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9,424,167 | 1 | 7 | 1. A method for automatically testing an application system graphical user interface (GUI), the method comprising: retrieving, in a computer communicatively connected to an application server providing the application system, a GUI page provided by the application server as part of the application system; automatically identifying, based on image-analysis of an image of the retrieved GUI page, a plurality of text elements of the GUI page; automatically identifying, based on image-analysis of the image of the retrieved GUI page, a plurality of user input objects of the GUI page; automatically associating with each of the plurality of automatically identified user input objects a text element of the plurality of automatically identified text elements; retrieving, based on the text elements associated with each of the plurality of user input objects, a plurality of test parameter values from a database storing test parameter data, wherein each test parameter value of the plurality of test parameter values is associated in the database storing test parameter data with a corresponding text element associated with one of the plurality of user input objects; testing the application system provided by the application server by, for each respective user input object identified in the GUI page, performing a function to: provide, in the respective user input object of the GUI page, the respective test parameter value that is associated in the database storing test parameter data with a same text element as is associated with the respective user input object of the GUI page; and monitoring a response of the application system to the providing of the respective test parameter value to each user input object identified in the GUI page. | 1. A method for automatically testing an application system graphical user interface (GUI), the method comprising: retrieving, in a computer communicatively connected to an application server providing the application system, a GUI page provided by the application server as part of the application system; automatically identifying, based on image-analysis of an image of the retrieved GUI page, a plurality of text elements of the GUI page; automatically identifying, based on image-analysis of the image of the retrieved GUI page, a plurality of user input objects of the GUI page; automatically associating with each of the plurality of automatically identified user input objects a text element of the plurality of automatically identified text elements; retrieving, based on the text elements associated with each of the plurality of user input objects, a plurality of test parameter values from a database storing test parameter data, wherein each test parameter value of the plurality of test parameter values is associated in the database storing test parameter data with a corresponding text element associated with one of the plurality of user input objects; testing the application system provided by the application server by, for each respective user input object identified in the GUI page, performing a function to: provide, in the respective user input object of the GUI page, the respective test parameter value that is associated in the database storing test parameter data with a same text element as is associated with the respective user input object of the GUI page; and monitoring a response of the application system to the providing of the respective test parameter value to each user input object identified in the GUI page. 7. The method of claim 1 , further comprising: receiving, from a test developer, test parameter values to associate with one text element of the plurality of identified text elements; and storing the received test parameter values in the database storing test parameter data in association with the one text element. | 0.790451 |
9,720,814 | 2 | 3 | 2. The method of claim 1 , wherein the inferring includes applying template inference techniques to symbolically represent the likely templates used by the respective services. | 2. The method of claim 1 , wherein the inferring includes applying template inference techniques to symbolically represent the likely templates used by the respective services. 3. The method of claim 2 , wherein the applying is performed using a set of known templated documents and the documents obtained from the clustered services, an output of which is the symbolic representations. | 0.5 |
4,066,998 | 7 | 9 | 7. The apparatus according to claim 6 further comprising: means for temporarily storing position data of said left-most and right-most grid locations for each examined row; means for providing and storing a no-hole indication when the interrogated grid locations of an examined row contain only character portions; and logic means for comparing the stored position data and stored no-hole indications to provide an indication when said left-most grid location of an examined row having no hole is further left than said left-most grid location of another examined row having no hold on the same character. | 7. The apparatus according to claim 6 further comprising: means for temporarily storing position data of said left-most and right-most grid locations for each examined row; means for providing and storing a no-hole indication when the interrogated grid locations of an examined row contain only character portions; and logic means for comparing the stored position data and stored no-hole indications to provide an indication when said left-most grid location of an examined row having no hole is further left than said left-most grid location of another examined row having no hold on the same character. 9. The apparatus according to claim 7 further comprising: additional logic means for providing an additional indication when said right-most grid location of an examined row having no hole is further right than said right-most grid location of another examined row having no hole in the same character. | 0.588556 |
8,868,402 | 10 | 14 | 10. A system comprising: one or more computers configured to perform operations including: receiving a collection of candidate phrases for a given topic; filtering the received candidate phrases to remove erroneously included candidate phrases; assigning weights to the candidate phrases, wherein assigning weights includes: scoring each candidate phrase using an initial classifier, and assigning a weight to each of the candidate phrases based on the respective scores from the initial classifier; generating a linear classifier using the filtered and weighted candidate phrases; and adjusting the linear classifier depending on a length of a document being classified, wherein adjusting the linear classifier includes determining whether and to what degree the given topic is affected by document length based on a learning process using a set of labeled example documents, each example document including a score assigned by the linear classifier, the length of the example document, and a label assigned to the example document, wherein the learning process outputs a decision function that assigns a particular label to each pair of score and document length such that a probability that a particular document having a given score from the linear classifier belongs to the topic depends on the length of the document. | 10. A system comprising: one or more computers configured to perform operations including: receiving a collection of candidate phrases for a given topic; filtering the received candidate phrases to remove erroneously included candidate phrases; assigning weights to the candidate phrases, wherein assigning weights includes: scoring each candidate phrase using an initial classifier, and assigning a weight to each of the candidate phrases based on the respective scores from the initial classifier; generating a linear classifier using the filtered and weighted candidate phrases; and adjusting the linear classifier depending on a length of a document being classified, wherein adjusting the linear classifier includes determining whether and to what degree the given topic is affected by document length based on a learning process using a set of labeled example documents, each example document including a score assigned by the linear classifier, the length of the example document, and a label assigned to the example document, wherein the learning process outputs a decision function that assigns a particular label to each pair of score and document length such that a probability that a particular document having a given score from the linear classifier belongs to the topic depends on the length of the document. 14. The system of claim 10 , where the received phrase candidates are generated by: receiving query log information associating queries with one or more Web sites identified as responsive to the query; for a set of Web sites identified in the log for which an associated topic is known, identifying a number of frequently submitted queries associated with those Web sites of the set; and using the frequently submitted queries as candidate phrases for the topic of the associated Web pages. | 0.613565 |
8,799,982 | 1 | 2 | 1. A computer-implemented method of selecting among a plurality of endpoint policy alternatives to apply to a message conveyed over a data communications network, the method comprising: configuring a computer system having at least one memory and at least one processor to perform the following steps: assigning a score to each of the plurality of endpoint policy alternatives, each of the plurality of endpoint policy alternatives comprising a plurality of policy assertions, and the score being a sum of predefined weights assigned to each of the plurality of policy assertions, wherein each predefined weight is represented by a unique bit sequence that distinguishes each of the plurality of policy assertions to which the unique bit sequence is assigned from each of the other of the plurality of policy assertions; and selecting according to a predetermined selection criterion one of the plurality of endpoint policy alternatives based upon the assigned scores. | 1. A computer-implemented method of selecting among a plurality of endpoint policy alternatives to apply to a message conveyed over a data communications network, the method comprising: configuring a computer system having at least one memory and at least one processor to perform the following steps: assigning a score to each of the plurality of endpoint policy alternatives, each of the plurality of endpoint policy alternatives comprising a plurality of policy assertions, and the score being a sum of predefined weights assigned to each of the plurality of policy assertions, wherein each predefined weight is represented by a unique bit sequence that distinguishes each of the plurality of policy assertions to which the unique bit sequence is assigned from each of the other of the plurality of policy assertions; and selecting according to a predetermined selection criterion one of the plurality of endpoint policy alternatives based upon the assigned scores. 2. The method of claim 1 , wherein assigning a score to each endpoint policy alternative comprises determining the predefined weights assigned to each of the plurality of policy assertions plurality of the endpoint policy alternatives. | 0.548077 |
9,779,066 | 8 | 13 | 8. A system for scanning and converting Punycode email addresses to Unicode with augmented reality, said system comprising: a client device, a computer, a scanner, an optical code recognizer including optical code recognition software, Punycode/ASCII and/or Unicode dictionary table, and Punycode text; said system scanning and saving an image of said Punycode text in said computer and displaying on said client device; wherein said image is scanned and subjected to said optical code recognizer to identify Punycode strings and converted and segregated Unicode strings; and said Unicode strings displayed on said client device adjacent said image of said Punycode strings; and wherein said optical character recognizer converts the optical image by recognizing and segregating Unicode data in a character string and generating a display corresponding to a described character string in alpha numeric characters and symbols adjacent said image on said client device. | 8. A system for scanning and converting Punycode email addresses to Unicode with augmented reality, said system comprising: a client device, a computer, a scanner, an optical code recognizer including optical code recognition software, Punycode/ASCII and/or Unicode dictionary table, and Punycode text; said system scanning and saving an image of said Punycode text in said computer and displaying on said client device; wherein said image is scanned and subjected to said optical code recognizer to identify Punycode strings and converted and segregated Unicode strings; and said Unicode strings displayed on said client device adjacent said image of said Punycode strings; and wherein said optical character recognizer converts the optical image by recognizing and segregating Unicode data in a character string and generating a display corresponding to a described character string in alpha numeric characters and symbols adjacent said image on said client device. 13. The system for scanning and converting Punycode text to Unicode text with augmented reality according to claim 8 , in which each of said Unicode strings are displayed on said client's device adjacent said image of said Punycode string displayed on that same device. | 0.517921 |
9,367,535 | 15 | 16 | 15. A computer program product as in claim 11 , wherein the operations further comprise: transforming a representation of each cell having at least one formula into a pre-defined notation format prior to the recursive evaluation. | 15. A computer program product as in claim 11 , wherein the operations further comprise: transforming a representation of each cell having at least one formula into a pre-defined notation format prior to the recursive evaluation. 16. A computer program product as in claim 15 , wherein each formula in the transformed notation comprises one or more tokens, and wherein the recursively evaluating comprises: creating a result stack; for each token in the transformed representation: if the token corresponds to a value, pushing the token onto the result stack; if the token corresponds to a function: popping required arguments off the result stack; evaluating the function; pushing the result of the function onto the result stack; if the token corresponds to at least one cell reference: recursively fetching the value of the at least one referenced cell. | 0.603797 |
7,840,073 | 1 | 8 | 1. A method of generating a pictographic character on a display of an electronic device comprising an input device, the method comprising: the electronic device generating on the display a pictographic character comprising a radical portion and at least one non-radical portion; designating at least one of the at least one non-radical portions as a selected portion; and the electronic device generating on the display a different pictographic character comprising the selected portion. | 1. A method of generating a pictographic character on a display of an electronic device comprising an input device, the method comprising: the electronic device generating on the display a pictographic character comprising a radical portion and at least one non-radical portion; designating at least one of the at least one non-radical portions as a selected portion; and the electronic device generating on the display a different pictographic character comprising the selected portion. 8. The method of claim 1 , wherein designating at least one of the at least one non-radical portions as the selected portion comprises selecting the selected portion from a list of pictographic character parts. | 0.685629 |
8,201,103 | 11 | 15 | 11. A computer-readable storage medium on a memory device having computer-executable instructions for accessing an out-space user interface for a document editor program, the instructions comprising: providing an in-space user interface having an out-space actuator associated with the in-space user interface, wherein the in-space user interface includes displaying a document and a ribbon that displays authoring features for authoring and editing the content of the document; receiving a selection of the out-space actuator; and in response to receiving the selection of the out-space actuator, displaying an out-space user interface, wherein displaying the out-space user interface includes expanding a display area of the ribbon and displaying a non-live document image of the document, wherein the expanded ribbon includes non-authoring features that do not affect the content of the document. | 11. A computer-readable storage medium on a memory device having computer-executable instructions for accessing an out-space user interface for a document editor program, the instructions comprising: providing an in-space user interface having an out-space actuator associated with the in-space user interface, wherein the in-space user interface includes displaying a document and a ribbon that displays authoring features for authoring and editing the content of the document; receiving a selection of the out-space actuator; and in response to receiving the selection of the out-space actuator, displaying an out-space user interface, wherein displaying the out-space user interface includes expanding a display area of the ribbon and displaying a non-live document image of the document, wherein the expanded ribbon includes non-authoring features that do not affect the content of the document. 15. The computer-implemented method of claim 11 , wherein the document editor includes at least one member of a group comprising: a word processing editor, a spreadsheet editor, an email editor, a webpage editor, and a slide presentation editor. | 0.54461 |
9,721,031 | 5 | 7 | 5. A computer-implemented method, comprising: displaying, using a device, a first page of content associated with a first layout, the first page including a first amount of content; selecting first content included in the first page; associating the first content with a first bookmark; storing the first bookmark and a first word location of the first content associated with the bookmark; determining to switch from the first layout to a second layout; identifying a section break indicating a beginning of a current section, the current section including the first page; determining the second layout of the current section; and displaying a second page of content in a manner to emphasize the first content relative to other content displayed with the first content, for a predetermined period of time, the second page of content associated with the second layout and including a second amount of content that is different from the first amount of content. | 5. A computer-implemented method, comprising: displaying, using a device, a first page of content associated with a first layout, the first page including a first amount of content; selecting first content included in the first page; associating the first content with a first bookmark; storing the first bookmark and a first word location of the first content associated with the bookmark; determining to switch from the first layout to a second layout; identifying a section break indicating a beginning of a current section, the current section including the first page; determining the second layout of the current section; and displaying a second page of content in a manner to emphasize the first content relative to other content displayed with the first content, for a predetermined period of time, the second page of content associated with the second layout and including a second amount of content that is different from the first amount of content. 7. The computer-implemented method of claim 5 , wherein the selecting further comprises: receiving a bookmark command causing the device to create the first bookmark; determining a length of time the first page has been displayed; determining an estimated reading speed; and determining the first content using the length of time and the estimated reading speed. | 0.65458 |
8,156,184 | 11 | 19 | 11. The method according to claim 8 , wherein, in the step of generating said at least one message, text data of said at least one message is generated from said at least one utterance such that said text data is displayed in a form varying in accordance with a value calculated from said at least one interest level and said at least one utterance strength. | 11. The method according to claim 8 , wherein, in the step of generating said at least one message, text data of said at least one message is generated from said at least one utterance such that said text data is displayed in a form varying in accordance with a value calculated from said at least one interest level and said at least one utterance strength. 19. The method of claim 11 , wherein said varying of said form comprises increasing a font size of said at least one text data in a first case, as compared to a second case, when said calculated value is greater in said first case than in said second case. | 0.5 |
8,260,914 | 8 | 14 | 8. A system for detecting automatically generated malicious domain names in a network, comprising: a detecting program configured to capture a plurality of domain name service (DNS) queries in the network, wherein the plurality of DNS queries share a common attribute; an analyzer program configured to: analyze the plurality of DNS queries to identify a plurality of alphanumeric elements embedded in a set of domain names associated with the plurality of DNS queries; and analyze the plurality of alphanumeric elements to determine a distribution metric of the set of domain names; and a processor and memory storing instructions when executed by the processor comprising functionality to: compare the distribution metric and a pre-determined threshold to generate a result; and generate an alert of domain fluxing based on the distribution metric according to a predetermined criterion. | 8. A system for detecting automatically generated malicious domain names in a network, comprising: a detecting program configured to capture a plurality of domain name service (DNS) queries in the network, wherein the plurality of DNS queries share a common attribute; an analyzer program configured to: analyze the plurality of DNS queries to identify a plurality of alphanumeric elements embedded in a set of domain names associated with the plurality of DNS queries; and analyze the plurality of alphanumeric elements to determine a distribution metric of the set of domain names; and a processor and memory storing instructions when executed by the processor comprising functionality to: compare the distribution metric and a pre-determined threshold to generate a result; and generate an alert of domain fluxing based on the distribution metric according to a predetermined criterion. 14. The system of claim 8 , wherein the distribution metric comprises information entropy of the plurality of alphanumeric elements. | 0.871845 |
8,594,239 | 7 | 13 | 7. A method comprising: receiving a first set of samples and a second set of samples at a computing device, wherein the first set of samples is associated with a first document and the second set of samples is associated with a second document; generating a first plurality of bit-strings based on the first set of samples by the computing device; generating a second plurality of bit-strings based on the second set of samples by the computing device; and estimating a similarity between the first document and the second document based on the first and second pluralities of bit-strings by the computing device, wherein each bit-string has an associated position, and estimating the similarity between the first document and the second document based on the first and second pluralities of bit sequences comprises: determining a first count of the number of bit-strings from the first and the second pluralities of bit-strings with the same associated position that agree; determining a second count of the number of bit-strings from the first and the second pluralities of bit-strings with the same associated position that disagree; and estimating the similarity between the first document and the second document based on the first count and the second count. | 7. A method comprising: receiving a first set of samples and a second set of samples at a computing device, wherein the first set of samples is associated with a first document and the second set of samples is associated with a second document; generating a first plurality of bit-strings based on the first set of samples by the computing device; generating a second plurality of bit-strings based on the second set of samples by the computing device; and estimating a similarity between the first document and the second document based on the first and second pluralities of bit-strings by the computing device, wherein each bit-string has an associated position, and estimating the similarity between the first document and the second document based on the first and second pluralities of bit sequences comprises: determining a first count of the number of bit-strings from the first and the second pluralities of bit-strings with the same associated position that agree; determining a second count of the number of bit-strings from the first and the second pluralities of bit-strings with the same associated position that disagree; and estimating the similarity between the first document and the second document based on the first count and the second count. 13. The method of claim 7 , further comprising determining that the estimated similarity is greater than a threshold similarity. | 0.866109 |
5,392,419 | 3 | 5 | 3. The method as recited in claim 2 wherein said further syntactical characteristic defined in step (c) is whether a said language vote count is greater or less than a prescribed value. | 3. The method as recited in claim 2 wherein said further syntactical characteristic defined in step (c) is whether a said language vote count is greater or less than a prescribed value. 5. The method as recited in claim 3 wherein said skew for each key type is an initial skew value for a key type modified by a skew modifier, said skew modifier causing said initial skew value to differ for second and subsequent appearances of a key type in a data block. | 0.5 |
8,352,266 | 24 | 25 | 24. A method for improving recognition accuracy of a speech recognition system, the speech recognition system having a speech recognition engine for converting audible signal representative of spoken words into a textual output and a storage unit, the method comprising the steps of: selecting a first plurality of pre-defined concepts stored on a storage medium of the storage unit; selecting a second plurality of pre-defined concept to keywords mappings stored on the storage medium, each concept of said first plurality of concepts having at least one concept to keywords mapping; selecting a third plurality of pre-defined sentence types stored on the storage medium, each pre-defined sentence type being associated with a pre-arranged ordered list of concepts, said pre-arranged ordered list of concepts being formed from said first plurality of pre-defined concepts, each of the concepts in the pre-arranged ordered list of concepts being expandable to a plurality of words that is conceptually related thereto; providing said first plurality of pre-defined concepts, said second plurality of pre-defined concept to keywords mappings and said third plurality of pre-defined sentence types, together with said associated pre-arranged ordered lists of concepts, to the speech recognition engine of the speech recognition system to enable the speech recognition engine to use said first plurality of concepts, said second plurality of pre-defined concept to keywords mappings, said third plurality of sentence types, and said associated pre-arranged ordered lists of concepts to resolve unrecognized sound groupings in the audible signal, wherein each of the concepts in the ordered lists of concepts are expanded to the plurality of conceptually related words for use by the speech recognition engine to resolve the unrecognized sound groupings in the speech corresponding to the expanded concepts in the ordered list. | 24. A method for improving recognition accuracy of a speech recognition system, the speech recognition system having a speech recognition engine for converting audible signal representative of spoken words into a textual output and a storage unit, the method comprising the steps of: selecting a first plurality of pre-defined concepts stored on a storage medium of the storage unit; selecting a second plurality of pre-defined concept to keywords mappings stored on the storage medium, each concept of said first plurality of concepts having at least one concept to keywords mapping; selecting a third plurality of pre-defined sentence types stored on the storage medium, each pre-defined sentence type being associated with a pre-arranged ordered list of concepts, said pre-arranged ordered list of concepts being formed from said first plurality of pre-defined concepts, each of the concepts in the pre-arranged ordered list of concepts being expandable to a plurality of words that is conceptually related thereto; providing said first plurality of pre-defined concepts, said second plurality of pre-defined concept to keywords mappings and said third plurality of pre-defined sentence types, together with said associated pre-arranged ordered lists of concepts, to the speech recognition engine of the speech recognition system to enable the speech recognition engine to use said first plurality of concepts, said second plurality of pre-defined concept to keywords mappings, said third plurality of sentence types, and said associated pre-arranged ordered lists of concepts to resolve unrecognized sound groupings in the audible signal, wherein each of the concepts in the ordered lists of concepts are expanded to the plurality of conceptually related words for use by the speech recognition engine to resolve the unrecognized sound groupings in the speech corresponding to the expanded concepts in the ordered list. 25. The method of claim 24 , further comprising the steps of: entering a sample utterance; parsing said sample utterance into a sentence type and an associated ordered list of concepts using a natural language processor; generating a grammar rule from said sentence type and said associated ordered list of concepts using a grammar rule generator; and providing said grammar rule to the speech recognition engine to enable the speech recognition engine to use said grammar rule to resolve unrecognized sound groupings in the audible signal. | 0.609827 |
9,773,283 | 24 | 25 | 24. The computer-implemented method of claim 23 , wherein determining one or more candidate nodes of an accessed communication from a communicating user unlikely to be candidates for representing the communicating user's intended meaning of the anchor term comprises: for each candidate node: identifying a term in the accessed communication other than the anchor term; determining a first category tree node associated with the identified term; determining a second category tree node associated with the candidate node; and determining a measure of relatedness between the first category tree node and the second category tree node; and determining one or more candidate nodes of the accessed communication from a communicating user unlikely to be candidates for representing the communicating user's intended meaning of the anchor term based on the determined measures of relatedness. | 24. The computer-implemented method of claim 23 , wherein determining one or more candidate nodes of an accessed communication from a communicating user unlikely to be candidates for representing the communicating user's intended meaning of the anchor term comprises: for each candidate node: identifying a term in the accessed communication other than the anchor term; determining a first category tree node associated with the identified term; determining a second category tree node associated with the candidate node; and determining a measure of relatedness between the first category tree node and the second category tree node; and determining one or more candidate nodes of the accessed communication from a communicating user unlikely to be candidates for representing the communicating user's intended meaning of the anchor term based on the determined measures of relatedness. 25. The computer-implemented method of claim 24 , wherein the determined measure of relatedness between the first category tree node and the second category tree node comprises the minimum number of edges between the first category tree node and the second category tree node in the category tree. | 0.5 |
9,179,250 | 2 | 3 | 2. The method of claim 1 , wherein providing the recommendation to the user comprises: obtaining the current context slice from context data associated with the user; identifying one or more transition rules corresponding to one or more transitions from the current context label to one or more destination context labels; selecting the recommendation from a corpus of recommendations based on the one or more transition rules, the selected recommendation corresponding to a recommended context label selected from the one or more destination context labels; and providing the recommendation for presentation to the user. | 2. The method of claim 1 , wherein providing the recommendation to the user comprises: obtaining the current context slice from context data associated with the user; identifying one or more transition rules corresponding to one or more transitions from the current context label to one or more destination context labels; selecting the recommendation from a corpus of recommendations based on the one or more transition rules, the selected recommendation corresponding to a recommended context label selected from the one or more destination context labels; and providing the recommendation for presentation to the user. 3. The method of claim 2 , wherein providing the recommendation further comprises: identifying a reason why the recommendation was selected; and providing the reason for presentation to the user in conjunction with the recommendation. | 0.775862 |
10,127,218 | 15 | 18 | 15. A method for setting one or more properties of multiple instances of an object, the method performed by a computing device having a processor, the method comprising: upon receiving, from a user, a selection identifying a template to apply to one or more objection instances of an object of an object type, searching for the one or more object instances that match the object type of the selected template; and applying the selected template to each of the matched one or more object instances of the object type, including: determining whether the template includes multiple levels of sub-objects; and in response to determining that the template includes multiple levels of sub-objects, determining whether a sub-object of the matched object instance that matches a hierarchical pattern of the selected template already exists in the matched object instance; and in response to determining that the sub-object of the matched object instance does not exist, creating a sub-object in the matched object instance according to the hierarchical pattern of the selected template and applying a template property and a corresponding template property value to the created sub-object according to the selected template. | 15. A method for setting one or more properties of multiple instances of an object, the method performed by a computing device having a processor, the method comprising: upon receiving, from a user, a selection identifying a template to apply to one or more objection instances of an object of an object type, searching for the one or more object instances that match the object type of the selected template; and applying the selected template to each of the matched one or more object instances of the object type, including: determining whether the template includes multiple levels of sub-objects; and in response to determining that the template includes multiple levels of sub-objects, determining whether a sub-object of the matched object instance that matches a hierarchical pattern of the selected template already exists in the matched object instance; and in response to determining that the sub-object of the matched object instance does not exist, creating a sub-object in the matched object instance according to the hierarchical pattern of the selected template and applying a template property and a corresponding template property value to the created sub-object according to the selected template. 18. The method of claim 15 wherein applying the template property value comprises overwriting an existing sub-object property value of the matched object instance with the template property value. | 0.678689 |
8,625,451 | 1 | 10 | 1. A method for non-intrusive mean opinion score estimation based on packet loss pattern, the method comprising: receiving a packet data stream; measuring the packet loss for the received data stream; calculating a probability of packet loss based on the measured packet loss; and calculating an estimated mean opinion score based on the calculated probability of packet loss using a function that maps probabilities of packet loss to measured mean opinion scores, wherein the function was derived by generating a plurality of probabilities of packet loss, and, for each generated probability of packet loss: generating, from a reference data stream, a degraded data stream suffering packet loss according to the generated probability, measuring a mean opinion score for the degraded data stream using an intrusive algorithm that operates on the contents of the data packets of the degraded data stream, and determining an association between the generated probability of packet loss and the calculated mean opinion score. | 1. A method for non-intrusive mean opinion score estimation based on packet loss pattern, the method comprising: receiving a packet data stream; measuring the packet loss for the received data stream; calculating a probability of packet loss based on the measured packet loss; and calculating an estimated mean opinion score based on the calculated probability of packet loss using a function that maps probabilities of packet loss to measured mean opinion scores, wherein the function was derived by generating a plurality of probabilities of packet loss, and, for each generated probability of packet loss: generating, from a reference data stream, a degraded data stream suffering packet loss according to the generated probability, measuring a mean opinion score for the degraded data stream using an intrusive algorithm that operates on the contents of the data packets of the degraded data stream, and determining an association between the generated probability of packet loss and the calculated mean opinion score. 10. The method of claim 1 wherein calculating a probability of packet loss based on the measured packet loss comprises calculating a probability p that a packet will be lost and calculating a probability (1−q) that a subsequent packet will also be lost. | 0.658108 |
8,935,200 | 1 | 2 | 1. A method of controlling a dump for a database, comprising: in response to a structured query language (SQL) statement being executed for the database, determining a state of a diagnosis flag associated with the SQL statement, the diagnosis flag indicating whether to perform a dump; performing, by a computer, a dump for the SQL statement in response to determining that the diagnosis flag indicates that a dump is to be performed; and for each of one or more processing steps for the SQL statement: executing the processing step; determining the state of the diagnosis flag in response to executing the processing step; accessing dump configuration information associated with the processing step; and performing the dump for the processing step based on the dump configuration information, in response to the dump configuration information indicating a dump is to be performed. | 1. A method of controlling a dump for a database, comprising: in response to a structured query language (SQL) statement being executed for the database, determining a state of a diagnosis flag associated with the SQL statement, the diagnosis flag indicating whether to perform a dump; performing, by a computer, a dump for the SQL statement in response to determining that the diagnosis flag indicates that a dump is to be performed; and for each of one or more processing steps for the SQL statement: executing the processing step; determining the state of the diagnosis flag in response to executing the processing step; accessing dump configuration information associated with the processing step; and performing the dump for the processing step based on the dump configuration information, in response to the dump configuration information indicating a dump is to be performed. 2. The method according to claim 1 , further comprising: generating dump data for the SQL statement based on the dump for the processing step. | 0.692641 |
9,483,643 | 17 | 18 | 17. A non-transitory computer-readable medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to: maintain a database that identifies: known malicious files and behaviors exhibited by the known malicious files; known non-malicious files and behaviors exhibited by the known non-malicious files; create a behavioral signature used to detect malware by: determining a combination of behaviors exhibited by at least one of the known malicious files identified within the database; identifying the number of known malicious files that exhibit each behavior within the combination of behaviors; identifying the number of known non-malicious files that exhibit each behavior within the combination of behaviors; determining that the number of known malicious files that exhibit each behavior within the combination exceeds the number of known non-malicious files that exhibit each behavior within the combination by a certain threshold; incorporating representations of each behavior within the combination of behaviors into the behavioral signature. | 17. A non-transitory computer-readable medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to: maintain a database that identifies: known malicious files and behaviors exhibited by the known malicious files; known non-malicious files and behaviors exhibited by the known non-malicious files; create a behavioral signature used to detect malware by: determining a combination of behaviors exhibited by at least one of the known malicious files identified within the database; identifying the number of known malicious files that exhibit each behavior within the combination of behaviors; identifying the number of known non-malicious files that exhibit each behavior within the combination of behaviors; determining that the number of known malicious files that exhibit each behavior within the combination exceeds the number of known non-malicious files that exhibit each behavior within the combination by a certain threshold; incorporating representations of each behavior within the combination of behaviors into the behavioral signature. 18. The non-transitory computer-readable medium of claim 17 , wherein the one or more computer-executable instructions cause the computing device to perform at least one of: determine that the number of known malicious files exceeds the number of known non-malicious files by a certain number; determine that the ratio of known malicious files to known non-malicious files exceeds a certain ratio. | 0.5 |
7,613,732 | 1 | 12 | 1. A method for email address automation, comprising: a) parsing, by a computing device, an entry in an email addressee field the email addressee field entry residing in computer readable memory; b) determining, by the computing device, whether the entry includes a predefined notation appended to the entry; and c) if the entry has a predefined notation appended to the entry, traversing, by the computing device, a hierarchy structure from a name in the entry to a designated level of the hierarchy structure based on the predefined notation; retrieving, by the computing device, email addresses of names listed at the designated level; and replacing, by the computing device, the entry in the email addressee field with the email addresses retrieved from the designated level of the hierarchy structure; wherein the predefined notation defines a relationship between the names at the designated level and the name included in the entry, the predefined notation including a special character indicating if the designated level is a higher or lower level than a level of the name in the entry, and a level indicator indicating a number of levels between the designated level and the level of the name in the entry. | 1. A method for email address automation, comprising: a) parsing, by a computing device, an entry in an email addressee field the email addressee field entry residing in computer readable memory; b) determining, by the computing device, whether the entry includes a predefined notation appended to the entry; and c) if the entry has a predefined notation appended to the entry, traversing, by the computing device, a hierarchy structure from a name in the entry to a designated level of the hierarchy structure based on the predefined notation; retrieving, by the computing device, email addresses of names listed at the designated level; and replacing, by the computing device, the entry in the email addressee field with the email addresses retrieved from the designated level of the hierarchy structure; wherein the predefined notation defines a relationship between the names at the designated level and the name included in the entry, the predefined notation including a special character indicating if the designated level is a higher or lower level than a level of the name in the entry, and a level indicator indicating a number of levels between the designated level and the level of the name in the entry. 12. The method of claim 1 , wherein the hierarchy structure comprises one of an organization hierarchy structure, a department hierarchy structure, an organization unit code hierarchy structure, or a cost center code hierarchy structure. | 0.640909 |
9,183,466 | 2 | 3 | 2. The method according to claim 1 , the receiving step including parsing a textual query to determine the one or more participant(s) identified in the textual query and the one or more condition(s) identified in the textual query with respect to the defined participant(s). | 2. The method according to claim 1 , the receiving step including parsing a textual query to determine the one or more participant(s) identified in the textual query and the one or more condition(s) identified in the textual query with respect to the defined participant(s). 3. The method according to claim 2 , wherein the textual query includes at least two words having respective, different parts of speech selected from the group consisting of noun, verb, adjective, adverb, and preposition. | 0.5 |
8,934,278 | 22 | 23 | 22. The TCAM of claim 7 , wherein the first TCAM stage is configured to consume more power evaluating comparisons as matches than evaluating comparisons as mismatches, and wherein the second TCAM stage is configured to consume more power evaluating comparisons as mismatches than evaluating comparisons as matches. | 22. The TCAM of claim 7 , wherein the first TCAM stage is configured to consume more power evaluating comparisons as matches than evaluating comparisons as mismatches, and wherein the second TCAM stage is configured to consume more power evaluating comparisons as mismatches than evaluating comparisons as matches. 23. The TCAM of claim 22 , wherein the comparison of the first portion of the search word to the first portion of the stored word statistically yields more mismatches than the comparison of the second portion of the search word to the second portion of the stored word. | 0.5 |
7,577,739 | 36 | 39 | 36. In a computer network, a computer system for implementing a method for maintaining an acceptable use policy the computer system comprising: a machine capable of executing instructions embodied as software; and a plurality of software portions comprising one of said software portions is configured to receive input from a user selecting a subject matter category for use in monitoring logged network data containing language elements; one of said software portions is configured to test the language elements of the network data for the presence of at least one preselected criterion, wherein the preselected criterion is defined by a user, comprises two or more subject matter categories each comprising regular expressions, with a first portion of said regular expressions assigned weights with negative values and a second portion of said regular expressions assigned weights with positive values, wherein the language elements of the network data are tested for the presence of the at least one preselected criterion and wherein said testing first tests the language elements of the network data for the presence of the negative valued regular expressions to facilitate avoidance of false hits; one of said software portions is configured to maintain a sum of values associated with said regular expressions found within at least one subject matter category as each regular expression is found by said testing by adding the value of the found regular expression to the sum of values; and one of said software portions is configured to store the network data for subsequent action selected from the group consisting of reporting, viewing, downloading and deleting when the sum of values associated with said regular expressions within a category meets or exceeds a positive threshold value selected based on user input. | 36. In a computer network, a computer system for implementing a method for maintaining an acceptable use policy the computer system comprising: a machine capable of executing instructions embodied as software; and a plurality of software portions comprising one of said software portions is configured to receive input from a user selecting a subject matter category for use in monitoring logged network data containing language elements; one of said software portions is configured to test the language elements of the network data for the presence of at least one preselected criterion, wherein the preselected criterion is defined by a user, comprises two or more subject matter categories each comprising regular expressions, with a first portion of said regular expressions assigned weights with negative values and a second portion of said regular expressions assigned weights with positive values, wherein the language elements of the network data are tested for the presence of the at least one preselected criterion and wherein said testing first tests the language elements of the network data for the presence of the negative valued regular expressions to facilitate avoidance of false hits; one of said software portions is configured to maintain a sum of values associated with said regular expressions found within at least one subject matter category as each regular expression is found by said testing by adding the value of the found regular expression to the sum of values; and one of said software portions is configured to store the network data for subsequent action selected from the group consisting of reporting, viewing, downloading and deleting when the sum of values associated with said regular expressions within a category meets or exceeds a positive threshold value selected based on user input. 39. The method of claim 36 , further comprising a software portion configured to output a report relating to the presence of predetermined expressions whose sum meets or exceeds the threshold value of a category. | 0.5 |
6,119,136 | 1 | 14 | 1. A manuscript text composition system comprising: templates specifying any one or all of texts and images with replacement detection keys so that part of said texts can be replaced with specific characters or character groups, or part or all of said images can be replaced with specific images; files storing specific characters or character groups and specific images that can be specified by said replacement detection keys; a parameter table specifying parameters corresponding to said specific characters or character groups and/or specific images in a tabular form having two or more dimensional coordinate axes, wherein one of said templates corresponds to one or a plurality of rows in one coordinate axis in said parameter table; a compiler to create an image display program using one of said templates, said parameter table and specific characters or character groups and/or specific images stored in one of said templates and said files and specified by said parameters; and a display unit to create a manuscript text in which specific characters or character groups and/or specific images corresponding to one of said templates are pasted based on said image display program. | 1. A manuscript text composition system comprising: templates specifying any one or all of texts and images with replacement detection keys so that part of said texts can be replaced with specific characters or character groups, or part or all of said images can be replaced with specific images; files storing specific characters or character groups and specific images that can be specified by said replacement detection keys; a parameter table specifying parameters corresponding to said specific characters or character groups and/or specific images in a tabular form having two or more dimensional coordinate axes, wherein one of said templates corresponds to one or a plurality of rows in one coordinate axis in said parameter table; a compiler to create an image display program using one of said templates, said parameter table and specific characters or character groups and/or specific images stored in one of said templates and said files and specified by said parameters; and a display unit to create a manuscript text in which specific characters or character groups and/or specific images corresponding to one of said templates are pasted based on said image display program. 14. A manuscript text composition system as set forth in claim 1 wherein replacement detection keys in said templates specify by the existence of said replacement detection keys a plurality of cells enclosed by a plurality of coordinate positions in said parameter table. | 0.71047 |
9,418,094 | 16 | 17 | 16. An apparatus configured for performing multi-stage table updates, comprising: a processor; a receiving mechanism configured to receive a query at the processor for updating a table in a database; a sub-query-generating mechanism configured to generate a set of sub-queries responsive to a storage space needed for storing a transaction log associated with the received query the pre-determined threshold, wherein while generating the sub-queries, the sub-query-generating mechanism is configured to: identify partitions in the table; and for each partition: determine if a storage space needed for storing a transaction log associated with a sub-query corresponding to the partition exceeds the pre-determined threshold; if not, process the sub-query corresponding to the partition; and if so, divide the partition into multiple subsets such that a storage space needed for storing a transaction log associated with each sub-query corresponding to a subset is less than the pre-determined threshold. | 16. An apparatus configured for performing multi-stage table updates, comprising: a processor; a receiving mechanism configured to receive a query at the processor for updating a table in a database; a sub-query-generating mechanism configured to generate a set of sub-queries responsive to a storage space needed for storing a transaction log associated with the received query the pre-determined threshold, wherein while generating the sub-queries, the sub-query-generating mechanism is configured to: identify partitions in the table; and for each partition: determine if a storage space needed for storing a transaction log associated with a sub-query corresponding to the partition exceeds the pre-determined threshold; if not, process the sub-query corresponding to the partition; and if so, divide the partition into multiple subsets such that a storage space needed for storing a transaction log associated with each sub-query corresponding to a subset is less than the pre-determined threshold. 17. The apparatus of claim 16 , further comprising: a translation mechanism configured to translate the query into a “create table” query that, when executed, creates a new table rather than updating the existing table; and a table replacement mechanism configured to replace the existing table with the new table upon completing execution of the “create table” query. | 0.607676 |
10,149,746 | 1 | 10 | 1. A method for producing a dental shaped body from a blank having a corpus of tooth restoration material by a tool adapted to remove said material, wherein, to detect a position of said corpus inserted in a machining device, contact scanning is performed on said blank by said tool, the method including steps of: providing a machining tool in a first position; detecting at least one geometric structure on said blank, the at least one geometric structure defines information that corresponds to at least one relevant dimension of said blank corpus; and using the information that corresponds to said at least one relevant dimension of said blank corpus to preposition said machining tool to a second position at or close to a first reference surface or a first reference structure for a contacting operation; determining a position of the first reference surface or first reference structure by contact scanning from said second position; and using the determined position as a starting position to detect one or more other geometric structures and/or to perform one or more other contact scanning such that contacting times of the tool during contact scanning and/or machining times of the tool during machining are reduced. | 1. A method for producing a dental shaped body from a blank having a corpus of tooth restoration material by a tool adapted to remove said material, wherein, to detect a position of said corpus inserted in a machining device, contact scanning is performed on said blank by said tool, the method including steps of: providing a machining tool in a first position; detecting at least one geometric structure on said blank, the at least one geometric structure defines information that corresponds to at least one relevant dimension of said blank corpus; and using the information that corresponds to said at least one relevant dimension of said blank corpus to preposition said machining tool to a second position at or close to a first reference surface or a first reference structure for a contacting operation; determining a position of the first reference surface or first reference structure by contact scanning from said second position; and using the determined position as a starting position to detect one or more other geometric structures and/or to perform one or more other contact scanning such that contacting times of the tool during contact scanning and/or machining times of the tool during machining are reduced. 10. The method as defined in claim 1 , wherein a contacting path is delimited according to said at least one dimension of said blank corpus detected in said detecting. | 0.755848 |
9,720,977 | 1 | 3 | 1. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: parse a received input question having a set of question characteristics; compare the set of question characteristics found in the received input question to a set of data characteristics respectively describing data in each corpus of a corpora; for each question characteristic in the set of found question characteristics: responsive to the question characteristic being more related to a data characteristic in the set of data characteristics, assign a first weight to the corpus within which data associated with the data characteristic resides; and responsive to the question characteristic being less related to the data characteristic in the set of data characteristics, assign a second weight to the corpus within which the data associated with the data characteristic resides, wherein the first weight is greater than the second weight; and selectively search for an answer to the received input question in one or more corpora with a higher weighting preferentially to one or more corpora with a lower weighting. | 1. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: parse a received input question having a set of question characteristics; compare the set of question characteristics found in the received input question to a set of data characteristics respectively describing data in each corpus of a corpora; for each question characteristic in the set of found question characteristics: responsive to the question characteristic being more related to a data characteristic in the set of data characteristics, assign a first weight to the corpus within which data associated with the data characteristic resides; and responsive to the question characteristic being less related to the data characteristic in the set of data characteristics, assign a second weight to the corpus within which the data associated with the data characteristic resides, wherein the first weight is greater than the second weight; and selectively search for an answer to the received input question in one or more corpora with a higher weighting preferentially to one or more corpora with a lower weighting. 3. The computer program product of claim 1 , wherein the first weight and the second weight are defined by a user. | 0.844262 |
7,958,501 | 10 | 13 | 10. The method according to claim 1 , wherein the populating the determined members of the persistent database object with the default values comprises: populating the determined members of the persistent database object with the default values before transferring the persistent database object to a requesting application. | 10. The method according to claim 1 , wherein the populating the determined members of the persistent database object with the default values comprises: populating the determined members of the persistent database object with the default values before transferring the persistent database object to a requesting application. 13. The method according to claim 10 , further comprising: transferring the persistent database object to the requesting application after the populating of the determined members of the persistent database object with the default values. | 0.5 |
8,548,246 | 9 | 10 | 9. The method of claim 1 , wherein calculating the word spacing associated with each column comprises: creating a histogram of spaces between consecutive components of the plurality of components associated with each column; identifying a frequently occurring space from the histogram, wherein the frequently occurring space is within a threshold range determined by the line height; and computing the word spacing based on the frequently occurring space. | 9. The method of claim 1 , wherein calculating the word spacing associated with each column comprises: creating a histogram of spaces between consecutive components of the plurality of components associated with each column; identifying a frequently occurring space from the histogram, wherein the frequently occurring space is within a threshold range determined by the line height; and computing the word spacing based on the frequently occurring space. 10. The method of claim 9 , wherein the consecutive components comprise at least one of vertically overlapping components and components separated by a predefined distance, wherein the vertically overlapping components share at least one coordinate along a vertical axis. | 0.712314 |
9,892,094 | 13 | 15 | 13. A computing device comprising: a display; one or more processors; and one or more computer-readable media including instructions that, when executed by the one or more processors, program the one or more processors to: present, on the display, a first portion of content of an electronic version of a content item; receive, via a user interface, a first page label associated with a print version of the content item; determine, based at least in part on a data object, a first position in the content associated with the first page label, wherein the data object indicates associations between page labels from the print version and positions of respective portions of content in the electronic version; present, on the display, a second portion of content of the electronic version corresponding to the first position; receive a selection of a third portion of content of the electronic version as a selected portion; generate a textual citation corresponding to the selected portion; determine, from the data object, based at least in part on a second position associated with the selected portion, a second page label associated with the selected portion; and present the textual citation associated with selected portion, the textual citation including the second page label. | 13. A computing device comprising: a display; one or more processors; and one or more computer-readable media including instructions that, when executed by the one or more processors, program the one or more processors to: present, on the display, a first portion of content of an electronic version of a content item; receive, via a user interface, a first page label associated with a print version of the content item; determine, based at least in part on a data object, a first position in the content associated with the first page label, wherein the data object indicates associations between page labels from the print version and positions of respective portions of content in the electronic version; present, on the display, a second portion of content of the electronic version corresponding to the first position; receive a selection of a third portion of content of the electronic version as a selected portion; generate a textual citation corresponding to the selected portion; determine, from the data object, based at least in part on a second position associated with the selected portion, a second page label associated with the selected portion; and present the textual citation associated with selected portion, the textual citation including the second page label. 15. The computing device as recited in claim 13 , wherein the instructions further program the one or more processors to receive the electronic version, wherein at least some of the page labels from the print version are included in the content of the electronic version as at least a portion of the data object. | 0.615764 |
7,738,705 | 1 | 4 | 1. A method to recognize model instances in an input signal, the method comprising the steps of: storing in a long-term memory a hierarchical collection of models, wherein: the instances of each model are represented by an ensemble of patterns; a non primitive pattern, defined on a domain and representative of an instance of a non-primitive model from said hierarchical collection has a fragmentation comprising a clique of local patterns; and wherein each local pattern, defined on a sub-domain of said domain, is representative of a local model from said hierarchical collection and provides an approximate representation of said non-primitive pattern within said sub-domain; generating, by a processing means, a plurality of descriptors wherein each of said descriptors specifies an estimated pattern representative of an instance of a model detected in said input signal; storing said descriptors in a short-term memory; extracting from said short-term memory, by said processing means, a clique of descriptors which specifies a clique of estimated patterns; selecting a model to be recognized from said hierarchical collection; and generating, by said processing means, and by using said clique of descriptors as auxiliary descriptors, a new descriptor that specifies a new pattern, wherein said new pattern has a fragmentation given by said clique of estimated patterns and is representative of an instance of said model to be recognized. | 1. A method to recognize model instances in an input signal, the method comprising the steps of: storing in a long-term memory a hierarchical collection of models, wherein: the instances of each model are represented by an ensemble of patterns; a non primitive pattern, defined on a domain and representative of an instance of a non-primitive model from said hierarchical collection has a fragmentation comprising a clique of local patterns; and wherein each local pattern, defined on a sub-domain of said domain, is representative of a local model from said hierarchical collection and provides an approximate representation of said non-primitive pattern within said sub-domain; generating, by a processing means, a plurality of descriptors wherein each of said descriptors specifies an estimated pattern representative of an instance of a model detected in said input signal; storing said descriptors in a short-term memory; extracting from said short-term memory, by said processing means, a clique of descriptors which specifies a clique of estimated patterns; selecting a model to be recognized from said hierarchical collection; and generating, by said processing means, and by using said clique of descriptors as auxiliary descriptors, a new descriptor that specifies a new pattern, wherein said new pattern has a fragmentation given by said clique of estimated patterns and is representative of an instance of said model to be recognized. 4. The method of claim 1 , further comprising the step of adding said new descriptor to said short-term memory if a discrepancy measure associated to said new descriptor is sufficiently low. | 0.915405 |
10,079,039 | 1 | 4 | 1. A method comprising: (a) receiving, at an electronic device, (i) data corresponding to a video, and (ii) data corresponding to a plurality of point comments associated with the video, each of the plurality of point comments being associated with a single point in time and with a particular user account of a plurality of user accounts, (iii) data corresponding to a plurality of segment comments associated with the video, each of the plurality of segment comments being associated with a video segment representing a span of time of the video and with a particular user account of the plurality of user accounts; (b) displaying, to a user via an electronic display associated with the electronic device, a video annotation interface comprising (i) a video pane configured to display the video, (ii) a first video timeline bar including a video play-head indicating a current point of the video which is being played, (iii) a second segment timeline bar disposed below the first video timeline bar, the second segment timeline bar including initial and final handles configured to define a segment of the video for playing, (iv) a first plurality of point comment markers identifiable as point comment markers by the presence of a first geometric shape displayed in connection with the video timeline bar, each of the first plurality of comment markers corresponding to one of the plurality of point comments associated with the video, (v) a second plurality of segment comment markers identifiable as segment comment markers by the presence of a second geometric shape displayed in connection with the video timeline bar, each of the second plurality of comment markers corresponding to one of the plurality of segment comments associated with the video, (vi) a comment display pane displaying text corresponding to at least some of the plurality of comments associated with the video, and (vii) a comment control configured to allow the user to add a comment to the video; and (c) receiving, at the electronic device from the user, input corresponding to engagement at a first point on the segment timeline bar; (d) automatically, in response to receiving the input corresponding to engagement at the first point on the segment timeline bar, moving the initial and final handles of the segment timeline bar to define a first segment of a first length centered around the first point, wherein the first length is one of a preconfigured length and a length determined based on a total length of the video; (e) receiving, at the electronic device from the user, input corresponding to dragging of the final handle to change the length of the first segment to a second length; (f) receiving, at the electronic device from the user, input corresponding to dragging of the first segment on the segment timeline bar, and simultaneously moving the initial and final handles while keeping the first segment its current length in response thereto; (g) receiving, at the electronic device from the user, input corresponding to engagement of the comment control; (h) in response to receiving input corresponding to engagement of the comment control, displaying, to the user via the electronic display associated with the electronic device, a comment interface; (i) receiving, at the electronic device from the user, input corresponding to one or more desired annotations; and (j) in response to receiving input corresponding to one or more desired annotations, (i) associating the input one or more annotations with the selected first segment of the video, (ii) updating the video annotation interface so that the plurality of comment markers displayed in connection with the video timeline bar includes a new segment comment marker corresponding to the first segment, and (iii) displaying an indication of the input one or more annotations overlaid over the video in the video pane. | 1. A method comprising: (a) receiving, at an electronic device, (i) data corresponding to a video, and (ii) data corresponding to a plurality of point comments associated with the video, each of the plurality of point comments being associated with a single point in time and with a particular user account of a plurality of user accounts, (iii) data corresponding to a plurality of segment comments associated with the video, each of the plurality of segment comments being associated with a video segment representing a span of time of the video and with a particular user account of the plurality of user accounts; (b) displaying, to a user via an electronic display associated with the electronic device, a video annotation interface comprising (i) a video pane configured to display the video, (ii) a first video timeline bar including a video play-head indicating a current point of the video which is being played, (iii) a second segment timeline bar disposed below the first video timeline bar, the second segment timeline bar including initial and final handles configured to define a segment of the video for playing, (iv) a first plurality of point comment markers identifiable as point comment markers by the presence of a first geometric shape displayed in connection with the video timeline bar, each of the first plurality of comment markers corresponding to one of the plurality of point comments associated with the video, (v) a second plurality of segment comment markers identifiable as segment comment markers by the presence of a second geometric shape displayed in connection with the video timeline bar, each of the second plurality of comment markers corresponding to one of the plurality of segment comments associated with the video, (vi) a comment display pane displaying text corresponding to at least some of the plurality of comments associated with the video, and (vii) a comment control configured to allow the user to add a comment to the video; and (c) receiving, at the electronic device from the user, input corresponding to engagement at a first point on the segment timeline bar; (d) automatically, in response to receiving the input corresponding to engagement at the first point on the segment timeline bar, moving the initial and final handles of the segment timeline bar to define a first segment of a first length centered around the first point, wherein the first length is one of a preconfigured length and a length determined based on a total length of the video; (e) receiving, at the electronic device from the user, input corresponding to dragging of the final handle to change the length of the first segment to a second length; (f) receiving, at the electronic device from the user, input corresponding to dragging of the first segment on the segment timeline bar, and simultaneously moving the initial and final handles while keeping the first segment its current length in response thereto; (g) receiving, at the electronic device from the user, input corresponding to engagement of the comment control; (h) in response to receiving input corresponding to engagement of the comment control, displaying, to the user via the electronic display associated with the electronic device, a comment interface; (i) receiving, at the electronic device from the user, input corresponding to one or more desired annotations; and (j) in response to receiving input corresponding to one or more desired annotations, (i) associating the input one or more annotations with the selected first segment of the video, (ii) updating the video annotation interface so that the plurality of comment markers displayed in connection with the video timeline bar includes a new segment comment marker corresponding to the first segment, and (iii) displaying an indication of the input one or more annotations overlaid over the video in the video pane. 4. The method of claim 1 , wherein the identification of a point of the video comprises a frame identification. | 0.853175 |
9,092,463 | 7 | 9 | 7. A system comprising: one or more data processing apparatus; and memory storing instructions that, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: receiving structured data describing a content item, the structured data including one or more data elements comprising one or more descriptions and values for the one or more data elements, the structured data indicating a category for the content item; retrieving stored data for the category, the stored data identifying one or more domains; forming a first query based on data elements in the structured data; searching one or more of the domains using the first query to identify resources associated with the one or more domains; determining one or more queries based on data reflecting past search queries, where each of the one or more queries resulted in one or more of the resources being returned as part of a search result; determining keywords based on the one or more queries; transmitting or storing the keywords for use in impression allocation decisions; determining an allocation score for the content item based at least in part on comparison of the keywords to a term associated with a request for an impression, where the allocation score is used to determine whether the content item will be selected for the impression; selecting the content item for display in response to the request, based on the allocation score; and transmitting data specifying the content item in response to the request. | 7. A system comprising: one or more data processing apparatus; and memory storing instructions that, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: receiving structured data describing a content item, the structured data including one or more data elements comprising one or more descriptions and values for the one or more data elements, the structured data indicating a category for the content item; retrieving stored data for the category, the stored data identifying one or more domains; forming a first query based on data elements in the structured data; searching one or more of the domains using the first query to identify resources associated with the one or more domains; determining one or more queries based on data reflecting past search queries, where each of the one or more queries resulted in one or more of the resources being returned as part of a search result; determining keywords based on the one or more queries; transmitting or storing the keywords for use in impression allocation decisions; determining an allocation score for the content item based at least in part on comparison of the keywords to a term associated with a request for an impression, where the allocation score is used to determine whether the content item will be selected for the impression; selecting the content item for display in response to the request, based on the allocation score; and transmitting data specifying the content item in response to the request. 9. The system of claim 7 , in which the resources are each assigned a score and only resources with scores better than a threshold score are used to determine the one or more queries. | 0.795759 |
8,949,359 | 16 | 17 | 16. A non-transitory computer readable storage medium having stored therein instructions, which when executed by one or more processors in a computer system, cause the computer system to: maintain a plurality of conversations, each having an identified set of participants; maintain for each respective participant in one or more of the conversations, a respective participant-specific inverse index of terms in conversations for which the respective participant is an identified participant; respond to receiving a search query from a first participant of a first conversation in the plurality of conversations by: using the participant-specific inverse index corresponding to the first participant to identify a second conversation in the plurality of conversations as relevant to the search query, and format all or a portion of the second conversation for display to the first participant; wherein the plurality of conversations are instant messaging conversations, and participants in each conversation in the plurality of conversations are instant messaging participants. | 16. A non-transitory computer readable storage medium having stored therein instructions, which when executed by one or more processors in a computer system, cause the computer system to: maintain a plurality of conversations, each having an identified set of participants; maintain for each respective participant in one or more of the conversations, a respective participant-specific inverse index of terms in conversations for which the respective participant is an identified participant; respond to receiving a search query from a first participant of a first conversation in the plurality of conversations by: using the participant-specific inverse index corresponding to the first participant to identify a second conversation in the plurality of conversations as relevant to the search query, and format all or a portion of the second conversation for display to the first participant; wherein the plurality of conversations are instant messaging conversations, and participants in each conversation in the plurality of conversations are instant messaging participants. 17. The computer readable storage medium of claim 16 , wherein the first participant is not an identified participant of the second conversation but is authorized to view content of the second conversation, the method further comprising: including terms from the second conversation in the participant-specific inverse index for the first participant. | 0.602941 |
8,996,687 | 13 | 21 | 13. A tangible computer readable memory comprising machine readable instructions which, when executed, cause a device to perform operations comprising: obtaining, from a context service in response to a query sent by the device, context information provisioned for a current location, the context information identifying a computing resource associated with the current location; and configuring interaction with the computing resource associated with the current location based on the context information received from the context service, wherein the context service is remote relative to the current location and maintains context profiles for a plurality of different geographically separated locations, and the context information is obtained from a first context profile provisioned for the current location. | 13. A tangible computer readable memory comprising machine readable instructions which, when executed, cause a device to perform operations comprising: obtaining, from a context service in response to a query sent by the device, context information provisioned for a current location, the context information identifying a computing resource associated with the current location; and configuring interaction with the computing resource associated with the current location based on the context information received from the context service, wherein the context service is remote relative to the current location and maintains context profiles for a plurality of different geographically separated locations, and the context information is obtained from a first context profile provisioned for the current location. 21. The tangible computer readable memory of claim 13 , wherein the operations further comprise: using the context information to configure an application to recognize the computing resource; and wherein configuring the interaction with the computing resource comprises communicating with the context service to establish the interaction with the computing resource. | 0.643275 |
7,849,026 | 1 | 3 | 1. A computer generated entity, comprising: a plurality of attributes, wherein at least one such attribute defines the vitality of the entity; and a plurality of actions, at least one of which will affect the vitality of the entity; wherein said actions simulate actions by the entity on objects in an environment; the environment is a computer generated simulated environment; and the computer generated entity identifies the objects by calculating one or more percepts identified with the objects. | 1. A computer generated entity, comprising: a plurality of attributes, wherein at least one such attribute defines the vitality of the entity; and a plurality of actions, at least one of which will affect the vitality of the entity; wherein said actions simulate actions by the entity on objects in an environment; the environment is a computer generated simulated environment; and the computer generated entity identifies the objects by calculating one or more percepts identified with the objects. 3. The computer generated entity of claim 1 , wherein: vitality level is determined by a quantity of energy packets. | 0.759336 |
8,560,322 | 10 | 11 | 10. The mobile terminal of claim 7 , wherein the controller writes the searched at least one word in attribute information of the image. | 10. The mobile terminal of claim 7 , wherein the controller writes the searched at least one word in attribute information of the image. 11. The mobile terminal of claim 10 , wherein when at least one word is selected from the attribute information, the controller searches the image having the selected word tagged thereto and then displays the searched image. | 0.5 |
9,251,144 | 11 | 12 | 11. A device comprising: a touchscreen display; one or more processors; and computer-readable storage media including instructions executable by the one or more processors to perform operations comprising: displaying, by the touchscreen display, an image that includes one or more words in a first language, wherein at least one word of the one or more words is displayed at a non-horizontal angle relative to an edge of the touchscreen display; receiving, by the touchscreen display, a swipe gesture selecting a first portion of the image that includes at least part of the at least one word, wherein the swipe gesture is performed at approximately the non-horizontal angle; identifying, using edge-based text detection, a second portion of the image based at least in part on the first portion of the image, the second portion of the image including the at least one word; sending the second portion of the image that includes the at least one word to a server; receiving, from the server, a translation comprising one or more translated words in a second language, the translation corresponding to the at least one word of the one or more words in the first language; and displaying the translation by the touchscreen display. | 11. A device comprising: a touchscreen display; one or more processors; and computer-readable storage media including instructions executable by the one or more processors to perform operations comprising: displaying, by the touchscreen display, an image that includes one or more words in a first language, wherein at least one word of the one or more words is displayed at a non-horizontal angle relative to an edge of the touchscreen display; receiving, by the touchscreen display, a swipe gesture selecting a first portion of the image that includes at least part of the at least one word, wherein the swipe gesture is performed at approximately the non-horizontal angle; identifying, using edge-based text detection, a second portion of the image based at least in part on the first portion of the image, the second portion of the image including the at least one word; sending the second portion of the image that includes the at least one word to a server; receiving, from the server, a translation comprising one or more translated words in a second language, the translation corresponding to the at least one word of the one or more words in the first language; and displaying the translation by the touchscreen display. 12. The device of claim 11 , the operations further comprising extracting one or more characters from the second portion of the image. | 0.798799 |
9,940,932 | 1 | 3 | 1. A method for performing speech to text conversion, the method comprising: receiving, via a processor, an audio data and a video data of a user while the user is speaking; generating, via the processor, a first raw text based on the audio data using a language model and an acoustic model in conjunction with a Hidden Markov Model; generating, via the processor, a second raw text based on the video data using Karhunen-Loeve Transform (KLT) in conjunction with the Hidden Markov Model; determining, via the processor, a plurality of errors by comparing the first raw text and the second raw text, wherein determining the one or more errors comprises comparing a sequence of phonemes in the first raw text with a corresponding sequence of visemes in the second raw text for one or more mismatches; correcting, via the processor, the plurality of errors by applying one or more rules, wherein the one or more rules employ at least one of a domain specific word database, a context of conversation, and a prior communication history; generating a correction to an error of the plurality of errors; automatically generating a rule based on the error, the correction and training; and applying the one or more rules to another error of the plurality of errors to obtain a final text. | 1. A method for performing speech to text conversion, the method comprising: receiving, via a processor, an audio data and a video data of a user while the user is speaking; generating, via the processor, a first raw text based on the audio data using a language model and an acoustic model in conjunction with a Hidden Markov Model; generating, via the processor, a second raw text based on the video data using Karhunen-Loeve Transform (KLT) in conjunction with the Hidden Markov Model; determining, via the processor, a plurality of errors by comparing the first raw text and the second raw text, wherein determining the one or more errors comprises comparing a sequence of phonemes in the first raw text with a corresponding sequence of visemes in the second raw text for one or more mismatches; correcting, via the processor, the plurality of errors by applying one or more rules, wherein the one or more rules employ at least one of a domain specific word database, a context of conversation, and a prior communication history; generating a correction to an error of the plurality of errors; automatically generating a rule based on the error, the correction and training; and applying the one or more rules to another error of the plurality of errors to obtain a final text. 3. The method of claim 1 , wherein generating the first raw text comprises: extracting a sequence of phonemes from the audio data; and mapping the sequence of phonemes to a corresponding text using a phoneme-to-text database and a word database. | 0.612342 |
8,589,231 | 1 | 7 | 1. A method for sensitivity categorization of web pages, the method comprising: (a) identifying a space of sensitive pages based on a sensitivity categorization of a first plurality of web pages and a second plurality of web pages, the first plurality of web pages being obtained from search queries using known sensitive words, the second plurality of web pages being randomly selected web pages; (b) identifying a third plurality of web pages that includes web pages on or near a boundary between the space of sensitive pages and a space without sensitive pages; (c) redefining the space of sensitive pages based on a sensitivity categorization of the first, second, and third pluralities of web pages; (d) determining that a given web page is sensitive when the given web page is in the space of sensitive pages; and (e) including the given web page in a marketing operation when the given web page is determined to be not sensitive and discarding the given web page for the marketing operation otherwise, wherein operations (a)-(e) are executed by a processor. | 1. A method for sensitivity categorization of web pages, the method comprising: (a) identifying a space of sensitive pages based on a sensitivity categorization of a first plurality of web pages and a second plurality of web pages, the first plurality of web pages being obtained from search queries using known sensitive words, the second plurality of web pages being randomly selected web pages; (b) identifying a third plurality of web pages that includes web pages on or near a boundary between the space of sensitive pages and a space without sensitive pages; (c) redefining the space of sensitive pages based on a sensitivity categorization of the first, second, and third pluralities of web pages; (d) determining that a given web page is sensitive when the given web page is in the space of sensitive pages; and (e) including the given web page in a marketing operation when the given web page is determined to be not sensitive and discarding the given web page for the marketing operation otherwise, wherein operations (a)-(e) are executed by a processor. 7. The method as recited in claim 1 , wherein sensitivity categorization is performed using a function selected from a group consisting of linear SVM, RBF kernel SVM, MaxEnt, Decision Trees, Naive Bayes, or Stochastic Gradient Descent. | 0.673611 |
10,097,785 | 11 | 13 | 11. A method of selectively supplementing main program video content with a sign language video content, comprising: at a video receiver device, receiving data representing audio and at least one frame of video content, the data having a plurality of packet identifiers (PIDs) where a first PID is associated with main program video content, and where a second PID is associated with sign language video content; where the main program video content comprises frames of video content having a plurality of locations to accept the sign language video content; at the video receiver device, receiving a signal indicative of a selection of a first location of the plurality of locations for display of the sign language video content; and responsive to receiving the signal indicative of the selection of the first location, at a content circuit within the video receiver device, presenting in the first location the sign language video content to produce a video frame having a sub-frame containing the sign language video content at the first location; responsive to a signal to view the sign language video content, disabling a video scaler; and responsive to a signal not to view the sign language video content, enabling the video scaler. | 11. A method of selectively supplementing main program video content with a sign language video content, comprising: at a video receiver device, receiving data representing audio and at least one frame of video content, the data having a plurality of packet identifiers (PIDs) where a first PID is associated with main program video content, and where a second PID is associated with sign language video content; where the main program video content comprises frames of video content having a plurality of locations to accept the sign language video content; at the video receiver device, receiving a signal indicative of a selection of a first location of the plurality of locations for display of the sign language video content; and responsive to receiving the signal indicative of the selection of the first location, at a content circuit within the video receiver device, presenting in the first location the sign language video content to produce a video frame having a sub-frame containing the sign language video content at the first location; responsive to a signal to view the sign language video content, disabling a video scaler; and responsive to a signal not to view the sign language video content, enabling the video scaler. 13. The method according to claim 11 , where the sign language video content is inter-coded so as to rely only on sign language video data present within the sign language video content. | 0.723214 |
9,892,111 | 1 | 16 | 1. A method for comparing a first document and a second document, the method comprising: associating, by a processor, a respective weight with each of a plurality of information types including text-based information, graphical information, audio information, or video information; identifying, for each of the first document and the second document, by the processor, one or more segments each corresponding to one of the plurality of information types; and estimating, by the processor, a similarity value between the first document and the second document, by comparing each segment of the first document with a segment of the second document that corresponds to a same information type, wherein the similarity value is based on a distance, in a semantic hierarchy, between a first semantic class associated with the first document and a common ancestor, in the semantic hierarchy, of the first semantic class and a second semantic class associated with a second document; and combining results of the comparison based on the respective associated weights. | 1. A method for comparing a first document and a second document, the method comprising: associating, by a processor, a respective weight with each of a plurality of information types including text-based information, graphical information, audio information, or video information; identifying, for each of the first document and the second document, by the processor, one or more segments each corresponding to one of the plurality of information types; and estimating, by the processor, a similarity value between the first document and the second document, by comparing each segment of the first document with a segment of the second document that corresponds to a same information type, wherein the similarity value is based on a distance, in a semantic hierarchy, between a first semantic class associated with the first document and a common ancestor, in the semantic hierarchy, of the first semantic class and a second semantic class associated with a second document; and combining results of the comparison based on the respective associated weights. 16. The method of claim 1 , further comprising: displaying the estimated similarity value through a user interface. | 0.801038 |
8,478,186 | 5 | 6 | 5. The educational system for testing memorization as recited in claim 4 , wherein said network interface is adapted for interfacing a plurality of the educational systems for testing memorization with one another. | 5. The educational system for testing memorization as recited in claim 4 , wherein said network interface is adapted for interfacing a plurality of the educational systems for testing memorization with one another. 6. The educational system for testing memorization as recited in claim 5 , wherein said network interface is adapted for interfacing the plurality of the educational systems for testing memorization with the central server. | 0.5 |
9,558,276 | 15 | 23 | 15. A system including an agent device, comprising: a processor; a non-transitory computer-readable storage medium containing instructions which when executed on the processor, cause the processor to perform operations including: determining availability as an agent for topic data stored in a system, wherein agents are active or inactive and are relevant or irrelevant to the topic data, and wherein agents are relevant when a topic included in one or more profiles of one or more relevant agents matches the topic data; transmitting availability as an active relevant agent for the topic data, wherein one or more real-time interaction options are associated with active relevant agents, wherein status data is generated and remotely stored according to the availability of active relevant agents associated with real-time interaction options, wherein the status data is transmitted by an agent search server to a search engine server operating remotely from the agent search server and in communication with the agent search server over a network, wherein an agent search request is generated using the topic data and includes the topic data, and wherein the agent search request is used to determine relevant agents associated with the topic data; detecting data corresponding to a selection of an interactive element associated with search results generated by the search engine server, wherein the search results are generated in response to a search request including the topic data, wherein the search request does not include a request for an agent, wherein the search request is separate from the agent search request, wherein interactive elements are associated with the search results according to remotely received status data, wherein the interactive elements are separate from the search results, wherein an interactive element is displayed concurrently with a search result, and wherein the selection of an interactive element facilitates a real-time interaction option among two or more devices; and participating in a real-time interaction option as an active relevant agent associated with the topic data. | 15. A system including an agent device, comprising: a processor; a non-transitory computer-readable storage medium containing instructions which when executed on the processor, cause the processor to perform operations including: determining availability as an agent for topic data stored in a system, wherein agents are active or inactive and are relevant or irrelevant to the topic data, and wherein agents are relevant when a topic included in one or more profiles of one or more relevant agents matches the topic data; transmitting availability as an active relevant agent for the topic data, wherein one or more real-time interaction options are associated with active relevant agents, wherein status data is generated and remotely stored according to the availability of active relevant agents associated with real-time interaction options, wherein the status data is transmitted by an agent search server to a search engine server operating remotely from the agent search server and in communication with the agent search server over a network, wherein an agent search request is generated using the topic data and includes the topic data, and wherein the agent search request is used to determine relevant agents associated with the topic data; detecting data corresponding to a selection of an interactive element associated with search results generated by the search engine server, wherein the search results are generated in response to a search request including the topic data, wherein the search request does not include a request for an agent, wherein the search request is separate from the agent search request, wherein interactive elements are associated with the search results according to remotely received status data, wherein the interactive elements are separate from the search results, wherein an interactive element is displayed concurrently with a search result, and wherein the selection of an interactive element facilitates a real-time interaction option among two or more devices; and participating in a real-time interaction option as an active relevant agent associated with the topic data. 23. The system of claim 15 , wherein status data is generated in response to the search request or one or more keywords. | 0.766537 |
9,712,885 | 7 | 9 | 7. A computer-implemented method, comprising: receiving a request for video data from a client device, the video data including closed captioning (CC) data; determining a future time to display an advertisement; setting a time window including the future display time for the advertisement, a first time period before and adjacent to the future display time, a second time period during the future display time, and a third time period adjacent to and after the future display time, the time window comprising less time than an entirety of running time of the video data; selecting a subset of the video data that will be displayed during the time window; decoding the CC data for the subset of video data with a processor circuit to obtain text; parsing the text to obtain words; providing the words to an advertising selector; receiving an advertisement from the advertising selector; and transmitting the advertisement to the client device for display. | 7. A computer-implemented method, comprising: receiving a request for video data from a client device, the video data including closed captioning (CC) data; determining a future time to display an advertisement; setting a time window including the future display time for the advertisement, a first time period before and adjacent to the future display time, a second time period during the future display time, and a third time period adjacent to and after the future display time, the time window comprising less time than an entirety of running time of the video data; selecting a subset of the video data that will be displayed during the time window; decoding the CC data for the subset of video data with a processor circuit to obtain text; parsing the text to obtain words; providing the words to an advertising selector; receiving an advertisement from the advertising selector; and transmitting the advertisement to the client device for display. 9. The computer-implemented method of claim 7 , comprising: selecting ad-relevant words from the obtained words; and providing the ad-relevant words to the advertising selector. | 0.70202 |
8,880,520 | 12 | 16 | 12. A method comprising: receiving, by a processor, a search query from a search user; classifying, by the processor, the search query into at least one query-class from a plurality of query-classes; performing, by the processor, a search using the search query over a plurality of non-trust data sources to obtain a plurality of non-trust search results; selectively performing, by the processor, another search using the search query over a plurality of identified trust data sources to obtain a plurality of trust search results, wherein the identified trust data sources include explicit trusted data sources that are trusted specifically by the search user and wherein the non-trust data sources are non-trusted specifically by the search user; categorizing, by the processor, the plurality of trust search results based on the search user's respective relationship with each identified trust data source, the search user's respective relationship being one from a group of relationships comprising an explicit trust data source relationship, an implicit trust data source relationship, and another trust data source relationship having a correspondence with a social networking source for which the search user is not a member; determining, by the processor and based on the at least one query-class for the search query and the trust search results categorization, a number and a position for selectively displaying each of the plurality of trust search results in a rank order; and selectively displaying, by the processor, the plurality of trust search results distinct from a display of the plurality of non-trust search results, wherein the selectively displayed plurality of trust search results is in accordance with the determination and includes display of information indicating an identified trust data source of each of the plurality of trust search results. | 12. A method comprising: receiving, by a processor, a search query from a search user; classifying, by the processor, the search query into at least one query-class from a plurality of query-classes; performing, by the processor, a search using the search query over a plurality of non-trust data sources to obtain a plurality of non-trust search results; selectively performing, by the processor, another search using the search query over a plurality of identified trust data sources to obtain a plurality of trust search results, wherein the identified trust data sources include explicit trusted data sources that are trusted specifically by the search user and wherein the non-trust data sources are non-trusted specifically by the search user; categorizing, by the processor, the plurality of trust search results based on the search user's respective relationship with each identified trust data source, the search user's respective relationship being one from a group of relationships comprising an explicit trust data source relationship, an implicit trust data source relationship, and another trust data source relationship having a correspondence with a social networking source for which the search user is not a member; determining, by the processor and based on the at least one query-class for the search query and the trust search results categorization, a number and a position for selectively displaying each of the plurality of trust search results in a rank order; and selectively displaying, by the processor, the plurality of trust search results distinct from a display of the plurality of non-trust search results, wherein the selectively displayed plurality of trust search results is in accordance with the determination and includes display of information indicating an identified trust data source of each of the plurality of trust search results. 16. The method of claim 12 , wherein the plurality of identified trust data sources comprises at least one of a plurality of social networking websites, or a plurality of messages from at least one of a friend or family member to the search user. | 0.778777 |
8,386,472 | 7 | 10 | 7. A method implemented in a computer-readable storage medium and processed by a processor to perform the method, comprising: iterating over Structured Query Language (SQL) statements to identify dependencies between rules embedded in the SQL statements, the SQL statements representing a query or report submitted by a user for execution and the SQL statements are preprocessed by the method processing; adding calculation dependencies for select rules that depend on prior referenced calculations within the SQL statements; and automatically and dynamically generating a processing order for executing the rules based on the dependencies and the calculation dependencies and modifying the SQL statements based on the processing order transparent to the user and the processing order aligned with the rules and the select rules regardless of a number of levels for and complexity of the rules and the select rules, and wherein the user providing the SQL statements does not provide the processing order with the SQL statements. | 7. A method implemented in a computer-readable storage medium and processed by a processor to perform the method, comprising: iterating over Structured Query Language (SQL) statements to identify dependencies between rules embedded in the SQL statements, the SQL statements representing a query or report submitted by a user for execution and the SQL statements are preprocessed by the method processing; adding calculation dependencies for select rules that depend on prior referenced calculations within the SQL statements; and automatically and dynamically generating a processing order for executing the rules based on the dependencies and the calculation dependencies and modifying the SQL statements based on the processing order transparent to the user and the processing order aligned with the rules and the select rules regardless of a number of levels for and complexity of the rules and the select rules, and wherein the user providing the SQL statements does not provide the processing order with the SQL statements. 10. The method of claim 7 , wherein iterating further includes accessing a rule list to resolve references to at least some of the rules identified in the SQL statements. | 0.670543 |
8,612,489 | 9 | 14 | 9. A computer program product for transforming an extensible business reporting language (XBRL) instance into a structured extensible markup language (XML) data model instance the computer program product comprising: a computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising a computer usable program code configured to: for each of a plurality of concepts indicated in an XBRL schema associated with the XBRL instance, determine concept relationship information for the concept from the XBRL schema, context information indicated in the XBRL instance, and at least one of a plurality of files that constitute a taxonomy set for the XBRL instance; determine attribute information for the concept based, at least in part, on the XBRL schema and at least one of the files that constitute the taxonomy set; generate an XML document with XML elements structured in accordance with the concept relationship information, wherein the XML elements correspond to the plurality of concepts and have attributes set based, at least in part, on the attribute information; populate each of the XML elements with corresponding ones of XBRL facts to yield the structured XML data model instance, wherein the XBRL instance indicates the XBRL facts and the XML data model instance comprises at least the XML document; retrieve an XBRL dimension document via a second reference indicated in the taxonomy set, the XBRL dimension document including at least one hypercube having a plurality of dimensions; add a parent element to an XML dimension mapping document, the parent element corresponding to the hypercube; add to the XML dimension document one or more child elements of the parent element, the one or more child elements representing one or more dimensions in the hypercube. | 9. A computer program product for transforming an extensible business reporting language (XBRL) instance into a structured extensible markup language (XML) data model instance the computer program product comprising: a computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising a computer usable program code configured to: for each of a plurality of concepts indicated in an XBRL schema associated with the XBRL instance, determine concept relationship information for the concept from the XBRL schema, context information indicated in the XBRL instance, and at least one of a plurality of files that constitute a taxonomy set for the XBRL instance; determine attribute information for the concept based, at least in part, on the XBRL schema and at least one of the files that constitute the taxonomy set; generate an XML document with XML elements structured in accordance with the concept relationship information, wherein the XML elements correspond to the plurality of concepts and have attributes set based, at least in part, on the attribute information; populate each of the XML elements with corresponding ones of XBRL facts to yield the structured XML data model instance, wherein the XBRL instance indicates the XBRL facts and the XML data model instance comprises at least the XML document; retrieve an XBRL dimension document via a second reference indicated in the taxonomy set, the XBRL dimension document including at least one hypercube having a plurality of dimensions; add a parent element to an XML dimension mapping document, the parent element corresponding to the hypercube; add to the XML dimension document one or more child elements of the parent element, the one or more child elements representing one or more dimensions in the hypercube. 14. The computer program product of claim 9 , wherein the computer usable program code is further configured to preserve the structure of the XBRL instance in a second XML document, wherein the structured XML data model instance also comprises the second XML document. | 0.678657 |
9,177,022 | 10 | 13 | 10. A computer storage device having computer-executable instructions for processing queries, comprising: receiving user input creating a pipeline configuration for executing a query from an input device; receiving a first query; obtaining a context and condition of the first query; determining rules based on the context and conditions of the first query by utilizing the pipeline configuration, wherein the rules are triggered in response to receiving the first query; applying the rules to the first query to determine additional queries to execute; executing the additional queries; receiving supplemental results from execution of each the additional queries; and mixing the received supplemental results with any core results to form mixed results. | 10. A computer storage device having computer-executable instructions for processing queries, comprising: receiving user input creating a pipeline configuration for executing a query from an input device; receiving a first query; obtaining a context and condition of the first query; determining rules based on the context and conditions of the first query by utilizing the pipeline configuration, wherein the rules are triggered in response to receiving the first query; applying the rules to the first query to determine additional queries to execute; executing the additional queries; receiving supplemental results from execution of each the additional queries; and mixing the received supplemental results with any core results to form mixed results. 13. The computer storage device of claim 10 , wherein executing the additional queries comprises: performing a federated search and executing parallel queries that are created in response to applying the rules to the first query. | 0.545635 |
9,377,951 | 2 | 3 | 2. The method of claim 1 , further comprising highlighting the linguistic element of a current key selection with a third highlighting to distinguish the current key selection from the highlighted keys corresponding to the default language object. | 2. The method of claim 1 , further comprising highlighting the linguistic element of a current key selection with a third highlighting to distinguish the current key selection from the highlighted keys corresponding to the default language object. 3. The method of claim 2 , wherein the predictive linguistic element is positioned in the language object at a location adjacent and subsequent to a current linguistic element corresponding to the current key selection. | 0.783597 |
10,068,617 | 1 | 8 | 1. A method comprising: storing comment data that indicates a plurality of comments that are associated with a media item; wherein two comments in the plurality of comments are from different users of a plurality of users; wherein each comment in the plurality of comments is associated with a time within the media item; receiving first input that indicates one or more search criteria; in response to receiving the first input: performing a search of the plurality of comments based on the one or more search criteria, wherein performing the search of the plurality of comments comprises limiting the search to comments that are associated with (1) the one or more search criteria and (2) a time that is within a time range that is based on a current playback position of the media item; identifying, as a result of performing the search, one or more comments of the plurality of comments; in response to identifying the one or more comments as the result of performing the search, causing, to be displayed on a screen of a computing device, the one or more comments of the plurality of comments; wherein the method is performed by one or more computing devices. | 1. A method comprising: storing comment data that indicates a plurality of comments that are associated with a media item; wherein two comments in the plurality of comments are from different users of a plurality of users; wherein each comment in the plurality of comments is associated with a time within the media item; receiving first input that indicates one or more search criteria; in response to receiving the first input: performing a search of the plurality of comments based on the one or more search criteria, wherein performing the search of the plurality of comments comprises limiting the search to comments that are associated with (1) the one or more search criteria and (2) a time that is within a time range that is based on a current playback position of the media item; identifying, as a result of performing the search, one or more comments of the plurality of comments; in response to identifying the one or more comments as the result of performing the search, causing, to be displayed on a screen of a computing device, the one or more comments of the plurality of comments; wherein the method is performed by one or more computing devices. 8. The method of claim 1 , further comprising: in response to identifying the one or more comments as the result of performing the search, causing the current playback position of the media item to move to a position that corresponds to a media time that is associated with one of the one or more comments. | 0.712946 |
8,001,118 | 6 | 24 | 6. The computer-implemented method of claim 1 , wherein determining the usage score from the frequency of visit value and the unique visit value associated with the document comprises: determining a frequency of visit score based on the frequency of visit value and a maximum frequency of visit value; determining a unique user score based on the unique visit value and a maximum unique visit value; and determining the usage score from the frequency of visit score and the unique user score. | 6. The computer-implemented method of claim 1 , wherein determining the usage score from the frequency of visit value and the unique visit value associated with the document comprises: determining a frequency of visit score based on the frequency of visit value and a maximum frequency of visit value; determining a unique user score based on the unique visit value and a maximum unique visit value; and determining the usage score from the frequency of visit score and the unique user score. 24. The computer-implemented method of claim 6 , wherein: determining the frequency of visit score based on the frequency of visit value and the maximum frequency of visit value comprises determining the frequency of visit score based on a log ratio of the frequency of visit value to the maximum frequency of visit value; and determining the unique user score based on the unique visit value and the maximum unique visit value comprises determining the unique user score based on a ratio of the unique visit value to the maximum unique visit value. | 0.5 |
9,836,778 | 16 | 17 | 16. The computer-implemented method of claim 14 , wherein generating the recommendation comprises: determining each historical scan message in the subset of historical scan messages is associated a number of different retail locations from a plurality of select retail locations of the merchant identified by a merchant definition; and determining the number of different retail locations of the merchant satisfies an inference threshold number of scan messages. | 16. The computer-implemented method of claim 14 , wherein generating the recommendation comprises: determining each historical scan message in the subset of historical scan messages is associated a number of different retail locations from a plurality of select retail locations of the merchant identified by a merchant definition; and determining the number of different retail locations of the merchant satisfies an inference threshold number of scan messages. 17. The computer-implemented method of claim 16 , further comprises: based on satisfaction of the inference threshold number of scan messages, generating the recommendation for the specific user based on the merchant. | 0.5 |
4,780,906 | 14 | 16 | 14. An electronic device as set forth in claim 12, wherein each reference vector of said plurality of reference templates is based upon a zero-crossing rate and an energy measurement of a reference analog speech signal corresponding to an individual word, and said word-discrimination information representative of said input analog speech signal including energy measurements and the zero-crossing rate of the input analog speech signal. | 14. An electronic device as set forth in claim 12, wherein each reference vector of said plurality of reference templates is based upon a zero-crossing rate and an energy measurement of a reference analog speech signal corresponding to an individual word, and said word-discrimination information representative of said input analog speech signal including energy measurements and the zero-crossing rate of the input analog speech signal. 16. An electronic device as set forth in claim 14, wherein said signal conditioning means includes energy measuring circuit means and zero-crossing detector means respectively receiving said input analog speech signal for providing said energy measurements and a zero-crossing count with respect to the input analog speech signal. | 0.5 |
8,983,986 | 1 | 3 | 1. A method comprising: receiving, by one or more computing devices, a search query from a first user of a social-networking system, the social-networking system comprising a graph that comprises a plurality of nodes and edges connecting the nodes, at least one node in the graph corresponding to the first user; identifying, by the one or more computing devices, one or more web pages responsive to the search query; for each of the web pages, determining, by the one or more computing devices, a value based at least in part on a number of interactions with the web page by one or more second users of the social-networking system, for each of the second users at least one node in the graph corresponding to the second user, at least one of the nodes corresponding to the first user and at least one of the nodes corresponding to a second user being connected to each other by one or more edges; and providing, by the one or more computing devices, a search results page responsive to the received search query, the search results page comprising a link for each one of the web pages with a value that is greater than a pre-determined minimum value. | 1. A method comprising: receiving, by one or more computing devices, a search query from a first user of a social-networking system, the social-networking system comprising a graph that comprises a plurality of nodes and edges connecting the nodes, at least one node in the graph corresponding to the first user; identifying, by the one or more computing devices, one or more web pages responsive to the search query; for each of the web pages, determining, by the one or more computing devices, a value based at least in part on a number of interactions with the web page by one or more second users of the social-networking system, for each of the second users at least one node in the graph corresponding to the second user, at least one of the nodes corresponding to the first user and at least one of the nodes corresponding to a second user being connected to each other by one or more edges; and providing, by the one or more computing devices, a search results page responsive to the received search query, the search results page comprising a link for each one of the web pages with a value that is greater than a pre-determined minimum value. 3. The method of claim 1 , wherein, for each of the web pages, the value is based at least in part on a number of times the web page has been clicked by the second users divided by a number of times the web page has been presented to the users. | 0.746888 |
8,527,452 | 2 | 3 | 2. The computer program product as recited in claim 1 , wherein said intermediate logical construct is created in response to said event logical construct. | 2. The computer program product as recited in claim 1 , wherein said intermediate logical construct is created in response to said event logical construct. 3. The computer program product as recited in claim 2 , wherein said event logical construct represents a trigger event for a rule. | 0.5 |
8,775,520 | 2 | 5 | 2. The method of claim 1 , wherein the electronic message includes a second attachment viewing link corresponding to a second attachment associated with the electronic message, the second attachment having a document type, and said method further comprising: in response to a single user selection of the second attachment viewing link, obtaining from the document storage system a second converted document corresponding to the second attachment, wherein the second converted document has a document type different from the document type of the second attachment; and displaying the second converted document in a third instance of the client application. | 2. The method of claim 1 , wherein the electronic message includes a second attachment viewing link corresponding to a second attachment associated with the electronic message, the second attachment having a document type, and said method further comprising: in response to a single user selection of the second attachment viewing link, obtaining from the document storage system a second converted document corresponding to the second attachment, wherein the second converted document has a document type different from the document type of the second attachment; and displaying the second converted document in a third instance of the client application. 5. The method of claim 2 , wherein the first and second attachments have document types selected from the set consisting of a word processing document type, a spreadsheet document type, a presentation document type, and a portable document type. | 0.5 |
9,262,513 | 1 | 2 | 1. One or more computer-readable media storing computer-executable instructions that, when executed by one or more processors, instruct the one or more processors to perform acts comprising: receiving a query by a server, the query including a keyword; obtaining multiple search results based at least in part on the keyword, wherein the multiple search results include: a first set of search results determined based on literal correlations with the keyword; and a second set of search results including one or more search results that are not in the first set of search results, each individual search result of the second set of search results being determined based at least in part on correlations among the keyword and transactional parameters, each individual transactional parameter of the transactional parameters being determined based on a ratio of a number of users purchasing one or more items associated with an individual search result to a number of users investigating the individual search result; and assigning the second set of search results a higher priority than the first set of search results. | 1. One or more computer-readable media storing computer-executable instructions that, when executed by one or more processors, instruct the one or more processors to perform acts comprising: receiving a query by a server, the query including a keyword; obtaining multiple search results based at least in part on the keyword, wherein the multiple search results include: a first set of search results determined based on literal correlations with the keyword; and a second set of search results including one or more search results that are not in the first set of search results, each individual search result of the second set of search results being determined based at least in part on correlations among the keyword and transactional parameters, each individual transactional parameter of the transactional parameters being determined based on a ratio of a number of users purchasing one or more items associated with an individual search result to a number of users investigating the individual search result; and assigning the second set of search results a higher priority than the first set of search results. 2. The one or more computer-readable media of claim 1 , further comprising removing, from the first set of search results, a search result that is substantially same as a particular search result of the second set of search results. | 0.60274 |
8,996,351 | 11 | 13 | 11. One or more non-transitory computer-readable storage media storing instructions which, when processed by one or more computing devices, cause: receiving both (a) a particular device identifier that identifies a scanning device associated with a business organization and (b) first processed scan data that was generated by performing one or more of (i) optical character recognition on initial scan data that was generated by the scanning device or (ii) natural language translation on data produced by performing optical character recognition on the initial scan data; and identifying, from a plurality of mappings of device identifiers to operational contexts of the business organization, a particular mapping of the particular device identifier to a particular operational context of the business organization; and selecting the particular operational context of the business organization; and identifying, from a plurality of mappings of operational contexts of the business organization to rules that define, for a set of one or more characters, a set of one or more replacement characters, a particular set of rules that defines, for a set of one or more characters, a set of one or more replacement characters; selecting the particular set of rules that defines, for a set of one or more characters, a set of one or more replacement characters; and generating second processed scan data by applying the particular set of rules to the first processed scan data by replacing one or more characters in the processed scan data with the set of one or more replacement characters. | 11. One or more non-transitory computer-readable storage media storing instructions which, when processed by one or more computing devices, cause: receiving both (a) a particular device identifier that identifies a scanning device associated with a business organization and (b) first processed scan data that was generated by performing one or more of (i) optical character recognition on initial scan data that was generated by the scanning device or (ii) natural language translation on data produced by performing optical character recognition on the initial scan data; and identifying, from a plurality of mappings of device identifiers to operational contexts of the business organization, a particular mapping of the particular device identifier to a particular operational context of the business organization; and selecting the particular operational context of the business organization; and identifying, from a plurality of mappings of operational contexts of the business organization to rules that define, for a set of one or more characters, a set of one or more replacement characters, a particular set of rules that defines, for a set of one or more characters, a set of one or more replacement characters; selecting the particular set of rules that defines, for a set of one or more characters, a set of one or more replacement characters; and generating second processed scan data by applying the particular set of rules to the first processed scan data by replacing one or more characters in the processed scan data with the set of one or more replacement characters. 13. The one or more non-transitory computer-readable storage media of claim 11 , wherein the first processed scan data is a translated document that was generated by a translation server as a result of the translation server performing a natural language translation process on an optical character recognition (OCR) document that was generated by an OCR server as a result of the OCR server performing an OCR process relative to the initial scan data; wherein the translation server is embodied in a machine that is separate from the scanning device; wherein the machine in which the translation server is embodied is accessible by the scanning device through one or more packet networks; and wherein text of the translated document is in a different natural language than a natural language in which text of the OCR document is. | 0.633068 |
8,037,086 | 11 | 15 | 11. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a pair of terms that includes a term and a candidate synonym of the term; determining that the terms of the pair have been identified as being potentially non-synonymous; evaluating the pair of terms using one or more penalty criteria that are only applied to terms that are identified as being potentially non-synonymous, comprising determining a quantity of switches that have occurred between queries that include the term and queries that include the candidate synonym of the term; selecting a first threshold if the pair of terms satisfies the penalty criteria, or a second threshold if the pair of terms does not satisfy the penalty criteria, wherein the first threshold is a same threshold that is applied to pairs of terms that are not identified as being potentially non-synonymous, and wherein the second threshold is higher than the first threshold; and determining that the terms of the pair are synonyms when the selected threshold is exceeded. | 11. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a pair of terms that includes a term and a candidate synonym of the term; determining that the terms of the pair have been identified as being potentially non-synonymous; evaluating the pair of terms using one or more penalty criteria that are only applied to terms that are identified as being potentially non-synonymous, comprising determining a quantity of switches that have occurred between queries that include the term and queries that include the candidate synonym of the term; selecting a first threshold if the pair of terms satisfies the penalty criteria, or a second threshold if the pair of terms does not satisfy the penalty criteria, wherein the first threshold is a same threshold that is applied to pairs of terms that are not identified as being potentially non-synonymous, and wherein the second threshold is higher than the first threshold; and determining that the terms of the pair are synonyms when the selected threshold is exceeded. 15. The system of claim 11 , wherein determining that the terms of the pair are synonyms comprises: determining a confidence value associated with the pair of terms; and applying the selected threshold to the confidence value. | 0.727053 |
9,412,382 | 8 | 11 | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: receiving, from a user of a speech verification system, a plurality of speech samples of a same word, wherein the plurality of speech samples of the same word comprise: a current speech response; and a plurality of previously recorded speech samples, wherein each of the previously recorded speech samples is associated with a distinct location; generating a sample similarity from the plurality of speech samples; making a decision whether to enroll the user in the speech verification system according to a comparison of the sample similarity with a threshold, wherein the decision is a first decision if the sample similarity is above the threshold and the decision is a second decision different from and mutually exclusive with the first decision if the sample similarity is below the threshold; and enrolling the user in the speech verification system responsively to the decision's being the second decision. | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: receiving, from a user of a speech verification system, a plurality of speech samples of a same word, wherein the plurality of speech samples of the same word comprise: a current speech response; and a plurality of previously recorded speech samples, wherein each of the previously recorded speech samples is associated with a distinct location; generating a sample similarity from the plurality of speech samples; making a decision whether to enroll the user in the speech verification system according to a comparison of the sample similarity with a threshold, wherein the decision is a first decision if the sample similarity is above the threshold and the decision is a second decision different from and mutually exclusive with the first decision if the sample similarity is below the threshold; and enrolling the user in the speech verification system responsively to the decision's being the second decision. 11. The system of claim 8 , wherein the speech verification system provides access to a restricted location. | 0.837349 |
8,200,485 | 26 | 27 | 26. The system as defined in claim 24 , wherein the query server selects the grammar by at least: executing a preliminary search to identify a subset of items that match the set of characters; and extracting text from the subset of items to incorporate into grammar. | 26. The system as defined in claim 24 , wherein the query server selects the grammar by at least: executing a preliminary search to identify a subset of items that match the set of characters; and extracting text from the subset of items to incorporate into grammar. 27. The system as defined in claim 26 , wherein the query server is programmed to extract author names from the subset of items to generate a grammar for performing a voice-based author search. | 0.5 |
8,538,759 | 1 | 2 | 1. A speech recognition system installed in a terminal coupled to a server via a network, wherein: the terminal holds map data including a landmark; the speech recognition system manages recognition data including a word corresponding to a name of the landmark included in the held map data, and sends update area information indicating an area of the map data to be updated and update data on the area indicated by the update area information to the server; the server is configured to: generate, in a case of which recognition data of the area indicated by the update area information sent from the terminal has been changed, after a time indicated by the update data sent from the terminal, difference data between latest recognition data and recognition data corresponding to the area indicated by the update area information at a time indicated by the update data; and send the generated difference data to the terminal along with map data on the area indicated by the update area information; the terminal updates the map data held in the terminal based on the map data sent from the server; and the speech recognition system updates the recognition data managed by the terminal based on the difference data sent from the server; wherein: the recognition data includes confusion information, the confusion information including a confusion word having a tendency to cause a recognition error with the word corresponding to a name of the landmark, and a confusion score which represents the tendency of the confusion word to cause recognition error; the server sends the difference data including the confusion information to the terminal; and the speech recognition system updates the confusion information included in the recognition data held by the terminal based on the confusion information sent from the server. | 1. A speech recognition system installed in a terminal coupled to a server via a network, wherein: the terminal holds map data including a landmark; the speech recognition system manages recognition data including a word corresponding to a name of the landmark included in the held map data, and sends update area information indicating an area of the map data to be updated and update data on the area indicated by the update area information to the server; the server is configured to: generate, in a case of which recognition data of the area indicated by the update area information sent from the terminal has been changed, after a time indicated by the update data sent from the terminal, difference data between latest recognition data and recognition data corresponding to the area indicated by the update area information at a time indicated by the update data; and send the generated difference data to the terminal along with map data on the area indicated by the update area information; the terminal updates the map data held in the terminal based on the map data sent from the server; and the speech recognition system updates the recognition data managed by the terminal based on the difference data sent from the server; wherein: the recognition data includes confusion information, the confusion information including a confusion word having a tendency to cause a recognition error with the word corresponding to a name of the landmark, and a confusion score which represents the tendency of the confusion word to cause recognition error; the server sends the difference data including the confusion information to the terminal; and the speech recognition system updates the confusion information included in the recognition data held by the terminal based on the confusion information sent from the server. 2. The speech recognition system according to claim 1 , wherein, in a case of which a word included in the confusion information sent from the server is included in confusion information for a different area, the speech recognition system is configured to update confusion information for the different area which corresponds to the word. | 0.638116 |
8,223,153 | 9 | 11 | 9. An animation authoring method for use with an animation authoring apparatus, the method comprising: displaying a storyboard editing display to edit a storyboard, wherein the storyboard comprises scene information, a screen shot for each cut, a screenplay, and a directing adjustment window to enable a user to adjust a directing value for a line or edited object of the storyboard editing display, all being displayed on the storyboard at the same time; converting parsed syntax of a storyboard edited by a user using the storyboard editing display, into a graphic animation in real time; outputting the graphic animation; and storing a storyboard corresponding to the graphic animation. | 9. An animation authoring method for use with an animation authoring apparatus, the method comprising: displaying a storyboard editing display to edit a storyboard, wherein the storyboard comprises scene information, a screen shot for each cut, a screenplay, and a directing adjustment window to enable a user to adjust a directing value for a line or edited object of the storyboard editing display, all being displayed on the storyboard at the same time; converting parsed syntax of a storyboard edited by a user using the storyboard editing display, into a graphic animation in real time; outputting the graphic animation; and storing a storyboard corresponding to the graphic animation. 11. The method of claim 9 , wherein the storyboard editing display comprises an interface to receive at least one of a text input and a graphic input from the user and to edit the storyboard according to the at least one of the text input and the graphic input. | 0.580386 |
8,897,151 | 11 | 12 | 11. The method of claim 8 wherein transforming the extraction specification further comprises identifying production rules from the extraction specification having nonterminals as either normal or non-normal; replacing each of the production rules identified as normal with a regular rule using decomposition methods; approximating a regular rule for each of the production rules identified as non-normal; and concatenating the regular rules to form a regular grammar. | 11. The method of claim 8 wherein transforming the extraction specification further comprises identifying production rules from the extraction specification having nonterminals as either normal or non-normal; replacing each of the production rules identified as normal with a regular rule using decomposition methods; approximating a regular rule for each of the production rules identified as non-normal; and concatenating the regular rules to form a regular grammar. 12. The method of claim 11 wherein identifying production rules further comprises classifying a production rule as normal when the production rule is regular or, for production rules having a given nonterminal, X, as its head, the given nonterminal is a last symbol in a body of the production rule and, for every nonterminal, Y, that is reachable from the given nonterminal, Y is normal and the given nonterminal, X, is not reachable from Y. | 0.5 |
8,606,804 | 1 | 5 | 1. A computer-implemented query system, comprising: a server including memory and a processing unit for executing computer-executable components, the memory storing computer-executable components including: a programming model for providing a web service that supports defining a concrete custom query builder subclass derived from a query builder base class included in the programming model and defining a concrete arguments class that extends an arguments base class included in the programming model, wherein: the query builder base class is configured to use query parameters of the arguments base class to create queries; the concrete arguments class includes one or more custom query parameters specific to the concrete custom query builder subclass; the concrete custom query builder subclass is configured to dynamically create a custom query at runtime using parameter values of the one or more custom query parameters which are to be bound to the concrete custom query builder subclass at runtime; the concrete custom query builder subclass uses the custom query to dynamically create a query run at runtime, wherein the query run is configured to execute the custom query for returning query results based on the one or more custom query parameters; and the query builder base class includes a method for initializing an instance of the custom query builder subclass at runtime and a method for retrieving the query run created by the concrete query builder subclass; and a query service for providing an interface to expose data access functionality via the query builder base class included in the programming model, wherein the query service is configured to: accept, from a consumer application at runtime, a query request that includes a reference to the concrete custom query builder subclass; invoke the concrete custom query builder subclass to initialize the instance of the concrete custom query builder subclass and retrieve the query run created by the concrete custom query builder subclass; execute the query run created by the concrete custom query builder subclass for retrieving the query results based on the one or more custom query parameters; and return the query results to the consumer application at runtime. | 1. A computer-implemented query system, comprising: a server including memory and a processing unit for executing computer-executable components, the memory storing computer-executable components including: a programming model for providing a web service that supports defining a concrete custom query builder subclass derived from a query builder base class included in the programming model and defining a concrete arguments class that extends an arguments base class included in the programming model, wherein: the query builder base class is configured to use query parameters of the arguments base class to create queries; the concrete arguments class includes one or more custom query parameters specific to the concrete custom query builder subclass; the concrete custom query builder subclass is configured to dynamically create a custom query at runtime using parameter values of the one or more custom query parameters which are to be bound to the concrete custom query builder subclass at runtime; the concrete custom query builder subclass uses the custom query to dynamically create a query run at runtime, wherein the query run is configured to execute the custom query for returning query results based on the one or more custom query parameters; and the query builder base class includes a method for initializing an instance of the custom query builder subclass at runtime and a method for retrieving the query run created by the concrete query builder subclass; and a query service for providing an interface to expose data access functionality via the query builder base class included in the programming model, wherein the query service is configured to: accept, from a consumer application at runtime, a query request that includes a reference to the concrete custom query builder subclass; invoke the concrete custom query builder subclass to initialize the instance of the concrete custom query builder subclass and retrieve the query run created by the concrete custom query builder subclass; execute the query run created by the concrete custom query builder subclass for retrieving the query results based on the one or more custom query parameters; and return the query results to the consumer application at runtime. 5. The system of claim 1 , wherein the query builder base class further includes: a method that returns an initialized query object to the query service at runtime. | 0.753754 |
6,064,958 | 19 | 26 | 19. An article of manufacture, comprising: a computer usable medium having computer readable program code means embodied therein for causing a computer to function as a pattern recognition system, the computer readable program code means including: first computer readable program code means for causing said computer to calculate a probability of each probabilistic model expressing features of each recognition category with respect to each input feature vector derived from each input signal, wherein the probabilistic model represents a feature parameter subspace in which feature vectors of each recognition category exist and the feature parameter subspace is expressed by using mixture distributions of one-dimensional discrete distributions with arbitrary distribution shapes which are arranged in respective dimensions; and second computer readable program code means for causing said computer to output a recognition category expressed by a probabilistic model with a highest probability among a plurality of probabilistic models as a recognition result. | 19. An article of manufacture, comprising: a computer usable medium having computer readable program code means embodied therein for causing a computer to function as a pattern recognition system, the computer readable program code means including: first computer readable program code means for causing said computer to calculate a probability of each probabilistic model expressing features of each recognition category with respect to each input feature vector derived from each input signal, wherein the probabilistic model represents a feature parameter subspace in which feature vectors of each recognition category exist and the feature parameter subspace is expressed by using mixture distributions of one-dimensional discrete distributions with arbitrary distribution shapes which are arranged in respective dimensions; and second computer readable program code means for causing said computer to output a recognition category expressed by a probabilistic model with a highest probability among a plurality of probabilistic models as a recognition result. 26. The article of manufacture of claim 19, further comprising: a third computer readable program code means for causing said computer to estimate parameters of the discrete distributions from training data, by first training a continuous distribution type model with a number of mixture component distributions greater than a desired number of distributions to be mixed in the mixture distribution, then merging continuous distributions of the continuous distribution type model until a number of mixture component distributions becomes equal to the desired number of distributions, and then training a probabilistic model obtained by discretizing each continuous distribution of the continuous distribution type model after merging as an initial model. | 0.61687 |
9,171,072 | 4 | 8 | 4. A computer implemented method for validating a document classification process for eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions, the method comprising: providing a document collection of N documents related to eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions; performing a document classification process on the document collection; automatically generating with a random selection module a random validation set S of documents based on a user selectable percentage P of the N documents from the document collection; and performing a manual document review process on the random validation set of documents to validate overall results of all of the documents classified by the document classification process; and dynamically and in real-time measuring and displaying on a computer display device a best case estimate of a quality of the results of the overall document classification process based on the documents that are validated, given the size N of a total data set of the document collection, and based on a predetermined quality threshold for an overall classification quality desired for the document classification process. | 4. A computer implemented method for validating a document classification process for eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions, the method comprising: providing a document collection of N documents related to eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions; performing a document classification process on the document collection; automatically generating with a random selection module a random validation set S of documents based on a user selectable percentage P of the N documents from the document collection; and performing a manual document review process on the random validation set of documents to validate overall results of all of the documents classified by the document classification process; and dynamically and in real-time measuring and displaying on a computer display device a best case estimate of a quality of the results of the overall document classification process based on the documents that are validated, given the size N of a total data set of the document collection, and based on a predetermined quality threshold for an overall classification quality desired for the document classification process. 8. The computer program product of claim 4 , further comprising allowing a user to monitor the best case estimate of the overall classification quality and terminate the document review process and change parameters and/or instruction for the document classification process based on the best case estimate of the overall classification quality being equal to or lower than the predetermined quality threshold of the documents in the random selected document set. | 0.5 |
6,108,632 | 3 | 4 | 3. Apparatus as in claim 1 which further comprises: a confirmatory output device coupled to said parameter output, to generate a confirmatory indication, recognizable by a said human transaction operator, of values of said parameters thus recognized. | 3. Apparatus as in claim 1 which further comprises: a confirmatory output device coupled to said parameter output, to generate a confirmatory indication, recognizable by a said human transaction operator, of values of said parameters thus recognized. 4. Apparatus as in claim 3, which further comprises: a confirmation input means for receiving, from said human transaction operator, a signal accepting or rejecting said confirmatory indication. | 0.557078 |
7,925,995 | 2 | 8 | 2. A method of operating a GPS-enabled wireless device, the method comprising: computing location coordinates of a user using the GPS-enabled wireless device; predicting a future activity of the user based on user context at the location coordinates; determining a direction in which the wireless device is pointed by the user; receiving user input determining dimensions of a field of view to query; generating the field of view including the direction; searching websites disposed on a network using a search query to identify businesses within the field of view related to the predicted future activity, the search query being based at least on the location coordinates and coordinates for the field of view; retrieving a list of links to websites of businesses that satisfy the search query; querying the websites on the list of links to find information associated with the businesses an associated business; inferring business information obtained from the querying of the websites that is of interest to the user based upon historical data associated with the user and user preferences; and presenting the inferred business information to the user. | 2. A method of operating a GPS-enabled wireless device, the method comprising: computing location coordinates of a user using the GPS-enabled wireless device; predicting a future activity of the user based on user context at the location coordinates; determining a direction in which the wireless device is pointed by the user; receiving user input determining dimensions of a field of view to query; generating the field of view including the direction; searching websites disposed on a network using a search query to identify businesses within the field of view related to the predicted future activity, the search query being based at least on the location coordinates and coordinates for the field of view; retrieving a list of links to websites of businesses that satisfy the search query; querying the websites on the list of links to find information associated with the businesses an associated business; inferring business information obtained from the querying of the websites that is of interest to the user based upon historical data associated with the user and user preferences; and presenting the inferred business information to the user. 8. The method of claim 2 , wherein the context data comprises a time since an activity of the same type as the predicted future activity was carried out. | 0.754808 |
7,831,534 | 27 | 29 | 27. A computer-implemented method for building a polyhierarchical classification of objects, comprising: a) identifying a plurality of criteria for specializing selected properties of the objects, wherein each criterion of the plurality of criteria is defined by a set of mutually exclusive attributes, wherein each attribute describes one or more properties of the objects; b) recurrently assigning to each criterion of the plurality of criteria an attributive expression that is either empty or represents a logical expression comprising one or more attributes of other criteria in the plurality of criteria whose attributive expressions have already been defined; wherein each non-empty attributive expression assigned to a criterion does not participate in its own definition; and c) storing in a computer-readable medium the plurality of criteria and their associated attributive expressions. | 27. A computer-implemented method for building a polyhierarchical classification of objects, comprising: a) identifying a plurality of criteria for specializing selected properties of the objects, wherein each criterion of the plurality of criteria is defined by a set of mutually exclusive attributes, wherein each attribute describes one or more properties of the objects; b) recurrently assigning to each criterion of the plurality of criteria an attributive expression that is either empty or represents a logical expression comprising one or more attributes of other criteria in the plurality of criteria whose attributive expressions have already been defined; wherein each non-empty attributive expression assigned to a criterion does not participate in its own definition; and c) storing in a computer-readable medium the plurality of criteria and their associated attributive expressions. 29. The method of claim 27 , further comprising: a) identifying a specific object; b) specializing properties of the object by selecting attributes of the stored plurality of criteria, wherein only attributes of applicable criterion may be selected; and c) composing the selected attributes into an attributive expression. | 0.5 |
8,826,338 | 11 | 19 | 11. A system for providing media assets in multiple languages comprising: control circuitry configured to: receive a first user selection of a language for interacting with an interactive media guidance application; transmit media guidance data associated with the selected language to a user device; receive a second user selection of a media asset, wherein the media asset has a plurality of associated tracks having content in at least two different languages, wherein each track is associated with a single language, and wherein the first and the second user selections are separate selections; in response to the second user selection, transmit only a track associated with the selected language to the user device. | 11. A system for providing media assets in multiple languages comprising: control circuitry configured to: receive a first user selection of a language for interacting with an interactive media guidance application; transmit media guidance data associated with the selected language to a user device; receive a second user selection of a media asset, wherein the media asset has a plurality of associated tracks having content in at least two different languages, wherein each track is associated with a single language, and wherein the first and the second user selections are separate selections; in response to the second user selection, transmit only a track associated with the selected language to the user device. 19. The system of claim 11 , wherein tracks in languages other than the selected language have been removed prior to transmission to the user device. | 0.780236 |
8,726,256 | 22 | 24 | 22. The computer of claim 21 , wherein the software causes the processor to control the in-degree and out-degree by trading off in-transitions for out-transitions in the automaton. | 22. The computer of claim 21 , wherein the software causes the processor to control the in-degree and out-degree by trading off in-transitions for out-transitions in the automaton. 24. The computer of claim 22 , wherein the in-degree is limited to a ratio of the out-degree. | 0.636719 |
8,799,244 | 6 | 15 | 6. A non-transitory computer readable medium storing computer executable instructions that when executed by a computer control the computer to perform a method, the method comprising: upon determining that a first de-duplication logic and a second de-duplication logic are to participate in a shared de-duplication action for an object, controlling the first de-duplication logic to establish a shared parse scope with the second de-duplication logic, by: controlling the first de-duplication logic to provide dialect data to the second de-duplication logic, and receiving feedback data from the second de-duplication logic, the feedback data being produced in response to the dialect data, the dialect data comprising one or more of, a rule, a hash of a rule, a rule identifier, a plurality of rules, a hash of the plurality of rules, and a plurality of rule identifiers, where the rule comprises one or more of: first information about a context associated with an object to be de-duplicated, second information identifying a previously negotiated shared parse scope associated with an object, third information identifying how an object is to be parsed; fourth information identifying an action to be performed after an object is parsed; fifth information identifying one or more of, a delta hash function, and a delta storage schema for an object; and sixth information identifying balancing rules for balancing performance and reduction; where the feedback data comprising one or more of: an acceptance notification that identifies that the second de-duplication logic is aware of the dialect identified by the dialect data and agrees to use the dialect identified by the dialect data, an update notification that identifies that the second de-duplication logic was not aware of the dialect identified by the dialect data, that the second de-duplication logic agrees to use the dialect identified by the dialect data, and that the second de-duplication logic has been updated as a function of receiving the dialect data, a counteroffer notification comprising an alternative dialect data, where the alternative dialect data comprises one or more of, a rule, a hash of a rule, a rule identifier, a plurality of rules, a hash of the plurality of rules, and a plurality of rule identifiers, where the alternative dialect data is associated with an alternate dialect in use by the second de-duplication logic, a request notification that identifies a hash of an item in the dialect for which a corresponding actual item is requested by the second de-duplication logic, and an acknowledgement notification that identifies that the second de-duplication logic will participate in the shared de-duplication action as controlled by a persisted parse scope previously negotiated for the object and persisting the shared parse scope. | 6. A non-transitory computer readable medium storing computer executable instructions that when executed by a computer control the computer to perform a method, the method comprising: upon determining that a first de-duplication logic and a second de-duplication logic are to participate in a shared de-duplication action for an object, controlling the first de-duplication logic to establish a shared parse scope with the second de-duplication logic, by: controlling the first de-duplication logic to provide dialect data to the second de-duplication logic, and receiving feedback data from the second de-duplication logic, the feedback data being produced in response to the dialect data, the dialect data comprising one or more of, a rule, a hash of a rule, a rule identifier, a plurality of rules, a hash of the plurality of rules, and a plurality of rule identifiers, where the rule comprises one or more of: first information about a context associated with an object to be de-duplicated, second information identifying a previously negotiated shared parse scope associated with an object, third information identifying how an object is to be parsed; fourth information identifying an action to be performed after an object is parsed; fifth information identifying one or more of, a delta hash function, and a delta storage schema for an object; and sixth information identifying balancing rules for balancing performance and reduction; where the feedback data comprising one or more of: an acceptance notification that identifies that the second de-duplication logic is aware of the dialect identified by the dialect data and agrees to use the dialect identified by the dialect data, an update notification that identifies that the second de-duplication logic was not aware of the dialect identified by the dialect data, that the second de-duplication logic agrees to use the dialect identified by the dialect data, and that the second de-duplication logic has been updated as a function of receiving the dialect data, a counteroffer notification comprising an alternative dialect data, where the alternative dialect data comprises one or more of, a rule, a hash of a rule, a rule identifier, a plurality of rules, a hash of the plurality of rules, and a plurality of rule identifiers, where the alternative dialect data is associated with an alternate dialect in use by the second de-duplication logic, a request notification that identifies a hash of an item in the dialect for which a corresponding actual item is requested by the second de-duplication logic, and an acknowledgement notification that identifies that the second de-duplication logic will participate in the shared de-duplication action as controlled by a persisted parse scope previously negotiated for the object and persisting the shared parse scope. 15. The computer readable medium of claim 6 , where the fourth information comprises one or more of, information concerning compressing a reduced object, information concerning encrypting a reduced object, information concerning verifying the existence of an object, and information concerning transmitting an object. | 0.882331 |
8,645,913 | 14 | 16 | 14. A computer-implemented method comprising: discovering, by a computer, using a registry of discoverable web services, an existing web service that provides web service functionality; receiving, by the computer, a Web Service Description Language (WSDL) file describing the web service; looping over all data type definitions in order to determine, by the computer, at least one data type included in the WSDL file; creating and storing a proxy data type corresponding to the at least one data type; extracting, by the computer, at least one interface operation from the WSDL file, the at least one interface operation including at least one message sent during implementation of the at least one interface operation, the at least one message using the at least one data type; and generating, by the computer, a business object based on the WSDL file, the business object including the at least one data type and the at least one interface operation, the business object configured to expose the web service functionality in an integrated manner within a business object based application environment, the generating including: converting the at least one data type to a format consistent with the business object based application environment, creating at least one business object node of the business object that corresponds to each interface operation of the WSDL file, the at least one business object node being based on the at least one message, and creating a node action for the at least one business object node, the node action corresponding to the at least one interface operation. | 14. A computer-implemented method comprising: discovering, by a computer, using a registry of discoverable web services, an existing web service that provides web service functionality; receiving, by the computer, a Web Service Description Language (WSDL) file describing the web service; looping over all data type definitions in order to determine, by the computer, at least one data type included in the WSDL file; creating and storing a proxy data type corresponding to the at least one data type; extracting, by the computer, at least one interface operation from the WSDL file, the at least one interface operation including at least one message sent during implementation of the at least one interface operation, the at least one message using the at least one data type; and generating, by the computer, a business object based on the WSDL file, the business object including the at least one data type and the at least one interface operation, the business object configured to expose the web service functionality in an integrated manner within a business object based application environment, the generating including: converting the at least one data type to a format consistent with the business object based application environment, creating at least one business object node of the business object that corresponds to each interface operation of the WSDL file, the at least one business object node being based on the at least one message, and creating a node action for the at least one business object node, the node action corresponding to the at least one interface operation. 16. The method of claim 14 wherein a parent node of the at least one business object node is a root node of the generated business object. | 0.591716 |
9,451,335 | 1 | 10 | 1. A device, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: scanning a plurality of images from a media content item to detect a plurality of visual features present within the plurality of images; analyzing interactions between the plurality of visual features to determine a plurality of visual events that are depicted in the media content item; generating a plurality of narrative descriptions corresponding to the plurality of visual features and the plurality of visual events, wherein the plurality of narrative descriptions are associated with a plurality of time stamps of the media content item; determining visual capabilities of a user for viewing the media content item; filtering the plurality of narrative descriptions according to requirements of an application and according to the visual capabilities of the user of the media content item to generate a plurality of filtered descriptions; presenting the media content item and a first portion of the plurality of filtered descriptions via the application; determining if a feature in the plurality of narrative descriptions has been provided in the first portion of the filtered description; and presenting a shortened description of the feature in a second portion of the filtered description responsive to determining that the feature has been provided in the first portion, wherein the shortened description occupies a smaller memory space than a non-shortened description of the feature provided in the first portion of the filtered description. | 1. A device, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: scanning a plurality of images from a media content item to detect a plurality of visual features present within the plurality of images; analyzing interactions between the plurality of visual features to determine a plurality of visual events that are depicted in the media content item; generating a plurality of narrative descriptions corresponding to the plurality of visual features and the plurality of visual events, wherein the plurality of narrative descriptions are associated with a plurality of time stamps of the media content item; determining visual capabilities of a user for viewing the media content item; filtering the plurality of narrative descriptions according to requirements of an application and according to the visual capabilities of the user of the media content item to generate a plurality of filtered descriptions; presenting the media content item and a first portion of the plurality of filtered descriptions via the application; determining if a feature in the plurality of narrative descriptions has been provided in the first portion of the filtered description; and presenting a shortened description of the feature in a second portion of the filtered description responsive to determining that the feature has been provided in the first portion, wherein the shortened description occupies a smaller memory space than a non-shortened description of the feature provided in the first portion of the filtered description. 10. The device of claim 1 , wherein the operations further comprise generating a graphical representation of a portion of the plurality of narrative descriptions. | 0.821586 |
8,335,381 | 1 | 11 | 1. A method comprising: receiving a query string; generating a plurality of computer-generated image based on the query string, each of the plurality of computer-generated images being generated in a different one of a set of selected fonts, the set of fonts having been identified based on a precision of the set of fonts for retrieving word images which match at least one selected query string; training a model based on the computer generated images; scoring candidate handwritten word images of a collection of handwritten word images using the trained model; and based on the scores, identifying a subset of the word images. | 1. A method comprising: receiving a query string; generating a plurality of computer-generated image based on the query string, each of the plurality of computer-generated images being generated in a different one of a set of selected fonts, the set of fonts having been identified based on a precision of the set of fonts for retrieving word images which match at least one selected query string; training a model based on the computer generated images; scoring candidate handwritten word images of a collection of handwritten word images using the trained model; and based on the scores, identifying a subset of the word images. 11. The method of claim 1 , wherein: the generating of the at least one computer-generated image based on the query string includes, for each of a set of fonts, automatically generating an image based on the query string; the training a model based on the at least one computer generated image includes modeling the query string with a semi-continuous hidden Markov model, a subset of the parameters of the semi-continuous hidden Markov model being estimated based on features extracted from the images in the different fonts, and other parameters of the semi-continuous hidden Markov model being previously trained on sample handwritten word images without consideration of the query string; the scoring of the candidate handwritten word images includes scoring candidate handwritten word images of the collection against the trained semi-continuous hidden Markov model; and the identifying of the subset of the word images based on the scores includes labeling one or more of the candidate handwritten word images, or a document containing one or more of the candidate handwritten word images. | 0.5 |
8,712,188 | 12 | 14 | 12. A document orientation detection system comprising: an imaging mechanism to capture a document image; a processor to detect document orientation of the captured document image; and one or more instruction modules, executable on the processor to binarize subimages of the document, to determine a plurality of values including a text-asymmetry ratio from strip-based projection profiles of the captured document image, the strip-based projection profiles being non-square and located within a bounding box, to detect portrait or landscape document orientation based on the values other than the text-asymmetry ratio, and to detect up or down text orientation based on the text-asymmetry ratio, wherein the portrait or landscape orientation is detected based on the values other than the text-asymmetry ratio in that the text-asymmetry ratio is not used to determine the portrait or landscape orientation. | 12. A document orientation detection system comprising: an imaging mechanism to capture a document image; a processor to detect document orientation of the captured document image; and one or more instruction modules, executable on the processor to binarize subimages of the document, to determine a plurality of values including a text-asymmetry ratio from strip-based projection profiles of the captured document image, the strip-based projection profiles being non-square and located within a bounding box, to detect portrait or landscape document orientation based on the values other than the text-asymmetry ratio, and to detect up or down text orientation based on the text-asymmetry ratio, wherein the portrait or landscape orientation is detected based on the values other than the text-asymmetry ratio in that the text-asymmetry ratio is not used to determine the portrait or landscape orientation. 14. A document orientation detection system as in claim 12 , further comprising: an image capture device comprising the imaging mechanism; and a remote image processing device comprising the processor and the one or more instruction modules. | 0.5 |
8,548,791 | 1 | 10 | 1. A method of determining consistency of training data for a machine translation system, comprising: receiving a signal indicative of a source language corpus and a target language corpus; extracting a textual string from the source language corpus; aligning the source language corpus with the target language corpus to identify a plurality of translations for the textual string from the target language corpus; utilizing a processor that is a component of a computing device to calculate a consistency index for each of the plurality of translations, the consistency index for each of the plurality of translations being based at least in part on a number of products in which the translation appears, a frequency of the translation in each of the products, and a total number of valid translations of the textual string in the products; calculating an overall consistency index for the plurality of translations; and storing indications of the consistency indexes and the overall consistency index onto a tangible medium. | 1. A method of determining consistency of training data for a machine translation system, comprising: receiving a signal indicative of a source language corpus and a target language corpus; extracting a textual string from the source language corpus; aligning the source language corpus with the target language corpus to identify a plurality of translations for the textual string from the target language corpus; utilizing a processor that is a component of a computing device to calculate a consistency index for each of the plurality of translations, the consistency index for each of the plurality of translations being based at least in part on a number of products in which the translation appears, a frequency of the translation in each of the products, and a total number of valid translations of the textual string in the products; calculating an overall consistency index for the plurality of translations; and storing indications of the consistency indexes and the overall consistency index onto a tangible medium. 10. The method of claim 1 , wherein the products include a number of different software products. | 0.781532 |
9,858,528 | 1 | 9 | 1. A method programmed in a non-transitory memory of a device comprising: a. parsing target information into segments and prioritizing the segments, so that a highest priority segment is fact checked first, wherein priority is based on a relatedness of a segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue, wherein a plurality of fact check queues are implemented, wherein a first fact check queue contains the segments to be fact checked in real-time, and a second fact check queue contains the segments to be fact checked in non-real-time; b. automatically fact checking the target information by comparing the target information with source information to generate a result; and c. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein comparing the target information with the source information begins searching the source information located on a fastest access time hardware device and continues to slower access time hardware devices. | 1. A method programmed in a non-transitory memory of a device comprising: a. parsing target information into segments and prioritizing the segments, so that a highest priority segment is fact checked first, wherein priority is based on a relatedness of a segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue, wherein a plurality of fact check queues are implemented, wherein a first fact check queue contains the segments to be fact checked in real-time, and a second fact check queue contains the segments to be fact checked in non-real-time; b. automatically fact checking the target information by comparing the target information with source information to generate a result; and c. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein comparing the target information with the source information begins searching the source information located on a fastest access time hardware device and continues to slower access time hardware devices. 9. The method of claim 1 further comprising only fact checking randomly selected segments. | 0.956772 |
8,688,448 | 1 | 2 | 1. A system comprising at least one processor programmed to: segment an unstructured text into a plurality of text sections; identify a portion of text that fully or partially identifies a section heading for a first text section of the plurality of text sections; remove, from the first text section, the portion of text that fully or partially identifies the section heading; create a structured text comprising the first text section and the section heading for the first text section, wherein the portion of text that fully or partially identifies the section heading has been removed from the first text section; and provide the structured text to a user. | 1. A system comprising at least one processor programmed to: segment an unstructured text into a plurality of text sections; identify a portion of text that fully or partially identifies a section heading for a first text section of the plurality of text sections; remove, from the first text section, the portion of text that fully or partially identifies the section heading; create a structured text comprising the first text section and the section heading for the first text section, wherein the portion of text that fully or partially identifies the section heading has been removed from the first text section; and provide the structured text to a user. 2. The system of claim 1 , wherein the section heading is a first section heading, and wherein the at least one processor is further programmed to: provide to the user a plurality of alternative section headings for the first text section. | 0.755123 |
9,423,908 | 8 | 10 | 8. An information handling system comprising: one or more processors; a touch-screen accessible by at least one of the processors; a memory coupled to at least one of the processors; and a set of instructions stored in the memory and executed by at least one of the processors to: receive one or more user inputs at a touch-screen of a device, wherein each user input includes a set of one or more input properties; identify, based on the input properties, an intended input type from a plurality of input types that includes a handwriting type and a gesture type, wherein the intended input type is identified based on previous intended input types associated with previously received user inputs; generate system inputs of the identified intended input type based on the received user inputs; and input the generated system inputs to the processors. | 8. An information handling system comprising: one or more processors; a touch-screen accessible by at least one of the processors; a memory coupled to at least one of the processors; and a set of instructions stored in the memory and executed by at least one of the processors to: receive one or more user inputs at a touch-screen of a device, wherein each user input includes a set of one or more input properties; identify, based on the input properties, an intended input type from a plurality of input types that includes a handwriting type and a gesture type, wherein the intended input type is identified based on previous intended input types associated with previously received user inputs; generate system inputs of the identified intended input type based on the received user inputs; and input the generated system inputs to the processors. 10. The information handling system of claim 8 where the set of instructions further comprise instructions to: identify an amount of time during which the one or more user inputs were received at the touch screen, wherein the one or more user inputs included a plurality of user inputs; and weight the intended input type based on the amount of time. | 0.77707 |
9,426,463 | 6 | 7 | 6. A video encoding device comprising: a data storage medium configured to store decoded reference pictures; and one or more processors configured to: generate a motion vector (MV) candidate list for a prediction unit (PU) of a coding unit (CU) in a B slice; after generating the MV candidate list, determine a selected MV candidate in the MV candidate list; after determining the selected MV candidate, convert the selected MV candidate from a bi-directional MV candidate into a uni-directional MV candidate; after converting the selected MV candidate into the uni-directional MV candidate, assign the uni-directional MV candidate to the PU; and generate a predictive video block for the PU based at least in part on one or more reference blocks of the decoded reference pictures, the one or more reference blocks indicated by motion information specified by the selected MV candidate; use the uni-directional MV candidate assigned to the PU for merge candidate list construction or advanced motion vector prediction (AMVP) candidate list construction for a next block in coding order; and output encoded video data based at least in part on the predictive video block. | 6. A video encoding device comprising: a data storage medium configured to store decoded reference pictures; and one or more processors configured to: generate a motion vector (MV) candidate list for a prediction unit (PU) of a coding unit (CU) in a B slice; after generating the MV candidate list, determine a selected MV candidate in the MV candidate list; after determining the selected MV candidate, convert the selected MV candidate from a bi-directional MV candidate into a uni-directional MV candidate; after converting the selected MV candidate into the uni-directional MV candidate, assign the uni-directional MV candidate to the PU; and generate a predictive video block for the PU based at least in part on one or more reference blocks of the decoded reference pictures, the one or more reference blocks indicated by motion information specified by the selected MV candidate; use the uni-directional MV candidate assigned to the PU for merge candidate list construction or advanced motion vector prediction (AMVP) candidate list construction for a next block in coding order; and output encoded video data based at least in part on the predictive video block. 7. The video encoding device of claim 6 , wherein the one or more processors are configured to convert, in response to determining that the CU has a size equal to a smallest coding unit (SCU) size, the selected MV candidate into the uni-directional MV candidate. | 0.852974 |
8,332,909 | 1 | 4 | 1. One or more computer-readable storage media comprising computer-executable instructions for generating software restriction policy rules, the computer-executable instructions directed to steps comprising: receiving a user's specification of preferred types of software restriction policy rules that are preferred by the user; receiving the user's specification of a metadata source; determining a software restriction policy rule for each entry in the metadata source in accordance with the specified preferred types of software restriction policy rules; determining if the software restriction policy rule is duplicative of a previously generated software restriction policy rule; determining if the software restriction policy rule is an exception to the previously generated software restriction policy rule; generating the software restriction policy rule determining reveals that the software restriction policy rule is neither duplicative of the previously generated software restriction policy rule nor is the exception to the previously generated software restriction policy rule; and generating the exception to the previously generated software restriction policy rule instead of generating software restriction policy rule if the determining reveals that the software restriction policy rule is not duplicative of the previously generated software restriction policy rule but is the exception to the previously generated software restriction policy rule. | 1. One or more computer-readable storage media comprising computer-executable instructions for generating software restriction policy rules, the computer-executable instructions directed to steps comprising: receiving a user's specification of preferred types of software restriction policy rules that are preferred by the user; receiving the user's specification of a metadata source; determining a software restriction policy rule for each entry in the metadata source in accordance with the specified preferred types of software restriction policy rules; determining if the software restriction policy rule is duplicative of a previously generated software restriction policy rule; determining if the software restriction policy rule is an exception to the previously generated software restriction policy rule; generating the software restriction policy rule determining reveals that the software restriction policy rule is neither duplicative of the previously generated software restriction policy rule nor is the exception to the previously generated software restriction policy rule; and generating the exception to the previously generated software restriction policy rule instead of generating software restriction policy rule if the determining reveals that the software restriction policy rule is not duplicative of the previously generated software restriction policy rule but is the exception to the previously generated software restriction policy rule. 4. The computer-readable storage media of claim 1 , wherein the received user's specification of preferred types of software restriction policy rules that are preferred by the user specifies at least one of: a publisher-based rule, a hash-based rule, and a path-based rule. | 0.833942 |
9,819,759 | 16 | 22 | 16. A computer system comprising: a processor; a memory comprising computer code executed using the processor, in which the computer code implements: a computing platform to: identify a first social site, the first social site having a first access interface comprising a first application programming interface (API) specific to the first social sites identifying a social event corresponding to a post on the first social site or a message on the first social site at the first social site, the social event corresponding to a first event type; sharing the social event from the first social site to a second social site by implementing an integration platform located separate from social sites, the sharing comprising the steps of: (1) receiving the social event from the first social site; (2) Identifying the second social site associated with a user that created the social event at the first social site, the second social site identified on a basis of having a supported event type that corresponds to the first event type associated with the social event, the second social site having a second access interface, that comprises a second API specific to the second social site and different from the first access interface; and (3) modifying the social event into a modified social event of the supported event type for the second social site; and sending the modified social event of the supported event type to the second social site through the second access interface having the second API specific to the second social site; creating the social event on the first social site by interacting with an application, wherein creation of the social event results in sending the social event to the first social site over a request path, the first social site responding to the social event with an acknowledgement that the first social site processed the social event; perform security processing on the social event; classifying the social event into at least one classification; performing mapping to standardize a set of common social networking concepts, wherein a mapping function comprises: receiving the social event from the first social site; determining semantics in the social event from the first social site, and mapping the social event from the first social site to a second social event on a second social event; contacting a network interface to broadcast the modified social event to additional sites, wherein the integration platform is configured by configuration data, wherein the configuration data comprises user preferences, wherein the modifying the social event into a modified social event further comprises at least one of modifying a header, modifying a destination address, modifying a source address, modifying a format, or modifying a message content. | 16. A computer system comprising: a processor; a memory comprising computer code executed using the processor, in which the computer code implements: a computing platform to: identify a first social site, the first social site having a first access interface comprising a first application programming interface (API) specific to the first social sites identifying a social event corresponding to a post on the first social site or a message on the first social site at the first social site, the social event corresponding to a first event type; sharing the social event from the first social site to a second social site by implementing an integration platform located separate from social sites, the sharing comprising the steps of: (1) receiving the social event from the first social site; (2) Identifying the second social site associated with a user that created the social event at the first social site, the second social site identified on a basis of having a supported event type that corresponds to the first event type associated with the social event, the second social site having a second access interface, that comprises a second API specific to the second social site and different from the first access interface; and (3) modifying the social event into a modified social event of the supported event type for the second social site; and sending the modified social event of the supported event type to the second social site through the second access interface having the second API specific to the second social site; creating the social event on the first social site by interacting with an application, wherein creation of the social event results in sending the social event to the first social site over a request path, the first social site responding to the social event with an acknowledgement that the first social site processed the social event; perform security processing on the social event; classifying the social event into at least one classification; performing mapping to standardize a set of common social networking concepts, wherein a mapping function comprises: receiving the social event from the first social site; determining semantics in the social event from the first social site, and mapping the social event from the first social site to a second social event on a second social event; contacting a network interface to broadcast the modified social event to additional sites, wherein the integration platform is configured by configuration data, wherein the configuration data comprises user preferences, wherein the modifying the social event into a modified social event further comprises at least one of modifying a header, modifying a destination address, modifying a source address, modifying a format, or modifying a message content. 22. The computer system of claim 16 , further comprising broadcasting the modified social event to an additional social site. | 0.630178 |
7,650,286 | 110 | 124 | 110. A system for using a computer to identify a matching resume for a job description, comprising: means for receiving the job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; means for storing the job description; means for receiving at least one resume; means for parsing each said at least one resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein said at least one skill or experience-related phrase includes the required skill or experience-related phrase for at least one of said at least one job requirement, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; means for storing each said at least one resume; means for computing, for each said at least one resume, a term of experience for the required skill or experience-related phrase for each said at least one job requirement; and means for determining whether each said at least one resume is the matching resume that satisfies the job description. | 110. A system for using a computer to identify a matching resume for a job description, comprising: means for receiving the job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; means for storing the job description; means for receiving at least one resume; means for parsing each said at least one resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein said at least one skill or experience-related phrase includes the required skill or experience-related phrase for at least one of said at least one job requirement, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; means for storing each said at least one resume; means for computing, for each said at least one resume, a term of experience for the required skill or experience-related phrase for each said at least one job requirement; and means for determining whether each said at least one resume is the matching resume that satisfies the job description. 124. The system of claim 110 , further comprising: means for displaying the matching resume on a display screen. | 0.843575 |
8,355,179 | 1 | 6 | 1. A printed multi-tonal document with enhanced copy evident distortions security features comprising: a multi-tonal background screen image area including a first set of various size halftone elements and a multi-tonal foreground hidden warning text and/or graphic screen image area including a second set of various size halftone elements, wherein said first set of various size halftone elements are smaller in size than said second set of various size halftone elements, wherein said multi-tonal foreground hidden warning text and/or graphic image area when electronically copied appear different from the background of the copy of said document and wherein each tone of multiple tones produced by a single said background screen and a single said foreground screen are a shade created by one ink color. | 1. A printed multi-tonal document with enhanced copy evident distortions security features comprising: a multi-tonal background screen image area including a first set of various size halftone elements and a multi-tonal foreground hidden warning text and/or graphic screen image area including a second set of various size halftone elements, wherein said first set of various size halftone elements are smaller in size than said second set of various size halftone elements, wherein said multi-tonal foreground hidden warning text and/or graphic image area when electronically copied appear different from the background of the copy of said document and wherein each tone of multiple tones produced by a single said background screen and a single said foreground screen are a shade created by one ink color. 6. The printed multi-tonal document in claim 1 , wherein said second set of various size halftone elements includes dots of varied shapes arranged in a random pattern and having a size ranging from 50 to 200 microns. | 0.708108 |
9,477,653 | 12 | 13 | 12. A non-transitory computer-readable medium having computer-executable instructions that, when executed by a processor, cause the processor to perform a method comprising: responsive to one or more character inputs from a keyboard operatively coupled to the electronic device: displaying the one or more character inputs as text on a display operatively coupled to the electronic device; determining a plurality of suggested character sequences, each suggested character sequence comprising one or more characters; and presenting a first set of suggested character sequences on the display in proximity to the displayed text and above the keyboard, the first set of suggested character sequences comprising at least some of the plurality of suggested character sequences, wherein each suggested character sequence in the first set of suggested character sequences is presented above a different region of the keyboard configured to receive a motion gesture for selecting the suggested character sequence; responsive to one or more sensed user digit positions on the keyboard: for each detected user digit position: identifying a region of the keyboard in which the sensed user digit position is located; and when the identified region of the keyboard is associated with a suggested character sequence of the first set of suggested character sequences, visually indicating the suggested character sequence of the first set of suggested character sequences that is associated with the identified region of the keyboard; and responsive to a sensed motion gesture beginning at a sensed user digit position of the one or more sensed user digit positions position: selecting the suggested character sequence indicated by the sensed user digit position for input to the electronic device. | 12. A non-transitory computer-readable medium having computer-executable instructions that, when executed by a processor, cause the processor to perform a method comprising: responsive to one or more character inputs from a keyboard operatively coupled to the electronic device: displaying the one or more character inputs as text on a display operatively coupled to the electronic device; determining a plurality of suggested character sequences, each suggested character sequence comprising one or more characters; and presenting a first set of suggested character sequences on the display in proximity to the displayed text and above the keyboard, the first set of suggested character sequences comprising at least some of the plurality of suggested character sequences, wherein each suggested character sequence in the first set of suggested character sequences is presented above a different region of the keyboard configured to receive a motion gesture for selecting the suggested character sequence; responsive to one or more sensed user digit positions on the keyboard: for each detected user digit position: identifying a region of the keyboard in which the sensed user digit position is located; and when the identified region of the keyboard is associated with a suggested character sequence of the first set of suggested character sequences, visually indicating the suggested character sequence of the first set of suggested character sequences that is associated with the identified region of the keyboard; and responsive to a sensed motion gesture beginning at a sensed user digit position of the one or more sensed user digit positions position: selecting the suggested character sequence indicated by the sensed user digit position for input to the electronic device. 13. The non-transitory computer-readable medium of claim 12 , wherein the method performed by the processor further comprises: when the identified region of the keyboard is a region not associated with a suggested character sequence of the first set of suggested character sequences: selecting a second set of suggested character sequences from the plurality of suggested character sequences in response to a sensed motion in the identified region; and presenting the second set of suggested character sequences on the display in proximity to the displayed text in place of the first set of suggested character sequences. | 0.64433 |
8,056,128 | 28 | 29 | 28. The method of claim 27 , further comprising: inhibiting access to the suspect document when the suspect document is determined to be untrustworthy. | 28. The method of claim 27 , further comprising: inhibiting access to the suspect document when the suspect document is determined to be untrustworthy. 29. The method of claim 28 , where inhibiting access to the suspect document comprises: denying access to the suspect document when the suspect document is determined to be untrustworthy. | 0.5 |
9,836,784 | 11 | 13 | 11. A non-transitory computer readable medium having stored thereon sequences of instructions including instructions that will cause a processor to perform a method of delivering advertising by an e-commerce website, the method comprising acts of: receiving, by the processor configured to perform functions associated with the e-commerce website, signals from at least one advertiser including a plurality of advertisements, each advertisement having an associated bid from the at least one advertiser to display the advertisement; receiving, from the at least one advertiser, a relevance type assignment for at least one of the plurality of advertisements; creating, within a database, a mapping between each one of the plurality of advertisements and an intent target, the mapping based on the relevance type assignment received from the at least one advertiser; transmitting, by an interface coupled to the processor, web page signals over a communications network to a web browser operated by a client computer, the web page signals configured to operate the web browser to display a web page associated with the e-commerce website; receiving, in real time from a publisher of the e-commerce website, a request to display an advertisement on the web page; receiving, in real time, client activity signals from the client computer over the communications network, the client activity signals corresponding to real time activity of a user operating the web browser to interact with the web page of the e-commerce website; determining, in real time based on the received client activity signals, a context of the user operating the web browser to interact with the web page of the e-commerce website, the determined context representing an intent of the user to locate a product for purchase via the web browser; defining a relation between one or more of the plurality of advertisements and the product based on the mapping; determining, with a hurdle rate engine in the processor, a hurdle rate set by the publisher of the e-commerce website, the hurdle rate being determined based on the intent of the user to locate the product for purchase and identifying a threshold amount to be bid by an advertiser in order to display an advertisement to the user in a portion of the display shown the user on the web page, the threshold amount of the hurdle rate being set by the hurdle rate engine at a level configured to prevent a loss of expected transaction revenue if the advertisement is displayed to the user via the web page; dynamically adjusting, with the hurdle rate engine, the hurdle rate set by the publisher of the e-commerce website responsive to real time updates of the intent of the user; comparing, with a decision engine in the processor configured to perform functions associated with the e-commerce website, the bid of at least one of the plurality of advertisements to the dynamically adjusted hurdle rate; determining, with the decision engine in the processor, based on the act of comparing and the context of the user, whether to display, in the portion of the display shown the user, at least one of the plurality of advertisements having the relation to the product, wherein the act of determining includes an act of dynamically changing the at least one of the plurality of advertisements based on the dynamically adjusted hurdle rate; and transmitting, by the interface coupled to the processor, display signals associated with the at least one of the plurality of advertisements in response to a determination that the dynamically adjusted hurdle rate has been exceeded by the bid from the advertiser to display the at least one of the plurality of advertisements, the display signals configured to operate the web browser to display, in real time, the at least one of the plurality of advertisements in the portion of the display shown the user on the web page associated with the e-commerce website. | 11. A non-transitory computer readable medium having stored thereon sequences of instructions including instructions that will cause a processor to perform a method of delivering advertising by an e-commerce website, the method comprising acts of: receiving, by the processor configured to perform functions associated with the e-commerce website, signals from at least one advertiser including a plurality of advertisements, each advertisement having an associated bid from the at least one advertiser to display the advertisement; receiving, from the at least one advertiser, a relevance type assignment for at least one of the plurality of advertisements; creating, within a database, a mapping between each one of the plurality of advertisements and an intent target, the mapping based on the relevance type assignment received from the at least one advertiser; transmitting, by an interface coupled to the processor, web page signals over a communications network to a web browser operated by a client computer, the web page signals configured to operate the web browser to display a web page associated with the e-commerce website; receiving, in real time from a publisher of the e-commerce website, a request to display an advertisement on the web page; receiving, in real time, client activity signals from the client computer over the communications network, the client activity signals corresponding to real time activity of a user operating the web browser to interact with the web page of the e-commerce website; determining, in real time based on the received client activity signals, a context of the user operating the web browser to interact with the web page of the e-commerce website, the determined context representing an intent of the user to locate a product for purchase via the web browser; defining a relation between one or more of the plurality of advertisements and the product based on the mapping; determining, with a hurdle rate engine in the processor, a hurdle rate set by the publisher of the e-commerce website, the hurdle rate being determined based on the intent of the user to locate the product for purchase and identifying a threshold amount to be bid by an advertiser in order to display an advertisement to the user in a portion of the display shown the user on the web page, the threshold amount of the hurdle rate being set by the hurdle rate engine at a level configured to prevent a loss of expected transaction revenue if the advertisement is displayed to the user via the web page; dynamically adjusting, with the hurdle rate engine, the hurdle rate set by the publisher of the e-commerce website responsive to real time updates of the intent of the user; comparing, with a decision engine in the processor configured to perform functions associated with the e-commerce website, the bid of at least one of the plurality of advertisements to the dynamically adjusted hurdle rate; determining, with the decision engine in the processor, based on the act of comparing and the context of the user, whether to display, in the portion of the display shown the user, at least one of the plurality of advertisements having the relation to the product, wherein the act of determining includes an act of dynamically changing the at least one of the plurality of advertisements based on the dynamically adjusted hurdle rate; and transmitting, by the interface coupled to the processor, display signals associated with the at least one of the plurality of advertisements in response to a determination that the dynamically adjusted hurdle rate has been exceeded by the bid from the advertiser to display the at least one of the plurality of advertisements, the display signals configured to operate the web browser to display, in real time, the at least one of the plurality of advertisements in the portion of the display shown the user on the web page associated with the e-commerce website. 13. The computer readable medium according to claim 11 , wherein the request includes one or more keywords, and wherein determining the intent of the user is based at least on one or more of the one or more keywords. | 0.674699 |
8,473,507 | 11 | 12 | 11. The data processing system of claim 10 , further comprising: means for combining the updated first tokenized search suggestion and the second tokenized search suggestion with a Boolean AND operator if the scope of the updated first tokenized search suggestion is different than the scope of the second tokenized search suggestion. | 11. The data processing system of claim 10 , further comprising: means for combining the updated first tokenized search suggestion and the second tokenized search suggestion with a Boolean AND operator if the scope of the updated first tokenized search suggestion is different than the scope of the second tokenized search suggestion. 12. The data processing system of claim 11 , wherein generating additional search suggestions from a text input is comprises merging suggestions generated by at least one suggestion engine using the text input. | 0.5 |
8,275,620 | 16 | 17 | 16. The computer-readable storage medium device of claim 15 , further comprising receiving an indication that the sound button has been selected. | 16. The computer-readable storage medium device of claim 15 , further comprising receiving an indication that the sound button has been selected. 17. The computer-readable storage medium device of claim 16 , further comprising, in response to the received indication that the sound button has been selected, providing over a speaker a sound corresponding to the image corresponding to the second one of the plurality of suggested spellings for the at least one word. | 0.5 |
9,558,280 | 17 | 21 | 17. An apparatus, comprising: one or more processors, a computer-readable medium coupled to said one or more processors having instructions stored thereon that, when executed by said one or more processors, cause said one or more processors to perform operations comprising: receiving, from a client device operated by a user, a request for a content item; in response to said request, identifying content items available to be sent to said client device; determining one or more designated geographic locations for each of the identified content items; determining one or more contacts of said user, said determined one or more contacts being members of a social network of said user; for each of the identified content items: determining a score for the content item based on a number of tagging actions that were performed by the user's contacts at the determined designated geographic location for the identified content item, wherein said tagging actions mark an association of a person with a particular geographic location; selecting, from the identified content items, a particular content item to be sent to the client device based on the scores; determining that a timestamp associated with at least one of the tagging actions performed at the designated geographic location for the particular content item is within a time period specified by a provider of the particular content item, the timestamp indicating a time of the tagging action; constructing, based on the determination that the timestamp is within the time period, an annotation that identifies at least one of the user's contacts with the tagging action corresponding to the designated geographic location and indicates the time of the tagging action based on the timestamp associated with the at least one location record; and sending said annotation to said client device. | 17. An apparatus, comprising: one or more processors, a computer-readable medium coupled to said one or more processors having instructions stored thereon that, when executed by said one or more processors, cause said one or more processors to perform operations comprising: receiving, from a client device operated by a user, a request for a content item; in response to said request, identifying content items available to be sent to said client device; determining one or more designated geographic locations for each of the identified content items; determining one or more contacts of said user, said determined one or more contacts being members of a social network of said user; for each of the identified content items: determining a score for the content item based on a number of tagging actions that were performed by the user's contacts at the determined designated geographic location for the identified content item, wherein said tagging actions mark an association of a person with a particular geographic location; selecting, from the identified content items, a particular content item to be sent to the client device based on the scores; determining that a timestamp associated with at least one of the tagging actions performed at the designated geographic location for the particular content item is within a time period specified by a provider of the particular content item, the timestamp indicating a time of the tagging action; constructing, based on the determination that the timestamp is within the time period, an annotation that identifies at least one of the user's contacts with the tagging action corresponding to the designated geographic location and indicates the time of the tagging action based on the timestamp associated with the at least one location record; and sending said annotation to said client device. 21. The apparatus of claim 17 , wherein said location record indicates a tagging action. | 0.973269 |
8,506,303 | 15 | 16 | 15. The system of claim 13 , wherein the system further includes an instruction set for receiving user content wherein the user content is combined with the integrated assembly instruction set. | 15. The system of claim 13 , wherein the system further includes an instruction set for receiving user content wherein the user content is combined with the integrated assembly instruction set. 16. The system of claim 15 , wherein the user content comprises at least one of plain text, lines, images, audio clips and video clips. | 0.5 |
7,895,571 | 8 | 9 | 8. The data processing system of claim 7 , wherein the webpage development framework determines whether a scripting language should be rendered in response to evaluating the value-binding expression. | 8. The data processing system of claim 7 , wherein the webpage development framework determines whether a scripting language should be rendered in response to evaluating the value-binding expression. 9. The data processing system of claim 8 , further comprising: the scripting language coupled to the script component, wherein the scripting language extracts a current value from the server-side data model in response to the scripting language being rendered, and wherein the scripting language inserts the current value into the value-binding expression. | 0.5 |
7,958,129 | 1 | 18 | 1. A method of checking input customer information against existing information, the method comprising tolerating writing variations in input data by the steps of: determining in an input customer data record a value of a data field, the data field representing an identifier, determining, by a processor, from a reference data set of predetermined identifier values in a computer readable database at least one synonym candidate for the value of the data field using a candidate selection criterion, determining if a synonym candidate of the determined at least one synonym candidate and the value of the data field fulfill a predetermined synonym acceptance criterion based on at least one quality parameter, wherein said at least one quality parameter takes into account writing variations that are evaluated based on differences in the value of the data field and the synonym candidate, and when the predetermined synonym acceptance criterion is fulfilled, associating the value of the data field and the synonym candidate as synonyms and automatically updating a synonym set representing known writing variations for the identifier in a computer readable database and referencing to respective entries in the reference data set by adding the value of the data field to the synonym set as a member referring to the accepted synonym candidate in the reference data set without intervention of a user before searching for a counterpart for the input customer data record, and checking the input customer data record by searching for the counterpart for the input customer data record in the reference data set by comparing the value of the data field to the updated synonym set in the computer readable database after the step of determining if the predetermined synonym acceptance criterion is fulfilled. | 1. A method of checking input customer information against existing information, the method comprising tolerating writing variations in input data by the steps of: determining in an input customer data record a value of a data field, the data field representing an identifier, determining, by a processor, from a reference data set of predetermined identifier values in a computer readable database at least one synonym candidate for the value of the data field using a candidate selection criterion, determining if a synonym candidate of the determined at least one synonym candidate and the value of the data field fulfill a predetermined synonym acceptance criterion based on at least one quality parameter, wherein said at least one quality parameter takes into account writing variations that are evaluated based on differences in the value of the data field and the synonym candidate, and when the predetermined synonym acceptance criterion is fulfilled, associating the value of the data field and the synonym candidate as synonyms and automatically updating a synonym set representing known writing variations for the identifier in a computer readable database and referencing to respective entries in the reference data set by adding the value of the data field to the synonym set as a member referring to the accepted synonym candidate in the reference data set without intervention of a user before searching for a counterpart for the input customer data record, and checking the input customer data record by searching for the counterpart for the input customer data record in the reference data set by comparing the value of the data field to the updated synonym set in the computer readable database after the step of determining if the predetermined synonym acceptance criterion is fulfilled. 18. A method as defined in claim 1 , wherein the identifier relates to a name of one of the following: a geographical entity, a person and an organization. | 0.827394 |
9,256,594 | 1 | 6 | 1. A method of analyzing element names in a patent document, said method comprising the steps of: providing a patent document, wherein said patent document includes text data having a claims section; identifying a first element name within a first claim in said claims section, by performing an optical character recognition (OCR) process of the first element name wherein said step of identifying a first element name is comprised of identifying an antecedent basis word in said first claim and identifying element name text following said antecedent basis word using the optical character recognition (OCR), wherein said antecedent basis word is comprised of the word “a” or “an”; and emphasizing, via a processor, said first element name within said first claim, wherein said step of emphasizing said first element name is comprised of one of the following: bolding, underlining, italics, highlighting, adding characters or coloring a font of said element name and inserting a first element number that corresponds to said first element name adjacent to said first element name, wherein said first element number is inserted after said first element name. | 1. A method of analyzing element names in a patent document, said method comprising the steps of: providing a patent document, wherein said patent document includes text data having a claims section; identifying a first element name within a first claim in said claims section, by performing an optical character recognition (OCR) process of the first element name wherein said step of identifying a first element name is comprised of identifying an antecedent basis word in said first claim and identifying element name text following said antecedent basis word using the optical character recognition (OCR), wherein said antecedent basis word is comprised of the word “a” or “an”; and emphasizing, via a processor, said first element name within said first claim, wherein said step of emphasizing said first element name is comprised of one of the following: bolding, underlining, italics, highlighting, adding characters or coloring a font of said element name and inserting a first element number that corresponds to said first element name adjacent to said first element name, wherein said first element number is inserted after said first element name. 6. The method of claim 1 , wherein said step of emphasizing said first element name is comprised of changing a font characteristic of said first element name compared to a normal font characteristic of said first claim. | 0.652381 |
8,997,041 | 1 | 5 | 1. A method for managing scripts carried out in a script management server which is connected to a user terminal and manages script codes, the method comprising: preparing, by the script management server, a plurality of databases including a meta database and a plurality of script databases, wherein the script management server comprises at least one computing device; designating, by the script management server, an active script database by providing a plurality of original script lists to the user terminal; and storing, by the script management server, identifiers of the user terminal and the designated active script database in the meta database, wherein the plurality of script databases are classified according to script version and each of the plurality of script databases manages the original script code and user-specific script code, and wherein the meta database manages the plurality of original script lists related to the plurality of script databases and a list of user-specific scripts, if a script code in the active script database is updated through the user terminal, updating, by the script management server, a script list and script codes of the corresponding user stored in the meta database and the designated active script database, respectively, wherein the updating a script list and script codes of the corresponding user further comprises, if the script code is updated through the user terminal, updating the script in the plurality of script databases into a script of new version for the corresponding script. | 1. A method for managing scripts carried out in a script management server which is connected to a user terminal and manages script codes, the method comprising: preparing, by the script management server, a plurality of databases including a meta database and a plurality of script databases, wherein the script management server comprises at least one computing device; designating, by the script management server, an active script database by providing a plurality of original script lists to the user terminal; and storing, by the script management server, identifiers of the user terminal and the designated active script database in the meta database, wherein the plurality of script databases are classified according to script version and each of the plurality of script databases manages the original script code and user-specific script code, and wherein the meta database manages the plurality of original script lists related to the plurality of script databases and a list of user-specific scripts, if a script code in the active script database is updated through the user terminal, updating, by the script management server, a script list and script codes of the corresponding user stored in the meta database and the designated active script database, respectively, wherein the updating a script list and script codes of the corresponding user further comprises, if the script code is updated through the user terminal, updating the script in the plurality of script databases into a script of new version for the corresponding script. 5. The method of claim 1 , further comprising, if another active script database is designated by the user terminal, updating, by the script management server, the stored identifier of the active script database. | 0.554622 |
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