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9,275,364 | 16 | 19 | 16. An apparatus comprising: a non-transitory, machine-readable medium; a processor coupled to the non-transitory, machine-readable medium, the non-transitory, computer-readable storage medium comprising code executable by the processor for implementing a method comprising: accessing a business process platform that includes a business process definition and a provider semantic configuration, the business process definition modeling a business process as a workflow comprising a plurality of dependent tasks, wherein the business process definition identifies a user interface definition, a business object definition, and business object data; generating a group semantic configuration that extends the provider semantic configuration; applying the group semantic configuration to one or more of the user interface definition, the business object definition, and the business object data; and customizing one of the plurality of dependent tasks of the workflow defined in the business process definition based on the group semantic configuration, the customization altering a meaning of at least one element of the customized dependent task, wherein the meaning of the customized dependent task comprises task functionality and behavior. | 16. An apparatus comprising: a non-transitory, machine-readable medium; a processor coupled to the non-transitory, machine-readable medium, the non-transitory, computer-readable storage medium comprising code executable by the processor for implementing a method comprising: accessing a business process platform that includes a business process definition and a provider semantic configuration, the business process definition modeling a business process as a workflow comprising a plurality of dependent tasks, wherein the business process definition identifies a user interface definition, a business object definition, and business object data; generating a group semantic configuration that extends the provider semantic configuration; applying the group semantic configuration to one or more of the user interface definition, the business object definition, and the business object data; and customizing one of the plurality of dependent tasks of the workflow defined in the business process definition based on the group semantic configuration, the customization altering a meaning of at least one element of the customized dependent task, wherein the meaning of the customized dependent task comprises task functionality and behavior. 19. The apparatus of claim 16 , wherein the business process definition includes a task descriptor that identifies the user interface definition, the business object definition, and the business object data. | 0.845291 |
8,126,715 | 6 | 13 | 6. A computer-implemented method for facilitating multimodal interaction, the method comprising: receiving a spoken utterance having two or more terms, the two or more terms including one or more acceptable terms; searching an index using the one or more acceptable terms as query terms; producing using a computer processor, from the searching of the index, at least one permissible phrase that includes the one or more acceptable terms; the index comprising a searchable data structure that represents multiple possible grammar paths that are ascertainable based on acceptable values for each term position of a grammar-based speech application; and presenting the at least one permissible phrase to a user as at least one option that may be selected to conduct multimodal interaction with the device. | 6. A computer-implemented method for facilitating multimodal interaction, the method comprising: receiving a spoken utterance having two or more terms, the two or more terms including one or more acceptable terms; searching an index using the one or more acceptable terms as query terms; producing using a computer processor, from the searching of the index, at least one permissible phrase that includes the one or more acceptable terms; the index comprising a searchable data structure that represents multiple possible grammar paths that are ascertainable based on acceptable values for each term position of a grammar-based speech application; and presenting the at least one permissible phrase to a user as at least one option that may be selected to conduct multimodal interaction with the device. 13. The method as recited in claim 6 , wherein producing comprises: retrieving from the index one or more retrieved acceptable terms as part of the at least one permissible phrase; wherein the method further comprises: for a forward case in which the one or more acceptable terms from the spoken utterance comprise one or more recognized acceptable terms that initiate the at least one permissible phrase, presenting the one or more recognized acceptable terms followed by the one or more retrieved acceptable terms. | 0.507634 |
9,262,412 | 8 | 12 | 8. A computing system having a display and at least one or more processors, the computing system configured to perform operations comprising: obtaining one or more source characters in a source language; obtaining a plurality of target words in a target language representing potential transliterations of a plurality of source words from the source language, each of the plurality of source words beginning with the one or more source characters; obtaining a selected target word having a highest likelihood that (i) a specific source word corresponding to the selected target word is an appropriate source word beginning with the one or more source characters and (ii) the selected target word is an appropriate transliteration of the specific source word; outputting, in a first area of the display, the selected target word; and outputting, in a second area of the display, (i) a remainder of the plurality of target words and corresponding indications of their relative likelihoods and (ii) the one or more source characters and a corresponding indication of a lowest relative likelihood. | 8. A computing system having a display and at least one or more processors, the computing system configured to perform operations comprising: obtaining one or more source characters in a source language; obtaining a plurality of target words in a target language representing potential transliterations of a plurality of source words from the source language, each of the plurality of source words beginning with the one or more source characters; obtaining a selected target word having a highest likelihood that (i) a specific source word corresponding to the selected target word is an appropriate source word beginning with the one or more source characters and (ii) the selected target word is an appropriate transliteration of the specific source word; outputting, in a first area of the display, the selected target word; and outputting, in a second area of the display, (i) a remainder of the plurality of target words and corresponding indications of their relative likelihoods and (ii) the one or more source characters and a corresponding indication of a lowest relative likelihood. 12. The computing system of claim 8 , wherein the first and second areas are arranged in an inline configuration. | 0.7749 |
8,516,008 | 8 | 9 | 8. A network device that is operative for searching data comprising: a transceiver that is operative to communicate over a network; a memory that is operative to store at least instructions; and a processor device that is operative to execute instructions that enable actions, including: storing data into at least one datastore; generating at least one field name that corresponds to at least one field value from the data; determining at least one posting value associated with the at least one field name that corresponds to the at least one field value, wherein the at least one posting value at least identifies a location of a record in the at least one datastore that includes the at least one field name that corresponds to the at least one field value; generating at least one lexicon that includes at least one lexicon record that comprises the at least one field name, the at least one field value, and the at least one posting value which correspond to each other; receiving a query directed to data stored in the at least one datastore; generating at least one result for the query based on at least a portion of the lexicon separate from the at least one datastore; if the at least one query includes at least one aggregation function, performing further actions, including: locating the at least one lexicon record for at least a first lexicon record that includes at least a field name that is associated with the at least one aggregation function; and generating at least one aggregated result by iterating over each lexicon record that includes the at least one field name and incorporating the corresponding at least one field value into the aggregated result; and projecting the at least one result into at least one row in at least one table. | 8. A network device that is operative for searching data comprising: a transceiver that is operative to communicate over a network; a memory that is operative to store at least instructions; and a processor device that is operative to execute instructions that enable actions, including: storing data into at least one datastore; generating at least one field name that corresponds to at least one field value from the data; determining at least one posting value associated with the at least one field name that corresponds to the at least one field value, wherein the at least one posting value at least identifies a location of a record in the at least one datastore that includes the at least one field name that corresponds to the at least one field value; generating at least one lexicon that includes at least one lexicon record that comprises the at least one field name, the at least one field value, and the at least one posting value which correspond to each other; receiving a query directed to data stored in the at least one datastore; generating at least one result for the query based on at least a portion of the lexicon separate from the at least one datastore; if the at least one query includes at least one aggregation function, performing further actions, including: locating the at least one lexicon record for at least a first lexicon record that includes at least a field name that is associated with the at least one aggregation function; and generating at least one aggregated result by iterating over each lexicon record that includes the at least one field name and incorporating the corresponding at least one field value into the aggregated result; and projecting the at least one result into at least one row in at least one table. 9. The network device of claim 8 , wherein generating at least one result further comprises, if the at least one query includes the at least one aggregation function, and if a where clause exists, employing a list indicated by at least one helper array for generating the at least one aggregated result. | 0.895083 |
10,003,922 | 1 | 17 | 1. A method comprising, by one or more computing devices: receiving, from a mobile-client system of a first user, geographic-location information associated with the mobile-client system; calculating, for each of a plurality of candidate place-entities corresponding to the geographic-location information, a confidence score based on both the geographic-location information and social-graph information associated with the first user, wherein the confidence score represents a probability that the mobile-client system is located at the candidate place-entity; and sending, to the mobile-client system, information associated with one or more of the candidate place-entities based on their respective confidence scores. | 1. A method comprising, by one or more computing devices: receiving, from a mobile-client system of a first user, geographic-location information associated with the mobile-client system; calculating, for each of a plurality of candidate place-entities corresponding to the geographic-location information, a confidence score based on both the geographic-location information and social-graph information associated with the first user, wherein the confidence score represents a probability that the mobile-client system is located at the candidate place-entity; and sending, to the mobile-client system, information associated with one or more of the candidate place-entities based on their respective confidence scores. 17. The method of claim 1 , wherein the information sent to the mobile-client system comprises a suggestion to a first user of the mobile-client system to perform an action associated with one of the one or more candidate place-entities. | 0.815708 |
9,414,004 | 25 | 26 | 25. The system as recited in claim 24 wherein the context object generator comprises generating intent objects from the first search request. | 25. The system as recited in claim 24 wherein the context object generator comprises generating intent objects from the first search request. 26. The system as recited in claim 25 wherein the intent objects comprise at least one of media type, genre, channel, content rating, date, episode, title and team. | 0.5 |
9,369,478 | 16 | 18 | 16. The computer system of claim 13 , wherein a respective record in the log data indicates a client event or a server event. | 16. The computer system of claim 13 , wherein a respective record in the log data indicates a client event or a server event. 18. The computer system of claim 16 , wherein a client event corresponds to a client process being started to initiate an outgoing Transmission Control Protocol (TCP) connection or to terminate an existing TCP connection. | 0.5 |
9,544,263 | 9 | 15 | 9. A non-transitory computer-readable medium containing instructions for displaying dynamic content from a networked post in a text message, the instructions for execution by a computer system, the non-transitory computer-readable medium comprising: instructions for receiving a text message, the text message containing dynamic content from a networked post, wherein the networked post is accessible on a network at a network location; wherein the networked post includes a photo or video, and the photo or video is displayed in the text message; instructions for displaying the text message to a user; instructions for initiating a call to a first server-side script to retrieve the number of likes that the networked post has received; instructions for, after completion of the first server-side script, executing a client-side handler function associated with the first server-side script to process a return value of the first server-side script and cause the display of the number of likes that the networked post has received; instructions for displaying a like button for liking the networked post; instructions for, in response to activation of the like button, transmitting an indication of the user liking the networked post to a server to cause a representation of the user's act of liking the networked post to be displayed with the networked post; wherein the instructions for transmitting the indication of the user liking the networked post to the server comprise instructions for initiating a call to a second server-side script to cause the indication of the user liking the networked post to be stored in a database accessible to the server; instructions for displaying one or more comments from one or more other users about the networked post in a comment section associated with the text message; instructions for displaying a comment field for accepting a comment from the user; instructions for, in response to the user submitting a comment via the comment field, initiating a call to a third server-side script to cause text of the user-submitted comment to be stored in the database accessible to the server; instructions for, in response to submission of a new comment by the user or another user, dynamically updating the display of comments associated with the text message to include the new comment. | 9. A non-transitory computer-readable medium containing instructions for displaying dynamic content from a networked post in a text message, the instructions for execution by a computer system, the non-transitory computer-readable medium comprising: instructions for receiving a text message, the text message containing dynamic content from a networked post, wherein the networked post is accessible on a network at a network location; wherein the networked post includes a photo or video, and the photo or video is displayed in the text message; instructions for displaying the text message to a user; instructions for initiating a call to a first server-side script to retrieve the number of likes that the networked post has received; instructions for, after completion of the first server-side script, executing a client-side handler function associated with the first server-side script to process a return value of the first server-side script and cause the display of the number of likes that the networked post has received; instructions for displaying a like button for liking the networked post; instructions for, in response to activation of the like button, transmitting an indication of the user liking the networked post to a server to cause a representation of the user's act of liking the networked post to be displayed with the networked post; wherein the instructions for transmitting the indication of the user liking the networked post to the server comprise instructions for initiating a call to a second server-side script to cause the indication of the user liking the networked post to be stored in a database accessible to the server; instructions for displaying one or more comments from one or more other users about the networked post in a comment section associated with the text message; instructions for displaying a comment field for accepting a comment from the user; instructions for, in response to the user submitting a comment via the comment field, initiating a call to a third server-side script to cause text of the user-submitted comment to be stored in the database accessible to the server; instructions for, in response to submission of a new comment by the user or another user, dynamically updating the display of comments associated with the text message to include the new comment. 15. The non-transitory computer-readable medium of claim 9 , wherein the text message includes a video and the video is playable from within the display of the text message. | 0.841575 |
9,355,143 | 10 | 23 | 10. A method of retrieving data from an Online Analytical Processing (“OLAP”) data source, wherein said data source has associated meta-data, said method comprising: providing a computing device that is selectively and communicatively coupled to a network; providing an Application Programming Interface (“API”) operating on said computing device; said computing device receiving as input via said API a two-dimensional query formulated in a two-dimensional query language such that said query includes a sequenced list of requested columns wherein said sequenced list includes a mixed order of measure columns and dimensional columns; said computing device converting said two-dimensional query into a multi-dimensional query which separates said measure columns from said dimensional columns and employing said multi-dimensional query to retrieve data from said data source. | 10. A method of retrieving data from an Online Analytical Processing (“OLAP”) data source, wherein said data source has associated meta-data, said method comprising: providing a computing device that is selectively and communicatively coupled to a network; providing an Application Programming Interface (“API”) operating on said computing device; said computing device receiving as input via said API a two-dimensional query formulated in a two-dimensional query language such that said query includes a sequenced list of requested columns wherein said sequenced list includes a mixed order of measure columns and dimensional columns; said computing device converting said two-dimensional query into a multi-dimensional query which separates said measure columns from said dimensional columns and employing said multi-dimensional query to retrieve data from said data source. 23. The method according to claim 10 , wherein said two-dimensional query language is Language Integrated Query (“LINQ”), said multi-dimensional query language is Multi-Dimensional eXpressions (“MDX”) and wherein said converting comprises: generating a Measure name in an MDX query in a same relative position where a matching LINQ Measurement Property is specified by a LINQ SELECT clause. | 0.72063 |
7,627,559 | 7 | 8 | 7. The system of claim 6 , the graph generation component provides a noise filter for the Co-occurrence Graph that, at least in part, prunes edges that are less than a first given threshold and prunes nodes that have less than a second given threshold. | 7. The system of claim 6 , the graph generation component provides a noise filter for the Co-occurrence Graph that, at least in part, prunes edges that are less than a first given threshold and prunes nodes that have less than a second given threshold. 8. The system of claim 7 , the graph generation component generates a Similarity Graph, prunes top E edges by edge weight for each node, and removes edges except edges that fall within at least one of the top E edges, where E is an integer from one to infinity. | 0.5 |
7,503,006 | 8 | 10 | 8. The method of claim 1 , further comprising modifying the voice data as a function of a predefined characteristic selected by the voice speaker. | 8. The method of claim 1 , further comprising modifying the voice data as a function of a predefined characteristic selected by the voice speaker. 10. The method of claim 8 , wherein modifying the voice data as a function of a predefined characteristic selected by the voice speaker comprises adjusting the voice data to sound like a preselected gender. | 0.5 |
8,677,232 | 1 | 3 | 1. An electronic device, comprising: a display; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying at least a portion of an electronic document at a first magnification level on the display; detecting a first input indicating a first insertion point in the document, wherein the first insertion point is proximate to a first portion of text in the document; in response to detecting the first input: selecting a second magnification level different from the first magnification level, wherein the second magnification level is selected so as to display the first portion of text at a default target text display size; and displaying a portion of the document at the second magnification level; detecting a second input corresponding to a request to display a portion of the document at a third magnification level different from the second magnification level; in response to detecting the second input: displaying the portion of the document at the third magnification level; and storing a user-adjusted target text display size corresponding to a text display size of the first portion of text at the third magnification level, wherein the user-adjusted target text display size is different from the default target text display size; and after storing the user-adjusted target text display size: detecting a third input indicating a second insertion point in the document, wherein the second insertion point is proximate to a second portion of text in the document; and in response to detecting the third input, displaying the document at a respective magnification level such that the second portion of text is displayed at the user-adjusted target text display size. | 1. An electronic device, comprising: a display; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying at least a portion of an electronic document at a first magnification level on the display; detecting a first input indicating a first insertion point in the document, wherein the first insertion point is proximate to a first portion of text in the document; in response to detecting the first input: selecting a second magnification level different from the first magnification level, wherein the second magnification level is selected so as to display the first portion of text at a default target text display size; and displaying a portion of the document at the second magnification level; detecting a second input corresponding to a request to display a portion of the document at a third magnification level different from the second magnification level; in response to detecting the second input: displaying the portion of the document at the third magnification level; and storing a user-adjusted target text display size corresponding to a text display size of the first portion of text at the third magnification level, wherein the user-adjusted target text display size is different from the default target text display size; and after storing the user-adjusted target text display size: detecting a third input indicating a second insertion point in the document, wherein the second insertion point is proximate to a second portion of text in the document; and in response to detecting the third input, displaying the document at a respective magnification level such that the second portion of text is displayed at the user-adjusted target text display size. 3. The device of claim 1 , including instructions for using the user-adjusted target text display size as a target display size for a plurality of different documents accessible by the device. | 0.681063 |
8,380,490 | 8 | 9 | 8. The reusable automatic text translation control of claim 7 , wherein said means for initializing further comprises means for initializing a subject area. | 8. The reusable automatic text translation control of claim 7 , wherein said means for initializing further comprises means for initializing a subject area. 9. The reusable automatic text translation control of claim 8 , wherein said means for initializing further comprises means for initializing domains. | 0.5 |
7,921,092 | 1 | 6 | 1. A method comprising: a computer processor determining a first key concept of a particular document; in response to receiving a search query from a user, the computer processor generating search results that include a search result listing for said particular document; the computer processor generating said search result listing for said particular document by creating a summary of said particular document that is less than all of said particular document; wherein generating said summary comprises the computer processor selecting, from said particular document, and including, in said summary, one or more excerpts that each contain both (a) said first key concept and (b) one or more non-key concept words that are within a specified proximity of an occurrence of said first key concept in said particular document; sending, toward an application, a search results page that comprises (a) one or more search result listings for one or more of the search results and (b) one or more key concepts for each of one or more of the search result listings; after sending said search results page toward said application, receiving, from said application, a request that specifies (a) a particular search result listing of said one or more search result listings sent toward said application and (b) a second key concept of said one or more key concepts sent toward said application; and in response to receiving the request, sending, toward the application, a particular summary for the particular search result listing, wherein the particular summary is generated based on the second key concept without regard to the query terms and without regard to the first key concept. | 1. A method comprising: a computer processor determining a first key concept of a particular document; in response to receiving a search query from a user, the computer processor generating search results that include a search result listing for said particular document; the computer processor generating said search result listing for said particular document by creating a summary of said particular document that is less than all of said particular document; wherein generating said summary comprises the computer processor selecting, from said particular document, and including, in said summary, one or more excerpts that each contain both (a) said first key concept and (b) one or more non-key concept words that are within a specified proximity of an occurrence of said first key concept in said particular document; sending, toward an application, a search results page that comprises (a) one or more search result listings for one or more of the search results and (b) one or more key concepts for each of one or more of the search result listings; after sending said search results page toward said application, receiving, from said application, a request that specifies (a) a particular search result listing of said one or more search result listings sent toward said application and (b) a second key concept of said one or more key concepts sent toward said application; and in response to receiving the request, sending, toward the application, a particular summary for the particular search result listing, wherein the particular summary is generated based on the second key concept without regard to the query terms and without regard to the first key concept. 6. The method of claim 1 , further comprising: determining whether a particular device from which the search query originated is a mobile device; if the particular device is not a mobile device, then generating the summary that has a first specified length; and if the particular device is a mobile device, then generating the summary that has a second specified length that is greater than the first specified length. | 0.594961 |
4,460,975 | 18 | 19 | 18. The process of claim 17 wherein the sequence of prompting stimuli also includes a request for an alphanumeric response as a command. | 18. The process of claim 17 wherein the sequence of prompting stimuli also includes a request for an alphanumeric response as a command. 19. The process of claim 18 wherein the sequence of presentation of prompting stimuli is determined by preceding commands. | 0.5 |
8,731,901 | 12 | 13 | 12. The method of claim 11 , wherein identifying the one or more references to entities having Romanized language names further comprises comparing contents of the Romanized language output with Romanized language names within one or more databases. | 12. The method of claim 11 , wherein identifying the one or more references to entities having Romanized language names further comprises comparing contents of the Romanized language output with Romanized language names within one or more databases. 13. The method of claim 12 , wherein the one or more databases comprise external databases selected from a group consisting of websites, internet databases, dictionaries, lexicons and native language classification databases and combinations thereof. | 0.5 |
9,600,497 | 9 | 10 | 9. The system of claim 1 , wherein the processing module is configured to perform one or more preprocessing operations on the target image to provide a preprocessed target image, the multiple image vectors for the target image to be generated based on the preprocessed target image. | 9. The system of claim 1 , wherein the processing module is configured to perform one or more preprocessing operations on the target image to provide a preprocessed target image, the multiple image vectors for the target image to be generated based on the preprocessed target image. 10. The system of claim 9 , wherein the one or more preprocessing operations comprises an edge detection operation. | 0.5 |
7,904,435 | 10 | 17 | 10. A computer-readable storage medium comprising a set of instructions for acquiring a lock of a data structure in a network file system (“NFS”) environment, the set of instructions to direct a processor to perform acts of: creating a text file in a management library of a data structure, wherein a name of the text file comprises an identifier of the lock, an identifier of a process attempting to acquire the lock, and an identifier of a machine on which the process attempting to acquire the lock is running; storing the identifier of the process attempting to acquire the lock in the contents of the text file; storing the identifier of the machine on which the process attempting to acquire the lock is running in the contents of the text file; creating a hard link that points to the text file; determining a number of links pointing to the text file; locking the data structure based on the number of links pointing to the text file; reading the contents of the text file; determining whether the contents of the text file comprise the identifier of the process that acquired the lock; determining whether the contents of the text file comprise the identifier of the machine on which the process that acquired the lock is running; and determining whether to release the lock of the data structure based on whether the contents of the text file comprise the identifier of the process that acquired the lock and the identifier of the machine on which the process that acquired the lock is running, wherein determining whether to release the lock of the data structure based on whether the contents of the text file comprise the identifier of the process that acquired the lock and the identifier of the machine on which the process that acquired the lock is running comprises: releasing the lock of the data structure in response to determining the contents of the text file comprises both the identifier of the process that acquired the lock and the identifier of the machine on which the process that acquired the lock is running, and maintaining the lock of the data structure in response to determining the contents of the text file does not comprise at least one of the identifier of the process that acquired the lock or the identifier of the machine on which the process that acquired the lock is running. | 10. A computer-readable storage medium comprising a set of instructions for acquiring a lock of a data structure in a network file system (“NFS”) environment, the set of instructions to direct a processor to perform acts of: creating a text file in a management library of a data structure, wherein a name of the text file comprises an identifier of the lock, an identifier of a process attempting to acquire the lock, and an identifier of a machine on which the process attempting to acquire the lock is running; storing the identifier of the process attempting to acquire the lock in the contents of the text file; storing the identifier of the machine on which the process attempting to acquire the lock is running in the contents of the text file; creating a hard link that points to the text file; determining a number of links pointing to the text file; locking the data structure based on the number of links pointing to the text file; reading the contents of the text file; determining whether the contents of the text file comprise the identifier of the process that acquired the lock; determining whether the contents of the text file comprise the identifier of the machine on which the process that acquired the lock is running; and determining whether to release the lock of the data structure based on whether the contents of the text file comprise the identifier of the process that acquired the lock and the identifier of the machine on which the process that acquired the lock is running, wherein determining whether to release the lock of the data structure based on whether the contents of the text file comprise the identifier of the process that acquired the lock and the identifier of the machine on which the process that acquired the lock is running comprises: releasing the lock of the data structure in response to determining the contents of the text file comprises both the identifier of the process that acquired the lock and the identifier of the machine on which the process that acquired the lock is running, and maintaining the lock of the data structure in response to determining the contents of the text file does not comprise at least one of the identifier of the process that acquired the lock or the identifier of the machine on which the process that acquired the lock is running. 17. The computer-readable storage medium of claim 10 , further comprising a set of instructions to direct the computer system to perform acts of: after a predetermined period of time, determining for a second time whether the contents of the text file comprise the identifier of the process that acquired the lock; after the predetermined period of time, determining for a second time whether the contents of the text file comprise the identifier of the machine on which the process that acquired the lock is running; and after the predetermined period of time, determining whether to release the lock of the data structure based on whether the contents of the text file comprise the identifier of the process that acquired the lock and the identifier of the machine on which the process that acquired the lock is running. | 0.5 |
5,444,840 | 5 | 8 | 5. A computer-implemented method of retrievably storing contents of a plurality of documents having images imprinted thereon comprising optically scanning the documents to form a digital representation of the images on the documents, machine selecting search words from each document to be used in locating the document from mass storage, converting the selected search words to code, storing the converted search words in a memory, storing the image representation of each document, establishing from images of the scanned documents a font table in image of alphanumeric characters in a plurality of different fonts each character in each font correlated with an equivalent character in code, searching for a document by the steps of manually selecting a search word, manually entering the selected search word in code, constructing by machine an image of the selected search word from the font table in at least one font, comparing the constructed search word with the image representations of scanned documents until a match in a stored document image is found, and displaying an image thereof of the matched document. | 5. A computer-implemented method of retrievably storing contents of a plurality of documents having images imprinted thereon comprising optically scanning the documents to form a digital representation of the images on the documents, machine selecting search words from each document to be used in locating the document from mass storage, converting the selected search words to code, storing the converted search words in a memory, storing the image representation of each document, establishing from images of the scanned documents a font table in image of alphanumeric characters in a plurality of different fonts each character in each font correlated with an equivalent character in code, searching for a document by the steps of manually selecting a search word, manually entering the selected search word in code, constructing by machine an image of the selected search word from the font table in at least one font, comparing the constructed search word with the image representations of scanned documents until a match in a stored document image is found, and displaying an image thereof of the matched document. 8. A method according to claim 5 and further comprising forming a logo table of stored images of logo designs identifying organizations from which the documents were sent together with information in code form, said code form corresponding to each sender employing each such design, when a document having a design is scanned, conducting a pattern search of the stored images in the logo table to seek a match between the scanned design and a stored image, when a pattern match is found, retrieving and correlating with the identification of the document the identifying organization information associated with the matched pattern from the logo table, and when a match is not found, flagging the document for manual addition of the design and identifying organization information to the logo table. | 0.5 |
9,407,768 | 15 | 17 | 15. A customer analysis computer program product stored on a non-transitory computer readable medium including computer executable code for analyzing electronic customer communication data and generating behavioral assessment data, the computer program product comprising: computer readable code to receive electronic customer communication data of two or more types on one or more servers configured to provide a user interface comprising a website, web portal, or virtual portal, wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; computer readable code to identify a customer associated with the electronic customer communication data received by the one or more servers; computer readable code to analyze the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; computer readable code to generate behavioral assessment data based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; and computer readable code to display instructions to a user via a reporting engine, wherein the instructions are based on the generated behavioral assessment data. | 15. A customer analysis computer program product stored on a non-transitory computer readable medium including computer executable code for analyzing electronic customer communication data and generating behavioral assessment data, the computer program product comprising: computer readable code to receive electronic customer communication data of two or more types on one or more servers configured to provide a user interface comprising a website, web portal, or virtual portal, wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; computer readable code to identify a customer associated with the electronic customer communication data received by the one or more servers; computer readable code to analyze the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; computer readable code to generate behavioral assessment data based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; and computer readable code to display instructions to a user via a reporting engine, wherein the instructions are based on the generated behavioral assessment data. 17. The customer analysis computer program product of claim 15 , wherein the electronic customer communication data is at least two of electronic-mail data, web content data, text message data, voice over IP data, and online forum data. | 0.640244 |
9,002,702 | 1 | 4 | 1. A method of assigning a confidence level to an axiom extracted from a text of a transcription of a voice recording; receiving, at a computer device, the text of the transcription; comparing, using the computer device, every word from the text to a customer specific dictionary and a dictionary of common language words; determining a number of inaccurately spelled words in the transcription based on the comparing; assigning, using a Gaussian distribution, a confidence level to the text of the transcription based on the determining; estimating an accuracy of the text based on the assigned confidence level; gathering, using the computer device, external information related to words in the text by retrieving a set of axioms that further define the words in the text of the transcription from a set of sources, each axiom in the set of axioms comprising a proposition that is regarded as being at least one of established, accepted, and self-evidently true; determining a confidence level of each source of the set of sources; and assigning a confidence level to each axiom of the set of axioms based on a combination of the confidence level of the set of sources and the accuracy of the text estimated based on the assigned confidence level. | 1. A method of assigning a confidence level to an axiom extracted from a text of a transcription of a voice recording; receiving, at a computer device, the text of the transcription; comparing, using the computer device, every word from the text to a customer specific dictionary and a dictionary of common language words; determining a number of inaccurately spelled words in the transcription based on the comparing; assigning, using a Gaussian distribution, a confidence level to the text of the transcription based on the determining; estimating an accuracy of the text based on the assigned confidence level; gathering, using the computer device, external information related to words in the text by retrieving a set of axioms that further define the words in the text of the transcription from a set of sources, each axiom in the set of axioms comprising a proposition that is regarded as being at least one of established, accepted, and self-evidently true; determining a confidence level of each source of the set of sources; and assigning a confidence level to each axiom of the set of axioms based on a combination of the confidence level of the set of sources and the accuracy of the text estimated based on the assigned confidence level. 4. The method of claim 1 , further comprising generating a notification indicating the assigned confidence level of the axiom. | 0.585526 |
9,082,403 | 2 | 3 | 2. The method of claim 1 , wherein assigning the pseudo-semantic label further comprises partitioning the spoken utterances into groupings of spoken utterances having unsettled denied confirmations and a current training set comprising settled spoken utterances, wherein the settled spoken utterances comprise accepted confirmations. | 2. The method of claim 1 , wherein assigning the pseudo-semantic label further comprises partitioning the spoken utterances into groupings of spoken utterances having unsettled denied confirmations and a current training set comprising settled spoken utterances, wherein the settled spoken utterances comprise accepted confirmations. 3. The method of claim 2 , wherein updating the classification model further comprises for each grouping, determining pseudo-semantic labels for the spoken utterances having the unsettled denied confirmations and training the classification model with a combination of the current training set and the spoken utterances having the unsettled denied confirmations. | 0.5 |
7,630,552 | 1 | 25 | 1. A method of assessing a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least one information field; and for at least one non-signature information field of the document, comparing, using the computer system, handwriting in the non-signature information field to at least two handwriting profile representations from at least one non-signature information field of at least one other document, wherein writing in at least one of the information fields of the document comprises at least two examples of a type of handwritten information, and further comprising comparing at least two of the examples to assess whether two or more of the examples approximately match. | 1. A method of assessing a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least one information field; and for at least one non-signature information field of the document, comparing, using the computer system, handwriting in the non-signature information field to at least two handwriting profile representations from at least one non-signature information field of at least one other document, wherein writing in at least one of the information fields of the document comprises at least two examples of a type of handwritten information, and further comprising comparing at least two of the examples to assess whether two or more of the examples approximately match. 25. The method of claim 1 , wherein at least one handwriting profile representation comprises at least one image. | 0.864183 |
9,762,618 | 5 | 6 | 5. The method of claim 1 , wherein the determining that the identified delivering email system is authorized to deliver email on behalf of the email domain owner system further comprises: accessing an authorization database that associates one or more authorized delivering organizations with email domains to determine whether the delivering email system is authorized to send email on behalf of the email domain owner system. | 5. The method of claim 1 , wherein the determining that the identified delivering email system is authorized to deliver email on behalf of the email domain owner system further comprises: accessing an authorization database that associates one or more authorized delivering organizations with email domains to determine whether the delivering email system is authorized to send email on behalf of the email domain owner system. 6. The method of claim 5 , wherein the identifying information further includes a local part of the Return-Path address for the email, and wherein the authorization database further associates, for each email domain, one or more local parts of the Return-Path address on behalf of which the one or more delivering organizations are authorized to send email, the method further comprising: accessing the authorization database to determine whether the delivering email system is authorized to send email on behalf of the identified local part of the Return-Path address for the email of the email domain. | 0.5 |
7,587,394 | 1 | 7 | 1. A method of rewriting a query during a database query processing operation, comprising the steps of: processing the query having one or more target attributes in accordance with at least a portion of a data set producing query results comprising the one or more target attributes and one or more auxiliary attributes, wherein the one or more auxiliary attributes are not included in the query; analyzing the query results with respect to the one or more target attributes and the one or more auxiliary attributes to determine a relative selectivity for the one or more auxiliary attributes; selecting at least one of the one or more auxiliary attributes based at least in part on a ranking of the determined relative selectivity for the one or more auxiliary attributes; and appending the query with at least one new predicate corresponding to the selected at least one of the one or more auxiliary attributes to form a rewritten query; wherein the step of analyzing the one or more target attributes and the one or more auxiliary attributes comprises the steps of: extracting statistics for the one or more auxiliary attributes from the query results; extracting statistics for the one or more auxiliary attributes from the at least a portion of the data set; and evaluating the relative selectivity for the one or more auxiliary attributes in accordance with the statistics from the query results and the statistics from the at least a portion of the data set, wherein the step of evaluating the relative selectivity comprises the step of: comparing a range of the statistics from the query results to a range of the statistics from the at least a portion of the data set for the one or more auxiliary attributes. | 1. A method of rewriting a query during a database query processing operation, comprising the steps of: processing the query having one or more target attributes in accordance with at least a portion of a data set producing query results comprising the one or more target attributes and one or more auxiliary attributes, wherein the one or more auxiliary attributes are not included in the query; analyzing the query results with respect to the one or more target attributes and the one or more auxiliary attributes to determine a relative selectivity for the one or more auxiliary attributes; selecting at least one of the one or more auxiliary attributes based at least in part on a ranking of the determined relative selectivity for the one or more auxiliary attributes; and appending the query with at least one new predicate corresponding to the selected at least one of the one or more auxiliary attributes to form a rewritten query; wherein the step of analyzing the one or more target attributes and the one or more auxiliary attributes comprises the steps of: extracting statistics for the one or more auxiliary attributes from the query results; extracting statistics for the one or more auxiliary attributes from the at least a portion of the data set; and evaluating the relative selectivity for the one or more auxiliary attributes in accordance with the statistics from the query results and the statistics from the at least a portion of the data set, wherein the step of evaluating the relative selectivity comprises the step of: comparing a range of the statistics from the query results to a range of the statistics from the at least a portion of the data set for the one or more auxiliary attributes. 7. An article of manufacture for rewriting a query during a database query processing operation; comprising a machine readable storage medium containing one or more programs which when executed implement the steps of claim 1 . | 0.5 |
8,380,712 | 16 | 17 | 16. The method of claim 15 , wherein words identified in text items authored by the user receive an increased weighting. | 16. The method of claim 15 , wherein words identified in text items authored by the user receive an increased weighting. 17. The method of claim 16 , wherein at least one text item is also associated with another user. | 0.5 |
5,442,738 | 6 | 9 | 6. The method of claim 1 wherein the objects comprise a plurality of control flow expressions. | 6. The method of claim 1 wherein the objects comprise a plurality of control flow expressions. 9. The method of claim 6 wherein the form of graphical emphasis comprises projection of a desired window using visual cues. | 0.526923 |
7,512,655 | 1 | 20 | 1. A system for structuring content within a message and transmitting the structured message over a computer network in a real time chat environment, the system comprising: a system administration computing system comprising: a system management program operative to provide a real time chat interface for enabling a plurality of users to communicate with one another in a plurality of different real time chat channels over the computer network, and a channel manager configured to allow an end user to manage the plurality of real time chat channels, wherein the channel manager configured to allow the end user to manage the plurality of real time chat channels comprises the channel manager being configured to allow the end user to: review the plurality of real time chat channels, create additional real time chat channels, and create a filtered channel, wherein the filtered channel comprises an aggregation of selected real time chat channels, the selected real time chat channels being selected by the end user according to at least one of the following: content associated with the plurality of real time chat channels, at least one user name associated with the plurality of real time chat channels, and previously stored criteria comprising at least one of the following: a specified content and at least one specified user name, wherein the previously stored criteria is used to monitor the plurality of real time chat channels and provide information associated with the stored criteria; and a second computing system having a network interface program for communicating with the real time chat interface, wherein the network interface program accepts message content comprising text and other content entered by one of the plurality of users, establishes the real time chat interface with the system management program, interacts with the system management program to structure the content within the message, and transmits the structured message over at least one of the channels of the computer network, wherein the system management program structures the message content in a specific format based on fields associated with the message content. | 1. A system for structuring content within a message and transmitting the structured message over a computer network in a real time chat environment, the system comprising: a system administration computing system comprising: a system management program operative to provide a real time chat interface for enabling a plurality of users to communicate with one another in a plurality of different real time chat channels over the computer network, and a channel manager configured to allow an end user to manage the plurality of real time chat channels, wherein the channel manager configured to allow the end user to manage the plurality of real time chat channels comprises the channel manager being configured to allow the end user to: review the plurality of real time chat channels, create additional real time chat channels, and create a filtered channel, wherein the filtered channel comprises an aggregation of selected real time chat channels, the selected real time chat channels being selected by the end user according to at least one of the following: content associated with the plurality of real time chat channels, at least one user name associated with the plurality of real time chat channels, and previously stored criteria comprising at least one of the following: a specified content and at least one specified user name, wherein the previously stored criteria is used to monitor the plurality of real time chat channels and provide information associated with the stored criteria; and a second computing system having a network interface program for communicating with the real time chat interface, wherein the network interface program accepts message content comprising text and other content entered by one of the plurality of users, establishes the real time chat interface with the system management program, interacts with the system management program to structure the content within the message, and transmits the structured message over at least one of the channels of the computer network, wherein the system management program structures the message content in a specific format based on fields associated with the message content. 20. The message content structuring and transmission system of claim 1 , wherein the system management program converts synchronous message content to asynchronous message content for storage. | 0.619048 |
9,734,130 | 1 | 16 | 1. A method for semantic attribution of a request, said method implemented by a processor of a computer system, said method comprising: said processor semantically analyzing source data statements that had been received for the request, said semantically analyzing comprising matching elements in the received source data statements to respective one or more entries in an ontology associated with a domain that had been selected for the received source data statements, wherein the ontology comprises items and relationships that define the selected domain, and wherein each element in the received source data statements is a word or a phrase; after said semantically analyzing, said processor assigning the one or more entries to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries; after said assigning, said processor saving the annotated elements with the respective annotations; and after said saving, said processor generating a search query for the request, said generating comprising using the annotations to generate the search query for the request. | 1. A method for semantic attribution of a request, said method implemented by a processor of a computer system, said method comprising: said processor semantically analyzing source data statements that had been received for the request, said semantically analyzing comprising matching elements in the received source data statements to respective one or more entries in an ontology associated with a domain that had been selected for the received source data statements, wherein the ontology comprises items and relationships that define the selected domain, and wherein each element in the received source data statements is a word or a phrase; after said semantically analyzing, said processor assigning the one or more entries to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries; after said assigning, said processor saving the annotated elements with the respective annotations; and after said saving, said processor generating a search query for the request, said generating comprising using the annotations to generate the search query for the request. 16. The method of claim 1 , wherein the annotation that annotates one matched element of the matched elements is a domain term that expresses that the one matched element is a noun defining a particular domain. | 0.902326 |
8,688,653 | 4 | 10 | 4. A multiple language support method for an application executed on a computer device comprising a processor having computer device-executable instructions, the method comprising: storing first resource data in multiple languages available in the application in a memory, the stored first resource data includes at least one of Menu, Help, Toolbar, Icon, Dialog and Font for a language, and information on a country; extracting second resource data corresponding to a selected language from the first resource data when a user selects a predetermined language in the application, and applying the extracted resource data to the application; and converting a language of data transmitted between the application and the operating system, when the languages of the operating system and the application are different, wherein the data received in the language of the application from the application is converted into data in the language supported by the operating system, and the converted data is transmitted to the operating system, wherein the converting the language of data transmitted between the application and the operating system comprises converting commands in a language of data transmitted from the operating system into commands in a common language used by all applications, and transmitting the converted data to the application, and wherein the stored first resource data is received through a predetermined recording medium or a predetermined communication medium. | 4. A multiple language support method for an application executed on a computer device comprising a processor having computer device-executable instructions, the method comprising: storing first resource data in multiple languages available in the application in a memory, the stored first resource data includes at least one of Menu, Help, Toolbar, Icon, Dialog and Font for a language, and information on a country; extracting second resource data corresponding to a selected language from the first resource data when a user selects a predetermined language in the application, and applying the extracted resource data to the application; and converting a language of data transmitted between the application and the operating system, when the languages of the operating system and the application are different, wherein the data received in the language of the application from the application is converted into data in the language supported by the operating system, and the converted data is transmitted to the operating system, wherein the converting the language of data transmitted between the application and the operating system comprises converting commands in a language of data transmitted from the operating system into commands in a common language used by all applications, and transmitting the converted data to the application, and wherein the stored first resource data is received through a predetermined recording medium or a predetermined communication medium. 10. The system of claim 4 , wherein in converting the data received in the language of the application from the application, the language of the received data is the common language used by all applications. | 0.5 |
10,055,462 | 14 | 24 | 14. The system of claim 2 , wherein the one or more computers are further configured to perform operations comprising identifying one or more attributes from a structured data source. | 14. The system of claim 2 , wherein the one or more computers are further configured to perform operations comprising identifying one or more attributes from a structured data source. 24. The system of claim 14 , wherein the structured data source is a knowledge graph. | 0.5 |
8,203,577 | 1 | 3 | 1. A method of operating a computer having a display, the method comprising: determining the proximity of a user of the computer to the display based on whether the computer is performing highly output intensive operations or highly input intensive operations; displaying information in a first mode in response to determining that the computer is performing highly input intensive operations, wherein displaying information in the first mode comprises displaying a plurality of text objects with a first size; displaying information in a second mode in response to determining that the computer is performing highly output intensive operations, wherein displaying information in the second mode comprises displaying a first portion of the plurality of text objects with a second size, wherein the second size is larger than the first size; wherein: displaying information in the first mode further comprises displaying a control object; and displaying information in the second mode further comprises displaying the first portion without the control object. | 1. A method of operating a computer having a display, the method comprising: determining the proximity of a user of the computer to the display based on whether the computer is performing highly output intensive operations or highly input intensive operations; displaying information in a first mode in response to determining that the computer is performing highly input intensive operations, wherein displaying information in the first mode comprises displaying a plurality of text objects with a first size; displaying information in a second mode in response to determining that the computer is performing highly output intensive operations, wherein displaying information in the second mode comprises displaying a first portion of the plurality of text objects with a second size, wherein the second size is larger than the first size; wherein: displaying information in the first mode further comprises displaying a control object; and displaying information in the second mode further comprises displaying the first portion without the control object. 3. The method of operating a computer of claim 1 , wherein the control object comprises a menu bar object. | 0.776371 |
4,464,731 | 16 | 17 | 16. An electronic translator according to claim 15, wherein the variable speed and direction retrieval control means further enables the access means to operate at a plurality of discrete speeds in addressing the memory means. | 16. An electronic translator according to claim 15, wherein the variable speed and direction retrieval control means further enables the access means to operate at a plurality of discrete speeds in addressing the memory means. 17. An electronic translator according to claim 16, wherein the retrieval control means enables the access means to operate at two speeds, rapid and slow. | 0.5 |
9,332,315 | 17 | 18 | 17. A system comprising: one or more processors; and a non-transitory computer-readable storage memory storing instructions for causing the one or more processors to: presenting, on a web page, a text entry field for a text string to be entered by a user; receiving the text string, the text string including a delimited label list; parsing the delimited label list to determine a number of, and labels for, categorized user-selectable interface elements to display; present a graphical interface that includes a motion video presentation and the number of categorized user-selectable interface elements, each user-selectable interface element having a separate label from the delimited label list; receive, through the graphical interface, at a first moment during the presentation, a first selection of a first interface element of the categorized interface elements; store, in response to receiving the first selection, first data that maps a first category, corresponding to the first interface element, to a first time point at which the motion video presentation was being presented at the first moment; and generate, based at least in part on the first data, a first tracking graphical element that indicates at least a first quantity of times that the first interface element has been selected during a first time interval that includes the first time point. | 17. A system comprising: one or more processors; and a non-transitory computer-readable storage memory storing instructions for causing the one or more processors to: presenting, on a web page, a text entry field for a text string to be entered by a user; receiving the text string, the text string including a delimited label list; parsing the delimited label list to determine a number of, and labels for, categorized user-selectable interface elements to display; present a graphical interface that includes a motion video presentation and the number of categorized user-selectable interface elements, each user-selectable interface element having a separate label from the delimited label list; receive, through the graphical interface, at a first moment during the presentation, a first selection of a first interface element of the categorized interface elements; store, in response to receiving the first selection, first data that maps a first category, corresponding to the first interface element, to a first time point at which the motion video presentation was being presented at the first moment; and generate, based at least in part on the first data, a first tracking graphical element that indicates at least a first quantity of times that the first interface element has been selected during a first time interval that includes the first time point. 18. The system of claim 17 , wherein non-transitory computer-readable storage memory stores instructions for causing the one or more processors to: receive, through the graphical interface, at a second moment during the presentation, a second selection of a second interface element of the plurality of interface elements; store, in response to receiving the second selection, second data that maps a second category, corresponding to the second interface element but not the first interface element, to a second time point at which the motion video was being presented at the second moment; and generate, based at least in part on the first data and the second data, a second tracking graphical element that indicates at least (a) the first quantity of times that the first interface element has been selected during the first time interval that includes the first time point and (b) a second quantity of times that the second interface element has been selected during a second time interval that includes the second time point but not the first time point; wherein the first interface element is a first color; wherein the second interface element is a second color that differs from the first color; wherein the second tracking graphical element includes a first quantity indicator that is the first color and that indicates the first quantity; wherein the second tracking graphical element includes a second quantity indicator that is the second color and that indicates the second quantity; wherein the second tracking graphical element is a bar chart; wherein the first quantity indicator is a bar, in the bar chart, having a size that is based on the first quantity; wherein the second quantity indicator is a bar, in the bar chart, having a size that is based on the second quantity; wherein the first interface element is a first button having a first label; and wherein the second interface element is a second button having a second label that differs from the first label. | 0.517736 |
8,463,610 | 13 | 14 | 13. An Application Specific Integration Circuit (ASIC) for use in a hardware-implemented backend search engine for a low-power speech recognition system, said ASIC comprising at least: a scoring engine that includes logic circuitry adapted to read a plurality of active acoustic unit models from external memory, update each of the plurality of active acoustic unit models based on one or more corresponding senone scores received from an acoustic scoring engine for a current frame of sampled speech, and write the plurality of active acoustic unit models back to the external memory; a transition engine that includes logic circuitry adapted to process the plurality of active acoustic unit models after the plurality of active acoustic unit models have been updated and written back to the external memory by the scoring engine in order to prune unlikely active acoustic unit models for the current frame of sampled speech, create or modify active acoustic unit models likely to be transitioned to, and identify any completed words, wherein the transition engine is in a low-power state while the scoring engine is processing the plurality of active acoustic unit models; and a language model engine that includes logic circuitry adapted to, for each completed word, identify one or more expected words that are likely to follow the completed word using an n-gram analysis, wherein as part of the n-gram analysis the language model engine performs a lookup for trigrams for the completed word in the external memory using a hashing technique. | 13. An Application Specific Integration Circuit (ASIC) for use in a hardware-implemented backend search engine for a low-power speech recognition system, said ASIC comprising at least: a scoring engine that includes logic circuitry adapted to read a plurality of active acoustic unit models from external memory, update each of the plurality of active acoustic unit models based on one or more corresponding senone scores received from an acoustic scoring engine for a current frame of sampled speech, and write the plurality of active acoustic unit models back to the external memory; a transition engine that includes logic circuitry adapted to process the plurality of active acoustic unit models after the plurality of active acoustic unit models have been updated and written back to the external memory by the scoring engine in order to prune unlikely active acoustic unit models for the current frame of sampled speech, create or modify active acoustic unit models likely to be transitioned to, and identify any completed words, wherein the transition engine is in a low-power state while the scoring engine is processing the plurality of active acoustic unit models; and a language model engine that includes logic circuitry adapted to, for each completed word, identify one or more expected words that are likely to follow the completed word using an n-gram analysis, wherein as part of the n-gram analysis the language model engine performs a lookup for trigrams for the completed word in the external memory using a hashing technique. 14. The ASIC of claim 13 wherein trigrams in a language model used for speech recognition are stored in a single hash table in the external memory and lookup for the trigrams is performed using a single hash function that computes a hash value for the completed word and a preceding word in a word history of the completed word. | 0.753383 |
8,152,636 | 35 | 36 | 35. The bowling system of claim 34 , wherein the interactive display is a plurality of web pages including at least one of: a home page, a theme page, a party experience page, a party package page, an explanation page and a registration page. | 35. The bowling system of claim 34 , wherein the interactive display is a plurality of web pages including at least one of: a home page, a theme page, a party experience page, a party package page, an explanation page and a registration page. 36. The bowling system of claim 35 , wherein the theme page includes different themes and animations thereof associated with the one or more animated characters displayed by the automated bowling scoring system. | 0.5 |
9,239,822 | 1 | 5 | 1. A method performed by a computer processor for incorporating media objects in a yearbook, the method comprising: maintaining, by a computer system, information describing customizable yearbooks for students of a school; receiving one or more videos for including in a printed hard copy of a customizable yearbook of a student, wherein the one or more videos are for presenting via a video presentation device physically attached to the printed hard copy of the customizable yearbook, the video presentation device comprising a display screen for presenting videos; receiving information describing layouts of one or more video presentation pages of the customizable yearbook, the layouts specifying: for each of the one or more videos, a position of a button for activating presentation of the video via the video presentation device, and a position in a video presentation page for physically attaching the video presentation device in a printed hard copy of the yearbook; selecting videos for suggesting to the student for including in the video presentation page of the yearbook, wherein selecting videos for suggesting to the students comprises: determining a time of capture of videos associated with the student; receiving information of timing of a current school year; and preferring videos captured within the current school year over videos captured before the current school year started; sending information describing the selected videos as suggestions for including in the video presentation page of the yearbook; and sending information describing the customizable yearbook for printing one or more hard copies of the customizable yearbook, wherein each printed hard copy of the customizable yearbook comprises the one or more video presentation pages and a video presentation device physically attached to a video presentation page. | 1. A method performed by a computer processor for incorporating media objects in a yearbook, the method comprising: maintaining, by a computer system, information describing customizable yearbooks for students of a school; receiving one or more videos for including in a printed hard copy of a customizable yearbook of a student, wherein the one or more videos are for presenting via a video presentation device physically attached to the printed hard copy of the customizable yearbook, the video presentation device comprising a display screen for presenting videos; receiving information describing layouts of one or more video presentation pages of the customizable yearbook, the layouts specifying: for each of the one or more videos, a position of a button for activating presentation of the video via the video presentation device, and a position in a video presentation page for physically attaching the video presentation device in a printed hard copy of the yearbook; selecting videos for suggesting to the student for including in the video presentation page of the yearbook, wherein selecting videos for suggesting to the students comprises: determining a time of capture of videos associated with the student; receiving information of timing of a current school year; and preferring videos captured within the current school year over videos captured before the current school year started; sending information describing the selected videos as suggestions for including in the video presentation page of the yearbook; and sending information describing the customizable yearbook for printing one or more hard copies of the customizable yearbook, wherein each printed hard copy of the customizable yearbook comprises the one or more video presentation pages and a video presentation device physically attached to a video presentation page. 5. The method of claim 1 , wherein selecting videos for suggesting to the student further comprises: selecting videos received by the student in messages from other students; and ranking each video received by the student in a message from another student based on a measure of closeness between the student and the other student. | 0.5 |
8,082,220 | 4 | 5 | 4. The computer-readable storage medium of claim 1 , wherein the association is made according to association rules. | 4. The computer-readable storage medium of claim 1 , wherein the association is made according to association rules. 5. The computer-readable storage medium of claim 4 , wherein the association rules are predetermined by an expert. | 0.5 |
8,670,985 | 1 | 6 | 1. A method for processing a voice input provided in response to a prompt, comprising: at an electronic device with at least one processor and memory: in response to a user invoking a voice mode, the electronic device providing a sequence of prompts, wherein each prompt is associated with a respective time period of a plurality of time periods; receiving a voice input while a prompt of the sequence of prompts is being provided; identifying a characteristic time associated with the received voice input; identifying a time period of the plurality of time periods that includes the characteristic time; and applying the received voice input to a respective prompt of the sequence of prompts associated with the identified time period. | 1. A method for processing a voice input provided in response to a prompt, comprising: at an electronic device with at least one processor and memory: in response to a user invoking a voice mode, the electronic device providing a sequence of prompts, wherein each prompt is associated with a respective time period of a plurality of time periods; receiving a voice input while a prompt of the sequence of prompts is being provided; identifying a characteristic time associated with the received voice input; identifying a time period of the plurality of time periods that includes the characteristic time; and applying the received voice input to a respective prompt of the sequence of prompts associated with the identified time period. 6. The method of claim 1 , further comprising: determining the relative importance of each prompt; and varying the length of the time period of each prompt based on the determined relative importance of that prompt. | 0.580078 |
8,566,790 | 9 | 10 | 9. The device of claim 8 , wherein a type definition of the data representation language schema is used to interpret the script. | 9. The device of claim 8 , wherein a type definition of the data representation language schema is used to interpret the script. 10. The device of claim 9 , wherein at least one of the type definitions is a complex type definition. | 0.666667 |
8,095,404 | 17 | 21 | 17. A method for assisting a user in a process of decision-making or analysis involving a topic, with the aid of a computer and a display screen in association with the computer and an application on the computer, comprising using the display, computer, and application for: a. displaying a screen set having information concerning the topic; b. displaying a screen set soliciting a set of input data, and inputting said set of input data, wherein optionally some of the data is characterized with a value representing a degree of certainty regarding the data; c. determining and displaying a current recommendation generated iteratively by processing the input data through at least a portion of the algorithm; d. providing the option to accept the current recommendation as a final recommendation and ending the processing; e. displaying a screen set soliciting additional input data and for modifying previous input data as desired when the current recommendation is not accepted as a final recommendation, the contents of said screen set being dependent on and determined by step (c), and inputting said additional input data or modified previous input data; f. repeating steps (c) and (d), and (e) as desired; and g. displaying a screen set showing the current recommendation or analysis; h. optionally providing information or links in step (c) to modify those inputs which are determined to have the highest importance and thus impact on the current recommendations; i. optionally providing information or links in step (c) to modify those-inputs which are determined to have the greatest effect on the calculated certainty of the current recommendation or analysis; j. optionally providing information or links in step (c) to modify those inputs which are determined to have the greatest effect on the calculated certainty of a particular calculated result. | 17. A method for assisting a user in a process of decision-making or analysis involving a topic, with the aid of a computer and a display screen in association with the computer and an application on the computer, comprising using the display, computer, and application for: a. displaying a screen set having information concerning the topic; b. displaying a screen set soliciting a set of input data, and inputting said set of input data, wherein optionally some of the data is characterized with a value representing a degree of certainty regarding the data; c. determining and displaying a current recommendation generated iteratively by processing the input data through at least a portion of the algorithm; d. providing the option to accept the current recommendation as a final recommendation and ending the processing; e. displaying a screen set soliciting additional input data and for modifying previous input data as desired when the current recommendation is not accepted as a final recommendation, the contents of said screen set being dependent on and determined by step (c), and inputting said additional input data or modified previous input data; f. repeating steps (c) and (d), and (e) as desired; and g. displaying a screen set showing the current recommendation or analysis; h. optionally providing information or links in step (c) to modify those inputs which are determined to have the highest importance and thus impact on the current recommendations; i. optionally providing information or links in step (c) to modify those-inputs which are determined to have the greatest effect on the calculated certainty of the current recommendation or analysis; j. optionally providing information or links in step (c) to modify those inputs which are determined to have the greatest effect on the calculated certainty of a particular calculated result. 21. The method of claim 17 , wherein the algorithm is used with a relational database. | 0.861736 |
10,127,222 | 16 | 18 | 16. A first communication device, comprising: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, comprising: detecting an auto-correction of a target word included in a corrected message comprising a group of words, the target word having a type; detecting a request to transmit the corrected message to a second communication device; and responsive to the detecting the request, presenting a correction alert comprising an audio signal, the correction alert indicating that the target word has been auto-corrected, and indicating the type of the target word, wherein the correction alert is selected from provisioning information accessible to the processing system, wherein the provisioning information is accessed to select the audio signal, wherein the selected audio signal is indexed to an intended recipient of the corrected message, a subject matter of the corrected message, or the type of the target word. | 16. A first communication device, comprising: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, comprising: detecting an auto-correction of a target word included in a corrected message comprising a group of words, the target word having a type; detecting a request to transmit the corrected message to a second communication device; and responsive to the detecting the request, presenting a correction alert comprising an audio signal, the correction alert indicating that the target word has been auto-corrected, and indicating the type of the target word, wherein the correction alert is selected from provisioning information accessible to the processing system, wherein the provisioning information is accessed to select the audio signal, wherein the selected audio signal is indexed to an intended recipient of the corrected message, a subject matter of the corrected message, or the type of the target word. 18. The first communication device of claim 16 , wherein the corrected message is not transmitted to the second communication device until after the presenting the correction alert and receiving a second request to transmit the corrected message. | 0.680519 |
8,650,024 | 11 | 17 | 11. A system of one or more computers configured to perform operations comprising: determining that a plurality of addresses cannot be geocoded by a geocoding system, wherein each address includes a plurality of terms; generating a plurality of variants of the addresses that can be geocoded by the geocoding system, wherein each variant of a respective address lacks a removed term included in the respective address; receiving a plurality of name terms for each variant provided by the geocoding system; associating each removed term with name terms received for all variants that lack the removed term, including determining, for each associated name term of each removed term, a count of the number of variants for which the geocoding system provided the name term; determining, for each associated name term of each removed term, whether the name term is an address term synonym for the removed term based at least in part on the count of the number of variants. | 11. A system of one or more computers configured to perform operations comprising: determining that a plurality of addresses cannot be geocoded by a geocoding system, wherein each address includes a plurality of terms; generating a plurality of variants of the addresses that can be geocoded by the geocoding system, wherein each variant of a respective address lacks a removed term included in the respective address; receiving a plurality of name terms for each variant provided by the geocoding system; associating each removed term with name terms received for all variants that lack the removed term, including determining, for each associated name term of each removed term, a count of the number of variants for which the geocoding system provided the name term; determining, for each associated name term of each removed term, whether the name term is an address term synonym for the removed term based at least in part on the count of the number of variants. 17. The system of claim 11 , wherein determining that a plurality of addresses cannot be geocoded by a geocoding system includes attempting to geocode each potential address in a corpus of potential addresses by sending each potential address to the geocoding system. | 0.692396 |
9,811,383 | 1 | 6 | 1. A method to process a composite task, the method comprising, by a processor: receiving the composite task; transforming the composite task into a set of atomic tasks, wherein each atomic task in the set of atomic tasks includes a respective assertion, wherein each atomic task is a subset task of the composite task, and wherein the set of atomic tasks includes at least a first atomic task, a second atomic task, and a third atomic task; wherein transforming the composite task into the set of atomic tasks includes: transforming the composite task into standard form descriptive logic notation, wherein the standard form descriptive logic notation of the composite task includes inclusion axioms and composite task concepts; transforming the inclusion axioms into additional concepts; transforming the composite task concepts and the additional concepts into negation normal form concepts; and transforming the negation normal form concepts into conjunctions which are used to separate the composite task into the set of atomic tasks; determining that the first atomic task is equivalent to the second atomic task based on an ontology; removing the second atomic task from the set of atomic tasks, based on the determination of equivalence, to generate a list of atomic tasks, wherein the list includes at least the first atomic task and the third atomic task; ordering the list of atomic tasks based on the ontology to produce an ordered list of atomic tasks; and processing at least a first selected atomic task in the ordered list of atomic tasks to process the composite task, wherein the ordered list of atomic tasks includes n atomic tasks, and wherein the first selected atomic task is at a position n/2 or (n+1)/2 within the ordered list of atomic tasks. | 1. A method to process a composite task, the method comprising, by a processor: receiving the composite task; transforming the composite task into a set of atomic tasks, wherein each atomic task in the set of atomic tasks includes a respective assertion, wherein each atomic task is a subset task of the composite task, and wherein the set of atomic tasks includes at least a first atomic task, a second atomic task, and a third atomic task; wherein transforming the composite task into the set of atomic tasks includes: transforming the composite task into standard form descriptive logic notation, wherein the standard form descriptive logic notation of the composite task includes inclusion axioms and composite task concepts; transforming the inclusion axioms into additional concepts; transforming the composite task concepts and the additional concepts into negation normal form concepts; and transforming the negation normal form concepts into conjunctions which are used to separate the composite task into the set of atomic tasks; determining that the first atomic task is equivalent to the second atomic task based on an ontology; removing the second atomic task from the set of atomic tasks, based on the determination of equivalence, to generate a list of atomic tasks, wherein the list includes at least the first atomic task and the third atomic task; ordering the list of atomic tasks based on the ontology to produce an ordered list of atomic tasks; and processing at least a first selected atomic task in the ordered list of atomic tasks to process the composite task, wherein the ordered list of atomic tasks includes n atomic tasks, and wherein the first selected atomic task is at a position n/2 or (n+1)/2 within the ordered list of atomic tasks. 6. The method of claim 1 , further comprising: receiving a response to processing of the first selected atomic task; and determining not to process a second selected atomic task in the ordered list based on the response to processing of the first selected atomic task. | 0.840476 |
10,095,782 | 9 | 12 | 9. A method comprising: receiving using one or more computer processors, from a comments website, an input that includes a plurality of comments related to a target entity, each comment of the plurality of comments including an overall rating related to the target entity and at least one phrase that includes a head term and a modifier associated with the head term that is represented by a bag of phrases; identifying a plurality of aspect clusters based on a plurality of comments, wherein each aspect cluster of the plurality of aspect clusters corresponds to an aspect of the target entity the identifying of the plurality of aspect clusters includes: identifying the head term in the at least one phrase of a portion of the comments in the plurality of comments, and mapping each head term to one of a plurality of aspect clusters; determining an aspect rating corresponding to each of the aspect clusters and the corresponding aspect of the target entity based on an aggregation of the overall ratings in the portion of the plurality of comments, the aspect rating including a numerical measure showing a degree of satisfaction demonstrated in the portion of comments towards the aspect; extracting, from the portion of comments, a representative phrase corresponding of the aspects that supports or explains the aspect rating; generating an output that includes the overall ratings of the portion of comments decomposed into two or more of the aspects of the target entity, the aspects having associated therewith the representative phrases with support information that serve as indices to navigate into a set of specific comments about a particular aspect of the two or more of the aspects; and causing presentation of the generated output on a client machine, to tailor comments related to the target entity to the generated output instead of overall ratings. | 9. A method comprising: receiving using one or more computer processors, from a comments website, an input that includes a plurality of comments related to a target entity, each comment of the plurality of comments including an overall rating related to the target entity and at least one phrase that includes a head term and a modifier associated with the head term that is represented by a bag of phrases; identifying a plurality of aspect clusters based on a plurality of comments, wherein each aspect cluster of the plurality of aspect clusters corresponds to an aspect of the target entity the identifying of the plurality of aspect clusters includes: identifying the head term in the at least one phrase of a portion of the comments in the plurality of comments, and mapping each head term to one of a plurality of aspect clusters; determining an aspect rating corresponding to each of the aspect clusters and the corresponding aspect of the target entity based on an aggregation of the overall ratings in the portion of the plurality of comments, the aspect rating including a numerical measure showing a degree of satisfaction demonstrated in the portion of comments towards the aspect; extracting, from the portion of comments, a representative phrase corresponding of the aspects that supports or explains the aspect rating; generating an output that includes the overall ratings of the portion of comments decomposed into two or more of the aspects of the target entity, the aspects having associated therewith the representative phrases with support information that serve as indices to navigate into a set of specific comments about a particular aspect of the two or more of the aspects; and causing presentation of the generated output on a client machine, to tailor comments related to the target entity to the generated output instead of overall ratings. 12. The method of claim 9 , further comprising evaluating the aspect rating using an aspect rating correlation. | 0.754425 |
8,468,163 | 26 | 30 | 26. A non-transitory computer readable medium storing one or more sequences of instructions for causing an ontology system to provide enhanced search capability, wherein said ontology system maintains information in the form of a plurality of ontologies, wherein each of said plurality of ontologies contains a corresponding plurality of nodes and a corresponding plurality of edges, some of said plurality of edges being of a corresponding one of a plurality of relationship types between a corresponding pair of said plurality of nodes, wherein the relationship type of an edge indicates the specific relation represented by the edge, wherein execution of said one or more sequences of instructions by one or more processors contained in said ontology system causes said ontology system to perform the actions of: receiving a search request specifying a set of nodes and a set of edges of interest, said search request further specifying a corresponding one of a set of relationship types for each of said set of edges of interest, wherein said set of relationship types is contained in said plurality of relationship types, wherein said received search request contains express data which explicitly identifies each of said set of nodes of interest, said set of edges of interest and said set of relationship types; determining a set of ontologies matching said search request based on said set of nodes and said set of edges of interest, wherein said set of ontologies is contained in said plurality of ontologies, wherein said set of ontologies contains a first ontology and a second ontology, said first ontology and said second ontology respectively containing a first edge and a second edge, wherein both of said first edge and said second edge are between a same pair of nodes of said first ontology and said second ontology, wherein both of said same pair of nodes are contained in said set of nodes received in said search request, wherein said first edge in said first ontology is of a first relationship type matching the corresponding relationship type explicitly identified for a first edge of interest in said search request, wherein said first edge of interest is also between said same pair of nodes in said search request, wherein said second edge in said second ontology is not of said first relationship type; computing a match score for each of said set of ontologies, wherein a first match score and a second match score are respectively computed for said first ontology and said second ontology, wherein said first edge contributes more to said first match score than said second edge contributes to said second match score in view of said first edge being of said first relationship type in said first ontology, and said second edge not being of said first relationship type in said second ontology, rank said set of ontologies according to the computed match scores; and send a data indicating said set of ontologies and corresponding ranks as a result of said search request. | 26. A non-transitory computer readable medium storing one or more sequences of instructions for causing an ontology system to provide enhanced search capability, wherein said ontology system maintains information in the form of a plurality of ontologies, wherein each of said plurality of ontologies contains a corresponding plurality of nodes and a corresponding plurality of edges, some of said plurality of edges being of a corresponding one of a plurality of relationship types between a corresponding pair of said plurality of nodes, wherein the relationship type of an edge indicates the specific relation represented by the edge, wherein execution of said one or more sequences of instructions by one or more processors contained in said ontology system causes said ontology system to perform the actions of: receiving a search request specifying a set of nodes and a set of edges of interest, said search request further specifying a corresponding one of a set of relationship types for each of said set of edges of interest, wherein said set of relationship types is contained in said plurality of relationship types, wherein said received search request contains express data which explicitly identifies each of said set of nodes of interest, said set of edges of interest and said set of relationship types; determining a set of ontologies matching said search request based on said set of nodes and said set of edges of interest, wherein said set of ontologies is contained in said plurality of ontologies, wherein said set of ontologies contains a first ontology and a second ontology, said first ontology and said second ontology respectively containing a first edge and a second edge, wherein both of said first edge and said second edge are between a same pair of nodes of said first ontology and said second ontology, wherein both of said same pair of nodes are contained in said set of nodes received in said search request, wherein said first edge in said first ontology is of a first relationship type matching the corresponding relationship type explicitly identified for a first edge of interest in said search request, wherein said first edge of interest is also between said same pair of nodes in said search request, wherein said second edge in said second ontology is not of said first relationship type; computing a match score for each of said set of ontologies, wherein a first match score and a second match score are respectively computed for said first ontology and said second ontology, wherein said first edge contributes more to said first match score than said second edge contributes to said second match score in view of said first edge being of said first relationship type in said first ontology, and said second edge not being of said first relationship type in said second ontology, rank said set of ontologies according to the computed match scores; and send a data indicating said set of ontologies and corresponding ranks as a result of said search request. 30. The non-transitory computer readable medium of claim 26 , wherein said first pair of nodes contains a first node and a second node, wherein said set of ontologies contains a third ontology having a third edge between said first node and a third node, wherein said third node is not contained in said set of nodes but said third edge is of said first relationship type to constitute a half edge in relation to said first edge, wherein said computing computes a third match score for said third ontology, wherein said third edge contributes less to said third match score than said first edge contributes to said first match score. | 0.5 |
9,405,448 | 4 | 6 | 4. A method according to claim 3 , further comprising: identifying one or more patterns in the another data channel by: assigning an importance level to one or more unexpected patterns; and identifying one or more significant patterns of the one or more unexpected patterns, wherein a significant pattern is an unexpected pattern. | 4. A method according to claim 3 , further comprising: identifying one or more patterns in the another data channel by: assigning an importance level to one or more unexpected patterns; and identifying one or more significant patterns of the one or more unexpected patterns, wherein a significant pattern is an unexpected pattern. 6. A method according to claim 4 , wherein the one or more unexpected patterns are identified within the time period of the graph. | 0.870775 |
8,161,112 | 1 | 4 | 1. A method for delivering dynamic media content to collaborators, the method comprising: providing collaborative event media content, wherein the collaborative event media content further comprises a grammar and a structured document, said structured document comprising a plurality of classified structural elements; acquiring data representing a client's environmental condition; storing, in the context server in a data structure comprising a dynamic client context for the client, the data representing a client's environmental condition; detecting an event in dependence upon the dynamic client context; identifying one or more collaborators in dependence upon the dynamic client context and the event; selecting from the structured document a classified structural element from among the plurality of classified structural elements based upon an event type and a collaborator classification associated with a collaborator among the one or more collaborators; and transmitting the selected classified structural element to the collaborator. | 1. A method for delivering dynamic media content to collaborators, the method comprising: providing collaborative event media content, wherein the collaborative event media content further comprises a grammar and a structured document, said structured document comprising a plurality of classified structural elements; acquiring data representing a client's environmental condition; storing, in the context server in a data structure comprising a dynamic client context for the client, the data representing a client's environmental condition; detecting an event in dependence upon the dynamic client context; identifying one or more collaborators in dependence upon the dynamic client context and the event; selecting from the structured document a classified structural element from among the plurality of classified structural elements based upon an event type and a collaborator classification associated with a collaborator among the one or more collaborators; and transmitting the selected classified structural element to the collaborator. 4. The method of claim 1 wherein detecting an event in dependence upon the dynamic client context further comprises: detecting a change in a value of a data element in the dynamic client context; and applying an event detection rules base to the dynamic client context. | 0.801329 |
8,458,207 | 15 | 20 | 15. A system for providing search results, the system comprising: a computing device coupled to a memory, the memory storing computer-executable instructions to: receive, by a search engine, a search string comprising search; identify pages relevant to the search string; for each of the identified pages relevant to the search string: obtain a snippet for the corresponding identified page, the snippet is an excerpt from the corresponding identified page, the snippet, generated by searching a database, illustrates relevance of the corresponding identified page to the search string; determine that the snippet does not contain search terms of the search string, obtaining reference information comprising first anchor text of a link to the corresponding identified page from a web page other than the corresponding identified page, the first anchor text is used by the web page other than the corresponding identified page to reference the corresponding identified page; and display links to each identified page with the snippet and the obtained reference information for the identified page, wherein the reference information further comprises a second anchor text used by another page to link to the at least one of the identified pages, wherein the second anchor text is different from the first anchor text, and wherein the second anchor text is relevant to the search string. | 15. A system for providing search results, the system comprising: a computing device coupled to a memory, the memory storing computer-executable instructions to: receive, by a search engine, a search string comprising search; identify pages relevant to the search string; for each of the identified pages relevant to the search string: obtain a snippet for the corresponding identified page, the snippet is an excerpt from the corresponding identified page, the snippet, generated by searching a database, illustrates relevance of the corresponding identified page to the search string; determine that the snippet does not contain search terms of the search string, obtaining reference information comprising first anchor text of a link to the corresponding identified page from a web page other than the corresponding identified page, the first anchor text is used by the web page other than the corresponding identified page to reference the corresponding identified page; and display links to each identified page with the snippet and the obtained reference information for the identified page, wherein the reference information further comprises a second anchor text used by another page to link to the at least one of the identified pages, wherein the second anchor text is different from the first anchor text, and wherein the second anchor text is relevant to the search string. 20. The system of claim 15 , the memory further storing computer-executable instructions to select the first anchor text from among multiple anchor text wordings based in part on similarity between the search string and a combination of elements present in the at least one of the identified pages and elements present in the first anchor text. | 0.5 |
8,468,442 | 1 | 9 | 1. A method of viewing information associated with business and/or financial data, comprising: parsing a document to retrieve information associated with business and/or financial data, the document including the business and/or financial data and the associated information; processing the associated information to identify at least one sentence included in the associated information; and for each sentence of the at least one sentence identified in the processing, identifying a topic of the sentence, wherein identifying a topic of the sentence comprises: comparing the sentence to at least one category in a taxonomy corresponding to the business and/or financial data to determine whether the topic of the sentence corresponds to the at least one category of the taxonomy corresponding to the business and/or financial data, each category of the at least one category in the taxonomy corresponding to a meaning of a type of business data or a type of financial data; assigning, based at least in part on the comparing, at least one association strength to the sentence, each of the at least one association strength indicating a likelihood that the topic of the sentence actually corresponds to one of the at least one category in the taxonomy; filtering the at least one association strength to determine one or more categories of the at least one category in the taxonomy with which to match the sentence; and outputting the sentence matched, based at least in part on the filtering, with the one or more categories of the at least one category in the taxonomy; wherein: the business and/or financial data of the document comprises a plurality of items of business and/or financial content, each item of the plurality of items being categorized according to at least one second category of a second set of categories; a sentence of the at least one sentence relates to at least one item of the plurality of items; outputting the sentence matched with the one or more categories comprises outputting the sentence matched with a first category of the at least one category of the taxonomy; one or more categories of the at least one category in the taxonomy correspond to one or more second categories of the second set of categories; and the method further comprises: evaluating the first category of the taxonomy with which the sentence is matched to determine an item of the plurality of items to which the sentence is related, associating the item of the plurality of items with at least one portion of a structured document, and associating the sentence with the at least one portion of the structured document. | 1. A method of viewing information associated with business and/or financial data, comprising: parsing a document to retrieve information associated with business and/or financial data, the document including the business and/or financial data and the associated information; processing the associated information to identify at least one sentence included in the associated information; and for each sentence of the at least one sentence identified in the processing, identifying a topic of the sentence, wherein identifying a topic of the sentence comprises: comparing the sentence to at least one category in a taxonomy corresponding to the business and/or financial data to determine whether the topic of the sentence corresponds to the at least one category of the taxonomy corresponding to the business and/or financial data, each category of the at least one category in the taxonomy corresponding to a meaning of a type of business data or a type of financial data; assigning, based at least in part on the comparing, at least one association strength to the sentence, each of the at least one association strength indicating a likelihood that the topic of the sentence actually corresponds to one of the at least one category in the taxonomy; filtering the at least one association strength to determine one or more categories of the at least one category in the taxonomy with which to match the sentence; and outputting the sentence matched, based at least in part on the filtering, with the one or more categories of the at least one category in the taxonomy; wherein: the business and/or financial data of the document comprises a plurality of items of business and/or financial content, each item of the plurality of items being categorized according to at least one second category of a second set of categories; a sentence of the at least one sentence relates to at least one item of the plurality of items; outputting the sentence matched with the one or more categories comprises outputting the sentence matched with a first category of the at least one category of the taxonomy; one or more categories of the at least one category in the taxonomy correspond to one or more second categories of the second set of categories; and the method further comprises: evaluating the first category of the taxonomy with which the sentence is matched to determine an item of the plurality of items to which the sentence is related, associating the item of the plurality of items with at least one portion of a structured document, and associating the sentence with the at least one portion of the structured document. 9. The method of claim 1 , wherein: associating the item with the at least one portion of the structured document comprises storing the item as content of a cell of a spreadsheet; and associating the sentence with the at least one portion of the structured document comprises associating the sentence with the at least one sentence such that, in response to receiving input from a user that requests output of the associated information and that identifies the at least one portion of the structured document, at least the sentence is output. | 0.716823 |
8,161,465 | 9 | 10 | 9. The non-transitory computer-readable storage medium of claim 8 , wherein the method further comprises storing the variable used during the evaluation of the condition to a persistent storage. | 9. The non-transitory computer-readable storage medium of claim 8 , wherein the method further comprises storing the variable used during the evaluation of the condition to a persistent storage. 10. The non-transitory computer-readable storage medium of claim 9 , wherein if the variable used during a conditional compilation has a changed value, the method further comprises: re-evaluating the condition based on the programming language file; creating a new preprocessed programming language file by conditionally including source code associated with the preprocessing directive based upon the re-evaluation of the condition; and compiling the new preprocessed programming language file. | 0.5 |
7,729,916 | 27 | 28 | 27. The method of claim 1 , further comprising the step of: memorizing an event, wherein the event comprises one of a user command, a user preference, an I/O event, and results of an executed task; and subsequently activating the memorized event at a desired time during the dialog. | 27. The method of claim 1 , further comprising the step of: memorizing an event, wherein the event comprises one of a user command, a user preference, an I/O event, and results of an executed task; and subsequently activating the memorized event at a desired time during the dialog. 28. The method of claim 27 , wherein the step of activating comprises activating the memorized event for presentation to the user. | 0.657895 |
8,312,022 | 23 | 24 | 23. The non-transitory computer readable storage medium of claim 18 wherein the method further comprises calculating relevancy scores for each of the plurality of multimedia content elements based on a degree of match between the extracted keywords and each topic in the topic listing. | 23. The non-transitory computer readable storage medium of claim 18 wherein the method further comprises calculating relevancy scores for each of the plurality of multimedia content elements based on a degree of match between the extracted keywords and each topic in the topic listing. 24. The non-transitory computer readable storage medium of claim 23 wherein the links to the multimedia content elements are ordered based on the relevancy scores of respective content elements. | 0.5 |
8,914,358 | 13 | 14 | 13. The system of claim 12 , wherein the operations further comprise: determining the second search query is related to the first search query based on a temporal relationship between the first search query and the second search query. | 13. The system of claim 12 , wherein the operations further comprise: determining the second search query is related to the first search query based on a temporal relationship between the first search query and the second search query. 14. The system of claim 13 , wherein the temporal relationship is determined by analyzing log files. | 0.5 |
8,281,310 | 1 | 9 | 1. A method comprising: retrieving, by a computer-based system for generating a job flowchart, job scheduling data based on a parameter, wherein said job scheduling data defines automated tasks, wherein said computer-based system includes a non-transitory memory and processor; transforming, by said computer-based system, said job scheduling data into a text file, wherein said job scheduling data is automatically transformed into a text file in response to predetermined, intervals; assigning, by said computer-based system, a file extension to said text file based on a charting application; and transmitting, by said computer-based system, said text file to facilitate opening said text file within said charting application, wherein said text file comprises said job flowchart. | 1. A method comprising: retrieving, by a computer-based system for generating a job flowchart, job scheduling data based on a parameter, wherein said job scheduling data defines automated tasks, wherein said computer-based system includes a non-transitory memory and processor; transforming, by said computer-based system, said job scheduling data into a text file, wherein said job scheduling data is automatically transformed into a text file in response to predetermined, intervals; assigning, by said computer-based system, a file extension to said text file based on a charting application; and transmitting, by said computer-based system, said text file to facilitate opening said text file within said charting application, wherein said text file comprises said job flowchart. 9. The computer-implemented method of claim 1 , further comprising receiving a request for said job flowchart from a personalized control panel interface. | 0.598958 |
9,665,765 | 1 | 15 | 1. A method comprising, by a computing device: accessing an image associated with an online social network, wherein the image portrays at least a first person; calculating, for each user in a first set of users of the online social network, a facial-recognition score with respect to the first person portrayed in the image, wherein the facial-recognition score is based at least in part on: a social-graph affinity associated with the user; and a facial-representation associated with the user, wherein the facial-representation associated with the user is compared with the image; and tagging the image with a particular user in the first set of users based on the calculated facial-recognition scores. | 1. A method comprising, by a computing device: accessing an image associated with an online social network, wherein the image portrays at least a first person; calculating, for each user in a first set of users of the online social network, a facial-recognition score with respect to the first person portrayed in the image, wherein the facial-recognition score is based at least in part on: a social-graph affinity associated with the user; and a facial-representation associated with the user, wherein the facial-representation associated with the user is compared with the image; and tagging the image with a particular user in the first set of users based on the calculated facial-recognition scores. 15. The method of claim 1 , wherein the facial-recognition score for each user measures a probability that the user matches the first person portrayed in the image. | 0.813636 |
9,386,037 | 1 | 6 | 1. A method for determining a similarity between two websites, the method comprising, at a computer system: receiving website information from a web server corresponding to a website; rendering a document object model (DOM) object of the website using the website information; separating content within the DOM object into a plurality of data portions, each of the plurality of data portions having a fixed length; generating, by a hardware processor of the computer system, a hash signature of the DOM object by: applying a predetermined number of hashing functions to each of the plurality of data portions, wherein the predetermined number of hashing functions are generated using a common seed value, and wherein applying the predetermined number of hashing functions results in a predetermined number of values for each of the plurality of data portions; and selecting, using a selection policy, a predetermined number of hashed data portions of the plurality of hashed data portions, wherein the predetermined number of hashed data portions are selected to create a hash signature of the DOM object; comparing the hash signature of the DOM object to a known hash signature of a DOM object associated with a known website having a first classification, wherein comparing the hash signature of the DOM object to the known hash signature of the DOM object associated with the known website includes comparing each of the plurality of hashed data portions to a plurality of known hashed data portions of the known hash signature; calculating a similarity measurement between the hash signature of the DOM object and the known hash signature of the DOM object associated with the known website; comparing the similarity measurement to a threshold; and determining that the website has the first classification based on the similarity measurement exceeding the threshold. | 1. A method for determining a similarity between two websites, the method comprising, at a computer system: receiving website information from a web server corresponding to a website; rendering a document object model (DOM) object of the website using the website information; separating content within the DOM object into a plurality of data portions, each of the plurality of data portions having a fixed length; generating, by a hardware processor of the computer system, a hash signature of the DOM object by: applying a predetermined number of hashing functions to each of the plurality of data portions, wherein the predetermined number of hashing functions are generated using a common seed value, and wherein applying the predetermined number of hashing functions results in a predetermined number of values for each of the plurality of data portions; and selecting, using a selection policy, a predetermined number of hashed data portions of the plurality of hashed data portions, wherein the predetermined number of hashed data portions are selected to create a hash signature of the DOM object; comparing the hash signature of the DOM object to a known hash signature of a DOM object associated with a known website having a first classification, wherein comparing the hash signature of the DOM object to the known hash signature of the DOM object associated with the known website includes comparing each of the plurality of hashed data portions to a plurality of known hashed data portions of the known hash signature; calculating a similarity measurement between the hash signature of the DOM object and the known hash signature of the DOM object associated with the known website; comparing the similarity measurement to a threshold; and determining that the website has the first classification based on the similarity measurement exceeding the threshold. 6. The method of claim 1 , wherein the similarity measurement includes a magnitude of hashed data portions that are shared between the hash signature of the DOM object and the known hash signature of the DOM object associated with the known website divided by a magnitude of hashed data portions including the plurality of hashed data portions and the plurality of known hashed data portions of the known hash signature. | 0.823232 |
10,157,347 | 1 | 2 | 1. A method, comprising: building a domain model for processing data specific to an enterprise; applying historical enterprise data and contextual data to the model to build entity relations annotated with contextual data; wherein said method comprises sending said enterprise data and/or said contextual data to one or more of an importer module, an extraction module, a learning module, a classification module, a feedback module, a scoring module, and/or an export module; extracting features of interest from the annotated entity relations defined in the domain model; classifying and clustering the features to develop enterprise-specific metadata; storing the metadata for use by the domain model; and receiving and applying expert feedback to improve the model. | 1. A method, comprising: building a domain model for processing data specific to an enterprise; applying historical enterprise data and contextual data to the model to build entity relations annotated with contextual data; wherein said method comprises sending said enterprise data and/or said contextual data to one or more of an importer module, an extraction module, a learning module, a classification module, a feedback module, a scoring module, and/or an export module; extracting features of interest from the annotated entity relations defined in the domain model; classifying and clustering the features to develop enterprise-specific metadata; storing the metadata for use by the domain model; and receiving and applying expert feedback to improve the model. 2. The method of claim 1 , wherein building the domain model comprises: adapting enterprise data by allowing expert to identify the features of interest; auto-suggesting appropriate learning algorithm; and interacting with the expert to learn domain knowledge. | 0.761029 |
9,448,990 | 15 | 20 | 15. A system for creating a language model, the system comprising: a processor; a data remembrance component; an input device; a display device; a web crawler that collects a set of documents, that evaluates said documents and that counts occurrence of N-grams in said documents, that creates data indicating counts of N-grams in said documents,that is configured to indicate counts of N-grams in a first set of documents, wherein said web crawler is configured to create a quantity indicating how well a first statistical language model predicts counts of N-grams in said first set of documents, and is configured to create a second statistical language model based on a first probability distribution in said first statistical language model, a second probability distribution based on N-gram counts of said first set of documents, and said quantity, M being a number of N-grams in said first set of documents, said web crawler being configured to create said quantity by calculating a divergence between said first probability distribution and said second probability distribution, and by raising a number to a power that is based on said divergence; and a text receipt component that is stored in said data remembrance component, that executes on said processor, that is configured to receive text entered by a user, and that is configured to use said second statistical language model to present, on said display, suggested phrases that begin with said text entered by said user. | 15. A system for creating a language model, the system comprising: a processor; a data remembrance component; an input device; a display device; a web crawler that collects a set of documents, that evaluates said documents and that counts occurrence of N-grams in said documents, that creates data indicating counts of N-grams in said documents,that is configured to indicate counts of N-grams in a first set of documents, wherein said web crawler is configured to create a quantity indicating how well a first statistical language model predicts counts of N-grams in said first set of documents, and is configured to create a second statistical language model based on a first probability distribution in said first statistical language model, a second probability distribution based on N-gram counts of said first set of documents, and said quantity, M being a number of N-grams in said first set of documents, said web crawler being configured to create said quantity by calculating a divergence between said first probability distribution and said second probability distribution, and by raising a number to a power that is based on said divergence; and a text receipt component that is stored in said data remembrance component, that executes on said processor, that is configured to receive text entered by a user, and that is configured to use said second statistical language model to present, on said display, suggested phrases that begin with said text entered by said user. 20. The system of claim 15 , said documents comprising web documents. | 0.900862 |
9,881,006 | 1 | 3 | 1. A computer implemented method comprising: receiving a first set of item listings for the sale of products or services in a first language and a second set of item listings for the sale of products or services in a second language, each of the item listings in the first and second sets of item listings comprising one or more descriptions and metadata identifying the products or services corresponding to the respective item listing; collecting the metadata from the first and second sets of item listings and aligning, using the collected metadata identifying the products or services, a first item listing of the first set of item listings with a second item listing of the second set of item listings in which the first item listing and the second item listing are aligned based on the first item listing and the second item listing being directed toward the same products or services; mapping the first item listing to the second item listing based on the aligning of the first item listing with the second item listing; fetching a first description of the first item listing and a second description of the second item listing; measuring the structural similarity of the fetched first description with respect to the fetched second description to assess whether the first description and the second description are likely to be translations of each other; and in response to the first description and the second description being structurally similar, forming the first description into a first sentence in the first language as a translation of the second description into the first language and forming the second description into a second sentence in the second language as a translation of the first description into the second language. | 1. A computer implemented method comprising: receiving a first set of item listings for the sale of products or services in a first language and a second set of item listings for the sale of products or services in a second language, each of the item listings in the first and second sets of item listings comprising one or more descriptions and metadata identifying the products or services corresponding to the respective item listing; collecting the metadata from the first and second sets of item listings and aligning, using the collected metadata identifying the products or services, a first item listing of the first set of item listings with a second item listing of the second set of item listings in which the first item listing and the second item listing are aligned based on the first item listing and the second item listing being directed toward the same products or services; mapping the first item listing to the second item listing based on the aligning of the first item listing with the second item listing; fetching a first description of the first item listing and a second description of the second item listing; measuring the structural similarity of the fetched first description with respect to the fetched second description to assess whether the first description and the second description are likely to be translations of each other; and in response to the first description and the second description being structurally similar, forming the first description into a first sentence in the first language as a translation of the second description into the first language and forming the second description into a second sentence in the second language as a translation of the first description into the second language. 3. The method of claim 1 , further comprising sorting the metadata based on one of a bar code, an item identifier, an item title, a Universal Product Code (UPC) aspect name, a European Article Number (EAN) aspect name, a UPC aspect value, an EAN aspect value, an International Standard Book Number (ISBN), a category identifier, a site identifier, a seller identifier, a picture of the item, or an auction end date. | 0.5 |
7,685,555 | 1 | 5 | 1. Within a computer-based Electronic Design Automation (EDA) tool executing within a computer, a method of macro inference comprising: translating a hardware description language (HDL) template into a macro template using an elaboration process of the EDA tool; translating a circuit design into a format corresponding to the macro template using the elaboration process of the EDA tool; matching, using the EDA tool, a portion of the translated circuit design with the macro template; replacing the portion of the circuit design matching the macro template with a macro associated with the macro template using the EDA tool, wherein an updated circuit design is generated; and storing the updated circuit design. | 1. Within a computer-based Electronic Design Automation (EDA) tool executing within a computer, a method of macro inference comprising: translating a hardware description language (HDL) template into a macro template using an elaboration process of the EDA tool; translating a circuit design into a format corresponding to the macro template using the elaboration process of the EDA tool; matching, using the EDA tool, a portion of the translated circuit design with the macro template; replacing the portion of the circuit design matching the macro template with a macro associated with the macro template using the EDA tool, wherein an updated circuit design is generated; and storing the updated circuit design. 5. The method of claim 1 , further comprising storing the macro template within a macro template library comprising a plurality of macro templates. | 0.659722 |
8,117,225 | 15 | 53 | 15. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information capable of being used to access a plurality of different online applications associated with an online application system including a first online application that provides access to a first one or more files associated with the first online application, a second online application that provides access to a second one or more files associated with the second online application, a third online application that provides access to a third one or more files associated with the third online application, and a fourth online application that provides access to a fourth one or more files associated with the fourth online application; code for receiving the global unique user login information in connection with a login; code for receiving an indication to add access to the first online application, utilizing at least one first online application identifier associated with the first online application; code for receiving an indication to add access to the second online application, utilizing at least one second online application identifier associated with the second online application; code for receiving an indication to add access to the third online application, utilizing at least one third online application identifier associated with the third online application; code for receiving an indication to add access to the fourth online application, utilizing at least one fourth online application identifier associated with the fourth online application; code for allowing registration of the first online application; code for allowing registration of the second online application; code for allowing registration of the third online application; code for allowing registration of the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application; code for identifying at least one profile, the at least one profile including: at least one user profile of an accessing user, the at least one user profile including: registration information determined when the accessing user registered, and automatically determined information that is determined automatically based on user selections of the accessing user; and at least one group profile; code for displaying a search interface in connection with the online application system, the search interface being displayed simultaneously with an advertisement that is selected based on the registration information and the automatically determined information of the at least one user profile, and the at least one group profile; code for performing a search in connection with the online application system utilizing the search interface; and code for displaying search results of the search, where the search results involve a plurality of the different online applications associated with the online application system. | 15. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information capable of being used to access a plurality of different online applications associated with an online application system including a first online application that provides access to a first one or more files associated with the first online application, a second online application that provides access to a second one or more files associated with the second online application, a third online application that provides access to a third one or more files associated with the third online application, and a fourth online application that provides access to a fourth one or more files associated with the fourth online application; code for receiving the global unique user login information in connection with a login; code for receiving an indication to add access to the first online application, utilizing at least one first online application identifier associated with the first online application; code for receiving an indication to add access to the second online application, utilizing at least one second online application identifier associated with the second online application; code for receiving an indication to add access to the third online application, utilizing at least one third online application identifier associated with the third online application; code for receiving an indication to add access to the fourth online application, utilizing at least one fourth online application identifier associated with the fourth online application; code for allowing registration of the first online application; code for allowing registration of the second online application; code for allowing registration of the third online application; code for allowing registration of the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application; code for identifying at least one profile, the at least one profile including: at least one user profile of an accessing user, the at least one user profile including: registration information determined when the accessing user registered, and automatically determined information that is determined automatically based on user selections of the accessing user; and at least one group profile; code for displaying a search interface in connection with the online application system, the search interface being displayed simultaneously with an advertisement that is selected based on the registration information and the automatically determined information of the at least one user profile, and the at least one group profile; code for performing a search in connection with the online application system utilizing the search interface; and code for displaying search results of the search, where the search results involve a plurality of the different online applications associated with the online application system. 53. The computer program product of claim 15 , wherein the computer program product is operable such that the at least one first online application identifier is identified by a provider other than the accessing user. | 0.857612 |
7,818,682 | 1 | 7 | 1. A computer program product, stored on a machine-readable medium, the computer program product comprising instructions operable to cause a data processing apparatus to: display an integrated development environment, the integrated development environment including a first user interface for managing an application model and a second user interface for drafting a graphical model, wherein the application model corresponds to an application being developed, the application model comprising a plurality of development objects used in the application and relationships between the development objects, wherein the graphical model comprises a plurality of graphical objects that represent, graphically, the development objects in the application model and the relationships between the development objects, and wherein the first and second user interfaces display a design-time view of the application model corresponding to the application and the graphical model corresponding to the application model; generate, independent of the application model and in response to input from the user, one or more first graphical objects; select, in response to input from the user, a first development object from the plurality of development objects to be associated with a first graphical object of the one or more first graphical objects; and associate the first development object with the first graphical object. | 1. A computer program product, stored on a machine-readable medium, the computer program product comprising instructions operable to cause a data processing apparatus to: display an integrated development environment, the integrated development environment including a first user interface for managing an application model and a second user interface for drafting a graphical model, wherein the application model corresponds to an application being developed, the application model comprising a plurality of development objects used in the application and relationships between the development objects, wherein the graphical model comprises a plurality of graphical objects that represent, graphically, the development objects in the application model and the relationships between the development objects, and wherein the first and second user interfaces display a design-time view of the application model corresponding to the application and the graphical model corresponding to the application model; generate, independent of the application model and in response to input from the user, one or more first graphical objects; select, in response to input from the user, a first development object from the plurality of development objects to be associated with a first graphical object of the one or more first graphical objects; and associate the first development object with the first graphical object. 7. The computer program product of claim 1 , wherein the graphical model comprises one or more graphical objects, and wherein a graphical object in the graphical model is a free formed object or a pre-defined object selected from a template of graphical objects. | 0.726514 |
8,457,663 | 1 | 7 | 1. A method for phone number encapsulation using a token based framework, comprising: a processor executing code in a memory to create a first plurality of generic tokens for a first cell phone user by a first cell phone service provider to which the first cell phone user is subscribed, wherein the first plurality of generic tokens resides with the first cell phone service provider and each include: a respective unique privacy token for the first cell phone user, wherein the respective unique privacy token includes a unique code identifying the first cell phone service provider and a respective unique token number; a phone number for a cell phone of the first cell phone user; and a respective privacy setting; issuing a first plurality of privacy tokens to the cell phone of the first cell phone user by the first cell phone service provider, wherein the first plurality of privacy tokens comprises the respective unique privacy token for each of the first plurality of generic tokens; receiving one of a second plurality of privacy tokens from the cell phone of the first cell phone user by the first cell phone service provider, wherein: the one of the second plurality of privacy tokens is associated with one of the first plurality of privacy tokens by the first cell phone user; the one of the second plurality of privacy tokens is received by the first cell phone user from a second cell phone user through an exchange between the cell phone of the first cell phone user and a cell phone of the second cell phone user; the second plurality of privacy tokens is received by the cell phone of the second cell phone user from a second cell phone service provider to which the second cell phone user is subscribed and comprises a respective unique privacy token for the second cell phone user corresponding to each of a second plurality of generic tokens for the second cell phone user created by the second cell phone service provider, wherein each respective unique privacy token includes a unique code identifying the second cell phone service provider and a respective unique token number, and the second plurality of generic tokens resides with the second cell phone service provider and each include the respective unique privacy token, a phone number for the cell phone of the second cell phone user, and a respective privacy setting; the one of the first plurality of privacy tokens is received by the second cell phone user from the first cell phone user through the exchange between the cell phone of the first cell phone user and the cell phone of the second cell phone user; the one of the first plurality of privacy tokens is associated with the one of the second plurality of privacy tokens by the second cell phone user; and the one of the first plurality of privacy tokens is received from the cell phone of the second cell phone user by the second cell phone service provider; and updating a one of the first plurality of generic tokens that includes the one of the first plurality of privacy tokens by adding the one of the second plurality of privacy tokens by the first cell phone service provider, wherein a one of the second plurality of generic tokens that includes the one of the second plurality of privacy tokens is updated by adding the one of the first plurality of privacy tokens by the second cell phone service provider; wherein the one of the first plurality of generic tokens and the one of the second plurality of generic tokens facilitate the first cell phone user to call the cell phone of the second cell phone user via the cell phone of the first cell phone user and the second cell phone user to call the cell phone of the first cell phone user via the cell phone of the second cell phone user without a disclosure of the phone number for the cell phone of the second cell phone user to the first cell phone user or an other party or a disclosure of the phone number for the cell phone of the first cell phone user to the second cell phone user or the other party. | 1. A method for phone number encapsulation using a token based framework, comprising: a processor executing code in a memory to create a first plurality of generic tokens for a first cell phone user by a first cell phone service provider to which the first cell phone user is subscribed, wherein the first plurality of generic tokens resides with the first cell phone service provider and each include: a respective unique privacy token for the first cell phone user, wherein the respective unique privacy token includes a unique code identifying the first cell phone service provider and a respective unique token number; a phone number for a cell phone of the first cell phone user; and a respective privacy setting; issuing a first plurality of privacy tokens to the cell phone of the first cell phone user by the first cell phone service provider, wherein the first plurality of privacy tokens comprises the respective unique privacy token for each of the first plurality of generic tokens; receiving one of a second plurality of privacy tokens from the cell phone of the first cell phone user by the first cell phone service provider, wherein: the one of the second plurality of privacy tokens is associated with one of the first plurality of privacy tokens by the first cell phone user; the one of the second plurality of privacy tokens is received by the first cell phone user from a second cell phone user through an exchange between the cell phone of the first cell phone user and a cell phone of the second cell phone user; the second plurality of privacy tokens is received by the cell phone of the second cell phone user from a second cell phone service provider to which the second cell phone user is subscribed and comprises a respective unique privacy token for the second cell phone user corresponding to each of a second plurality of generic tokens for the second cell phone user created by the second cell phone service provider, wherein each respective unique privacy token includes a unique code identifying the second cell phone service provider and a respective unique token number, and the second plurality of generic tokens resides with the second cell phone service provider and each include the respective unique privacy token, a phone number for the cell phone of the second cell phone user, and a respective privacy setting; the one of the first plurality of privacy tokens is received by the second cell phone user from the first cell phone user through the exchange between the cell phone of the first cell phone user and the cell phone of the second cell phone user; the one of the first plurality of privacy tokens is associated with the one of the second plurality of privacy tokens by the second cell phone user; and the one of the first plurality of privacy tokens is received from the cell phone of the second cell phone user by the second cell phone service provider; and updating a one of the first plurality of generic tokens that includes the one of the first plurality of privacy tokens by adding the one of the second plurality of privacy tokens by the first cell phone service provider, wherein a one of the second plurality of generic tokens that includes the one of the second plurality of privacy tokens is updated by adding the one of the first plurality of privacy tokens by the second cell phone service provider; wherein the one of the first plurality of generic tokens and the one of the second plurality of generic tokens facilitate the first cell phone user to call the cell phone of the second cell phone user via the cell phone of the first cell phone user and the second cell phone user to call the cell phone of the first cell phone user via the cell phone of the second cell phone user without a disclosure of the phone number for the cell phone of the second cell phone user to the first cell phone user or an other party or a disclosure of the phone number for the cell phone of the first cell phone user to the second cell phone user or the other party. 7. The method as claimed in claim 1 , wherein the exchange between the cell phone of the first cell phone user and the cell phone of the second cell phone user comprises one of infrared (IR) signal communication or low power radio frequency (RF) signal communication between the cell phone of the first cell phone user and the cell phone of the second cell phone user. | 0.902023 |
9,043,252 | 3 | 6 | 3. An information handling system, comprising: one or more processing devices configured to execute a network management system (NMS) that includes an ontology-based command line interface (CLI) knowledge model; where the one or more processing devices of the information handling system are configured to be communicatively-coupled across a network to one or more network devices of a networking system; where the one or more processing devices are configured to execute the NMS to maintain and administer the networking system using the ontology-based CLI knowledge model; where the ontology-based command line interface (CLI) knowledge model includes one or more domain categories, each of the domain categories including multiple concepts therein that are interlinked with other concepts in the same or different domain category of the ontology-based CLI knowledge model to define the relationship between the separate interlinked concepts; and where the ontology-based CLI knowledge model comprises an ontology build module, the one or more processing devices are configured to execute the ontology build module as one or more ontology build steps that comprise: a seed learning step where build parameter information is received by the ontology build module, a learning and knowledge building step for CLI command structure and network device behavior where each given one of the network devices is interrogated over the network to elicit and receive a response from the given network device describing one or more of the CLI characteristics it possesses, and a CLI knowledge model creation step where the one or more CLI characteristics received from each given network device is organized as CLI data to create a CLI knowledge model. | 3. An information handling system, comprising: one or more processing devices configured to execute a network management system (NMS) that includes an ontology-based command line interface (CLI) knowledge model; where the one or more processing devices of the information handling system are configured to be communicatively-coupled across a network to one or more network devices of a networking system; where the one or more processing devices are configured to execute the NMS to maintain and administer the networking system using the ontology-based CLI knowledge model; where the ontology-based command line interface (CLI) knowledge model includes one or more domain categories, each of the domain categories including multiple concepts therein that are interlinked with other concepts in the same or different domain category of the ontology-based CLI knowledge model to define the relationship between the separate interlinked concepts; and where the ontology-based CLI knowledge model comprises an ontology build module, the one or more processing devices are configured to execute the ontology build module as one or more ontology build steps that comprise: a seed learning step where build parameter information is received by the ontology build module, a learning and knowledge building step for CLI command structure and network device behavior where each given one of the network devices is interrogated over the network to elicit and receive a response from the given network device describing one or more of the CLI characteristics it possesses, and a CLI knowledge model creation step where the one or more CLI characteristics received from each given network device is organized as CLI data to create a CLI knowledge model. 6. The information handling system of claim 3 , where the one or more processing devices are configured to execute the ontology build module to control the starting and stopping points of the ontology build steps. | 0.820405 |
9,697,283 | 4 | 6 | 4. The system of claim 1 , wherein the prior user interactions include a first prior user interaction and a second prior user interaction and wherein the first plurality of categories includes a first category and a second category. | 4. The system of claim 1 , wherein the prior user interactions include a first prior user interaction and a second prior user interaction and wherein the first plurality of categories includes a first category and a second category. 6. The system of claim 4 , wherein the second prior user interaction includes viewing an item that is described by the second listing that is included in the second category. | 0.502857 |
9,904,679 | 8 | 9 | 8. The computer-implemented method of claim 7 , wherein determining the quality rating for the translation is based at least in part on qualification information for the viewing user. | 8. The computer-implemented method of claim 7 , wherein determining the quality rating for the translation is based at least in part on qualification information for the viewing user. 9. The computer-implemented method of claim 8 , wherein the qualification information for the viewing user is based at least in part on one or more quality ratings for one or more translations generated by the viewing user. | 0.5 |
5,507,649 | 6 | 7 | 6. An educational device as claimed in claim 5 wherein said tactile-visual aids comprise: a first set of nearest neighbor linkages between said four rings of said first set of four rings allowing to simultaneously and unambiguously fit the said four rings on the four specific fingers of the left hand, and a second set of nearest neighbor linkages between said four rings of said second set of four rings allowing to simultaneously and unambiguously fit the said four rings on the four specific fingers of the right hand. | 6. An educational device as claimed in claim 5 wherein said tactile-visual aids comprise: a first set of nearest neighbor linkages between said four rings of said first set of four rings allowing to simultaneously and unambiguously fit the said four rings on the four specific fingers of the left hand, and a second set of nearest neighbor linkages between said four rings of said second set of four rings allowing to simultaneously and unambiguously fit the said four rings on the four specific fingers of the right hand. 7. An educational device as claimed in claim 6 wherein: said ring of said first set of four rings to be worn on a major finger of the left hand is attached to the top of a first triangular-shaped network of interconnections; said ring of said second set of four rings to be worn on a major finger of the right hand is attached to the top of a second triangular-shaped network of interconnections; said first triangular-shaped network of interconnections being attached at its base to a first bracelet, said first bracelet to be worn on the wrist of the left hand; said second triangular-shaped network of interconnections being attached at its base to a second bracelet, said second bracelet to be worn on the wrist of the right hand; said triangular-shaped networks of interconnections to be worn on the back side of said hands giving a touch of sophistication to said hands. | 0.5 |
8,285,706 | 19 | 20 | 19. A computer-implemented method for using a human computation game to improve search engine performance, the computer-implemented method comprising performing computer-implemented operations for: displaying a page to two or more players via a multi-player game; upon displaying the page, receiving first terms from a first player and receiving second terms from a second player, causing a search engine to return first candidate pages in response to performing a first query using the first terms, causing the search engine to return second candidate pages in response to performing a second query using the second terms, and assigning points to the first player and the second player when the first player and the second player agree and correctly indicate that they are viewing the same or a different page as the other player; storing one or more of the first terms and the second terms provided by the two or more players during play of the multi-player game and associated data; and utilizing the one or more of the first terms and the second terms and the associated data to improve results returned by the search engine. | 19. A computer-implemented method for using a human computation game to improve search engine performance, the computer-implemented method comprising performing computer-implemented operations for: displaying a page to two or more players via a multi-player game; upon displaying the page, receiving first terms from a first player and receiving second terms from a second player, causing a search engine to return first candidate pages in response to performing a first query using the first terms, causing the search engine to return second candidate pages in response to performing a second query using the second terms, and assigning points to the first player and the second player when the first player and the second player agree and correctly indicate that they are viewing the same or a different page as the other player; storing one or more of the first terms and the second terms provided by the two or more players during play of the multi-player game and associated data; and utilizing the one or more of the first terms and the second terms and the associated data to improve results returned by the search engine. 20. The computer-implemented method of claim 19 , further comprising: displaying a second page via a single-player game; upon displaying the second page, receiving one or more terms from a player via the single-player game, causing the search engine to return the candidate pages in response to performing a query using the terms, and assigning second points to the player if the second page displayed to the player is included in the candidate pages returned by the search engine; storing the terms provided by the player during play of the single-player game and associated second data; and utilizing the terms and the associated second data to improve results returned by the search engine. | 0.5 |
9,122,740 | 1 | 4 | 1. A method performed by a product data management (PDM) data processing system, comprising: receiving traversal parameters including a plurality of unique object identifiers (UIDs) corresponding to objects in a data structure; receiving input objects, including input runtime objects, and closure rule clauses; configuring runtime objects, from the objects in the data structure, according to the traversal parameters; storing the runtime objects in a temporary table; constructing database queries corresponding to the closure rule clauses; executing the database queries on the data structure and the temporary table; traversing the data structure and the temporary table using the closure rules to produce traversed objects; and serializing and storing the traversed objects. | 1. A method performed by a product data management (PDM) data processing system, comprising: receiving traversal parameters including a plurality of unique object identifiers (UIDs) corresponding to objects in a data structure; receiving input objects, including input runtime objects, and closure rule clauses; configuring runtime objects, from the objects in the data structure, according to the traversal parameters; storing the runtime objects in a temporary table; constructing database queries corresponding to the closure rule clauses; executing the database queries on the data structure and the temporary table; traversing the data structure and the temporary table using the closure rules to produce traversed objects; and serializing and storing the traversed objects. 4. The method of claim 1 , wherein the PDM data processing system groups the UIDs by associated real classes. | 0.583969 |
9,483,643 | 1 | 7 | 1. A computer-implemented method for creating behavioral signatures used to detect malware, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: maintaining 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; creating 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. | 1. A computer-implemented method for creating behavioral signatures used to detect malware, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: maintaining 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; creating 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. 7. The method of claim 1 , further comprising: identifying a file on an endpoint computing device; determining, before the endpoint computing device executes the file, that the file is potentially malicious due at least in part to the file exhibiting each behavior in the behavioral signature; in response to determining that the file is potentially malicious, preventing the endpoint computing device from executing the file. | 0.717131 |
9,026,903 | 5 | 6 | 5. The computer-implemented method of claim 4 , wherein evaluating further comprises evaluating instructions included in the AST tag. | 5. The computer-implemented method of claim 4 , wherein evaluating further comprises evaluating instructions included in the AST tag. 6. The computer-implemented method of claim 5 , wherein the AST tag indicates a traversal of another abstract syntax tree. | 0.5 |
9,619,398 | 7 | 11 | 7. An apparatus, comprising: a memory configured to store a plurality of translation entries, each translation entry from the plurality of translation entries including a virtual memory identifier, a physical memory identifier, a first access identifier, a second access identifier, a shared indicator, a first access type associated with the first access identifier, and a second access type associated with the second access identifier; a selection module operatively coupled to the memory, the selection module configured to select a translation entry from the plurality of translation entries based on a comparison of a virtual memory identifier associated with a software module at a processor and a virtual memory identifier of the translation entry; and an access module operatively coupled to the selection module, the access module configured to output a signal associated with a physical memory identifier of the translation entry in response to an output signal from the selection module if a shared indicator of the translation entry is associated with a group identifier class and a group identifier of the software module is associated with an access identifier of the translation entry. | 7. An apparatus, comprising: a memory configured to store a plurality of translation entries, each translation entry from the plurality of translation entries including a virtual memory identifier, a physical memory identifier, a first access identifier, a second access identifier, a shared indicator, a first access type associated with the first access identifier, and a second access type associated with the second access identifier; a selection module operatively coupled to the memory, the selection module configured to select a translation entry from the plurality of translation entries based on a comparison of a virtual memory identifier associated with a software module at a processor and a virtual memory identifier of the translation entry; and an access module operatively coupled to the selection module, the access module configured to output a signal associated with a physical memory identifier of the translation entry in response to an output signal from the selection module if a shared indicator of the translation entry is associated with a group identifier class and a group identifier of the software module is associated with an access identifier of the translation entry. 11. The apparatus of claim 7 , wherein: the access module is configured to output a signal associated with the shared indicator before the signal associated with the physical memory identifier of the translation entry is output such that the processor sends the virtual memory identifier associated with the software module to the access module in response to the signal associated with the shared indicator. | 0.603883 |
7,493,499 | 6 | 9 | 6. The apparatus of claim 1 further comprising a publishing tool that accepts plaintext documents, encrypts the plaintext documents and generates document identifiers for each encrypted document. | 6. The apparatus of claim 1 further comprising a publishing tool that accepts plaintext documents, encrypts the plaintext documents and generates document identifiers for each encrypted document. 9. The apparatus of claim 6 wherein the publishing tool computes a document identifier for each encrypted document from the encrypted document content and a text string embedded in the publishing tool code. | 0.536036 |
8,095,364 | 1 | 3 | 1. A computer-implemented method for processing language input in a system that includes a server and mobile computer, the mobile computer including a microphone and a display and a text input device operable by a user, the method comprising operations of: responsive to the mobile computing device receiving via the microphone voice input comprising multiple discrete utterances from a user, converting the voice input into a digital sequence of vectors and then wirelessly transmitting the digital sequence of vectors to the server; the server creating an initial N-best list of words corresponding to each of the utterances by conducting speech recognition operations including matching the vectors to potential phonemes and matching the phonemes against a lexicon model and a language model, the operation of creating each initial N-best list of words further considering context of the corresponding utterance with respect to words of N-best lists corresponding to others of the received utterances, said context including subject-verb agreement, proper case, proper gender, and numerical agreement; the server transmitting each of the initial N-best lists of words to the mobile computing device; for each of said utterances, the mobile computing device visually displaying a best word from the initial N-best list of words corresponding to said utterance; responsive to implied or explicit user selection of one of the displayed best words, said selected word being from a given N-best list of words corresponding to a given utterance, causing the display to present additional words from the given initial N-best list of words; during said presentation of the additional words, the mobile computing device receiving via the text input device hand-entered input from a user, and responsive to said text input, constraining said presentation of the additional words to exclude words of the given initial N-best list that are inconsistent with the textual input; responsive to said presentation of the additional words being constrained to a resultant word, displaying the resultant word instead of the selected word and transmitting the resultant word to the server; responsive to receiving the resultant word, the server updating the initial N-best lists of others of the utterances besides the given utterance to provide subject-verb agreement, employ proper case, use proper gender, and exhibit numerical agreement when considered in context of the resultant word, and transmitting the updated N-best lists to the mobile computing device; for each of the utterances having an updated N-best list, the mobile computing device causing the display to present a best word of the updated N-best list of words for that utterance; and for each of the utterances without an updated N-best list, the mobile computing device causing the display to present a best word of the initial N-best list of words for said utterance. | 1. A computer-implemented method for processing language input in a system that includes a server and mobile computer, the mobile computer including a microphone and a display and a text input device operable by a user, the method comprising operations of: responsive to the mobile computing device receiving via the microphone voice input comprising multiple discrete utterances from a user, converting the voice input into a digital sequence of vectors and then wirelessly transmitting the digital sequence of vectors to the server; the server creating an initial N-best list of words corresponding to each of the utterances by conducting speech recognition operations including matching the vectors to potential phonemes and matching the phonemes against a lexicon model and a language model, the operation of creating each initial N-best list of words further considering context of the corresponding utterance with respect to words of N-best lists corresponding to others of the received utterances, said context including subject-verb agreement, proper case, proper gender, and numerical agreement; the server transmitting each of the initial N-best lists of words to the mobile computing device; for each of said utterances, the mobile computing device visually displaying a best word from the initial N-best list of words corresponding to said utterance; responsive to implied or explicit user selection of one of the displayed best words, said selected word being from a given N-best list of words corresponding to a given utterance, causing the display to present additional words from the given initial N-best list of words; during said presentation of the additional words, the mobile computing device receiving via the text input device hand-entered input from a user, and responsive to said text input, constraining said presentation of the additional words to exclude words of the given initial N-best list that are inconsistent with the textual input; responsive to said presentation of the additional words being constrained to a resultant word, displaying the resultant word instead of the selected word and transmitting the resultant word to the server; responsive to receiving the resultant word, the server updating the initial N-best lists of others of the utterances besides the given utterance to provide subject-verb agreement, employ proper case, use proper gender, and exhibit numerical agreement when considered in context of the resultant word, and transmitting the updated N-best lists to the mobile computing device; for each of the utterances having an updated N-best list, the mobile computing device causing the display to present a best word of the updated N-best list of words for that utterance; and for each of the utterances without an updated N-best list, the mobile computing device causing the display to present a best word of the initial N-best list of words for said utterance. 3. The method of claim 1 , where operation (g) further comprises: responsive to the text input starting with a letter or letters that conflict with all of the additional words, instead of constraining the presentation of additional words and completing operations (h) and (i) and (j), expanding the additional words to include words that phonetically resemble the best word of the initial N-best list but begin with said starting letter or letters. | 0.515152 |
5,583,762 | 19 | 20 | 19. The method of claim 15 in which said step for applying a recursive reduction procedure includes the step of applying a collapse OR's reduction procedure wherein: a determination is made as to whether the rule R of said acquired grammar element and the subrule NS thereof is an OR rule and whether the repetition characteristic of said OR rule R subsumes the repetition characteristics of said OR subrule NS; and in the event that the said rule R and subrules NS are OR rules, and said subsumption is available, then each subrule of said OR subrule NS is made said OR subrule. | 19. The method of claim 15 in which said step for applying a recursive reduction procedure includes the step of applying a collapse OR's reduction procedure wherein: a determination is made as to whether the rule R of said acquired grammar element and the subrule NS thereof is an OR rule and whether the repetition characteristic of said OR rule R subsumes the repetition characteristics of said OR subrule NS; and in the event that the said rule R and subrules NS are OR rules, and said subsumption is available, then each subrule of said OR subrule NS is made said OR subrule. 20. The method of claim 19 in which said collapse OR's reduction procedure is carried out subsequent to the execution of a collapse AND's reduction procedure. | 0.5 |
7,752,534 | 13 | 14 | 13. A computer readable memory containing a plurality of instructions configured to run on a processor of a computer to customize a display of a tag cloud, the plurality of instructions comprising: a first instruction to display an interactive legend in conjunction with the display of the tag cloud, the interactive legend comprising a plurality of tag attributes, each tag attribute associated with a drop down menu comprising a plurality of display characteristics; a second instruction, responsive to a selection of a display characteristic from the drop down menu, mapping the display characteristic to a tag in the tag cloud, each display characteristic representing one of the plurality of tag attributes; a third instruction to modify the tag cloud, wherein each tag is displayed in accordance with a display characteristic mapped to the tag by the interactive legend; and wherein the tag attributes are rearranged, added, or removed from the interactive legend. | 13. A computer readable memory containing a plurality of instructions configured to run on a processor of a computer to customize a display of a tag cloud, the plurality of instructions comprising: a first instruction to display an interactive legend in conjunction with the display of the tag cloud, the interactive legend comprising a plurality of tag attributes, each tag attribute associated with a drop down menu comprising a plurality of display characteristics; a second instruction, responsive to a selection of a display characteristic from the drop down menu, mapping the display characteristic to a tag in the tag cloud, each display characteristic representing one of the plurality of tag attributes; a third instruction to modify the tag cloud, wherein each tag is displayed in accordance with a display characteristic mapped to the tag by the interactive legend; and wherein the tag attributes are rearranged, added, or removed from the interactive legend. 14. The computer readable memory of claim 13 wherein the plurality of display characteristics comprise: font color, font size, transparency, opacity, background color, borders, motion, underlines, italics, strikethroughs, three dimensional representation of depth, shadowing and no display. | 0.532258 |
9,134,906 | 2 | 4 | 2. The method of claim 1 , further comprising: selecting, by the computing device and based at least in part on the indication of the continuous gesture, the first key and the second key of the plurality of keys; determining, by the computing device and based at least in part on the first key, a word-level token comprising a single string of a plurality of predicted characters; determining, by the computing device, that the word-level token represents a candidate word included in a lexicon; and determining, by the computing device and in response to determining that the word-level token represents the candidate word in the lexicon, a phrase-level token based at least in part on the word-level token and the second key, wherein the phrase-level token comprises a plurality of character strings. | 2. The method of claim 1 , further comprising: selecting, by the computing device and based at least in part on the indication of the continuous gesture, the first key and the second key of the plurality of keys; determining, by the computing device and based at least in part on the first key, a word-level token comprising a single string of a plurality of predicted characters; determining, by the computing device, that the word-level token represents a candidate word included in a lexicon; and determining, by the computing device and in response to determining that the word-level token represents the candidate word in the lexicon, a phrase-level token based at least in part on the word-level token and the second key, wherein the phrase-level token comprises a plurality of character strings. 4. The method of claim 2 , wherein the plurality of character strings of the phrase-level token comprises a first character string and a second character string, wherein the word-level token comprises the first character string. | 0.847594 |
9,678,857 | 1 | 6 | 1. A method for listing optimal machine instances in a computing environment to address one or more received tasks based on user context, the method comprising: receiving a task request based on a first task to be performed within the computing environment, wherein the received task request comprises a request to resolve at least one problem associated with at least one application, wherein the first task comprises at least one project task to resolve the at least one problem and comprises metadata associated with the first task to identify the at least one problem, and wherein a description of the first task is received via the metadata and user input; based on the received task request, identifying one or more similar tasks from a plurality of other tasks comprising: comparing the metadata for the first task to a plurality of metadata for the plurality of other tasks based on a classification analysis, and selecting the identified one or more similar tasks based on the comparison, wherein similarity of the identified and selected one or more similar tasks to the first task is based on a result from the classification analysis exceeding a predetermined confidence level, and wherein the plurality of other tasks comprise previous tasks performed within the computing environment on corresponding previous machine instances that are associated with previous problems; and in response to identifying and selecting the one or more similar tasks, generating a list of one or more previous machine instances corresponding to the identified and selected one or more similar tasks, wherein the list of one or more previous machine instances is associated with instructions to commence the one or more previous machine instances, and wherein the one or more previous machine instances comprises at least one of a virtual machine (VM) instance or a physical machine instance, and wherein generating the list comprises ranking the one or more previous machine instances based on a priority ranking and information associated with the first task and the identified and selected one or more similar tasks, and listing the one or more previous machine instances based on the ranking. | 1. A method for listing optimal machine instances in a computing environment to address one or more received tasks based on user context, the method comprising: receiving a task request based on a first task to be performed within the computing environment, wherein the received task request comprises a request to resolve at least one problem associated with at least one application, wherein the first task comprises at least one project task to resolve the at least one problem and comprises metadata associated with the first task to identify the at least one problem, and wherein a description of the first task is received via the metadata and user input; based on the received task request, identifying one or more similar tasks from a plurality of other tasks comprising: comparing the metadata for the first task to a plurality of metadata for the plurality of other tasks based on a classification analysis, and selecting the identified one or more similar tasks based on the comparison, wherein similarity of the identified and selected one or more similar tasks to the first task is based on a result from the classification analysis exceeding a predetermined confidence level, and wherein the plurality of other tasks comprise previous tasks performed within the computing environment on corresponding previous machine instances that are associated with previous problems; and in response to identifying and selecting the one or more similar tasks, generating a list of one or more previous machine instances corresponding to the identified and selected one or more similar tasks, wherein the list of one or more previous machine instances is associated with instructions to commence the one or more previous machine instances, and wherein the one or more previous machine instances comprises at least one of a virtual machine (VM) instance or a physical machine instance, and wherein generating the list comprises ranking the one or more previous machine instances based on a priority ranking and information associated with the first task and the identified and selected one or more similar tasks, and listing the one or more previous machine instances based on the ranking. 6. The method according to claim 1 , wherein the classification analysis is performed by comprises at least one of natural language processing or machine-learning. | 0.908837 |
7,945,896 | 1 | 2 | 1. A method for facilitating communications between components of a distributed application comprising the steps of: receiving a request by a middleware program from a first distributed application component, wherein a second distributed application component is identified in said request as a recipient of said request; identifying by the middleware program a publish/subscribe topic by identifying a first property of said second distributed application component; sending the request by the middleware program to a publisher associated with the first publish/subscribe topic; publishing by the publisher said request on the first publish/subscribe request topic; and in response to said publishing said request on the first publish/subscribe topic: sending the message to the second distributed application component, wherein the distributed application, the middleware program, the publisher and the publish/subscribe topic, are embodied in communicating computing devices. | 1. A method for facilitating communications between components of a distributed application comprising the steps of: receiving a request by a middleware program from a first distributed application component, wherein a second distributed application component is identified in said request as a recipient of said request; identifying by the middleware program a publish/subscribe topic by identifying a first property of said second distributed application component; sending the request by the middleware program to a publisher associated with the first publish/subscribe topic; publishing by the publisher said request on the first publish/subscribe request topic; and in response to said publishing said request on the first publish/subscribe topic: sending the message to the second distributed application component, wherein the distributed application, the middleware program, the publisher and the publish/subscribe topic, are embodied in communicating computing devices. 2. The method of claim 1 , wherein said first property is a type of said second distributed application component. | 0.93617 |
8,091,022 | 16 | 17 | 16. The system as set forth in claim 11 wherein the source reference data item recorder is configured to record a publication date for the one or more source reference data items. | 16. The system as set forth in claim 11 wherein the source reference data item recorder is configured to record a publication date for the one or more source reference data items. 17. The system as set forth in claim 16 wherein the monitor report generator is further configured to generate one or more reports selected from the group consisting of an electronic mail message, a text file, a binary data file, and a report on a printer. | 0.5 |
10,051,009 | 6 | 7 | 6. A method, comprising: a user agent providing at least one privacy preference relative to at least one user identity; the user agent receiving user selections relating to the user identity wherein the user identity is represented by at least one information card used in completing an online transaction with a relying party; the user agent generating at least one privacy preference, using the user selections; the user agent furnishing the at least one generated privacy preference; the user agent evaluating at least one privacy preference against a privacy policy associated with an online transaction and obtained from the relying party, the evaluating using the at least one privacy preference of any category referencing at least one required attribute; and a host computer providing the at least one information card representing the user identity to the relying party. | 6. A method, comprising: a user agent providing at least one privacy preference relative to at least one user identity; the user agent receiving user selections relating to the user identity wherein the user identity is represented by at least one information card used in completing an online transaction with a relying party; the user agent generating at least one privacy preference, using the user selections; the user agent furnishing the at least one generated privacy preference; the user agent evaluating at least one privacy preference against a privacy policy associated with an online transaction and obtained from the relying party, the evaluating using the at least one privacy preference of any category referencing at least one required attribute; and a host computer providing the at least one information card representing the user identity to the relying party. 7. The method of claim 6 , further comprises the user agent conducting a process to define at least one category, populate each category with a respective group of user identity attributes, and determine a privacy preference for each category. | 0.668033 |
8,672,683 | 12 | 17 | 12. A computer-based method for training a user in the operation of an abacus comprising: generating a series of mathematical problems without displaying the mathematical problems to a user; converting the mathematical problems into corresponding hand movements for manipulation of beads of the abacus; generating animations of the corresponding hand movements; displaying the animations to the user without displaying the mathematical problems to the user; accepting user input describing the mathematical problems, which have not been displayed to the user; comparing the user input to the mathematical problems to determine the accuracy of the user input; formulating a measure of user mastery based on the accuracy of the user input; and adjusting the series of mathematical problems based on the measure of user mastery. | 12. A computer-based method for training a user in the operation of an abacus comprising: generating a series of mathematical problems without displaying the mathematical problems to a user; converting the mathematical problems into corresponding hand movements for manipulation of beads of the abacus; generating animations of the corresponding hand movements; displaying the animations to the user without displaying the mathematical problems to the user; accepting user input describing the mathematical problems, which have not been displayed to the user; comparing the user input to the mathematical problems to determine the accuracy of the user input; formulating a measure of user mastery based on the accuracy of the user input; and adjusting the series of mathematical problems based on the measure of user mastery. 17. The method of claim 12 , wherein the formulating a measure of user mastery comprises measuring user mastery corresponding to plurality of mathematical concept categories. | 0.848696 |
8,023,962 | 1 | 2 | 1. A system for providing geographic information comprising: a database containing geographic information, the database accessible via a network connection; and a mobile device connectable to the database from a remote location, the mobile device having a controller, a position sensor for determining a location of the mobile device and a pointing device adapted to orient the mobile device pointing in a direction to intersect a particular one of an object, geographical feature or location of interest to a user, the controller being adapted to receive a thematic query from a user, the controller being further adapted retrieve a portion of the geographic information from the database selected by a combination of the location of the mobile device, a pointing direction of the device and the thematic query, and the geographical information is about the particular object, geographical feature or location. | 1. A system for providing geographic information comprising: a database containing geographic information, the database accessible via a network connection; and a mobile device connectable to the database from a remote location, the mobile device having a controller, a position sensor for determining a location of the mobile device and a pointing device adapted to orient the mobile device pointing in a direction to intersect a particular one of an object, geographical feature or location of interest to a user, the controller being adapted to receive a thematic query from a user, the controller being further adapted retrieve a portion of the geographic information from the database selected by a combination of the location of the mobile device, a pointing direction of the device and the thematic query, and the geographical information is about the particular object, geographical feature or location. 2. The system of claim 1 further comprising a wireless router for connecting the mobile device to the database. | 0.824921 |
8,301,619 | 28 | 34 | 28. A computer implemented method for generating a Boolean query comprising: a. getting training data, wherein the training data comprises a plurality of training documents and wherein each of the plurality of training documents comprises at least one training token; b. cleaning the training data; c. identifying, by a processor, at least one salient token from the at least one training token in each of the plurality of training documents; d. clustering the plurality of training documents into a plurality of clusters based on the at least one training token in the plurality of training documents or the at least one salient token, wherein each cluster comprises at least one training document; e. generating the Boolean query for a cluster of the plurality of clusters based on an occurrence of at least one salient token in the at least one training document of the plurality of training documents; f. getting production data, wherein the production data comprises a plurality of production documents and wherein each of the plurality of production documents comprises at least one production token; and g. executing, by the processor, the Boolean query on the plurality of production documents in the production data. | 28. A computer implemented method for generating a Boolean query comprising: a. getting training data, wherein the training data comprises a plurality of training documents and wherein each of the plurality of training documents comprises at least one training token; b. cleaning the training data; c. identifying, by a processor, at least one salient token from the at least one training token in each of the plurality of training documents; d. clustering the plurality of training documents into a plurality of clusters based on the at least one training token in the plurality of training documents or the at least one salient token, wherein each cluster comprises at least one training document; e. generating the Boolean query for a cluster of the plurality of clusters based on an occurrence of at least one salient token in the at least one training document of the plurality of training documents; f. getting production data, wherein the production data comprises a plurality of production documents and wherein each of the plurality of production documents comprises at least one production token; and g. executing, by the processor, the Boolean query on the plurality of production documents in the production data. 34. The method of claim 28 , wherein clustering the training data is accomplished by an algorithm selected from the group comprising: a k-means, a bisecting k-means, an agglomerative, and a divisive hierarchical. | 0.904332 |
8,180,153 | 1 | 6 | 1. A method for processing image data, comprising using a processor to perform: providing input image data; segmenting the input image data to generate: a background layer representing the background attributes of an image; a selector layer for identifying one or more foreground attributes of the image not included in the background layer; and a foreground layer representing the foreground attributes of the image; generating a black text layer comprising pixel data representing black text in the input image data; assigning the black text pixel data a predetermined value for the color black; and integrating the background layer, the selector layer, the foreground layer, and the black text layer into a data structure having machine-readable instructions that may be stored in a memory device. | 1. A method for processing image data, comprising using a processor to perform: providing input image data; segmenting the input image data to generate: a background layer representing the background attributes of an image; a selector layer for identifying one or more foreground attributes of the image not included in the background layer; and a foreground layer representing the foreground attributes of the image; generating a black text layer comprising pixel data representing black text in the input image data; assigning the black text pixel data a predetermined value for the color black; and integrating the background layer, the selector layer, the foreground layer, and the black text layer into a data structure having machine-readable instructions that may be stored in a memory device. 6. The method according to claim 1 , further comprising using a processor to perform: removing isolated pixels from the black text pixel data. | 0.818414 |
10,025,848 | 11 | 17 | 11. A non-transitory machine-readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising: receiving, at a communication device, information associated with a voicemail message, wherein the information includes a transcript and a transcript index that are generated from the voicemail message, and wherein each respective word in the voicemail message is indexed relative to an occurrence in time of the respective word in the voicemail message, to yield the transcript index; displaying, at a graphical user interface, the information associated with the voicemail message; receiving a selection of a portion of the information via the graphical user interface, wherein the selection of the portion of the information includes selection of a portion of the transcript; and transmitting the portion of the information to an intended recipient, wherein the portion of the information is identified based on the transcript index. | 11. A non-transitory machine-readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising: receiving, at a communication device, information associated with a voicemail message, wherein the information includes a transcript and a transcript index that are generated from the voicemail message, and wherein each respective word in the voicemail message is indexed relative to an occurrence in time of the respective word in the voicemail message, to yield the transcript index; displaying, at a graphical user interface, the information associated with the voicemail message; receiving a selection of a portion of the information via the graphical user interface, wherein the selection of the portion of the information includes selection of a portion of the transcript; and transmitting the portion of the information to an intended recipient, wherein the portion of the information is identified based on the transcript index. 17. The non-transitory machine-readable storage medium of claim 11 , wherein the information is received as an electronic mail message. | 0.796073 |
8,645,390 | 30 | 31 | 30. The system of claim 27 , wherein each search context is associated with a respective group of users and a respective class of search queries. | 30. The system of claim 27 , wherein each search context is associated with a respective group of users and a respective class of search queries. 31. The system of claim 30 , wherein the respective class for a particular search query is determined in accordance with a number of search terms in the particular search query. | 0.534211 |
9,760,545 | 1 | 8 | 1. A method comprising: entering a source digitized text into a memory of an information technology system; delineating the source digitized text into a plurality of segments by a user; associating a first selection of the segments by the user with a first tag; individually assigning by the user a unique sequence number to each segment of the first selection, whereby each segment of the first selection is associated with a unique sequence number within the first selection; associating a second selection of the segments by the user with a second tag; individually assigning by the user a unique sequence number to each segment of the second selection, whereby each segment of the second selection is associated with a unique sequence number within the second selection; receiving a user command to proceed to thereafter sequentially render segments associated with the first tag; generating a first node record and associating the segments associated with the first tag with the first node record; associating the first node record with at least one other selected segment associated with the second tag when at least one of the segments associated with the first node record shares the second tag; sequentially rendering each segment associated with the first tag node record in accordance with the order of each individually assigned sequence number of each segment of the first selection until the associated selected segment is rendered; receiving a user command to sequentially render segments associated with the second tag; generating a second node record and associating segments associated with the second tag with the second node record; sequentially rendering segments associated with the second node record in accordance with the order of each individually assigned sequence number of each segment of the second selection. | 1. A method comprising: entering a source digitized text into a memory of an information technology system; delineating the source digitized text into a plurality of segments by a user; associating a first selection of the segments by the user with a first tag; individually assigning by the user a unique sequence number to each segment of the first selection, whereby each segment of the first selection is associated with a unique sequence number within the first selection; associating a second selection of the segments by the user with a second tag; individually assigning by the user a unique sequence number to each segment of the second selection, whereby each segment of the second selection is associated with a unique sequence number within the second selection; receiving a user command to proceed to thereafter sequentially render segments associated with the first tag; generating a first node record and associating the segments associated with the first tag with the first node record; associating the first node record with at least one other selected segment associated with the second tag when at least one of the segments associated with the first node record shares the second tag; sequentially rendering each segment associated with the first tag node record in accordance with the order of each individually assigned sequence number of each segment of the first selection until the associated selected segment is rendered; receiving a user command to sequentially render segments associated with the second tag; generating a second node record and associating segments associated with the second tag with the second node record; sequentially rendering segments associated with the second node record in accordance with the order of each individually assigned sequence number of each segment of the second selection. 8. The method of claim 1 , wherein the first tag is associated with a user selected aspect of the source digitized text. | 0.661017 |
6,072,461 | 9 | 11 | 9. Apparatus according to claim 8 wherein said scanned image comprises a scanned image of an original document. | 9. Apparatus according to claim 8 wherein said scanned image comprises a scanned image of an original document. 11. Apparatus according to claim 9 wherein said scanned image of an original document comprises a scanned image of a handwritten text and said corresponding typed-in image comprises a word-processed version of said handwritten text. | 0.5 |
6,101,537 | 12 | 13 | 12. The system of claim 11 wherein said computer accessible through said interconnected network is a local server. | 12. The system of claim 11 wherein said computer accessible through said interconnected network is a local server. 13. The system of claim 12 further comprising: at least one client computer, wherein said local server is also accessible to said client computer; computer implemented software at said local server for receiving from said client computer said request using a resource alias and for returning to said client computer said data from said resource alias record. | 0.5 |
9,760,640 | 14 | 20 | 14. A non-transitory computer-readable storage medium having computer-executable instructions that, when executed by at least one processor, causes the at least one processor to perform operations comprising: computer program code for receiving, by a Web server over a communications network including the Internet, a request from a user client device to access content of a target domain, the request being addressed to a domain address of the target domain; computer program code for identifying, by the Web server, a new content domain that is determined to be relevant to the request to access content of a target domain based on a combination of the domain address of the target domain, source context factors that characterize the user client device, and historical relevance data associated with the target domain, the historical relevance data including source context factors of multiple users who requested to access at least one given address from addresses belonging to the domain address of the target domain and interests of the multiple users, the interests of the multiple users based on pre-access behavior of the multiple users; and computer program code for providing, by the Web server, the user client device with access to content of the identified new content domain over the communications network, responsive to the request. | 14. A non-transitory computer-readable storage medium having computer-executable instructions that, when executed by at least one processor, causes the at least one processor to perform operations comprising: computer program code for receiving, by a Web server over a communications network including the Internet, a request from a user client device to access content of a target domain, the request being addressed to a domain address of the target domain; computer program code for identifying, by the Web server, a new content domain that is determined to be relevant to the request to access content of a target domain based on a combination of the domain address of the target domain, source context factors that characterize the user client device, and historical relevance data associated with the target domain, the historical relevance data including source context factors of multiple users who requested to access at least one given address from addresses belonging to the domain address of the target domain and interests of the multiple users, the interests of the multiple users based on pre-access behavior of the multiple users; and computer program code for providing, by the Web server, the user client device with access to content of the identified new content domain over the communications network, responsive to the request. 20. The tangible computer-readable medium of claim 14 wherein the domain address is a URI. | 0.868035 |
8,468,446 | 10 | 11 | 10. The method of claim 9 , wherein executing the instructions of the template during the execution stage for each record of the set of records comprises executing at least one instruction that creates an attribute. | 10. The method of claim 9 , wherein executing the instructions of the template during the execution stage for each record of the set of records comprises executing at least one instruction that creates an attribute. 11. The method of claim 10 , wherein executing the instructions of the template during the execution stage for each record of the set of records further comprises executing at least one instruction that closes the at least one other element. | 0.5 |
8,903,759 | 13 | 17 | 13. The method of claim 1 , wherein receiving captured text from a printed document further comprises: receiving information identifying a region of the printed document from which the captured text was captured; and determining the action at least in part on the received information related to the region. | 13. The method of claim 1 , wherein receiving captured text from a printed document further comprises: receiving information identifying a region of the printed document from which the captured text was captured; and determining the action at least in part on the received information related to the region. 17. The method of claim 13 , wherein determining the action at least in part on the received information related to the region further comprises: combining actions determined from regions of more than one related document. | 0.557769 |
9,411,327 | 13 | 14 | 13. The system of claim 12 , wherein calculating the indicator of the probability comprises using a naive Bayes classifier. | 13. The system of claim 12 , wherein calculating the indicator of the probability comprises using a naive Bayes classifier. 14. The system of claim 13 , wherein generating the first matrix comprises using latent semantic indexing. | 0.5 |
8,890,806 | 4 | 5 | 4. The method of claim 3 , further comprising outputting an indication that the object is a proposed spelling correction. | 4. The method of claim 3 , further comprising outputting an indication that the object is a proposed spelling correction. 5. The method of claim 4 , wherein the indication that the object is a proposed spelling correction includes a visual indication. | 0.5 |
9,378,647 | 22 | 23 | 22. A non-transitory computer-readable storage medium storing executable computer program instructions for automatically deconstructing an educational course into discrete learning units, the computer program instructions comprising instructions for: analyzing content related to an educational course stored by an education platform; extracting distinct concepts from the content; identifying passive, active, and recall user activities associated with respective distinct concepts, including instructions for: extracting a time duration for each passive, active, and recall activity from users activity logs, normalizing the extracted time durations across users, and reporting the normalized extracted time durations; generating a plurality of learning units, each learning unit comprising a distinct concept and the passive, active, and recall user activities associated with the distinct concept; and delivering at least one discrete learning unit to a registered user through the education platform. | 22. A non-transitory computer-readable storage medium storing executable computer program instructions for automatically deconstructing an educational course into discrete learning units, the computer program instructions comprising instructions for: analyzing content related to an educational course stored by an education platform; extracting distinct concepts from the content; identifying passive, active, and recall user activities associated with respective distinct concepts, including instructions for: extracting a time duration for each passive, active, and recall activity from users activity logs, normalizing the extracted time durations across users, and reporting the normalized extracted time durations; generating a plurality of learning units, each learning unit comprising a distinct concept and the passive, active, and recall user activities associated with the distinct concept; and delivering at least one discrete learning unit to a registered user through the education platform. 23. The non-transitory computer-readable storage medium of claim 22 , wherein the content related to the course includes content added by registered users through interactions with the education platform during on-line sessions. | 0.750547 |
8,639,829 | 1 | 8 | 1. A system comprising: a communications server to: receive a first language construct in a first language from a first entity, identify a first numerical identifier associated with the first language construct; and a processing server to: identify a language identifier from a user table of a network-based transaction facility, the language identifier associated with a second entity, the second entity being a user of the network-based transaction facility, the user table containing user information about the second entity, and retrieve a second language construct based on the first numerical identifier and the language identifier associated with the second entity, the second language construct being a translation of the first language construct in a second language, the language identifier corresponding to the second language. | 1. A system comprising: a communications server to: receive a first language construct in a first language from a first entity, identify a first numerical identifier associated with the first language construct; and a processing server to: identify a language identifier from a user table of a network-based transaction facility, the language identifier associated with a second entity, the second entity being a user of the network-based transaction facility, the user table containing user information about the second entity, and retrieve a second language construct based on the first numerical identifier and the language identifier associated with the second entity, the second language construct being a translation of the first language construct in a second language, the language identifier corresponding to the second language. 8. The system of claim 1 , wherein the first language construct forms a portion of a message formatted in a hypertext markup language. | 0.757246 |
8,099,662 | 15 | 21 | 15. An apparatus comprising: one or more processors and a memory; input means for receiving, from a user interface, an annotation associated with a background image; control means for adding the annotation to a queue of pending annotations; output means for transmitting the annotation from the apparatus to a server; wherein the control means removes the annotation from the queue of pending annotations, and adds the annotation to a list of acknowledged annotations, when an acknowledgment of the annotation is received by the apparatus from the server; wherein the output means generates a display image comprising the background image, annotations in the list of acknowledged annotations, and annotations in the queue of pending annotations; and wherein the one or more processors and the memory cooperate to implement at least in part the input, output and control means. | 15. An apparatus comprising: one or more processors and a memory; input means for receiving, from a user interface, an annotation associated with a background image; control means for adding the annotation to a queue of pending annotations; output means for transmitting the annotation from the apparatus to a server; wherein the control means removes the annotation from the queue of pending annotations, and adds the annotation to a list of acknowledged annotations, when an acknowledgment of the annotation is received by the apparatus from the server; wherein the output means generates a display image comprising the background image, annotations in the list of acknowledged annotations, and annotations in the queue of pending annotations; and wherein the one or more processors and the memory cooperate to implement at least in part the input, output and control means. 21. The apparatus of claim 15 : wherein the output means generates an acknowledged annotation image comprising the background image, and the annotations in the list of acknowledged annotations; and wherein the output means generates the display image based on the acknowledged annotation image and the annotations in the queue of pending annotations. | 0.5 |
9,256,813 | 11 | 15 | 11. A computerized device comprising: a processor receiving images of a previously printed document, a second document to be printed, and instructions to use previous layout parameters of said previously printed document to print said second document, without providing access to said previous layout parameters of said previously printed document; said processor automatically reverse engineering said previous layout parameters used to print said previously printed document from said images of said previously printed document, without access to said previous layout parameters, by detecting page boundaries, detecting page orientation, and detecting page sequencing within said images of said previously printed document, said processor automatically preparing a print job ticket for said second document having job ticket layout parameters matching said previous layout parameters, and said processor outputting said second document using said print job ticket to cause said second document to match said previous layout parameters of said previously printed document. | 11. A computerized device comprising: a processor receiving images of a previously printed document, a second document to be printed, and instructions to use previous layout parameters of said previously printed document to print said second document, without providing access to said previous layout parameters of said previously printed document; said processor automatically reverse engineering said previous layout parameters used to print said previously printed document from said images of said previously printed document, without access to said previous layout parameters, by detecting page boundaries, detecting page orientation, and detecting page sequencing within said images of said previously printed document, said processor automatically preparing a print job ticket for said second document having job ticket layout parameters matching said previous layout parameters, and said processor outputting said second document using said print job ticket to cause said second document to match said previous layout parameters of said previously printed document. 15. The computerized device according to claim 11 , said processor detecting said page orientation by at least one of: identifying sequential page numbers at repeatable standard locations in said images of said previously printed document; and performing sentence-level grammatical analysis, when sentences break across adjacent pages in said images of said previously printed document. | 0.755696 |
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