; and an action generator for automatically generating user device actions based on the target graphics data for a test case for generating test graphics data substantially similar to the target graphics data; the document reader being configured to determine one or more graphics data attributes of selected graphics data of the target graphics data, and the action generator being configured to generate an input device action for selecting an appropriate graphics data attribute through a user interface control of the graphics design application. 13. The one or more computer readable storage media of claim 9 , wherein the action generator generates user input device actions with pauses in movement of a user input device applicator over a portion of a display of the graphics design application. | 0.685464 |
8,135,617 | 16 | 19 | 16. A computer-based method of delivering contextual content with a computer system operably connected to one or more publishers via a data communications network, the method comprising: identifying, by a computer, one or more conventional hyperlinks in a document; and determining, by the computer, a context associated with each of the identified hyperlinks; selecting, by the computer for each of the identified hyperlinks, one of a plurality of bubble types based on a uniform resource locator extracted from the identified hyperlink; wherein each of the bubbles comprises a first display area and a second display area; and for each of the identified hyperlinks: a) selecting, by the computer, content for the first display area of the associated bubble type based on the uniform resource locator extracted from the identified hyperlink; and b) selecting, by the computer, content for the second display area of the bubble type based on the determined context of the identified hyperlink; and converting, by the computer, each of the identified hyperlinks to an enhanced hyperlink for invoking the associated bubble type and content. | 16. A computer-based method of delivering contextual content with a computer system operably connected to one or more publishers via a data communications network, the method comprising: identifying, by a computer, one or more conventional hyperlinks in a document; and determining, by the computer, a context associated with each of the identified hyperlinks; selecting, by the computer for each of the identified hyperlinks, one of a plurality of bubble types based on a uniform resource locator extracted from the identified hyperlink; wherein each of the bubbles comprises a first display area and a second display area; and for each of the identified hyperlinks: a) selecting, by the computer, content for the first display area of the associated bubble type based on the uniform resource locator extracted from the identified hyperlink; and b) selecting, by the computer, content for the second display area of the bubble type based on the determined context of the identified hyperlink; and converting, by the computer, each of the identified hyperlinks to an enhanced hyperlink for invoking the associated bubble type and content. 19. The method of claim 16 , wherein the plurality of bubble types comprise a video type incorporating a player application. | 0.800643 |
8,311,807 | 1 | 10 | 1. A method for updating a dictionary in a dictionary updating system with an unregistered word not registered in the dictionary, the method comprising: extracting a document of interest of a user in each predetermined extraction period from a predetermined server connected to the dictionary updating system through a network, and extracting candidate unregistered words existing in the extracted document according to predetermined unregistered word extraction rules; extracting unregistered words among the candidate unregistered words and extracting candidate semantic classes of the unregistered words based on information on appearance frequencies of the candidate unregistered words retrieved from the document; verifying the unregistered words according to a predetermined unregistered word verification method and determining semantic classes of the verified unregistered words with usage examples of the unregistered words obtained through a searching unit; updating a first dictionary of the dictionary updating system by registering all of the verified unregistered words and the semantic classes of the verified unregistered words; and re-registering, in a second dictionary of the dictionary updating system, registered words among registered words registered in the first dictionary, based on the user's usage frequency of the registered words and appearance frequency information in a document of the registered words, wherein registered words registered in the second dictionary are retrieved prior to registered words registered in only the first dictionary. | 1. A method for updating a dictionary in a dictionary updating system with an unregistered word not registered in the dictionary, the method comprising: extracting a document of interest of a user in each predetermined extraction period from a predetermined server connected to the dictionary updating system through a network, and extracting candidate unregistered words existing in the extracted document according to predetermined unregistered word extraction rules; extracting unregistered words among the candidate unregistered words and extracting candidate semantic classes of the unregistered words based on information on appearance frequencies of the candidate unregistered words retrieved from the document; verifying the unregistered words according to a predetermined unregistered word verification method and determining semantic classes of the verified unregistered words with usage examples of the unregistered words obtained through a searching unit; updating a first dictionary of the dictionary updating system by registering all of the verified unregistered words and the semantic classes of the verified unregistered words; and re-registering, in a second dictionary of the dictionary updating system, registered words among registered words registered in the first dictionary, based on the user's usage frequency of the registered words and appearance frequency information in a document of the registered words, wherein registered words registered in the second dictionary are retrieved prior to registered words registered in only the first dictionary. 10. The method of claim 1 , wherein the re-registering of the registered words comprises: calculating the user's usage frequency of the registered words among registered words registered in the first dictionary; calculating the appearance frequency in a document of the registered words among registered words registered in the first dictionary, and the changed appearance frequency value of the registered words in each extraction period; retrieving a registered word satisfying at least one of the user's usage frequency equal to or greater than a first threshold, the appearance frequency equal to or greater than a second threshold, and the changed appearance frequency value equal to or greater than a third threshold; and determining whether the retrieved registered word is registrable in the second dictionary and re-registering the retrieved registered word in the second dictionary. | 0.5 |
8,022,934 | 5 | 8 | 5. A handheld electronic device comprising: a processor apparatus comprising a processor and a memory in electronic communication, the memory having stored therein a plurality of objects comprising a plurality of language objects, at least some of the language objects each having a frequency value associated therewith; an input apparatus structured to provide input to the processor apparatus; an output apparatus structured to receive output signals from the processor apparatus; the memory further having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: detecting an ambiguous input; determining that at least a first language object and a second language object each correspond with at least a portion of the ambiguous input, the first language object being associated with a first frequency value, the second language object being associated with a second frequency value; detecting an occurrence of a predetermined input; responsive to the occurrence of the predetermined input, initiating the storing of a revised frequency value that effectively alters the frequency value with which one of the first language object and the second language object is associated; detecting another ambiguous input; determining that at least a third language object and a fourth language object each correspond with at least a portion of the another ambiguous input, one of the third language object and the fourth language object being associated with a frequency value higher than the frequency value with which the other of the third language object and the fourth language object is associated; making a determination that the third and fourth language objects are in a special category, the special category including word objects stored in the memory that correspond to a particular ambiguous input sequence and are of a same length; detecting another occurrence of the predetermined input; and responsive to said making a determination, maintaining the one of the third language object and the fourth language object associated with a frequency value higher than the frequency value with which the other of the third language object and the fourth language object is associated despite said detecting another occurrence of the predetermined input. | 5. A handheld electronic device comprising: a processor apparatus comprising a processor and a memory in electronic communication, the memory having stored therein a plurality of objects comprising a plurality of language objects, at least some of the language objects each having a frequency value associated therewith; an input apparatus structured to provide input to the processor apparatus; an output apparatus structured to receive output signals from the processor apparatus; the memory further having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: detecting an ambiguous input; determining that at least a first language object and a second language object each correspond with at least a portion of the ambiguous input, the first language object being associated with a first frequency value, the second language object being associated with a second frequency value; detecting an occurrence of a predetermined input; responsive to the occurrence of the predetermined input, initiating the storing of a revised frequency value that effectively alters the frequency value with which one of the first language object and the second language object is associated; detecting another ambiguous input; determining that at least a third language object and a fourth language object each correspond with at least a portion of the another ambiguous input, one of the third language object and the fourth language object being associated with a frequency value higher than the frequency value with which the other of the third language object and the fourth language object is associated; making a determination that the third and fourth language objects are in a special category, the special category including word objects stored in the memory that correspond to a particular ambiguous input sequence and are of a same length; detecting another occurrence of the predetermined input; and responsive to said making a determination, maintaining the one of the third language object and the fourth language object associated with a frequency value higher than the frequency value with which the other of the third language object and the fourth language object is associated despite said detecting another occurrence of the predetermined input. 8. The handheld electronic device of claim 5 , wherein the operations further comprise: making, as at least a portion of said determination, another determination that the third and fourth language objects each are of a length equal to the length of the another ambiguous input. | 0.726916 |
9,552,420 | 2 | 3 | 2. The method of claim 1 , further comprising generating the surrogate document by identifying and aggregating a plurality of search queries, corresponding user actions, and user action frequencies associated with the at least one document. | 2. The method of claim 1 , further comprising generating the surrogate document by identifying and aggregating a plurality of search queries, corresponding user actions, and user action frequencies associated with the at least one document. 3. The method of claim 2 , wherein identifying the plurality of search queries comprises normalizing the queries for space, punctuation, syntax, and term variations. | 0.536517 |
7,584,185 | 15 | 16 | 15. The search system of claim 13 , and comprising a current page analyzing part that analyzes a covering degree of the topic representation that is contained in a current version of one of the multiple Web pages, wherein the re-ranking part generates a renewed page ranking to each of the multiple Web pages by comparing the analysis results obtained by the current page analyzing part between the current versions of the multiple Web pages. | 15. The search system of claim 13 , and comprising a current page analyzing part that analyzes a covering degree of the topic representation that is contained in a current version of one of the multiple Web pages, wherein the re-ranking part generates a renewed page ranking to each of the multiple Web pages by comparing the analysis results obtained by the current page analyzing part between the current versions of the multiple Web pages. 16. The search system of claim 15 , wherein the covering degree of the topic representation that is contained in the current version of one of the multiple Web pages is a similarity degree or a difference degree concerning the topic representation between the current versions of the multiple Web pages. | 0.5 |
7,774,193 | 1 | 15 | 1. A method, implemented by a computing system comprising one or more processors, the method comprising: comparing, using one or more of the processors, one or more collocations from a text sample with a corpus; identifying, using one or more of the processors, whether the collocations are disfavored in the corpus; and providing indications of whether the collocations are disfavored via an output device; in which comparing the collocations with the corpus comprises performing one or more searches of the World Wide Web using one or more query terms that comprise each of one or more of the collocations; and in which for each of one or more of the collocations for which searches are performed, a search is performed for each of the one or more query terms that comprise the collocation until either one of the query terms provides search results that meet a preselected threshold for matching the collocation, or all the query terms that comprise the collocation are used without meeting the preselected threshold, and further comprising: composing one or more query terms with a wild card replacing a word in one of the disfavored collocations; searching a word collocation reference for the query terms; identifying results of the search having a relatively high proportion of a candidate word replacing the wild card; and providing the results of the search having the candidate word via the output device as potentially proper word collocations. | 1. A method, implemented by a computing system comprising one or more processors, the method comprising: comparing, using one or more of the processors, one or more collocations from a text sample with a corpus; identifying, using one or more of the processors, whether the collocations are disfavored in the corpus; and providing indications of whether the collocations are disfavored via an output device; in which comparing the collocations with the corpus comprises performing one or more searches of the World Wide Web using one or more query terms that comprise each of one or more of the collocations; and in which for each of one or more of the collocations for which searches are performed, a search is performed for each of the one or more query terms that comprise the collocation until either one of the query terms provides search results that meet a preselected threshold for matching the collocation, or all the query terms that comprise the collocation are used without meeting the preselected threshold, and further comprising: composing one or more query terms with a wild card replacing a word in one of the disfavored collocations; searching a word collocation reference for the query terms; identifying results of the search having a relatively high proportion of a candidate word replacing the wild card; and providing the results of the search having the candidate word via the output device as potentially proper word collocations. 15. The method of claim 1 , further comprising enabling a user to select one of the potentially proper word collocations to replace the disfavored word collocation to which it corresponds. | 0.806584 |
5,404,435 | 32 | 33 | 32. A data processing system for archiving image objects in a document, comprising: means for loading an existing index into a data processing system; means for inputting a document architecture envelope including a text object and an image object into said system; means coupled to said loading means and said inputting means for generating a first key word for said text object from said text object and adding said first key word to said index; said generating means automatically generating a second key word for said image object from said text object and adding said second key word to said index; means coupled to said inputting means for storing said document architecture envelope in said system; means coupled to said generating means for storing said index including said first and second key words in said system; means for entering a search term into said data processing system; means for comparing said search term with candidate key words in said index; and means for retrieving said image object if said second key word is found in said means for comparing. | 32. A data processing system for archiving image objects in a document, comprising: means for loading an existing index into a data processing system; means for inputting a document architecture envelope including a text object and an image object into said system; means coupled to said loading means and said inputting means for generating a first key word for said text object from said text object and adding said first key word to said index; said generating means automatically generating a second key word for said image object from said text object and adding said second key word to said index; means coupled to said inputting means for storing said document architecture envelope in said system; means coupled to said generating means for storing said index including said first and second key words in said system; means for entering a search term into said data processing system; means for comparing said search term with candidate key words in said index; and means for retrieving said image object if said second key word is found in said means for comparing. 33. The system of claim 32, wherein said second key word is generated from a caption word string in said text object. | 0.520492 |
7,814,404 | 22 | 36 | 22. The system of claim 21 , wherein the events are selected from the group comprising user events and system events. | 22. The system of claim 21 , wherein the events are selected from the group comprising user events and system events. 36. The system of claim 22 , wherein the embedded elements are selected from the group comprising: HTML; JSP; and ASP page-based applications. | 0.831354 |
6,044,387 | 31 | 32 | 31. The article of manufacture of claim 29, wherein the machine instructions cause the computer to create a list of files by identifying any file from the plurality of files for which the editing operation is applicable and adding the file to said list of files. | 31. The article of manufacture of claim 29, wherein the machine instructions cause the computer to create a list of files by identifying any file from the plurality of files for which the editing operation is applicable and adding the file to said list of files. 32. The article of manufacture of claim 31, wherein the machine instructions cause the list of the files for which the editing operation is applicable to be presented to the user, said list indicating an extent to which the editing operation is applicable to the files in the list. | 0.5 |
7,649,478 | 15 | 17 | 15. A data input system for generating character signals from a set of characters, the system comprising: a keyboard comprising a plurality of keys; a key signal detector coupled to said keyboard, said key signal detector being configured for detecting a keystroke of a key from said plurality of keys; and a character signal generator coupled to said key signal detector, said character signal generator being configured for generating a character signal when a keystroke sequence from a plurality of predefined key sequences is detected, wherein said plurality of predefined key sequences is generated using a variable-length prefix-fee encoding. | 15. A data input system for generating character signals from a set of characters, the system comprising: a keyboard comprising a plurality of keys; a key signal detector coupled to said keyboard, said key signal detector being configured for detecting a keystroke of a key from said plurality of keys; and a character signal generator coupled to said key signal detector, said character signal generator being configured for generating a character signal when a keystroke sequence from a plurality of predefined key sequences is detected, wherein said plurality of predefined key sequences is generated using a variable-length prefix-fee encoding. 17. The data input system of claim 15 , wherein: said character signal generator comprises a memory for storing a currently received keystroke sequence. | 0.70428 |
8,577,913 | 17 | 18 | 17. A server system, for query suggestion, comprising: one or more processors; and memory storing one or more programs to be executed by the one or more processors; the one or more programs comprising instructions for: receiving an original query from a client distinct from the server system; identifying one or more segments in the original query; identifying an anchor segment of the one or more segments in the original query, wherein the anchor segment is identified based on cursor placement within the original query, and identifying zero or more remaining segments of the original query, excluding the anchor segment; identifying one or more sibling segments associated with the anchor segment, wherein the one or more sibling segments are identified by the server system to be semantically distinct from anchor segment; identifying one or more query refinement candidates, wherein a respective query refinement candidate includes a respective sibling segment in place of the anchor segment and includes the remaining segments, if any, of the original query; sending to the client for presentation information including one or more of the query refinement candidates; receiving from the client one or more deleted characters from the original query and any remaining characters from the original query, the remaining characters consisting of characters of the original query which are not deleted characters; and reconstructing the original query from the deleted characters and the remaining characters; wherein the one or more sibling segments are identified using an algorithm that identifies sibling segments that are conceptually related to the anchor segment; and wherein, when the original query includes two or more segments, including the anchor segment and one or more remaining segments, identifying the one or more query refinement candidates comprises: forming potential query refinement candidates from the identified sibling segments and the one or more remaining segments; and excluding from the identified one or more query refinement candidates any of the potential refinement candidates not present in a predefined database of historical complete queries. | 17. A server system, for query suggestion, comprising: one or more processors; and memory storing one or more programs to be executed by the one or more processors; the one or more programs comprising instructions for: receiving an original query from a client distinct from the server system; identifying one or more segments in the original query; identifying an anchor segment of the one or more segments in the original query, wherein the anchor segment is identified based on cursor placement within the original query, and identifying zero or more remaining segments of the original query, excluding the anchor segment; identifying one or more sibling segments associated with the anchor segment, wherein the one or more sibling segments are identified by the server system to be semantically distinct from anchor segment; identifying one or more query refinement candidates, wherein a respective query refinement candidate includes a respective sibling segment in place of the anchor segment and includes the remaining segments, if any, of the original query; sending to the client for presentation information including one or more of the query refinement candidates; receiving from the client one or more deleted characters from the original query and any remaining characters from the original query, the remaining characters consisting of characters of the original query which are not deleted characters; and reconstructing the original query from the deleted characters and the remaining characters; wherein the one or more sibling segments are identified using an algorithm that identifies sibling segments that are conceptually related to the anchor segment; and wherein, when the original query includes two or more segments, including the anchor segment and one or more remaining segments, identifying the one or more query refinement candidates comprises: forming potential query refinement candidates from the identified sibling segments and the one or more remaining segments; and excluding from the identified one or more query refinement candidates any of the potential refinement candidates not present in a predefined database of historical complete queries. 18. The server system of claim 17 , wherein the sibling segment is identified without regard to any characters in the anchor segment. | 0.83375 |
10,152,543 | 14 | 17 | 14. A non-transitory machine-readable medium comprising instructions stored therein, which when executed by a machine, cause the machine to perform operations comprising: identifying content items provided in response to a query including a set of search terms associated with a topic; receiving an indication of selection of at least one content item of the content items, wherein the selection of the at least one content item provides access to the at least one content item; associating, in response to receiving the indication, the set of search terms of the query with the topic of the at least one content item; selecting one or more terms from the set of search terms based on one or more criteria; generating a label from the selected one or more terms by restricting titles of the content items to be excluded from the label; and applying the label to the content items relating to the topic. | 14. A non-transitory machine-readable medium comprising instructions stored therein, which when executed by a machine, cause the machine to perform operations comprising: identifying content items provided in response to a query including a set of search terms associated with a topic; receiving an indication of selection of at least one content item of the content items, wherein the selection of the at least one content item provides access to the at least one content item; associating, in response to receiving the indication, the set of search terms of the query with the topic of the at least one content item; selecting one or more terms from the set of search terms based on one or more criteria; generating a label from the selected one or more terms by restricting titles of the content items to be excluded from the label; and applying the label to the content items relating to the topic. 17. The non-transitory machine-readable medium of claim 14 , wherein the label comprises a hash tag applied to one or more posts discussing the topic. | 0.652778 |
9,910,914 | 12 | 18 | 12. A computer-implemented method of semantic information retrieval based on a semantic dictionary augmented with explicit rules that enable machine learning and deep contextual understanding comprising: curating in real-time and interactively semantic expressions taken from a networked database; configuring a gloss vector engine operable to generate semantic gloss vectors for data mining by unsupervised machine learning; configuring a deconstruction engine operable to identify well-formed sentences; configuring a data discovery engine operable to identify indirect communicating links; configuring a collocation engine operable to identify compound nouns; configuring a disambiguation engine operable to assign appropriate nouns given context; configuring a generic noun disambiguation engine operable to identify context shifts produced by use of generic or common nouns; configuring a pronoun disambiguation engine operable to link common nouns to proper nouns; configuring a data evaluation engine operable to identify well-formed sentences containing information of maximal semantic value; configuring a retrieval engine operable to return information of the highest semantic value for a given search term; and configuring a context targeting engine operable to display in context the specific sentence in the source article showing the query results wherein one or more users can dynamically obtain responses to queries of multiple search terms across bodies of corpus. | 12. A computer-implemented method of semantic information retrieval based on a semantic dictionary augmented with explicit rules that enable machine learning and deep contextual understanding comprising: curating in real-time and interactively semantic expressions taken from a networked database; configuring a gloss vector engine operable to generate semantic gloss vectors for data mining by unsupervised machine learning; configuring a deconstruction engine operable to identify well-formed sentences; configuring a data discovery engine operable to identify indirect communicating links; configuring a collocation engine operable to identify compound nouns; configuring a disambiguation engine operable to assign appropriate nouns given context; configuring a generic noun disambiguation engine operable to identify context shifts produced by use of generic or common nouns; configuring a pronoun disambiguation engine operable to link common nouns to proper nouns; configuring a data evaluation engine operable to identify well-formed sentences containing information of maximal semantic value; configuring a retrieval engine operable to return information of the highest semantic value for a given search term; and configuring a context targeting engine operable to display in context the specific sentence in the source article showing the query results wherein one or more users can dynamically obtain responses to queries of multiple search terms across bodies of corpus. 18. The computer-based method of claim 12 further comprising: identifying a context shift; and retaining factual information. | 0.84976 |
9,009,747 | 19 | 20 | 19. An apparatus for gesture recognition comprising: a control device; a processor operable to execute a program of a method for gesture recognition, wherein the method comprising: receiving sample motion data from one or more sensors; calculating a local variance of the sample motion data over a predetermined number of local variance samples; beginning recording one or more values of the sample motion data for a gesture if the local variance scalar value is greater than a start threshold; calculating an average local variance scalar value using the one or more values of the sample motion data for a gesture; and stopping the recording of the one or more values of the sample motion data for a gesture if the local variance scalar value is less than a stop threshold. | 19. An apparatus for gesture recognition comprising: a control device; a processor operable to execute a program of a method for gesture recognition, wherein the method comprising: receiving sample motion data from one or more sensors; calculating a local variance of the sample motion data over a predetermined number of local variance samples; beginning recording one or more values of the sample motion data for a gesture if the local variance scalar value is greater than a start threshold; calculating an average local variance scalar value using the one or more values of the sample motion data for a gesture; and stopping the recording of the one or more values of the sample motion data for a gesture if the local variance scalar value is less than a stop threshold. 20. The apparatus of claim 19 , wherein the method for gesture recognition further comprises: calculating a figure of merit using the sample values in the gesture and sample values in one or more catalog gesture, wherein the figure of merit is a measure of how well the gesture matched the catalog gesture; determining whether an input gesture matches one of the one or more catalog gesture based on the figure of merit; and taking action if the input gesture matches the one of the one or more catalog gesture. | 0.5 |
8,521,587 | 2 | 10 | 2. A method for placing advertisements on a user interface comprising the steps of: providing a user interface having a plurality of user interface screens, at least some of said plurality of user interface screens containing user-selectable objects; and determining, by using a processor, which of a plurality of advertisements to display on a user interface screen based on at least one of the following criteria: topical relevance, contextual relevance, path relevance and cognitive prominence, wherein said at least one criteria includes contextual relevance and said contextual relevance is a measure of a relationship between a theme of the respective user interface screen and a theme associated with each advertisement, and further wherein said contextual relevance is calculated as: HD ( q , c ) = ∑ x ∈ { P q - P c } α r x + ∑ y ∈ { P c - P q } β r y + ∑ z ∈ { q , c } γ r z where: α, β, and γ are weighting factors, r n is a hierarchical level of a given topic, and P n is a set of parent topics of an item. | 2. A method for placing advertisements on a user interface comprising the steps of: providing a user interface having a plurality of user interface screens, at least some of said plurality of user interface screens containing user-selectable objects; and determining, by using a processor, which of a plurality of advertisements to display on a user interface screen based on at least one of the following criteria: topical relevance, contextual relevance, path relevance and cognitive prominence, wherein said at least one criteria includes contextual relevance and said contextual relevance is a measure of a relationship between a theme of the respective user interface screen and a theme associated with each advertisement, and further wherein said contextual relevance is calculated as: HD ( q , c ) = ∑ x ∈ { P q - P c } α r x + ∑ y ∈ { P c - P q } β r y + ∑ z ∈ { q , c } γ r z where: α, β, and γ are weighting factors, r n is a hierarchical level of a given topic, and P n is a set of parent topics of an item. 10. The method of claim 2 , further comprising the step of: displaying at least one advertisement on said user interface as a result of said determining step. | 0.892077 |
7,937,269 | 12 | 18 | 12. A non-transitory program storage device readable by machine, embodying a program of instructions executable by a processor of the machine to perform method steps for real-time classification of a continuous data stream, the method steps comprising: receiving a continuous data stream; clustering, incrementally, speech data in each contiguous segment of the received data stream into a plurality of micro-clusters, wherein the plurality of micro-clusters is stored as a snapshot in time, the snapshot updating with time and indicating a dominant micro-cluster in the data stream; generating a target profile for each segment of the received data stream based on the snapshot of micro-clusters associated with each segment, wherein generating the target profile comprises generating a histogram profile for a given segment using summary information of data records associated with the micro-clusters for the given segment, wherein the histogram profile is generated based on relative frequencies of data points associated with each micro-cluster for the given segment as compared to a total number of data points in the micro-clusters for the given segment; and classifying each segment of the received data stream using the target profile associated with each segment. | 12. A non-transitory program storage device readable by machine, embodying a program of instructions executable by a processor of the machine to perform method steps for real-time classification of a continuous data stream, the method steps comprising: receiving a continuous data stream; clustering, incrementally, speech data in each contiguous segment of the received data stream into a plurality of micro-clusters, wherein the plurality of micro-clusters is stored as a snapshot in time, the snapshot updating with time and indicating a dominant micro-cluster in the data stream; generating a target profile for each segment of the received data stream based on the snapshot of micro-clusters associated with each segment, wherein generating the target profile comprises generating a histogram profile for a given segment using summary information of data records associated with the micro-clusters for the given segment, wherein the histogram profile is generated based on relative frequencies of data points associated with each micro-cluster for the given segment as compared to a total number of data points in the micro-clusters for the given segment; and classifying each segment of the received data stream using the target profile associated with each segment. 18. The non-transitory program storage device of claim 12 , wherein the instructions for classifying comprise instructions for comparing the target profiles over a plurality of segments to detect an event in the data stream. | 0.521368 |
9,460,719 | 9 | 10 | 9. The system according to claim 8 , wherein the delivery agent component is further configured to: receive a request for status information; and respond to the request for the status information by transmitting status information descriptive of the QA transcription information. | 9. The system according to claim 8 , wherein the delivery agent component is further configured to: receive a request for status information; and respond to the request for the status information by transmitting status information descriptive of the QA transcription information. 10. The system according to claim 9 , wherein the delivery agent component is further configured to: receive a request for a latest transcription product; evaluate the first delivery criteria at least in part by identifying the request for the latest transcription product; evaluate the third delivery criteria at least in part by identifying the request for the latest transcription product; evaluate the fourth delivery criteria at least in part by identifying the request for the latest transcription product; and respond to the request for the latest transcription product by transmitting the fourth transcription product. | 0.5 |
8,948,789 | 24 | 26 | 24. A method for inferring a context associated with a mobile device, the method comprising: accessing low-level context information for each of a plurality of other devices, wherein location information associated with each of the other devices indicates a proximity between a location of the other device at a first time and a location of the mobile device at a second time, the first time and the second time being different, and wherein the low-level context information for each of the other devices is based on data collected by a sensor of the respective other device; aggregating the low-level context information across the plurality of other devices; comparing the aggregated low-level context information to a plurality of templates, each template being associated with a high-level context and including one or more histograms of context data; determining match scores between the aggregated low-level context information and each of the one or more histograms of context data; and transmitting, to the mobile device, a multi-device statistical summary comprising the aggregated low-level context information and the match scores; and the mobile device inferring a context based on the multi-device statistical summary and additional data not included in the multi-device statistical summary. | 24. A method for inferring a context associated with a mobile device, the method comprising: accessing low-level context information for each of a plurality of other devices, wherein location information associated with each of the other devices indicates a proximity between a location of the other device at a first time and a location of the mobile device at a second time, the first time and the second time being different, and wherein the low-level context information for each of the other devices is based on data collected by a sensor of the respective other device; aggregating the low-level context information across the plurality of other devices; comparing the aggregated low-level context information to a plurality of templates, each template being associated with a high-level context and including one or more histograms of context data; determining match scores between the aggregated low-level context information and each of the one or more histograms of context data; and transmitting, to the mobile device, a multi-device statistical summary comprising the aggregated low-level context information and the match scores; and the mobile device inferring a context based on the multi-device statistical summary and additional data not included in the multi-device statistical summary. 26. The method of claim 24 , wherein the inferred context includes a high-level context. | 0.658915 |
9,055,074 | 11 | 12 | 11. A system for aggregating social media content items from a plurality of social media providers, the system comprising: one or more processors programmed with computer program instructions to: obtain at least a first parameter that specifies one or more geographically definable locations; generate a first request that specifies the one or more geographically definable locations in a first format used by a first social media content provider; generate a second request that specifies the one or more geographically definable locations in a second format used by a second social media content provider; communicate the first request to the first social media content provider; communicate the second request to the second social media content provider; receive a first set of social media content items from the first social media content provider, wherein the first set of social media content items includes at least a first social media content item associated with information that indicates that the first social media item is relevant to one or more geographically definable locations; receive a second set of social media content items from the second social media content provider, wherein the second set of social media content items includes at least a second social media item associated with information that indicates that the second social media content item is relevant to the one or more geographically definable locations; and communicate the at least a portion of the first set of social media content items and at least a portion of the second set of social media content items. | 11. A system for aggregating social media content items from a plurality of social media providers, the system comprising: one or more processors programmed with computer program instructions to: obtain at least a first parameter that specifies one or more geographically definable locations; generate a first request that specifies the one or more geographically definable locations in a first format used by a first social media content provider; generate a second request that specifies the one or more geographically definable locations in a second format used by a second social media content provider; communicate the first request to the first social media content provider; communicate the second request to the second social media content provider; receive a first set of social media content items from the first social media content provider, wherein the first set of social media content items includes at least a first social media content item associated with information that indicates that the first social media item is relevant to one or more geographically definable locations; receive a second set of social media content items from the second social media content provider, wherein the second set of social media content items includes at least a second social media item associated with information that indicates that the second social media content item is relevant to the one or more geographically definable locations; and communicate the at least a portion of the first set of social media content items and at least a portion of the second set of social media content items. 12. The system of claim 11 , wherein the one or more processors are further programmed to: store in a storage for later retrieval: at least the portion of the first set of social media content items, at least the portion of the second set of social media content items, and/or a geofeed definition that comprises the first parameters that specifies the one or more geographically definable locations. | 0.547511 |
9,337,955 | 3 | 4 | 3. The mobile communication device of claim 1 , wherein to generate the initial code word, the ECC decoder is further configured to retain reliability values of respective bits of the given code word. | 3. The mobile communication device of claim 1 , wherein to generate the initial code word, the ECC decoder is further configured to retain reliability values of respective bits of the given code word. 4. The mobile communication device of claim 3 , wherein to iteratively decode the given code word, the ECC decoder is further configured to converge to the error pattern dependent upon the retained reliability values. | 0.5 |
8,423,485 | 16 | 17 | 16. A correspondence learning apparatus according to claim 5 , further comprising: a information update module that updates the covariance matrices C xx , C yy , C xy and C yx in accordance with a following equation (105) and solves the eigenvalue problem of the equation (3) to obtain the transformation to derive the latent variables when a n th combination of a new first feature x(n) and a new second feature y(n) occurs in the presence of n−1 combinations of the first features x(1), . . . , x(i), . . . , x(n−1) and the second feature y(1), . . . , y(i), . . . , y(n−1), where n>=2, 1 represents a decay rate, x ˜ (n) and y ˜ (n) are given in a following equation (106), m x (n) and m y (n) are given in a following equation (107): C xx ( n ) = n - 1 - l n C xx ( n - 1 ) + 1 + l n x ~ ( n ) x ~ T ( n ) C yy ( n ) = n - 1 - l n C yy ( n - 1 ) + 1 + l n y ~ ( n ) y ~ T ( n ) C xy ( n ) = n - 1 - l n C xy ( n - 1 ) + 1 + l n x ~ ( n ) y ~ T ( n ) C yx ( n ) = C xy T ( n ) } ( 105 ) x ~ ( n ) = x ( n ) - m x ( n ) y ~ ( n ) = y ( n ) - m y ( n ) } ( 106 ) m x ( n ) = n - 1 - l n m x ( n - 1 ) + 1 + l n x ( n ) m y ( n ) = n - 1 - l n m y ( n - 1 ) + 1 + l n y ( n ) } . ( 107 ) | 16. A correspondence learning apparatus according to claim 5 , further comprising: a information update module that updates the covariance matrices C xx , C yy , C xy and C yx in accordance with a following equation (105) and solves the eigenvalue problem of the equation (3) to obtain the transformation to derive the latent variables when a n th combination of a new first feature x(n) and a new second feature y(n) occurs in the presence of n−1 combinations of the first features x(1), . . . , x(i), . . . , x(n−1) and the second feature y(1), . . . , y(i), . . . , y(n−1), where n>=2, 1 represents a decay rate, x ˜ (n) and y ˜ (n) are given in a following equation (106), m x (n) and m y (n) are given in a following equation (107): C xx ( n ) = n - 1 - l n C xx ( n - 1 ) + 1 + l n x ~ ( n ) x ~ T ( n ) C yy ( n ) = n - 1 - l n C yy ( n - 1 ) + 1 + l n y ~ ( n ) y ~ T ( n ) C xy ( n ) = n - 1 - l n C xy ( n - 1 ) + 1 + l n x ~ ( n ) y ~ T ( n ) C yx ( n ) = C xy T ( n ) } ( 105 ) x ~ ( n ) = x ( n ) - m x ( n ) y ~ ( n ) = y ( n ) - m y ( n ) } ( 106 ) m x ( n ) = n - 1 - l n m x ( n - 1 ) + 1 + l n x ( n ) m y ( n ) = n - 1 - l n m y ( n - 1 ) + 1 + l n y ( n ) } . ( 107 ) 17. A correspondence learning apparatus according to claim 16 , wherein the information update module updates the covariance matrices associated with the second feature in accordance with a following equation (108) when the order of the second feature increases with an occurrence of the new first feature x(n) and the new second feature y(n), where m y (n) is given in a following equation (109): C yy ( n ) = n - 1 - l n ( C yy ( n - 1 ) 0 0 0 ) + 1 + l n y ~ ( n ) y ~ T ( n ) C xy ( n ) = n - 1 - l n ( C xy ( n - 1 ) 0 ) + 1 + l n x ~ ( n ) y ~ T ( n ) } ( 108 ) m y ( n ) = n - 1 - l n ( m y ( n - 1 ) 0 ) + 1 + l n y ( n ) . ( 109 ) | 0.5 |
8,682,391 | 5 | 6 | 5. The mobile terminal of claim 1 , further comprising: a memory configured to store an object information database including at least textual object information for objects within a predetermined vicinity of the current location of the mobile terminal, wherein the control unit is further configured to search for and obtain the textual object information corresponding to the object within the camera preview image from the object information database stored in the memory. | 5. The mobile terminal of claim 1 , further comprising: a memory configured to store an object information database including at least textual object information for objects within a predetermined vicinity of the current location of the mobile terminal, wherein the control unit is further configured to search for and obtain the textual object information corresponding to the object within the camera preview image from the object information database stored in the memory. 6. The mobile terminal of claim 5 , wherein the controller is further configured to populate the object information database by downloading, via the wireless communication unit, said at least textual object information for objects within the predetermined vicinity of the current location of the mobile terminal from an external server. | 0.5 |
8,386,251 | 1 | 9 | 1. A method to be executed at least in part in a computing device for providing multistage speech recognition, the method comprising: receiving an utterance from a speaker; performing a first pass speech recognition on the utterance employing at least one algorithm including a gender detection algorithm and a feature MLLR (fMLLR) algorithm executed sequentially; adapting the at least one algorithm based on a result of the first pass speech recognition; performing a second pass speech recognition on the utterance employing the adapted at least one algorithm wherein at least one algorithm is adapted in a progressive manner at the second pass based on a result of the first pass of speech recognition by constraining at least one of an acoustic model and a language model associated with the at least one algorithm, wherein constraining at least one of the acoustic model and the language model associated with the algorithms includes reducing a search space for the at least one algorithm; and employing the adapted at least one algorithm for performing speech recognition on subsequent utterances from the same speaker. | 1. A method to be executed at least in part in a computing device for providing multistage speech recognition, the method comprising: receiving an utterance from a speaker; performing a first pass speech recognition on the utterance employing at least one algorithm including a gender detection algorithm and a feature MLLR (fMLLR) algorithm executed sequentially; adapting the at least one algorithm based on a result of the first pass speech recognition; performing a second pass speech recognition on the utterance employing the adapted at least one algorithm wherein at least one algorithm is adapted in a progressive manner at the second pass based on a result of the first pass of speech recognition by constraining at least one of an acoustic model and a language model associated with the at least one algorithm, wherein constraining at least one of the acoustic model and the language model associated with the algorithms includes reducing a search space for the at least one algorithm; and employing the adapted at least one algorithm for performing speech recognition on subsequent utterances from the same speaker. 9. The method of claim 1 , wherein the at least one algorithm is adapted to determine at least one from a set of: a speaker attribute, a speaker environment, and a context of the utterance. | 0.667254 |
8,490,050 | 10 | 13 | 10. A computer-readable memory comprising computer-executable instructions which when executed cause a computing environment to: schematize a reference object according to an analysis of metadata associated with a reference object, wherein at least one reference object access point is schematized according to whether the analysis of the metadata reveals a communicative intent of the at least one reference object access point; determine via the analysis an existence of the communicative intent by determining if an access point to the reference object has both an input and an output that complies with a provided service-specific schema pattern; and auto-generate a service-specific user interface targeted to a particular platform by applying a target-specific transform to a service-neutral internal representation of the at least one reference object access point. | 10. A computer-readable memory comprising computer-executable instructions which when executed cause a computing environment to: schematize a reference object according to an analysis of metadata associated with a reference object, wherein at least one reference object access point is schematized according to whether the analysis of the metadata reveals a communicative intent of the at least one reference object access point; determine via the analysis an existence of the communicative intent by determining if an access point to the reference object has both an input and an output that complies with a provided service-specific schema pattern; and auto-generate a service-specific user interface targeted to a particular platform by applying a target-specific transform to a service-neutral internal representation of the at least one reference object access point. 13. The computer-readable memory of claim 10 , comprising further computer-executable instructions, which when executed cause the computing environment to: generate Windows Presentation Foundation (WPF) XAML from a web services operation. | 0.791958 |
8,185,517 | 7 | 10 | 7. The computer program product of claim 6 , further comprising: refining the query context, wherein refining the query context includes: presenting one or more search result contexts related to the first results to the user; receiving input from the user regarding a user-chosen search result context; and modifying the query context based on the user-chosen search result context; searching second data for second results, wherein the searching is limited by the refined query context; and providing second results to the user. | 7. The computer program product of claim 6 , further comprising: refining the query context, wherein refining the query context includes: presenting one or more search result contexts related to the first results to the user; receiving input from the user regarding a user-chosen search result context; and modifying the query context based on the user-chosen search result context; searching second data for second results, wherein the searching is limited by the refined query context; and providing second results to the user. 10. The computer program product of claim 7 wherein developing a query context comprises: parsing the query for keywords; and identifying the user. | 0.5 |
8,103,110 | 14 | 15 | 14. The logic of claim 13 , wherein the logic is further operable to calculate the third probability using Bayes rules. | 14. The logic of claim 13 , wherein the logic is further operable to calculate the third probability using Bayes rules. 15. The logic of claim 14 , wherein the logic is further operable to calculate the third probability using one or more metaprobabilities to adjust for the weight of evidence. | 0.5 |
8,527,509 | 14 | 15 | 14. A search system, comprising: a search service subsystem having a processor and a storage including instructions that, when executed by the processor, cause the processor, to receive a search request, receive a meta index reported by each member engine, select a member engine according to the meta index of each member engine, the search request, and a user interest model, and send the search request to the selected member engine; and at least one member engine, configured to report the meta index of the member engine to the search service subsystem, and receive the search request sent from the search service subsystem, so as to complete searching; wherein the user interest model is a vector formed with scores given to each of several interest dimensions denoting user interests; the user interest model comprises a static interest model and a dynamic interest model: the static interest model is obtained by obtaining frequencies of words belonging to a certain interest dimension in a static user profile of a user, calculating a sum of the frequencies of the words belonging to the interest dimension as a score of the interest dimension, and forming a score vector with different scores to create a static interest model; and the dynamic interest model is obtained by obtaining frequencies of words belonging to a certain interest dimension in a document clicked in a search history of a user, calculating a sum of the frequencies of the words belonging to the interest dimension in the document as a score specific to the interest dimension in the document, forming a score vector specific to the document with different scores specific to different interest dimensions, and a sum of the score vectors specific to different documents to create a dynamic interest model. | 14. A search system, comprising: a search service subsystem having a processor and a storage including instructions that, when executed by the processor, cause the processor, to receive a search request, receive a meta index reported by each member engine, select a member engine according to the meta index of each member engine, the search request, and a user interest model, and send the search request to the selected member engine; and at least one member engine, configured to report the meta index of the member engine to the search service subsystem, and receive the search request sent from the search service subsystem, so as to complete searching; wherein the user interest model is a vector formed with scores given to each of several interest dimensions denoting user interests; the user interest model comprises a static interest model and a dynamic interest model: the static interest model is obtained by obtaining frequencies of words belonging to a certain interest dimension in a static user profile of a user, calculating a sum of the frequencies of the words belonging to the interest dimension as a score of the interest dimension, and forming a score vector with different scores to create a static interest model; and the dynamic interest model is obtained by obtaining frequencies of words belonging to a certain interest dimension in a document clicked in a search history of a user, calculating a sum of the frequencies of the words belonging to the interest dimension in the document as a score specific to the interest dimension in the document, forming a score vector specific to the document with different scores specific to different interest dimensions, and a sum of the score vectors specific to different documents to create a dynamic interest model. 15. The search system according to claim 14 , wherein the search service subsystem further comprises instructions that, when executed by the processor, cause the processor to extract the user interest model from user personalized data according to the search request, so as to select the member engine according to the meta index of each member engine, the search request, and the user interest model. | 0.5 |
9,537,674 | 37 | 39 | 37. A computerized telephone as defined in claim 36 , wherein said computerized telephone is a cordless telephone including a base station and at least one handset that is capable of wireless communication with the base station. | 37. A computerized telephone as defined in claim 36 , wherein said computerized telephone is a cordless telephone including a base station and at least one handset that is capable of wireless communication with the base station. 39. A computerized telephone as defined in claim 37 , wherein the handset comprises the display. | 0.524752 |
8,793,565 | 12 | 13 | 12. An apparatus comprising: a display; and a processor coupled to said display and programmed with instructions to: parse a first electronic file having a first electronic file format to identify one or more interactive elements defined in said first electronic file format, the one or more interactive elements configured to provide one or more dynamic functions, at least one of said dynamic functions comprising cursor control interactivity; create a second electronic file in a second electronic file format based at least in part on said first electronic file, said second electronic file includes one or more interactive elements defined in said second electronic file format that provide one or more dynamic functions associated with states of said interactive elements defined in said first electronic file format in said second electronic file, at least one of said dynamic functions being cursor control interactivity; and apply an actuation event to at least one of said interactive elements of said second electronic file to change a state of said at least one of said interactive elements, the changing said state is associated with a change in displayed information from a first image to a second image and that reverts back to the first image when the actuation event is no longer detected. | 12. An apparatus comprising: a display; and a processor coupled to said display and programmed with instructions to: parse a first electronic file having a first electronic file format to identify one or more interactive elements defined in said first electronic file format, the one or more interactive elements configured to provide one or more dynamic functions, at least one of said dynamic functions comprising cursor control interactivity; create a second electronic file in a second electronic file format based at least in part on said first electronic file, said second electronic file includes one or more interactive elements defined in said second electronic file format that provide one or more dynamic functions associated with states of said interactive elements defined in said first electronic file format in said second electronic file, at least one of said dynamic functions being cursor control interactivity; and apply an actuation event to at least one of said interactive elements of said second electronic file to change a state of said at least one of said interactive elements, the changing said state is associated with a change in displayed information from a first image to a second image and that reverts back to the first image when the actuation event is no longer detected. 13. The apparatus of claim 12 , wherein said first electronic file format comprises a hypertext markup language type format and said second electronic tile format comprises a non-hypertext markup language type format. | 0.708333 |
9,158,821 | 1 | 5 | 1. A method comprising: establishing a pool of potential matches for a user in a computer-implemented matching system, wherein each of the potential matches meet at least one criteria of the user; determining a messaging score for each of the potential matches of the pool, the messaging score indicating a messaging aptitude of the potential match; and ranking the potential matches, wherein each of the potential matches is ranked based on a similarity of the messaging score of the potential match to a messaging score of the user; wherein the messaging score for each of the potential matches comprises a combination of at least one of a number of three way interactions initiated by the potential match as compared to an average number of three way interactions initiated by other users having a similar age and same gender as the potential match, a number of messages sent by the potential match as compared to an average number of messages sent by other users having a similar age and same gender as the potential match, and a number of messages received by the potential match as compared to an average number of messages received by other users having a similar age and same gender as the potential match. | 1. A method comprising: establishing a pool of potential matches for a user in a computer-implemented matching system, wherein each of the potential matches meet at least one criteria of the user; determining a messaging score for each of the potential matches of the pool, the messaging score indicating a messaging aptitude of the potential match; and ranking the potential matches, wherein each of the potential matches is ranked based on a similarity of the messaging score of the potential match to a messaging score of the user; wherein the messaging score for each of the potential matches comprises a combination of at least one of a number of three way interactions initiated by the potential match as compared to an average number of three way interactions initiated by other users having a similar age and same gender as the potential match, a number of messages sent by the potential match as compared to an average number of messages sent by other users having a similar age and same gender as the potential match, and a number of messages received by the potential match as compared to an average number of messages received by other users having a similar age and same gender as the potential match. 5. The method of claim 1 further comprising determining an attractiveness factor for each of the potential matches, wherein each of the potential matches is ranked based on a weighted combination of a similarity of the attractiveness factor of the potential match and an attractiveness factor of the user and the similarity of the messaging score of the potential match to the messaging score of the user. | 0.681102 |
8,768,062 | 1 | 3 | 1. A method for recognizing a handwritten sub-word unit for a script, the method comprising: receiving, by a processor, a handwritten-text on an user interface; segmenting, by the processor, the handwritten-text into words, each word comprising sub-word units; segmenting strokes from the sub-word units such that each sub-word unit comprises one or more strokes; identifying critical points on a stroke of the one or more strokes based on directional properties of a curve present in the stroke, wherein the critical points are representative of a curvature change in the stroke; determining fuzzy directional features based on an angle between consecutive critical points on the stroke and two or more directions associated with the angle between the consecutive critical points, wherein the fuzzy directional features represent the stroke; extracting one or more reference strokes from a primitive stroke database based upon a matching of the strokes with the primitive stroke database, wherein the primitive stroke database comprises a plurality of reference strokes for the script; combining, by the processor, the one or more reference strokes based on a rule set to generate the sub-word unit, wherein the rule set is script specific. | 1. A method for recognizing a handwritten sub-word unit for a script, the method comprising: receiving, by a processor, a handwritten-text on an user interface; segmenting, by the processor, the handwritten-text into words, each word comprising sub-word units; segmenting strokes from the sub-word units such that each sub-word unit comprises one or more strokes; identifying critical points on a stroke of the one or more strokes based on directional properties of a curve present in the stroke, wherein the critical points are representative of a curvature change in the stroke; determining fuzzy directional features based on an angle between consecutive critical points on the stroke and two or more directions associated with the angle between the consecutive critical points, wherein the fuzzy directional features represent the stroke; extracting one or more reference strokes from a primitive stroke database based upon a matching of the strokes with the primitive stroke database, wherein the primitive stroke database comprises a plurality of reference strokes for the script; combining, by the processor, the one or more reference strokes based on a rule set to generate the sub-word unit, wherein the rule set is script specific. 3. The method of claim 1 , wherein combining further comprises validating a sequence of the one or more reference strokes to generate the sub-word unit based on the rule set. | 0.759669 |
8,359,394 | 1 | 2 | 1. A computer-implemented process for determining whether a computer user is a human or a computer program, comprising: using a computer for: generating a string of characters to be used as the foreground of a human interactive proof; arranging the characters spatially; tearing the characters into torn pieces by cutting an image of the arranged string characters into slices and dividing each of the slices into one or more parts, wherein the characters are arranged in a single line and characters are cut into upper and lower slices and wherein the upper and lower slices are based on a roughly horizontal curve defined by a set of cutting points; applying a conformal transform to the arranged torn characters, wherein the conformal transformation preserves the angles of any two crossing lines of any character of the string of characters to create a human interactive proof of the string of characters; requiring a computer user to identify the characters of the human interactive proof; comparing the computer user's identification of the characters of the human interactive proof to the string of characters; and determining whether the computer user is a human or a computer program by using the comparison of the computer user's identification of the characters of the human interactive proof to the string of characters. | 1. A computer-implemented process for determining whether a computer user is a human or a computer program, comprising: using a computer for: generating a string of characters to be used as the foreground of a human interactive proof; arranging the characters spatially; tearing the characters into torn pieces by cutting an image of the arranged string characters into slices and dividing each of the slices into one or more parts, wherein the characters are arranged in a single line and characters are cut into upper and lower slices and wherein the upper and lower slices are based on a roughly horizontal curve defined by a set of cutting points; applying a conformal transform to the arranged torn characters, wherein the conformal transformation preserves the angles of any two crossing lines of any character of the string of characters to create a human interactive proof of the string of characters; requiring a computer user to identify the characters of the human interactive proof; comparing the computer user's identification of the characters of the human interactive proof to the string of characters; and determining whether the computer user is a human or a computer program by using the comparison of the computer user's identification of the characters of the human interactive proof to the string of characters. 2. The computer-implemented process of claim 1 , further comprising: warping each part of the divided slices. | 0.72335 |
6,137,863 | 10 | 11 | 10. A method of recognizing an identifier entered by a user, the identifier including a first plurality of predetermined characters, the method comprising the steps of: a) providing a recognized identifier based on the entered identifier, the recognized identifier comprising a second plurality of predetermined characters; b) providing a plurality of reference identifiers, each one of the plurality of reference identifiers comprising a different plurality of predetermined characters; c) obtaining from a stored data structure, for each character position in at least one of the reference identifiers and each character position in the recognized identifier, a previously determined probability that a character in the at least one reference identifier is recognized as a character found in the corresponding character position in the recognized identifier, each probability in the stored data structure representing a quantification of a tendency of one predetermined character to be recognized as one of the predetermined character and another predetermined character; d) determining an identifier recognition probability based on the obtained probabilities; e) repeating steps c) and d) for every reference identifier in the plurality of reference identifiers, each one of the plurality of reference identifiers being associated with a corresponding identifier recognition probability; and f) selecting the reference identifier most likely matching the entered identifier based on the plurality of obtained recognition probabilities, wherein the entered identifier is entered by the user through a touch-tone input device. | 10. A method of recognizing an identifier entered by a user, the identifier including a first plurality of predetermined characters, the method comprising the steps of: a) providing a recognized identifier based on the entered identifier, the recognized identifier comprising a second plurality of predetermined characters; b) providing a plurality of reference identifiers, each one of the plurality of reference identifiers comprising a different plurality of predetermined characters; c) obtaining from a stored data structure, for each character position in at least one of the reference identifiers and each character position in the recognized identifier, a previously determined probability that a character in the at least one reference identifier is recognized as a character found in the corresponding character position in the recognized identifier, each probability in the stored data structure representing a quantification of a tendency of one predetermined character to be recognized as one of the predetermined character and another predetermined character; d) determining an identifier recognition probability based on the obtained probabilities; e) repeating steps c) and d) for every reference identifier in the plurality of reference identifiers, each one of the plurality of reference identifiers being associated with a corresponding identifier recognition probability; and f) selecting the reference identifier most likely matching the entered identifier based on the plurality of obtained recognition probabilities, wherein the entered identifier is entered by the user through a touch-tone input device. 11. The method of claim 10, wherein the recognized identifier is provided by a touch-tone recognizer. | 0.5 |
7,996,214 | 9 | 12 | 9. A system for exploiting information in an utterance for dialog act tagging, the system comprising: a first module configured to control a processor to receive a user utterance; a second module configured to control the processor to compute at periodic intervals at least one parameter in the user utterance; a third module configured to control the processor to quantize the at least one parameter at each periodic interval; a fourth module configured to control the processor to approximate conditional probabilities using an n-gram over a sliding window over the periodic intervals; and a fifth module configured to control the processor to tag the utterance as a dialog act based on the approximated conditional probabilities. | 9. A system for exploiting information in an utterance for dialog act tagging, the system comprising: a first module configured to control a processor to receive a user utterance; a second module configured to control the processor to compute at periodic intervals at least one parameter in the user utterance; a third module configured to control the processor to quantize the at least one parameter at each periodic interval; a fourth module configured to control the processor to approximate conditional probabilities using an n-gram over a sliding window over the periodic intervals; and a fifth module configured to control the processor to tag the utterance as a dialog act based on the approximated conditional probabilities. 12. The system of claim 9 , wherein the conditional probability is further approximated based on a length of the utterance. | 0.695545 |
8,271,451 | 1 | 2 | 1. A method for record archive disposition implemented with a computer system comprising one or more computer processors operatively connected to memory, the method comprising: storing in memory archival records, each archival record being associated with at least one archival record metadata attribute; storing in memory at least one or more legal holds, each legal hold having legal hold metadata attributes; generating with at least one of the processors a deletion candidate list for at least one record type by: including on the deletion candidate list archival records identified as having one or more archival record metadata attributes corresponding to the at least one record type; excluding from the deletion candidate list identified archival records if a selected set of legal hold metadata attributes for at least one legal hold corresponds to at least a subset of metadata attributes for the identified archival records; and deleting from memory archival records included on the deletion candidate list. | 1. A method for record archive disposition implemented with a computer system comprising one or more computer processors operatively connected to memory, the method comprising: storing in memory archival records, each archival record being associated with at least one archival record metadata attribute; storing in memory at least one or more legal holds, each legal hold having legal hold metadata attributes; generating with at least one of the processors a deletion candidate list for at least one record type by: including on the deletion candidate list archival records identified as having one or more archival record metadata attributes corresponding to the at least one record type; excluding from the deletion candidate list identified archival records if a selected set of legal hold metadata attributes for at least one legal hold corresponds to at least a subset of metadata attributes for the identified archival records; and deleting from memory archival records included on the deletion candidate list. 2. The computer-implemented method of claim 1 , wherein the archival record metadata attributes include at least an entry date and a record class code corresponding to a record type. | 0.75 |
9,405,736 | 3 | 7 | 3. The method of claim 1 , further comprising providing a command language set allowing selection, viewing, and other processing of the one or more portions of the first markup language document, the command language set comprising a plurality of commands for selection. | 3. The method of claim 1 , further comprising providing a command language set allowing selection, viewing, and other processing of the one or more portions of the first markup language document, the command language set comprising a plurality of commands for selection. 7. The method of claim 3 , further comprising creating XML, formatted documents that contain references to tag variables, allowing insertion into a markup language document the contents of a folder, subfolder or file from a second markup language document. | 0.57047 |
8,914,357 | 1 | 10 | 1. A method comprising: identifying, by one or more computing devices, location keywords for each of a plurality of granular locations; identifying, by the one or more computing devices, geographic features associated with an area of interest that includes the plurality of granular locations; for each geographic feature of the identified geographic features: determining, by the one or more computing devices, geo data for the geographic feature; forming, by the one or more computing devices, a set of granular locations that is associated with the geographic feature using the determined geo data, the set of granular locations being from among the plurality of granular locations, wherein the forming is based on a threshold percentage of coverage of each of the plurality of granular locations by the geographic feature; and generating, by the one or more computing devices, a keyword mapping for the geographic feature based at least in part on a set of location keywords from the identified location keywords, wherein the set of location keywords is associated with the set of granular locations; receiving, by the one or more computing devices, an indication of a geographic location that is proximate to a user or is of interest to the user; determining, by the one or more computing devices, a first one of the geographic features that includes the geographic location; and selecting, by the one or more computing devices, content for delivery to the user using a corresponding keyword mapping for the determined first one of the geographic features, wherein the corresponding keyword mapping for the determined first one of the geographic features is formed from a corresponding set of location keywords associated with the determined first one of the geographic features. | 1. A method comprising: identifying, by one or more computing devices, location keywords for each of a plurality of granular locations; identifying, by the one or more computing devices, geographic features associated with an area of interest that includes the plurality of granular locations; for each geographic feature of the identified geographic features: determining, by the one or more computing devices, geo data for the geographic feature; forming, by the one or more computing devices, a set of granular locations that is associated with the geographic feature using the determined geo data, the set of granular locations being from among the plurality of granular locations, wherein the forming is based on a threshold percentage of coverage of each of the plurality of granular locations by the geographic feature; and generating, by the one or more computing devices, a keyword mapping for the geographic feature based at least in part on a set of location keywords from the identified location keywords, wherein the set of location keywords is associated with the set of granular locations; receiving, by the one or more computing devices, an indication of a geographic location that is proximate to a user or is of interest to the user; determining, by the one or more computing devices, a first one of the geographic features that includes the geographic location; and selecting, by the one or more computing devices, content for delivery to the user using a corresponding keyword mapping for the determined first one of the geographic features, wherein the corresponding keyword mapping for the determined first one of the geographic features is formed from a corresponding set of location keywords associated with the determined first one of the geographic features. 10. The method of claim 1 , further comprising subdividing one or more of the geographic features to create one or more sub-features, and performing a keyword mapping for each of the one or more sub-features. | 0.707042 |
9,563,407 | 8 | 13 | 8. The method of claim 1 , wherein the topological framework model is a simulated world. | 8. The method of claim 1 , wherein the topological framework model is a simulated world. 13. The method of claim 8 , wherein the simulated world can delete an existing agent submodel. | 0.669014 |
8,135,218 | 15 | 16 | 15. A character recognition method of recognizing a character or a character string included in an image, for use in a mobile communication system in which a mobile terminal device and a fixed station device communicate via a wireless transmission path with each other, comprising: the mobile terminal device shooting an image; the mobile terminal device measuring a shooting position of an image to obtain shooting position information indicating the shooting position; the mobile terminal device detecting a shooting direction of an image to obtain shooting direction information indicating the shooting direction; the mobile terminal device transmitting the shooting position information, the shooting direction information, and an image imaged by the imaging means via a communication network to the fixed station device; the fixed station device determining, based on the shooting position information and the shooting direction information that are received from the mobile terminal device, a range of a shooting object of the mobile terminal device; the fixed station device extracting, from position corresponding information storage means storing position corresponding information that is words associated with respective positional information indicating positions of respective places, position corresponding information associated with positions included in the range; the fixed station device recognizing, using the extracted position corresponding information, a character or a character string included in the image received from the mobile terminal device; and the fixed station device transmits information of a character or a character string via a communication network to the mobile terminal device. | 15. A character recognition method of recognizing a character or a character string included in an image, for use in a mobile communication system in which a mobile terminal device and a fixed station device communicate via a wireless transmission path with each other, comprising: the mobile terminal device shooting an image; the mobile terminal device measuring a shooting position of an image to obtain shooting position information indicating the shooting position; the mobile terminal device detecting a shooting direction of an image to obtain shooting direction information indicating the shooting direction; the mobile terminal device transmitting the shooting position information, the shooting direction information, and an image imaged by the imaging means via a communication network to the fixed station device; the fixed station device determining, based on the shooting position information and the shooting direction information that are received from the mobile terminal device, a range of a shooting object of the mobile terminal device; the fixed station device extracting, from position corresponding information storage means storing position corresponding information that is words associated with respective positional information indicating positions of respective places, position corresponding information associated with positions included in the range; the fixed station device recognizing, using the extracted position corresponding information, a character or a character string included in the image received from the mobile terminal device; and the fixed station device transmits information of a character or a character string via a communication network to the mobile terminal device. 16. The character recognition method in accordance with claim 15 , further comprising: the mobile terminal device receiving information of a character or a character string recognized by the fixed station device, via a communication network from the fixed station device; and the mobile terminal device outputting information of the character or the character string. | 0.5 |
8,254,647 | 1 | 16 | 1. A method comprising: capturing, by a camera of a mobile computing device, an image; generating, by the mobile computing device, a facial detection confidence score based at least in part on a likelihood that a representation of at least a portion of a face is included in the image; generating, by the mobile computing device, a facial landmark detection confidence score based at least in part on a likelihood that representations of facial landmarks are accurately identified in the image; generating, by the mobile computing device, a geometric consistency score based at least in part on a difference between a point of intersection between a nose base and a line segment that passes through each eye and a midpoint of the line segment in the image; generating, by the mobile computing device, an image quality score based at least in part on a combination of the facial detection confidence score, the facial landmark detection confidence score, and the geometric consistency score; and classifying, by the mobile computing device, a quality of the image based at least in part on the image quality score. | 1. A method comprising: capturing, by a camera of a mobile computing device, an image; generating, by the mobile computing device, a facial detection confidence score based at least in part on a likelihood that a representation of at least a portion of a face is included in the image; generating, by the mobile computing device, a facial landmark detection confidence score based at least in part on a likelihood that representations of facial landmarks are accurately identified in the image; generating, by the mobile computing device, a geometric consistency score based at least in part on a difference between a point of intersection between a nose base and a line segment that passes through each eye and a midpoint of the line segment in the image; generating, by the mobile computing device, an image quality score based at least in part on a combination of the facial detection confidence score, the facial landmark detection confidence score, and the geometric consistency score; and classifying, by the mobile computing device, a quality of the image based at least in part on the image quality score. 16. The method of claim 1 , further comprising: outputting, by the mobile computing device, the image. | 0.922137 |
9,348,854 | 9 | 24 | 9. A method of performing XBRL taxonomy migration comprising: receiving an XBRL document having XBRL tags of a first version of a first XBRL taxonomy; migrating, by a processor, the received XBRL document to a second version of the first XBRL taxonomy by replacing XBRL concepts of the first version of the first XBRL taxonomy in the received XBRL document with XBRL concepts of the second version of the first XBRL taxonomy such that the migrated XBRL document no longer uses the first version of the first XBRL taxonomy, each of the first version of the first XBRL taxonomy and the second version of the first XBRL taxonomy including a base taxonomy and optionally one or more extensions of the base taxonomy, wherein the migrating includes maintaining tags from the received XBRL document that are of a second XBRL taxonomy in the migrated XBRL document, the second XBRL taxonomy being different from the first XBRL taxonomy and tags of the second XBRL taxonomy being simultaneously included with the XBRL tags of the first XBRL taxonomy in the received XBRL document. | 9. A method of performing XBRL taxonomy migration comprising: receiving an XBRL document having XBRL tags of a first version of a first XBRL taxonomy; migrating, by a processor, the received XBRL document to a second version of the first XBRL taxonomy by replacing XBRL concepts of the first version of the first XBRL taxonomy in the received XBRL document with XBRL concepts of the second version of the first XBRL taxonomy such that the migrated XBRL document no longer uses the first version of the first XBRL taxonomy, each of the first version of the first XBRL taxonomy and the second version of the first XBRL taxonomy including a base taxonomy and optionally one or more extensions of the base taxonomy, wherein the migrating includes maintaining tags from the received XBRL document that are of a second XBRL taxonomy in the migrated XBRL document, the second XBRL taxonomy being different from the first XBRL taxonomy and tags of the second XBRL taxonomy being simultaneously included with the XBRL tags of the first XBRL taxonomy in the received XBRL document. 24. The method of claim 9 , wherein the migrating comprises a many-to-one mapping in which a plurality of deprecated XBRL concepts of the first version of the first XBRL taxonomy are mapped to a single XBRL concept of the second version of the first XBRL taxonomy, the single XBRL concept of the second version aggregating the plurality of deprecated XBRL concepts of the first version which have greater specificity than the single XBRL concept of the second version. | 0.780488 |
8,510,345 | 1 | 4 | 1. A method for generating a Service-Oriented Architecture (SOA) policy based on a context model, comprising: generating, by a computer hardware system, an application scope of the SOA policy; generating, by the computer hardware system, the context model by collecting SOA metadata documents compliant with the application scope of the SOA policy, establishing inter-document references among the SOA metadata documents, and aggregating the SOA metadata documents based on the inter-document references to generate the context model; generating, by the computer hardware system, an action list for the context model based on action semantic modules customized by a user; generating, by the computer hardware system, a condition part of the SOA policy; generating, by the computer hardware system, an action part of the SOA policy according to the action list; and combining, by the computer hardware system, the condition part and the action part of the SOA policy to generate the SOA policy wherein the inter-document references causes the SOA metadata documents to be mutually referenced. | 1. A method for generating a Service-Oriented Architecture (SOA) policy based on a context model, comprising: generating, by a computer hardware system, an application scope of the SOA policy; generating, by the computer hardware system, the context model by collecting SOA metadata documents compliant with the application scope of the SOA policy, establishing inter-document references among the SOA metadata documents, and aggregating the SOA metadata documents based on the inter-document references to generate the context model; generating, by the computer hardware system, an action list for the context model based on action semantic modules customized by a user; generating, by the computer hardware system, a condition part of the SOA policy; generating, by the computer hardware system, an action part of the SOA policy according to the action list; and combining, by the computer hardware system, the condition part and the action part of the SOA policy to generate the SOA policy wherein the inter-document references causes the SOA metadata documents to be mutually referenced. 4. The method of claim 1 , wherein the generating the condition part of the SOA policy includes: extracting condition terms and their relations from the SOA metadata documents in the context model; displaying the condition terms; and selecting the condition terms and operators to generate the condition part. | 0.533233 |
9,323,743 | 6 | 8 | 6. The method according to claim 1 , further comprising: accessing at least one of historical data or event data for the primary data channel and the one or more related data channels; and causing the at least one of the historical data or the event data to be expressed linguistically in the situational analysis text. | 6. The method according to claim 1 , further comprising: accessing at least one of historical data or event data for the primary data channel and the one or more related data channels; and causing the at least one of the historical data or the event data to be expressed linguistically in the situational analysis text. 8. The method according to claim 6 , wherein the historical data is related to a historical alert condition other than the alert condition. | 0.700431 |
9,275,052 | 1 | 10 | 1. A server system comprising: one or more processors; and one or more computer-readable storage media storing computer-executable instructions that, when executed on the one or more processors, cause the one or more processors to perform acts comprising: storing, by the server system, annotation data from a first electronic book (eBook) reader device to a data store; determining that the annotation data is specific to a digital work; determining that an invariant location reference identifier is assigned to the annotation data, wherein the digital work is partitioned into a plurality of segments, a first segment has the invariant location reference identifier assigned thereto, such that the invariant location reference identifier is uniquely assigned with the first segment of the digital work, regardless of display conditions used to display the digital work; receiving a request from a second eBook reader device for the annotation data; synchronizing the annotation data stored in the data store with annotations stored on the second eBook reader device; determining that the second eBook reader device has presented a valid authorization credential for receiving the annotation data; and sending the second eBook reader device the annotation data. | 1. A server system comprising: one or more processors; and one or more computer-readable storage media storing computer-executable instructions that, when executed on the one or more processors, cause the one or more processors to perform acts comprising: storing, by the server system, annotation data from a first electronic book (eBook) reader device to a data store; determining that the annotation data is specific to a digital work; determining that an invariant location reference identifier is assigned to the annotation data, wherein the digital work is partitioned into a plurality of segments, a first segment has the invariant location reference identifier assigned thereto, such that the invariant location reference identifier is uniquely assigned with the first segment of the digital work, regardless of display conditions used to display the digital work; receiving a request from a second eBook reader device for the annotation data; synchronizing the annotation data stored in the data store with annotations stored on the second eBook reader device; determining that the second eBook reader device has presented a valid authorization credential for receiving the annotation data; and sending the second eBook reader device the annotation data. 10. The server system of claim 1 , the acts further comprising receiving payment for the annotation data, the payment for compensating an author of the annotation data. | 0.717172 |
5,519,867 | 1 | 3 | 1. An apparatus for enabling an object-oriented application, said application including object-oriented statements, to access in an object-oriented manner a procedural operating system by use of said object-oriented statements, said system providing services, including procedural functions saved as executable program logic that are called to access said services, said apparatus comprising: (a) a computer; (b) a memory component in said computer; (c) a code library, stored in said memory component, comprising means for storing said executable program logic in an object-oriented class library; and means for interfacing said object-oriented application to said procedural operating system utilizing said executable program logic; (d) means, in said computer, for processing said object-oriented statements by executing methods from said object-oriented class library corresponding to said object-oriented statements; and (e) means, in said object-oriented class library, including object-oriented thread classes, for enabling said object-oriented application to access said services to spawn, control, and obtain information relating to a thread of execution. | 1. An apparatus for enabling an object-oriented application, said application including object-oriented statements, to access in an object-oriented manner a procedural operating system by use of said object-oriented statements, said system providing services, including procedural functions saved as executable program logic that are called to access said services, said apparatus comprising: (a) a computer; (b) a memory component in said computer; (c) a code library, stored in said memory component, comprising means for storing said executable program logic in an object-oriented class library; and means for interfacing said object-oriented application to said procedural operating system utilizing said executable program logic; (d) means, in said computer, for processing said object-oriented statements by executing methods from said object-oriented class library corresponding to said object-oriented statements; and (e) means, in said object-oriented class library, including object-oriented thread classes, for enabling said object-oriented application to access said services to spawn, control, and obtain information relating to a thread of execution. 3. The apparatus of claim 1, wherein said object-oriented class library comprises object-oriented task classes for enabling said application to access in an object-oriented manner said services to reference and control a task, said task representing an execution environment for at least one thread of execution associated with said task. | 0.730032 |
8,447,588 | 1 | 14 | 1. A computer implemented method, comprising: recording in a memory input data having delimited strings; recording in the memory a region-matching transducer defining one or more patterns of one or more sequences of delimited strings, with at least one of the patterns defined in the region-matching transducer having an arrangement of a plurality of class-matching networks; the plurality of class-matching networks defining a combination of two or more entity classes from one or both of part-of-speech classes and application-specific classes; the region-matching transducer (i) having, for each of the one or more patterns, an arc that leads from a penultimate state with a transition label that identifies the entity class of the pattern, and (ii) sharing states between patterns leading to a penultimate state when segments of delimited strings making up two or more patterns overlap; applying the region-matching transducer recorded in the memory to the input data with an apply-stage replacement method, which apply-stage replacement method follows a longest match principle for identifying one or more patterns in the region-matching transducer that match one or more sequences of delimited strings in the input data; at least one of the matching sequences of delimited strings satisfying at least one pattern in the region-matching transducer defined by an arrangement of a plurality of class-matching networks, wherein the input data is not labeled with morphological tags when applying the region-matching transducer to the input data; and recording in the memory, in response to said applying, the one or more sequences of delimited strings in the input data matching the one or more patterns in the region-matching transducer. | 1. A computer implemented method, comprising: recording in a memory input data having delimited strings; recording in the memory a region-matching transducer defining one or more patterns of one or more sequences of delimited strings, with at least one of the patterns defined in the region-matching transducer having an arrangement of a plurality of class-matching networks; the plurality of class-matching networks defining a combination of two or more entity classes from one or both of part-of-speech classes and application-specific classes; the region-matching transducer (i) having, for each of the one or more patterns, an arc that leads from a penultimate state with a transition label that identifies the entity class of the pattern, and (ii) sharing states between patterns leading to a penultimate state when segments of delimited strings making up two or more patterns overlap; applying the region-matching transducer recorded in the memory to the input data with an apply-stage replacement method, which apply-stage replacement method follows a longest match principle for identifying one or more patterns in the region-matching transducer that match one or more sequences of delimited strings in the input data; at least one of the matching sequences of delimited strings satisfying at least one pattern in the region-matching transducer defined by an arrangement of a plurality of class-matching networks, wherein the input data is not labeled with morphological tags when applying the region-matching transducer to the input data; and recording in the memory, in response to said applying, the one or more sequences of delimited strings in the input data matching the one or more patterns in the region-matching transducer. 14. The method according to claim 1 , wherein the region-matching transducer identifies intelligible information in the input data. | 0.788026 |
9,829,984 | 18 | 19 | 18. The method of claim 10 , wherein a special visual gesture is used to indicate selection or deselection in a computer application, including selecting a button, window, object, or link. | 18. The method of claim 10 , wherein a special visual gesture is used to indicate selection or deselection in a computer application, including selecting a button, window, object, or link. 19. The method of claim 18 , wherein the visual gesture for selection or deselection is comprised of closing an open hand and making a first or opening a fist. | 0.506211 |
9,484,024 | 8 | 10 | 8. A system comprising: a processor configured to perform speech recognition; and a computer-readable storage medium having instruction stored which, when executed by the processor, cause the processor to perform operations comprising: identifying, based on past interactions with a user participating in a dialog with a speech dialog system, an adaptation schema which, when applied to a speech recognition model, increases a likelihood the speech recognition model will recognize misrecognized speech from the user relative to an unadapted speech recognition model; determining that the user has previously repeated speech inputs based on interactions with the user prior to initiating the dialog, to yield a determination; and adapting, based on the determination, the speech recognition model using the adaptation schema before an expected repeat speech input, wherein adapting the speech recognition model further comprises modifying an acoustic model, a language model, and a semantic model. | 8. A system comprising: a processor configured to perform speech recognition; and a computer-readable storage medium having instruction stored which, when executed by the processor, cause the processor to perform operations comprising: identifying, based on past interactions with a user participating in a dialog with a speech dialog system, an adaptation schema which, when applied to a speech recognition model, increases a likelihood the speech recognition model will recognize misrecognized speech from the user relative to an unadapted speech recognition model; determining that the user has previously repeated speech inputs based on interactions with the user prior to initiating the dialog, to yield a determination; and adapting, based on the determination, the speech recognition model using the adaptation schema before an expected repeat speech input, wherein adapting the speech recognition model further comprises modifying an acoustic model, a language model, and a semantic model. 10. The system of claim 8 , wherein adapting the speech recognition model further comprises preparing a personalized search speech recognition model for the expected repeat speech input based on a usage history of the user and entries in a recognition lattice. | 0.747573 |
7,904,461 | 23 | 25 | 23. The method of claim 21 , further comprising determining which of the users are substantially similar based on user labels associated with the user nodes. | 23. The method of claim 21 , further comprising determining which of the users are substantially similar based on user labels associated with the user nodes. 25. The method of claim 23 , further comprising outputting, for each node, weights for the advertiser labels based on weights of advertiser labels associated with neighboring nodes, which are related to the node by a relationship. | 0.5 |
9,690,847 | 19 | 20 | 19. The system of claim 16 wherein the instructions further cause the one or more processors to parse the first query, look up the stand-alone score for each segment in the first query, and apply a second function to the stand-alone scores for each segment to determine a self-sufficiency score for the first query. | 19. The system of claim 16 wherein the instructions further cause the one or more processors to parse the first query, look up the stand-alone score for each segment in the first query, and apply a second function to the stand-alone scores for each segment to determine a self-sufficiency score for the first query. 20. The system of claim 19 wherein the second function is a sum. | 0.5 |
7,917,350 | 7 | 16 | 7. A word boundary probability estimating method comprising the steps of: calculating, on a computer processor, a probability that a word boundary exists between each of a plurality of characters in a first character string stored in a first corpus, the calculating comprising: determining if a sequence of characters matching the plurality of characters already exists in the first corpus; determining if a word boundary already exists between the plurality of characters in the first character string in response to determining that a matching sequence exists; calculating the probability that a word boundary exists in the plurality of characters based on relations in the sequence of character types of successive characters in the first character string in the first corpus by using only the probability of a word boundary already existing between characters of those character types in response to determining that a word boundary already exists between the plurality of characters in the first character string; and using a probability of 0.5 in response to determining that the sequence matching the plurality of character does not exist in the first corpus; and estimating, on a computer processor, the probability that a word boundary will exist in a plurality of non-word-segmented characters stored in a second corpus by referring to the calculated probability of the boundaries between each of the plurality of characters in the first character string. | 7. A word boundary probability estimating method comprising the steps of: calculating, on a computer processor, a probability that a word boundary exists between each of a plurality of characters in a first character string stored in a first corpus, the calculating comprising: determining if a sequence of characters matching the plurality of characters already exists in the first corpus; determining if a word boundary already exists between the plurality of characters in the first character string in response to determining that a matching sequence exists; calculating the probability that a word boundary exists in the plurality of characters based on relations in the sequence of character types of successive characters in the first character string in the first corpus by using only the probability of a word boundary already existing between characters of those character types in response to determining that a word boundary already exists between the plurality of characters in the first character string; and using a probability of 0.5 in response to determining that the sequence matching the plurality of character does not exist in the first corpus; and estimating, on a computer processor, the probability that a word boundary will exist in a plurality of non-word-segmented characters stored in a second corpus by referring to the calculated probability of the boundaries between each of the plurality of characters in the first character string. 16. A non-transitory computer readable storage device comprising computer executable instructions tangibly embodied on a computer readable medium that when executed by said computer perform a method for word boundary probability estimating, the method comprising the steps of claim 7 . | 0.702505 |
8,521,748 | 12 | 13 | 12. The method according to claim 1 , wherein a structure in the structure dictionary takes a form of a word built using an alphabet of symbols taking a form of constants corresponding to at least one of alpha-numeric strings and characters, and variables corresponding to at least one generic data type, said word being built using formation rules of a formal language. | 12. The method according to claim 1 , wherein a structure in the structure dictionary takes a form of a word built using an alphabet of symbols taking a form of constants corresponding to at least one of alpha-numeric strings and characters, and variables corresponding to at least one generic data type, said word being built using formation rules of a formal language. 13. The method of claim 12 , wherein the generic data type is at least one of numeric, alpha-numeric and binary. | 0.971253 |
10,133,814 | 11 | 20 | 11. A non-transitory computer-readable storage medium coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for providing an explanatory electronic document, the operations comprising: receiving, by the one or more processors, input from a user, the input comprising data that is at least partially representative of a subject; performing, by the one or more processors, semantic context association based on the user input, one or more computer-readable ontologies, and a computer-readable knowledge graph to provide a target subject profile, the target subject profile comprising two or more associations describing the subject at respective degrees of specificity, at least one association comprising concepts from the knowledge graph that are more general than respective entities provided in the input; providing, by the one or more processors, a set of peer user profiles based on a user profile and a superset of peer user profiles using semantic user profile association between the user profile and each peer user profile in the superset of peer user profiles; retrieving, by the one or more processors, one or more peer subject profiles from computer-readable memory, each peer subject profile being associated with a peer user profile in the set of peer user profiles, and comprising one or more associations, each association describing a past subject experienced by a peer user; filtering, by the one or more processors, at least one association from a peer subject profile based on a comparison with a respective association in the target subject profile and data provided in a knowledge graph; providing, by the one or more processors, at least one explanatory text string associated with the subject based on at least one remaining association in the peer subject profile; and providing, by the one or more processors, the explanatory electronic document comprising the at least one explanatory text string. | 11. A non-transitory computer-readable storage medium coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations for providing an explanatory electronic document, the operations comprising: receiving, by the one or more processors, input from a user, the input comprising data that is at least partially representative of a subject; performing, by the one or more processors, semantic context association based on the user input, one or more computer-readable ontologies, and a computer-readable knowledge graph to provide a target subject profile, the target subject profile comprising two or more associations describing the subject at respective degrees of specificity, at least one association comprising concepts from the knowledge graph that are more general than respective entities provided in the input; providing, by the one or more processors, a set of peer user profiles based on a user profile and a superset of peer user profiles using semantic user profile association between the user profile and each peer user profile in the superset of peer user profiles; retrieving, by the one or more processors, one or more peer subject profiles from computer-readable memory, each peer subject profile being associated with a peer user profile in the set of peer user profiles, and comprising one or more associations, each association describing a past subject experienced by a peer user; filtering, by the one or more processors, at least one association from a peer subject profile based on a comparison with a respective association in the target subject profile and data provided in a knowledge graph; providing, by the one or more processors, at least one explanatory text string associated with the subject based on at least one remaining association in the peer subject profile; and providing, by the one or more processors, the explanatory electronic document comprising the at least one explanatory text string. 20. The computer-readable storage medium of claim 11 , wherein operations further comprise receiving data informative of an enterprise associated with the user, the at least one explanatory text string being partially based on the data. | 0.707196 |
8,503,661 | 17 | 18 | 17. The apparatus for handling contact requests as in claim 12 further comprising a contact broker for receiving the contact from a public communication network. | 17. The apparatus for handling contact requests as in claim 12 further comprising a contact broker for receiving the contact from a public communication network. 18. The apparatus for handling contact requests as in claim 17 further comprising contact associated information received by the broker along with the contact. | 0.5 |
4,831,525 | 20 | 21 | 20. A method of generating a source program in an information processing system having processing means and memory means comprising: storing into said memory means various schematic information items including a structure of program modules, processing flow, internal data definition and interface data definition; inputting the schematic information items from said memory means to said processing means; and generating the source program based on inputted schematic information items in said processing means. | 20. A method of generating a source program in an information processing system having processing means and memory means comprising: storing into said memory means various schematic information items including a structure of program modules, processing flow, internal data definition and interface data definition; inputting the schematic information items from said memory means to said processing means; and generating the source program based on inputted schematic information items in said processing means. 21. A method of generating a source program according to claim 20, wherein said information processing system further includes a display terminal, the method further comprising the step of editing said schematic information items to be stored in said memory means by conversational operations through said display terminal. | 0.5 |
9,805,027 | 1 | 6 | 1. A method performed by a computing device having at least one processor and a memory, the method comprising: receiving, from an application being executed by the at least one processor, a request to provide a first word for use by the application; determining a default language of the computing device; accessing, in the memory of the computing device, one or more resources; determining if the one or more resources include the first word in the default language by iteratively eliminating, based on identified qualifiers, resource directories for the one or more resources until only one resource directory remains, the one resource directory excluding resource files that contradict a configuration of the computing device; if the one or more resources include the first word in the default language, then providing, from the one resource directory, the first word to the application; and if the one or more resources do not include the first word in the default language, then: transmitting the first word and an indication of the default language to a translation server; receiving from the translation server a second word obtained by translating the first word into the default language; and providing the second word to the application. | 1. A method performed by a computing device having at least one processor and a memory, the method comprising: receiving, from an application being executed by the at least one processor, a request to provide a first word for use by the application; determining a default language of the computing device; accessing, in the memory of the computing device, one or more resources; determining if the one or more resources include the first word in the default language by iteratively eliminating, based on identified qualifiers, resource directories for the one or more resources until only one resource directory remains, the one resource directory excluding resource files that contradict a configuration of the computing device; if the one or more resources include the first word in the default language, then providing, from the one resource directory, the first word to the application; and if the one or more resources do not include the first word in the default language, then: transmitting the first word and an indication of the default language to a translation server; receiving from the translation server a second word obtained by translating the first word into the default language; and providing the second word to the application. 6. The method of claim 1 , wherein the default language is a preferred language of a user of the computing device. | 0.747788 |
9,177,557 | 1 | 2 | 1. A method of providing speech recognition functionality for an utterance spoken in a noisy environment having multiple human speakers, the method comprising: receiving speech energy corresponding to the utterance, the received speech energy comprising contributions from multiple human speakers; converting the received speech energy to an electronic form; digitizing the electronic form of the received speech energy to render a digitization of the received speech energy; decomposing the digitization of the received speech energy to produce feature data representative of features in the digitization of the received speech energy, wherein the feature data does not distinguish between different speakers and between speech and background noise; processing the feature data to produce speaker dependent feature data and speaker independent feature data; projecting only the speaker independent feature data into a feature space, the feature space having multiple human speaker subspaces for multiple human speakers, wherein each one of the multiple human speakers is associated with a distinct one of the multiple human speaker subspaces and wherein the features of the speaker independent feature data project either into one of the multiple human speaker subspaces or outside of all human speaker subspaces; identifying the speaker independent feature data associated with a speaker subspace associated with a primary human speaker; and performing a speech recognition operation on speaker independent feature data associated with the speaker subspace associated with the primary human speaker to resolve the utterance to a command or data, wherein the speaker independent feature data includes contributions from at least two speakers, and wherein performing a speech recognition operation on the feature data associated with the speaker subspace associated with the primary human speaker to resolve the utterance to a command or data comprises removing all feature data not associated with the speaker subspace associated with the primary human speaker. | 1. A method of providing speech recognition functionality for an utterance spoken in a noisy environment having multiple human speakers, the method comprising: receiving speech energy corresponding to the utterance, the received speech energy comprising contributions from multiple human speakers; converting the received speech energy to an electronic form; digitizing the electronic form of the received speech energy to render a digitization of the received speech energy; decomposing the digitization of the received speech energy to produce feature data representative of features in the digitization of the received speech energy, wherein the feature data does not distinguish between different speakers and between speech and background noise; processing the feature data to produce speaker dependent feature data and speaker independent feature data; projecting only the speaker independent feature data into a feature space, the feature space having multiple human speaker subspaces for multiple human speakers, wherein each one of the multiple human speakers is associated with a distinct one of the multiple human speaker subspaces and wherein the features of the speaker independent feature data project either into one of the multiple human speaker subspaces or outside of all human speaker subspaces; identifying the speaker independent feature data associated with a speaker subspace associated with a primary human speaker; and performing a speech recognition operation on speaker independent feature data associated with the speaker subspace associated with the primary human speaker to resolve the utterance to a command or data, wherein the speaker independent feature data includes contributions from at least two speakers, and wherein performing a speech recognition operation on the feature data associated with the speaker subspace associated with the primary human speaker to resolve the utterance to a command or data comprises removing all feature data not associated with the speaker subspace associated with the primary human speaker. 2. The method of providing speech recognition functionality according to claim 1 , wherein the step of converting the received speech energy to an electronic form comprises transducing audible speech energy to an analog electronic signal. | 0.754639 |
9,070,084 | 5 | 6 | 5. A method of claim 1 , wherein the steps of generating the canonical expression from the base expression and generating the comparison canonical expression from the modified base expression include the execution of a function that is dependent on the stored ontology. | 5. A method of claim 1 , wherein the steps of generating the canonical expression from the base expression and generating the comparison canonical expression from the modified base expression include the execution of a function that is dependent on the stored ontology. 6. A method of claim 5 , wherein the function satisfies the property:
function(expression)==function(function(expression)+expression). | 0.527778 |
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