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8,250,467 | 1 | 4 | 1. A visual markup to voice markup transcoding hardware system comprising: a hardware processor configured to include: an annotator configured to convert implicit topical headings in original visual markup to explicit topical headings in converted visual markup; and, a transcoding plug-in to a transcoding publisher, said transcoding plug-in having a configuration both for generating menu items in voice markup for identified explicit topical headings in said converted visual markup, and also for linking individual text blocks in said voice markup with associated explicit topical headings in said voice markup, said linking providing a configuration for audio playback of said text blocks responsive to a vocalization of said associated explicit topical headings in said voice markup, wherein the implicit topical headings and the explicit topical headings each include at least two different levels of headings. | 1. A visual markup to voice markup transcoding hardware system comprising: a hardware processor configured to include: an annotator configured to convert implicit topical headings in original visual markup to explicit topical headings in converted visual markup; and, a transcoding plug-in to a transcoding publisher, said transcoding plug-in having a configuration both for generating menu items in voice markup for identified explicit topical headings in said converted visual markup, and also for linking individual text blocks in said voice markup with associated explicit topical headings in said voice markup, said linking providing a configuration for audio playback of said text blocks responsive to a vocalization of said associated explicit topical headings in said voice markup, wherein the implicit topical headings and the explicit topical headings each include at least two different levels of headings. 4. The visual markup to voice markup transcoding system of claim 1 , wherein said visual markup is formatted according to the hypertext markup language (HTML), and the voice markup is formatted according to the voice extensible markup language (VXML). | 0.5369 |
8,886,545 | 7 | 9 | 7. The method of claim 1 , wherein the voice command is user selectable. | 7. The method of claim 1 , wherein the voice command is user selectable. 9. The method of claim 7 , wherein the user inputs the voice command by typing. | 0.980061 |
9,047,623 | 13 | 18 | 13. A method for determining recommendation data, comprising: extracting a first set of keywords from a set of user action logs that occurred prior to a predetermined time point; extracting a second set of keywords from a set of user action logs that occurred subsequent to the predetermined time point; merging at least a portion of the first set of keywords and at least a portion of the second set of keywords to obtain a third set of keywords; matching, using one or more processors, at least one keyword in the third set of keywords with a database of data that can potentially be recommended to a user; and in the event that a piece of data in the database is determined to match the at least one keyword from the third set of keywords, determining that the piece of data is to be recommended to the user. | 13. A method for determining recommendation data, comprising: extracting a first set of keywords from a set of user action logs that occurred prior to a predetermined time point; extracting a second set of keywords from a set of user action logs that occurred subsequent to the predetermined time point; merging at least a portion of the first set of keywords and at least a portion of the second set of keywords to obtain a third set of keywords; matching, using one or more processors, at least one keyword in the third set of keywords with a database of data that can potentially be recommended to a user; and in the event that a piece of data in the database is determined to match the at least one keyword from the third set of keywords, determining that the piece of data is to be recommended to the user. 18. The method of claim 13 , wherein the first set of keywords is extracted at every first time interval and the second set of keywords is extracted at every second time interval and wherein the first time interval is greater than the second time interval. | 0.882998 |
10,049,097 | 1 | 2 | 1. A method for creating a multi-layered Optical Character Recognition (OCR) document, the method comprising: receiving a scanned image corresponding to a document, the document includes text information; generating a binary image from the scanned image; performing a morphological dilation operation to create one or more text groups, using a horizontal structuring element and a vertical structuring element; applying OCR on each text group to generate a corresponding OCR layer; combining the one or more OCR layers while creating a multi-layered OCR document; and superimposing the combined OCR layers as invisible text layers over the scanned image to create the multi-layered OCR document, the multi-layered OCR document facilitates selection of a text group corresponding to the OCR layer. | 1. A method for creating a multi-layered Optical Character Recognition (OCR) document, the method comprising: receiving a scanned image corresponding to a document, the document includes text information; generating a binary image from the scanned image; performing a morphological dilation operation to create one or more text groups, using a horizontal structuring element and a vertical structuring element; applying OCR on each text group to generate a corresponding OCR layer; combining the one or more OCR layers while creating a multi-layered OCR document; and superimposing the combined OCR layers as invisible text layers over the scanned image to create the multi-layered OCR document, the multi-layered OCR document facilitates selection of a text group corresponding to the OCR layer. 2. The method as claimed in claim 1 , wherein the applying OCR further comprises: extracting text information corresponding to the one or more text groups. | 0.918249 |
8,818,910 | 12 | 13 | 12. The method of claim 10 , wherein: there are N historical candidates in the training data set; and selecting, for the training of each of the T decision trees, comprises selecting N historical candidates in the training dataset randomly with replacement. | 12. The method of claim 10 , wherein: there are N historical candidates in the training data set; and selecting, for the training of each of the T decision trees, comprises selecting N historical candidates in the training dataset randomly with replacement. 13. The method of claim 12 , wherein generating the T decision trees comprises generating a N×M matrix, where each of the N rows in the matrix corresponds to one of the historical candidates in the training dataset, and each of the M columns corresponds to an input variable for classifying the candidates; to construct each of the T decision trees, at each node of each of the T decision trees, selecting randomly m out of M input variables; and determining a best split on the m input variables to split the node. | 0.785058 |
10,026,047 | 1 | 5 | 1. A system for crowd sourcing tasks, comprising: a processor; a crowd sourcing module operating on the processor, the crowd sourcing module being configured to cause the processor to perform a set of functions comprising: identifying a group of potential candidates for crowd sourcing, wherein each candidate of the group of potential candidates is identified based on the candidate being expected to accept an offer for performance of a certain type of task, the certain type of task being at least performable within a predetermined range of time; receiving a request to perform a particular task from a requester; determining if the particular task corresponds to the certain type of task; and transmitting an offer for performance of the particular task to a subgroup of the group of potential candidates in response to the particular task corresponding to the certain type of task, wherein transmitting the offer for performance of the particular task to the subgroup of the group of potential candidates comprises: determining when any candidates of the group of potential candidates are currently performing the same task or similar task to the particular task, and transmitting the offer for performance of the particular task to the subgroup of potential candidates that are currently performing the same task or the similar task; determining when any candidates of the group of potential candidates have a history of completing the same task or the similar task to the particular task faster than other candidates, and transmitting the offer for performance of the particular task to the subgroup of potential candidates that have the history of completing the same task or the similar task faster than the other candidates; determining when a particular candidate of the group of potential candidates has completed a specific task, and transmitting the offer for performance of the particular task to the particular candidate in response to the particular candidate having completed the specific task, wherein the specific task is related to the particular task being offered; and determining when any candidates of the group of potential candidates have reached a predefined quota of one of a total time in performing a group of tasks during a set time period or a number of tasks performed during the set time period, and not transmitting an offer for performance of another task to any candidates of the group of potential candidates that have reached the predefined quota until a next set time period, wherein the next set time period is configurable by a user based on a policy. | 1. A system for crowd sourcing tasks, comprising: a processor; a crowd sourcing module operating on the processor, the crowd sourcing module being configured to cause the processor to perform a set of functions comprising: identifying a group of potential candidates for crowd sourcing, wherein each candidate of the group of potential candidates is identified based on the candidate being expected to accept an offer for performance of a certain type of task, the certain type of task being at least performable within a predetermined range of time; receiving a request to perform a particular task from a requester; determining if the particular task corresponds to the certain type of task; and transmitting an offer for performance of the particular task to a subgroup of the group of potential candidates in response to the particular task corresponding to the certain type of task, wherein transmitting the offer for performance of the particular task to the subgroup of the group of potential candidates comprises: determining when any candidates of the group of potential candidates are currently performing the same task or similar task to the particular task, and transmitting the offer for performance of the particular task to the subgroup of potential candidates that are currently performing the same task or the similar task; determining when any candidates of the group of potential candidates have a history of completing the same task or the similar task to the particular task faster than other candidates, and transmitting the offer for performance of the particular task to the subgroup of potential candidates that have the history of completing the same task or the similar task faster than the other candidates; determining when a particular candidate of the group of potential candidates has completed a specific task, and transmitting the offer for performance of the particular task to the particular candidate in response to the particular candidate having completed the specific task, wherein the specific task is related to the particular task being offered; and determining when any candidates of the group of potential candidates have reached a predefined quota of one of a total time in performing a group of tasks during a set time period or a number of tasks performed during the set time period, and not transmitting an offer for performance of another task to any candidates of the group of potential candidates that have reached the predefined quota until a next set time period, wherein the next set time period is configurable by a user based on a policy. 5. The system of claim 1 , wherein the crowd sourcing module is further configured to perform a set of functions comprising: determining that a threshold number of users have completed a specific task; determining which user of the threshold number of users successfully completed the specific task in a shortest time period; setting a trigger for a subsequent user starting a same task or a similar task to the specific task; detecting the subsequent user starting the same or the similar task; and requesting the user that successfully completed specific task in the shortest time period to perform the specific task for the subsequent user. | 0.500776 |
8,761,988 | 11 | 12 | 11. The method of claim 10 , wherein determining minimum and maximum permissible engine torques subject to constraints at the candidate engine speed comprises determining the minimum and maximum permissible engine torques subject to minimum and maximum battery power limits associated with a high-voltage battery configured to transfer electric power to torque machines coupled to the multi-mode transmission and subject to minimum and maximum torque limits associated with the torque machines. | 11. The method of claim 10 , wherein determining minimum and maximum permissible engine torques subject to constraints at the candidate engine speed comprises determining the minimum and maximum permissible engine torques subject to minimum and maximum battery power limits associated with a high-voltage battery configured to transfer electric power to torque machines coupled to the multi-mode transmission and subject to minimum and maximum torque limits associated with the torque machines. 12. The method of claim 11 , wherein the minimum and maximum torque limits associated with the torque machines are determined relative to speeds of the torque machines determined relative to the candidate engine speed and an output speed of the multi-mode transmission. | 0.909183 |
9,348,499 | 31 | 51 | 31. One or more non-transitory computer-readable media storing instructions for sharing information from a first data system with a second data system, which instructions, when executed by one or more processors, cause performance of steps comprising: receiving, from a first server of the first data system, at a second server of the second data system (a) a document comprising one or more instructions configured to cause generation of one or more presented components of the document based on retrieving data belonging to a first object within a first repository of the first data system, and (b) evidence data describing one or more aspects of the first object; wherein the first object has a first name; wherein the evidence data is not identical to the first name; wherein the retrieved data that belongs to the first object is not included in the document or the evidence data; using the evidence data to identify a second object, stored within a second repository of the second data system, to be utilized as a substitute for the first object; and generating and storing a copy of the document, wherein the copy of the document comprises a reference to the second object instead of the first object, and further comprises one or more instructions configured to cause generation of the one or more presented components based on retrieving data that belongs to the second object. | 31. One or more non-transitory computer-readable media storing instructions for sharing information from a first data system with a second data system, which instructions, when executed by one or more processors, cause performance of steps comprising: receiving, from a first server of the first data system, at a second server of the second data system (a) a document comprising one or more instructions configured to cause generation of one or more presented components of the document based on retrieving data belonging to a first object within a first repository of the first data system, and (b) evidence data describing one or more aspects of the first object; wherein the first object has a first name; wherein the evidence data is not identical to the first name; wherein the retrieved data that belongs to the first object is not included in the document or the evidence data; using the evidence data to identify a second object, stored within a second repository of the second data system, to be utilized as a substitute for the first object; and generating and storing a copy of the document, wherein the copy of the document comprises a reference to the second object instead of the first object, and further comprises one or more instructions configured to cause generation of the one or more presented components based on retrieving data that belongs to the second object. 51. The one or more non-transitory computer-readable media of claim 31 : wherein the document is viewable in a viewing application; wherein the one or more instructions in the document are configured to cause the viewing application to retrieve the data belonging to the first object and dynamically generate a view of the retrieved data. | 0.599526 |
8,756,515 | 1 | 5 | 1. At a computer system that includes one or more processors and system memory, a method for providing a real-time incremental editor for enacting changes to user interface (UI) elements of an active UI, the method comprising: an act of the computer system presenting a first UI of an executing application program based on a UI model that includes declarative model data that drives the behavior of the first UI, the first UI including a plurality of UI elements, the UI model including particular declarative model data that declaratively defines a visual appearance of the plurality of UI elements of the first UI, each of the plurality of UI elements being an instance of the particular declarative model data; an-act of the computer system visually indicating a state of the first UI, including visually indicating within the first UI that a particular UI element of the plurality of UI elements has been selected by a user at the first UI; concurrent to presenting the first UI of the application program, and concurrent to visually indicating within the first UI that the particular UI element has been selected by a user: an act of the computer system presenting a second UI of a real-time incremental editor that is separate from the application program and that is configured to receive one or more editing inputs that are to be applied to the particular declarative model data of the UI model, to edit the first UI of the application program while the application program is executing; an act of the computer system receiving a first editing user input at the second UI of the real-time incremental editor, the first editing input selecting the particular declarative model data that declaratively defines the plurality of UI elements; based on selection of the particular declarative model data within the real-time incremental editor, visually distinguishing each of the plurality of UI elements, including the particular UI element, within the first UI as being selected at the second UI of the real-time incremental editor, while also visually indicating within the first UI that the particular UI element has been selected at the first UI; an act of the computer system receiving a second editing user input at the second UI of the real-time incremental editor, the second editing input indicating one or more desired edits that are to be made to the plurality of UI elements that affect the visual appearance of the plurality of UI elements within the first UI; an act of the computer system determining, based on the received editing input, one or more changes that are to be made to the particular declarative model data corresponding to the plurality of UI elements in order to enact the one or more desired edits to each of the plurality of UI elements; and an act of the computer system updating the first UI to reflect the one or more desired edits to the plurality of UI elements, including: preserving the state of the first UI to reflect the user selection of the particular UI element by continuing to visually indicate that the particular UI element has been selected by the user; and concurrent to continuing to visually indicate that the particular UI element has been selected by the user, altering the visual appearance of each of the plurality of UI elements, including the particular UI element, based on the one or more changes to the particular declarative model data corresponding to the plurality of UI elements. | 1. At a computer system that includes one or more processors and system memory, a method for providing a real-time incremental editor for enacting changes to user interface (UI) elements of an active UI, the method comprising: an act of the computer system presenting a first UI of an executing application program based on a UI model that includes declarative model data that drives the behavior of the first UI, the first UI including a plurality of UI elements, the UI model including particular declarative model data that declaratively defines a visual appearance of the plurality of UI elements of the first UI, each of the plurality of UI elements being an instance of the particular declarative model data; an-act of the computer system visually indicating a state of the first UI, including visually indicating within the first UI that a particular UI element of the plurality of UI elements has been selected by a user at the first UI; concurrent to presenting the first UI of the application program, and concurrent to visually indicating within the first UI that the particular UI element has been selected by a user: an act of the computer system presenting a second UI of a real-time incremental editor that is separate from the application program and that is configured to receive one or more editing inputs that are to be applied to the particular declarative model data of the UI model, to edit the first UI of the application program while the application program is executing; an act of the computer system receiving a first editing user input at the second UI of the real-time incremental editor, the first editing input selecting the particular declarative model data that declaratively defines the plurality of UI elements; based on selection of the particular declarative model data within the real-time incremental editor, visually distinguishing each of the plurality of UI elements, including the particular UI element, within the first UI as being selected at the second UI of the real-time incremental editor, while also visually indicating within the first UI that the particular UI element has been selected at the first UI; an act of the computer system receiving a second editing user input at the second UI of the real-time incremental editor, the second editing input indicating one or more desired edits that are to be made to the plurality of UI elements that affect the visual appearance of the plurality of UI elements within the first UI; an act of the computer system determining, based on the received editing input, one or more changes that are to be made to the particular declarative model data corresponding to the plurality of UI elements in order to enact the one or more desired edits to each of the plurality of UI elements; and an act of the computer system updating the first UI to reflect the one or more desired edits to the plurality of UI elements, including: preserving the state of the first UI to reflect the user selection of the particular UI element by continuing to visually indicate that the particular UI element has been selected by the user; and concurrent to continuing to visually indicate that the particular UI element has been selected by the user, altering the visual appearance of each of the plurality of UI elements, including the particular UI element, based on the one or more changes to the particular declarative model data corresponding to the plurality of UI elements. 5. The method of claim 1 , wherein the declarative model data comprises a schematized XAF application description. | 0.892655 |
9,489,376 | 15 | 21 | 15. A computer program product in a non-transitory computer-readable storage medium in a data processing system, the computer program product holding computer program instructions which, when executed by the data processing system, perform a method of identifying potential confidential information in a data item, the data item associated with a source, the method comprising: obtaining, from each of a set of alternative sources, a data item of a same type and format as the data item; comparing the data item to the data item(s) obtained from the set of alternative sources to identify occurrences of particular pieces of information in the data item, wherein multiple occurrences of a particular piece of information within a data item from each alternative source are treated as a single occurrence; and based on the occurrences of particular pieces of information in the data item and a given sensitivity criteria, and without knowledge that the particular pieces of information are considered by the source to be confidential, segmenting one or more pieces of information in the data item as representing the potential confidential information. | 15. A computer program product in a non-transitory computer-readable storage medium in a data processing system, the computer program product holding computer program instructions which, when executed by the data processing system, perform a method of identifying potential confidential information in a data item, the data item associated with a source, the method comprising: obtaining, from each of a set of alternative sources, a data item of a same type and format as the data item; comparing the data item to the data item(s) obtained from the set of alternative sources to identify occurrences of particular pieces of information in the data item, wherein multiple occurrences of a particular piece of information within a data item from each alternative source are treated as a single occurrence; and based on the occurrences of particular pieces of information in the data item and a given sensitivity criteria, and without knowledge that the particular pieces of information are considered by the source to be confidential, segmenting one or more pieces of information in the data item as representing the potential confidential information. 21. The computer program product as described in claim 15 wherein the given sensitivity criteria is a configurable threshold. | 0.632353 |
7,657,515 | 26 | 27 | 26. The method of claim 25 further comprising: combining the results from all sub-queries to create a single query result; and returning the single query result. | 26. The method of claim 25 further comprising: combining the results from all sub-queries to create a single query result; and returning the single query result. 27. The method of claim 26 further comprising removing duplicate results from the single query result. | 0.961567 |
8,249,347 | 4 | 5 | 4. The method of claim 1 , wherein processing includes improving a quality of the at least one portion. | 4. The method of claim 1 , wherein processing includes improving a quality of the at least one portion. 5. The method of claim 4 , wherein improving is performed using an adaptive image normalization algorithm. | 0.971459 |
9,305,101 | 15 | 18 | 15. A method, comprising: at a computer system with one or more servers that are configured to host an online media store: receiving, over a network, at least one search character entered at a client application on a client device; determining a set of words that match the at least one search character, each word in the determined set of words being associated with one or more digital media assets available at the online media store; based on capabilities of the client device, filtering out a particular set of words from the determined set of words that match the at least one search character; obtaining sales popularity data for the digital media assets, wherein the sales popularity data for a respective digital media asset is based on purchase data for the respective digital media asset; ordering words in the determined set of words based on the sales popularity data of corresponding digital media assets; and sending at least a subset of the ordered words to the client device for presentation in the client application. | 15. A method, comprising: at a computer system with one or more servers that are configured to host an online media store: receiving, over a network, at least one search character entered at a client application on a client device; determining a set of words that match the at least one search character, each word in the determined set of words being associated with one or more digital media assets available at the online media store; based on capabilities of the client device, filtering out a particular set of words from the determined set of words that match the at least one search character; obtaining sales popularity data for the digital media assets, wherein the sales popularity data for a respective digital media asset is based on purchase data for the respective digital media asset; ordering words in the determined set of words based on the sales popularity data of corresponding digital media assets; and sending at least a subset of the ordered words to the client device for presentation in the client application. 18. The method of claim 15 , wherein filtering out the particular set of words based on the capabilities of the client device includes filtering out a set of words that corresponds to a particular media asset that is not usable on the client device due to hardware on the client device. | 0.660333 |
5,493,678 | 7 | 8 | 7. A method of manipulating data organized as a hierarchy or tree with a single root data element and one or more lower layers of subsidiary (child) data elements such that zero, one or more subsidiary data elements are related to only one parent data element in the next higher level in the hierarchy wherein said data is stored in a storage means of a data processing system, and said manipulating is performed by said data processing system in response to operator directions, said method of manipulating data comprising the steps of: (a) selecting from said hierarchically organized data elements a plurality of data elements for removal, said data elements being selected without regard to their relationship to other selected data elements; (b) grouping said selected data elements into simply connected groups such that each element of a group is connected to at most one data element in the hierarchical layer immediately above its layer while preserving existing hierarchical relationships; and (c) for each simply connected group: (1) identifying the highest-order data element in said group; (2) identifying the parent data element of said highest-order data element; (3) identifying all data elements connected to one of said selected data elements in said group but not selected; (4) removing all data elements contained in said group from said tree; and (5) connecting to said parent of said highest-order data elements all data elements connected to said group but not removed. | 7. A method of manipulating data organized as a hierarchy or tree with a single root data element and one or more lower layers of subsidiary (child) data elements such that zero, one or more subsidiary data elements are related to only one parent data element in the next higher level in the hierarchy wherein said data is stored in a storage means of a data processing system, and said manipulating is performed by said data processing system in response to operator directions, said method of manipulating data comprising the steps of: (a) selecting from said hierarchically organized data elements a plurality of data elements for removal, said data elements being selected without regard to their relationship to other selected data elements; (b) grouping said selected data elements into simply connected groups such that each element of a group is connected to at most one data element in the hierarchical layer immediately above its layer while preserving existing hierarchical relationships; and (c) for each simply connected group: (1) identifying the highest-order data element in said group; (2) identifying the parent data element of said highest-order data element; (3) identifying all data elements connected to one of said selected data elements in said group but not selected; (4) removing all data elements contained in said group from said tree; and (5) connecting to said parent of said highest-order data elements all data elements connected to said group but not removed. 8. The method of claim 7, wherein each data element is classified into a type category and wherein the method further comprises the step of specifying permitted relationships between data elements, said permitted relationships defining when and how data elements of different types may be connected. | 0.606579 |
8,108,214 | 7 | 8 | 7. The method of claim 5 further comprising generating a second machine response the user utterance including an additional indirect confirmation question related to the proper name, wherein the second machine response does not repeat the proper name, if the second confidence score is below the defined threshold value. | 7. The method of claim 5 further comprising generating a second machine response the user utterance including an additional indirect confirmation question related to the proper name, wherein the second machine response does not repeat the proper name, if the second confidence score is below the defined threshold value. 8. The method of claim 7 further comprising formulating the additional indirect confirmation question by incorporating at least one additional characteristic of the one or more characteristics from the first machine response in the second machine response. | 0.843137 |
9,208,214 | 2 | 3 | 2. The method of claim 1 wherein the column attributes are selected from the group consisting of a column name, a column data type, and a column data size, and wherein the comparing further comprises: identifying a column attribute type, a wildcard character and a search string in one of the attributes included in the identified expression clause; and comparing the search string to a portion of the identified column attribute type based on a position of the wildcard character in relation to the search string. | 2. The method of claim 1 wherein the column attributes are selected from the group consisting of a column name, a column data type, and a column data size, and wherein the comparing further comprises: identifying a column attribute type, a wildcard character and a search string in one of the attributes included in the identified expression clause; and comparing the search string to a portion of the identified column attribute type based on a position of the wildcard character in relation to the search string. 3. The method of claim 2 wherein the column attributes include a plurality of column attributes related with one or more logical operators, wherein the logical operators are selected from the group consisting of AND, OR, and NOT. | 0.898132 |
9,693,198 | 8 | 10 | 8. The method according to claim 1 , comprising determining a distance from one or more of said sources of textual information in the vicinity of said wireless communication device based on known optical properties of a camera in said wireless communication device. | 8. The method according to claim 1 , comprising determining a distance from one or more of said sources of textual information in the vicinity of said wireless communication device based on known optical properties of a camera in said wireless communication device. 10. The method according to claim 8 , wherein said determined distance is used to determine an accurate location based on said captured one or more images. | 0.904674 |
8,037,086 | 6 | 9 | 6. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a pair of terms that includes a term and a candidate synonym of the term; determining that the terms of the pair have been identified as being potentially non-synonymous; evaluating the pair of terms using one or more penalty criteria that are only applied to terms that are identified as being potentially non-synonymous, comprising determining a quantity of switches that have occurred between queries that include the term and queries that include the candidate synonym of the term; selecting a first threshold if the pair of terms satisfies the penalty criteria, or a second threshold if the pair of terms does not satisfy the penalty criteria, wherein the first threshold is a same threshold that is applied to pairs of terms that are not identified as being potentially non-synonymous, and wherein the second threshold is higher than the first threshold; and determining that the terms of the pair are synonyms when the selected threshold is exceeded. | 6. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a pair of terms that includes a term and a candidate synonym of the term; determining that the terms of the pair have been identified as being potentially non-synonymous; evaluating the pair of terms using one or more penalty criteria that are only applied to terms that are identified as being potentially non-synonymous, comprising determining a quantity of switches that have occurred between queries that include the term and queries that include the candidate synonym of the term; selecting a first threshold if the pair of terms satisfies the penalty criteria, or a second threshold if the pair of terms does not satisfy the penalty criteria, wherein the first threshold is a same threshold that is applied to pairs of terms that are not identified as being potentially non-synonymous, and wherein the second threshold is higher than the first threshold; and determining that the terms of the pair are synonyms when the selected threshold is exceeded. 9. The computer storage medium of claim 6 , wherein evaluating the pair of terms using one or more penalty criteria comprises: determining a first quantity, representing a number of times that users of a search engine have submitted queries that include the term; and calculating a ratio by dividing the quantity of switches by the first quantity; and determining whether the ratio satisfies a predetermined comparison threshold. | 0.533696 |
8,060,816 | 19 | 24 | 19. An article of manufacture for performing document retrieval in accordance with an information network, comprising a machine readable medium containing one or more programs which when executed implement the steps of: initially retrieving one or more documents from the information network that satisfy a user-defined predicate, wherein the initial document retrieval operation is performed without assuming a specific model of a linkage structure such that the initial document retrieval operation retrieves the one or more documents without assuming that a relationship exists between a feature of a first one of the one or more documents and a feature of at least another one of the one or more documents that links to the first one; collecting at least a set of aggregate statistical information and a set of predicate-specific statistical information about the one or more retrieved documents as the one or more retrieved documents are analyzed; and using the collected statistical information to automatically determine further document retrieval operations to be performed in accordance with the information network, wherein the statistical information using step further comprises learning a linkage structure from at least a portion of the collected statistical information with each successive document retrieval operation such that the learned linkage structure is available for use in performing subsequent document retrieval operations requested by a user. | 19. An article of manufacture for performing document retrieval in accordance with an information network, comprising a machine readable medium containing one or more programs which when executed implement the steps of: initially retrieving one or more documents from the information network that satisfy a user-defined predicate, wherein the initial document retrieval operation is performed without assuming a specific model of a linkage structure such that the initial document retrieval operation retrieves the one or more documents without assuming that a relationship exists between a feature of a first one of the one or more documents and a feature of at least another one of the one or more documents that links to the first one; collecting at least a set of aggregate statistical information and a set of predicate-specific statistical information about the one or more retrieved documents as the one or more retrieved documents are analyzed; and using the collected statistical information to automatically determine further document retrieval operations to be performed in accordance with the information network, wherein the statistical information using step further comprises learning a linkage structure from at least a portion of the collected statistical information with each successive document retrieval operation such that the learned linkage structure is available for use in performing subsequent document retrieval operations requested by a user. 24. The article of claim 19 , wherein the collected statistical information is used to direct further document retrieval operations toward documents which are similar to the one or more retrieved documents that also satisfy the predicate. | 0.645833 |
9,798,703 | 12 | 17 | 12. The method of claim 11 , wherein executing the document validation system comprises executing an interface to an external validation system and receiving from the external validation system results from the external validation system's validation of the generated instance document including the generated status indicator corresponding to the code via the interface to the external validation system. | 12. The method of claim 11 , wherein executing the document validation system comprises executing an interface to an external validation system and receiving from the external validation system results from the external validation system's validation of the generated instance document including the generated status indicator corresponding to the code via the interface to the external validation system. 17. The method of claim 12 , wherein executing the interface to the external validation system and receiving from the external validation system validation results comprises both the document preparation system and the external validation system accessing a commonly accessible data store. | 0.848055 |
9,043,474 | 7 | 13 | 7. The method of claim 1 , the instructions configured to, upon receiving from at least one user at least one operation relating to the communication session, perform the operation on the communication session. | 7. The method of claim 1 , the instructions configured to, upon receiving from at least one user at least one operation relating to the communication session, perform the operation on the communication session. 13. The method of claim 7 : at least one first user of the communication session having a user profile describing the at least one first user; the operation comprising a request to share at least a portion of the user profile with at least one second user; and performing the operation on the communication session comprising: representing to the at least one second user the at least one first user according to the at least a portion of the user profile. | 0.845528 |
8,428,359 | 15 | 17 | 15. An electronic device comprising: a display having a plurality of discrete areas for entering a series of characters; a user input for entering characters via the plurality of discrete areas; a detector for detecting a first input associated with a first one of the plurality of discrete areas, the first input comprises an initiation stage and a composition stage, the composition stage comprising a plurality of drag actions; and a processor for recognizing the first input in the first one of the plurality of discrete areas as a first character input while the detector is operable to detect a second input, in a second one of the plurality of areas, for recognition as a second character input, the recognition of the second character input occurring separately to the recognition of the first character input, the processor further associating one of the plurality of discrete areas with the first input from the position of the initiation stage of the first input and continuing the association when the composition stage of the first input extends outside of the discrete area in which the initiation stage occurred so long as each of the plurality of drag actions is initiated within the discrete area. | 15. An electronic device comprising: a display having a plurality of discrete areas for entering a series of characters; a user input for entering characters via the plurality of discrete areas; a detector for detecting a first input associated with a first one of the plurality of discrete areas, the first input comprises an initiation stage and a composition stage, the composition stage comprising a plurality of drag actions; and a processor for recognizing the first input in the first one of the plurality of discrete areas as a first character input while the detector is operable to detect a second input, in a second one of the plurality of areas, for recognition as a second character input, the recognition of the second character input occurring separately to the recognition of the first character input, the processor further associating one of the plurality of discrete areas with the first input from the position of the initiation stage of the first input and continuing the association when the composition stage of the first input extends outside of the discrete area in which the initiation stage occurred so long as each of the plurality of drag actions is initiated within the discrete area. 17. A device as claimed in claim 15 , wherein a character input comprises a single character. | 0.829044 |
8,363,918 | 10 | 13 | 10. An apparatus for detecting a plurality of anatomical landmarks in an image comprising: means for detecting a first landmark of the plurality of anatomical landmarks in the image using marginal space learning (MSL); means for estimating locations of remaining landmarks of the plurality of anatomical landmarks in the image based on the detected first landmark using a learned geometric model relating the plurality of anatomical landmarks; and means for detecting each of said remaining landmarks using MSL in a portion of the image constrained based on the estimated location of each of said remaining landmarks. | 10. An apparatus for detecting a plurality of anatomical landmarks in an image comprising: means for detecting a first landmark of the plurality of anatomical landmarks in the image using marginal space learning (MSL); means for estimating locations of remaining landmarks of the plurality of anatomical landmarks in the image based on the detected first landmark using a learned geometric model relating the plurality of anatomical landmarks; and means for detecting each of said remaining landmarks using MSL in a portion of the image constrained based on the estimated location of each of said remaining landmarks. 13. The apparatus of claim 10 , wherein said means for estimating locations of remaining landmarks of the plurality of anatomical landmarks in the image based on the detected first landmark using a learned geometric model relating the plurality of anatomical landmarks comprises: means for transforming a mean shape of the learned geometric model based on a similarity transformation of the detected first landmark. | 0.808048 |
8,738,355 | 15 | 18 | 15. An apparatus comprising: means for obtaining a request for translation information from a mobile station, said translation information being associated with one or more written and/or spoken languages; means for associating a location with said request for translation information; and means for generating requested translation information based, at least in part, on said request for translation information, said location, and predicted information, wherein the predicted information is associated with at least one other request for translation information associated with at least one other location and previously obtained from at least one other mobile station. | 15. An apparatus comprising: means for obtaining a request for translation information from a mobile station, said translation information being associated with one or more written and/or spoken languages; means for associating a location with said request for translation information; and means for generating requested translation information based, at least in part, on said request for translation information, said location, and predicted information, wherein the predicted information is associated with at least one other request for translation information associated with at least one other location and previously obtained from at least one other mobile station. 18. The apparatus as recited in claim 15 , further comprising: means for translating first information of said request for translation information that is represented in a first language into corresponding second information represented in a second language, wherein said requested translation information comprises said second information. | 0.81441 |
9,138,591 | 1 | 25 | 1. An external medical device, comprising: a housing; an energy storage module within the housing for storing an electrical charge; a defibrillation port for guiding via electrodes the stored electrical charge to a person; a user interface structured to deliver prompts to a user during a defibrillation session; and a language detector in the housing structured to determine a vicinity language, in which the prompts delivered by the user interface to the user during the defibrillation session are in a language that is selected based on the determined vicinity language, and further in which the language detector includes an optical character recognition (OCR) module, or both a voice recognition module and an OCR module. | 1. An external medical device, comprising: a housing; an energy storage module within the housing for storing an electrical charge; a defibrillation port for guiding via electrodes the stored electrical charge to a person; a user interface structured to deliver prompts to a user during a defibrillation session; and a language detector in the housing structured to determine a vicinity language, in which the prompts delivered by the user interface to the user during the defibrillation session are in a language that is selected based on the determined vicinity language, and further in which the language detector includes an optical character recognition (OCR) module, or both a voice recognition module and an OCR module. 25. The device of claim 1 , in which the language detector is structured to monitor ambient sounds. | 0.8213 |
9,508,341 | 9 | 16 | 9. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, generating a prediction performance model for a pronunciation prediction model based on: a comparison of an automatically predicted pronunciation of a word with a manually provided pronunciation of the word, and confidence scores for the automatically predicted pronunciations, wherein the prediction performance model is adapted to generate performance information for a grapheme-to-phoneme model, the performance information indicating a degree of confidence in the grapheme-to-phoneme model to predict a new word added to a lexicon based upon an input predicted pronunciation generated by the grapheme-to-phoneme model for the new word and the confidence score for the input predicted pronunciation generated by the grapheme-to-phoneme model; generating, from the pronunciation prediction model, a pronunciation prediction for a candidate word to be added to the lexicon and a confidence score for the candidate word; generating, from the prediction performance model, an annotation priority for the candidate word based on the confidence score for the pronunciation prediction of the candidate word and the predicted pronunciation of the candidate word; generating a value identifying a relationship between the annotation priority for the candidate word and a threshold; and routing the candidate word to one of a manual pronunciation generator or an automatic pronunciation generator based on the value. | 9. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, generating a prediction performance model for a pronunciation prediction model based on: a comparison of an automatically predicted pronunciation of a word with a manually provided pronunciation of the word, and confidence scores for the automatically predicted pronunciations, wherein the prediction performance model is adapted to generate performance information for a grapheme-to-phoneme model, the performance information indicating a degree of confidence in the grapheme-to-phoneme model to predict a new word added to a lexicon based upon an input predicted pronunciation generated by the grapheme-to-phoneme model for the new word and the confidence score for the input predicted pronunciation generated by the grapheme-to-phoneme model; generating, from the pronunciation prediction model, a pronunciation prediction for a candidate word to be added to the lexicon and a confidence score for the candidate word; generating, from the prediction performance model, an annotation priority for the candidate word based on the confidence score for the pronunciation prediction of the candidate word and the predicted pronunciation of the candidate word; generating a value identifying a relationship between the annotation priority for the candidate word and a threshold; and routing the candidate word to one of a manual pronunciation generator or an automatic pronunciation generator based on the value. 16. The computer-implemented method of claim 9 , wherein the computer-implemented method further comprises receiving a manually provided pronunciation for the candidate word from the manual pronunciation generator. | 0.91157 |
9,946,696 | 6 | 7 | 6. The computer-implemented method according to claim 1 , wherein the guidelines comprise a hierarchical order of the guidelines, and where the insertion point is automatically adjusted in accordance with the hierarchical order. | 6. The computer-implemented method according to claim 1 , wherein the guidelines comprise a hierarchical order of the guidelines, and where the insertion point is automatically adjusted in accordance with the hierarchical order. 7. The computer-implemented method according to claim 6 , wherein the selecting of the dominant guideline is based on evaluation of the hierarchical order. | 0.903965 |
7,792,855 | 9 | 10 | 9. A computer system comprising: a processor; and a program storage device readable by the computer system, embodying a program of instructions executable by the processor to perform method steps for mapping a document to a directory, the method comprising: establishing an entry in the directory corresponding to the document, the document comprising an unparsed XML document; storing one or more search attributes in the entry containing one or more corresponding search terms, each of the one or more corresponding search terms having a particular value selected from the unparsed XML document; storing a full-text attribute containing the unparsed XML document in the entry; storing a summary attribute containing at least a portion of the unparsed XML document in the entry, wherein the summary attribute, the full-text attribute, and the one or more search attributes are stored as separate attributes in the entry; receiving a search request comprising at least one search parameter; identifying the entry in the directory by comparing the at least one search parameter to the one or more search attributes in the entry; retrieving the summary attribute; and transmitting data operable to display the summary attribute. | 9. A computer system comprising: a processor; and a program storage device readable by the computer system, embodying a program of instructions executable by the processor to perform method steps for mapping a document to a directory, the method comprising: establishing an entry in the directory corresponding to the document, the document comprising an unparsed XML document; storing one or more search attributes in the entry containing one or more corresponding search terms, each of the one or more corresponding search terms having a particular value selected from the unparsed XML document; storing a full-text attribute containing the unparsed XML document in the entry; storing a summary attribute containing at least a portion of the unparsed XML document in the entry, wherein the summary attribute, the full-text attribute, and the one or more search attributes are stored as separate attributes in the entry; receiving a search request comprising at least one search parameter; identifying the entry in the directory by comparing the at least one search parameter to the one or more search attributes in the entry; retrieving the summary attribute; and transmitting data operable to display the summary attribute. 10. The computer system of claim 9 , wherein the directory is an LDAP directory. | 0.798995 |
7,642,922 | 1 | 8 | 1. A drive support apparatus for a movable body, comprising: a driving state detecting portion for acquiring driving state information comprising at least either information about a traveling situation of the movable body or information about a driving operation of a driver of the movable body, from a sensor provided in the movable body during a drive of the movable body by the driver; a driver information storing portion for storing awareness information that represents a digitized awareness of the driver indicating how much the driver is aware of a regulated or recommended driving condition for safe driving of the movable body; an interaction controlling portion configured to, decide whether to start an interaction with the driver based on whether the driving state information and the awareness information satisfy a predetermined interaction-start condition; generate a question to check the driver's awareness that indicates how much the driver is aware of a regulated or recommended driving condition for safe driving in the case of a decision to start the interaction; output the generated question as a synthesized voice; recognize an answer content from a voice of the driver to the question; generate advice for safe driving in response to the answer; and output the generated advice as a synthesized voice; an awareness information generating portion for updating the awareness information in accordance with the answer content recognized by the interaction controlling portion; and a safe-driving information storing portion for storing safe driving information comprising information that represents a condition for safe driving, wherein the awareness information generating portion decides whether the answer content recognized by the interaction controlling portion is correct or not, on the basis of the answer content and the safe driving information; when the answer content is decided as correct, awareness information generating portion decides whether or not to update the awareness information stored in the driver information storing portion depending on the answer content and the driving state information satisfy a predetermined awareness information updating condition, and in a case of a decision that the awareness information should be updated, the awareness information generating portion updates the awareness information to a value representing a state of a higher awareness, and when the answer content is decided as incorrect, the awareness information generating portion updates the awareness information stored in the driver information storing portion to a value representing a state of a lower awareness. | 1. A drive support apparatus for a movable body, comprising: a driving state detecting portion for acquiring driving state information comprising at least either information about a traveling situation of the movable body or information about a driving operation of a driver of the movable body, from a sensor provided in the movable body during a drive of the movable body by the driver; a driver information storing portion for storing awareness information that represents a digitized awareness of the driver indicating how much the driver is aware of a regulated or recommended driving condition for safe driving of the movable body; an interaction controlling portion configured to, decide whether to start an interaction with the driver based on whether the driving state information and the awareness information satisfy a predetermined interaction-start condition; generate a question to check the driver's awareness that indicates how much the driver is aware of a regulated or recommended driving condition for safe driving in the case of a decision to start the interaction; output the generated question as a synthesized voice; recognize an answer content from a voice of the driver to the question; generate advice for safe driving in response to the answer; and output the generated advice as a synthesized voice; an awareness information generating portion for updating the awareness information in accordance with the answer content recognized by the interaction controlling portion; and a safe-driving information storing portion for storing safe driving information comprising information that represents a condition for safe driving, wherein the awareness information generating portion decides whether the answer content recognized by the interaction controlling portion is correct or not, on the basis of the answer content and the safe driving information; when the answer content is decided as correct, awareness information generating portion decides whether or not to update the awareness information stored in the driver information storing portion depending on the answer content and the driving state information satisfy a predetermined awareness information updating condition, and in a case of a decision that the awareness information should be updated, the awareness information generating portion updates the awareness information to a value representing a state of a higher awareness, and when the answer content is decided as incorrect, the awareness information generating portion updates the awareness information stored in the driver information storing portion to a value representing a state of a lower awareness. 8. The drive support apparatus for a movable body according to claim 1 , wherein the sensor comprises a sensor for detecting a sign of dozing of the driver, and when the dozing of the driver is detected by the sensor, the interaction controlling portion starts an interaction with the driver irrespective of satisfaction of the interaction-start conditions. | 0.501397 |
8,498,994 | 15 | 16 | 15. The computing system recited in claim 10 , the one or more computing devices further configured to: designate the second document file as being associated with the social file, the social file providing access to the second document file via the social network. | 15. The computing system recited in claim 10 , the one or more computing devices further configured to: designate the second document file as being associated with the social file, the social file providing access to the second document file via the social network. 16. The computing system recited in claim 15 , wherein the first and second document files are each divided into a plurality of document file portions, the document file portions being capable of segmenting a visual display of the first and second document files. | 0.888465 |
7,681,125 | 1 | 7 | 1. A computer program product comprising computer readable instruction code executing in a tangible memory medium of a computer, said computer readable instruction code configured to: present a text detail window in a first screen region of a graphical user interface; present an expanded text window in a second screen region of said graphical user interface; present at least one clause in a third screen region of said graphical user interface; present at least one function a fourth screen region of said graphical user interface; present at least one operator in a fifth screen region of said graphical user interface; present at least one selector in a sixth screen region of said graphical user interface; accept text, clause, function, operator and selector input from a user via said graphical user interface; access data from a database; and, output text wherein said text comprises said data from said database and conditional text based on said text, clause, function, operator and selector input. | 1. A computer program product comprising computer readable instruction code executing in a tangible memory medium of a computer, said computer readable instruction code configured to: present a text detail window in a first screen region of a graphical user interface; present an expanded text window in a second screen region of said graphical user interface; present at least one clause in a third screen region of said graphical user interface; present at least one function a fourth screen region of said graphical user interface; present at least one operator in a fifth screen region of said graphical user interface; present at least one selector in a sixth screen region of said graphical user interface; accept text, clause, function, operator and selector input from a user via said graphical user interface; access data from a database; and, output text wherein said text comprises said data from said database and conditional text based on said text, clause, function, operator and selector input. 7. The computer program product of claim 1 further comprising: present a value input user interface area in an eighth screen region of said graphical user interface. | 0.817881 |
9,223,897 | 1 | 15 | 1. A method performed by one or more server devices, the method comprising: obtaining, by the one or more server devices, a rank position map, the rank position map specifying, for a plurality of rank positions, an expected utility rate for a document presented at a particular one of the plurality of rank positions as a search result, the expected utility rate being derived from an aggregate quantity of selections of the document presented as a search result at the particular one of the plurality of rank positions; determining, by the one or more server devices, an expected utility rate, for a particular document, based on the obtained rank position map and based on a quantity of times that the particular document was presented as a search result at particular ones of the plurality of rank positions; determining, by the one or more server devices, an actual utility rate for the particular document based on an actual quantity of selections of the particular document and based on a total quantity of times that the particular document was presented as a search result; calculating, by the one or more server devices, a correction factor, for the particular document, based on the determined expected utility rate and the determined actual utility rate; determining, by the one or more server devices, a confidence level for the correction factor, the confidence level representing a measure of confidence associated with the correction factor; adjusting, by the one or more server devices, the correction factor based on the determined confidence level; selecting, by the one or more server devices and based on determining that the confidence level is less than an aggregation threshold, a set of documents, the particular document being included in the set of documents; calculating, by the one or more server devices, an aggregated correction factor for the set of documents; using, by the one or more server devices, the aggregated correction factor as the correction factor for the particular document; adjusting, by the one or more server devices, a score of the particular document based on the correction factor; and providing, for presentation, a ranked list of search results, one of the search results corresponding to the particular document, and a ranking of the search result corresponding to the particular document being based on the adjusted score. | 1. A method performed by one or more server devices, the method comprising: obtaining, by the one or more server devices, a rank position map, the rank position map specifying, for a plurality of rank positions, an expected utility rate for a document presented at a particular one of the plurality of rank positions as a search result, the expected utility rate being derived from an aggregate quantity of selections of the document presented as a search result at the particular one of the plurality of rank positions; determining, by the one or more server devices, an expected utility rate, for a particular document, based on the obtained rank position map and based on a quantity of times that the particular document was presented as a search result at particular ones of the plurality of rank positions; determining, by the one or more server devices, an actual utility rate for the particular document based on an actual quantity of selections of the particular document and based on a total quantity of times that the particular document was presented as a search result; calculating, by the one or more server devices, a correction factor, for the particular document, based on the determined expected utility rate and the determined actual utility rate; determining, by the one or more server devices, a confidence level for the correction factor, the confidence level representing a measure of confidence associated with the correction factor; adjusting, by the one or more server devices, the correction factor based on the determined confidence level; selecting, by the one or more server devices and based on determining that the confidence level is less than an aggregation threshold, a set of documents, the particular document being included in the set of documents; calculating, by the one or more server devices, an aggregated correction factor for the set of documents; using, by the one or more server devices, the aggregated correction factor as the correction factor for the particular document; adjusting, by the one or more server devices, a score of the particular document based on the correction factor; and providing, for presentation, a ranked list of search results, one of the search results corresponding to the particular document, and a ranking of the search result corresponding to the particular document being based on the adjusted score. 15. The method of claim 1 , where determining the actual utility rate includes: dividing the actual quantity of selections of the particular document by the total quantity of times that the particular document was presented as a search result to obtain the actual utility rate. | 0.733141 |
8,738,355 | 63 | 64 | 63. The mobile station as recited in claim 60 , wherein said request for translation information comprises first information that is represented in a first language, and said requested translation information comprises corresponding second information as translated in a second language. | 63. The mobile station as recited in claim 60 , wherein said request for translation information comprises first information that is represented in a first language, and said requested translation information comprises corresponding second information as translated in a second language. 64. The mobile station as recited in claim 63 , wherein said second information comprises a plurality of different translated versions of said first information, and said one or more processing units to: select at least one of said plurality of different translated versions of said first information for said presentation. | 0.875865 |
7,523,394 | 11 | 12 | 11. A computer-readable storage medium having computer-executable components, comprising: a first component for reading a word-processor document stored as a single XML file; a second component that utilizes an XSD for interpreting the word-processor document; wherein the XSD represents a word-processor's rich formatting and wherein the XSD is published and is available to applications other than the word-processor; a third component for performing actions on the word-processor document; including: fully recreating the word-processor document from the single XML file according to a word processor's set of features; storing only text between a first text tag and a second text tag within the word-processor document; wherein all of the text of the word-processor document is contained within one or more of the first text tags and the second text tags; wherein there are no intervening tags between each of the first text tags and each of the corresponding second text tags and wherein each of the first and second text tags do not include formatting information for the text between each of the first text tags and the second text tags; storing an image within the word-processor document as a binary encoding; and storing template information as a binary encoding within the word-processor document; and a fourth component that is configured to validate the word-process document. | 11. A computer-readable storage medium having computer-executable components, comprising: a first component for reading a word-processor document stored as a single XML file; a second component that utilizes an XSD for interpreting the word-processor document; wherein the XSD represents a word-processor's rich formatting and wherein the XSD is published and is available to applications other than the word-processor; a third component for performing actions on the word-processor document; including: fully recreating the word-processor document from the single XML file according to a word processor's set of features; storing only text between a first text tag and a second text tag within the word-processor document; wherein all of the text of the word-processor document is contained within one or more of the first text tags and the second text tags; wherein there are no intervening tags between each of the first text tags and each of the corresponding second text tags and wherein each of the first and second text tags do not include formatting information for the text between each of the first text tags and the second text tags; storing an image within the word-processor document as a binary encoding; and storing template information as a binary encoding within the word-processor document; and a fourth component that is configured to validate the word-process document. 12. The computer-readable storage medium of claim 11 , wherein the word-processor document includes hints within the single XML file that describe to an application that did not create the single XML file how to recreate one of the features from the word-processors set of features without user interaction. | 0.501623 |
8,886,519 | 15 | 17 | 15. The text processing method according to claim 14 , wherein the (b) step comprises deriving, based on the result of the determination in the (a) step, an extent to which the content of the homogeneous segment is included in the second text corresponding to the other first text which includes the homogeneous segment, further deriving, based on the derived extent, a degree to which each segment constituting the first text which is set as the analysis target should be described in the second text corresponding to the first text which is set as the analysis target, and performing the determination using the degree. | 15. The text processing method according to claim 14 , wherein the (b) step comprises deriving, based on the result of the determination in the (a) step, an extent to which the content of the homogeneous segment is included in the second text corresponding to the other first text which includes the homogeneous segment, further deriving, based on the derived extent, a degree to which each segment constituting the first text which is set as the analysis target should be described in the second text corresponding to the first text which is set as the analysis target, and performing the determination using the degree. 17. The text processing method according to claim 15 , wherein the (b) step comprises deriving, as the extent of inclusion in the second text, a percentage at which the content of the homogeneous segment is described in the second text corresponding to the other first text which includes the homogeneous segment, further deriving a degree to which each segment constituting the first text which is set as the analysis target should be described in the second text corresponding to the first text which is set as the analysis target, such that the degree increases the higher the percentage, and performing the determination using the derived degree. | 0.767359 |
9,135,517 | 5 | 7 | 5. A method, comprising: obtaining an image of at least a portion of a document; processing the image to determine a plurality of image characteristics of the image wherein the plurality of image characteristics comprise at least one of a first image characteristic representing ascending letters in the image, a second image characteristic representing descending letters in the image, a third image characteristic representing a number of letters in a word in the image and a fourth image characteristic representing a number of words in a line of text in the image; and identifying a previously stored source document based at least in part on the plurality of image characteristics. | 5. A method, comprising: obtaining an image of at least a portion of a document; processing the image to determine a plurality of image characteristics of the image wherein the plurality of image characteristics comprise at least one of a first image characteristic representing ascending letters in the image, a second image characteristic representing descending letters in the image, a third image characteristic representing a number of letters in a word in the image and a fourth image characteristic representing a number of words in a line of text in the image; and identifying a previously stored source document based at least in part on the plurality of image characteristics. 7. The method of claim 5 , wherein the plurality of image characteristics comprises at least one of: a fifth image characteristic representing a margin width in the image, a sixth image characteristic representing information about a graphic in the image, and a seventh image characteristic representing information about a header or a footer in the image. | 0.84721 |
9,098,568 | 6 | 7 | 6. The computer-implemented method of claim 1 , wherein: the attributes of the query trigger further include a popularity score of the query trigger, the popularity score stored in the dictionary and being a measure of a popularity of the query trigger as a query for multiple users of a search engine; and calculating at the client device a rank score for the query trigger based on attributes of the query trigger comprises generating the rank score based on a function of the context of the query trigger, the frequency of occurrence of the query trigger, a length of the query trigger, and the popularity of the query trigger. | 6. The computer-implemented method of claim 1 , wherein: the attributes of the query trigger further include a popularity score of the query trigger, the popularity score stored in the dictionary and being a measure of a popularity of the query trigger as a query for multiple users of a search engine; and calculating at the client device a rank score for the query trigger based on attributes of the query trigger comprises generating the rank score based on a function of the context of the query trigger, the frequency of occurrence of the query trigger, a length of the query trigger, and the popularity of the query trigger. 7. The computer-implemented method of claim 6 , wherein each of the one or more terms of the query triggers are queries received from users of the search system and have a popularity score exceeding a minimum popularity threshold. | 0.932313 |
8,682,883 | 12 | 15 | 12. A non-transitory computer-readable medium having software instructions stored thereon, which, when executed by a client device, causes the client device to perform the operations comprising: receiving an identification of a product for clustering into one or more sets of similar products; transmitting a query to one or more internet websites having information related to the product; receiving from the one or more internet websites information relevant to the product; merging and storing the received information into one or more databases; transforming all received information into a text file; cleansing the text file to create a cleansed text file; creating a dictionary from the cleansed text file, wherein the dictionary comprises all words found in the cleansed text file; performing topic modeling on the cleansed text file to determine a cluster of one or more substitutes of the product, further comprising the steps of: computing a count of documents in which a word in the cleansed text file appears; and deleting one or more words that appear at a predetermined frequency from the dictionary; and computing a weight calculated by w = log [ total number of documents Documents in which the word appears ] wherein w is the “weight”. | 12. A non-transitory computer-readable medium having software instructions stored thereon, which, when executed by a client device, causes the client device to perform the operations comprising: receiving an identification of a product for clustering into one or more sets of similar products; transmitting a query to one or more internet websites having information related to the product; receiving from the one or more internet websites information relevant to the product; merging and storing the received information into one or more databases; transforming all received information into a text file; cleansing the text file to create a cleansed text file; creating a dictionary from the cleansed text file, wherein the dictionary comprises all words found in the cleansed text file; performing topic modeling on the cleansed text file to determine a cluster of one or more substitutes of the product, further comprising the steps of: computing a count of documents in which a word in the cleansed text file appears; and deleting one or more words that appear at a predetermined frequency from the dictionary; and computing a weight calculated by w = log [ total number of documents Documents in which the word appears ] wherein w is the “weight”. 15. The non-transitory computer-readable medium of claim 12 , wherein the method for performing topic modeling on the cleansed file is selected from the group consisting of latent semantic analysis, nonnegative matrix factorization, and singular value decomposition. | 0.507407 |
8,358,843 | 14 | 16 | 14. A method comprising: on an Internet-enabled portable electronic device, obtaining digital image information, wherein the digital image information corresponds to a digital image, and wherein the digital image relates to a digital photograph; using one or more computers or computerized devices, utilizing one or more character recognition techniques, determining a URI or URL included within the digital image; and on the Internet-enabled portable electronic device, utilizing the URI or URL, accessing a Web page corresponding to the URI or URL. | 14. A method comprising: on an Internet-enabled portable electronic device, obtaining digital image information, wherein the digital image information corresponds to a digital image, and wherein the digital image relates to a digital photograph; using one or more computers or computerized devices, utilizing one or more character recognition techniques, determining a URI or URL included within the digital image; and on the Internet-enabled portable electronic device, utilizing the URI or URL, accessing a Web page corresponding to the URI or URL. 16. The method of claim 14 , comprising determining the URI or URL utilizing an application on the Internet-enabled portable electronic device. | 0.71627 |
9,195,386 | 1 | 7 | 1. A method for an electronic device comprising: detecting a first touch input representing a selection of text in a first selection mode, the text being displayed on a touch-sensitive display of the electronic device; determining whether the selected text meets or exceeds a predetermined size, wherein the predetermined size comprises at least one complete row of displayed text; and responsive to the determination that the selected text comprises at least one complete row, enabling a second selection mode and displaying a paragraph selection handle proximate to the selected text. | 1. A method for an electronic device comprising: detecting a first touch input representing a selection of text in a first selection mode, the text being displayed on a touch-sensitive display of the electronic device; determining whether the selected text meets or exceeds a predetermined size, wherein the predetermined size comprises at least one complete row of displayed text; and responsive to the determination that the selected text comprises at least one complete row, enabling a second selection mode and displaying a paragraph selection handle proximate to the selected text. 7. The method according to claim 1 , wherein displaying the selection handle proximal to the selected text comprises displaying a start point handle proximal to a first row of selected rows and an end point handle proximal to a last row of the selected rows. | 0.520446 |
9,996,566 | 1 | 21 | 1. A system, the system comprising: a memory; a processor; a visual design system having an editor to enable a user to create and edit a visual data structure, said visual data structure based on a hierarchy of components, said components having types as defined by said visual design system; a database to store at least one visual data structure and an associated signature wherein said signature represents at least a semantic composition of said at least one visual data structure; a page analyzer to analyze at least said types and to generate an associated signature for said visual data structure wherein said associated signature for said visual data structure represents at least a semantic composition of said hierarchy of components of said visual data structure; a signature comparer to match a signature of said visual data structure to an associated signature of at least one visual data structure stored in said database and to present multiple versions of alternate visual data structures for said hierarchy of components for selection by a user; a visual data structure adapter and applier to adapt at least the attributes, said component types and content of said visual data structure to a selected visual data structure; and wherein said alternate visual data structures are visually different and semantically similar to each other; and wherein said processor activates said page analyzer, said signature comparer and said adapter and applier. | 1. A system, the system comprising: a memory; a processor; a visual design system having an editor to enable a user to create and edit a visual data structure, said visual data structure based on a hierarchy of components, said components having types as defined by said visual design system; a database to store at least one visual data structure and an associated signature wherein said signature represents at least a semantic composition of said at least one visual data structure; a page analyzer to analyze at least said types and to generate an associated signature for said visual data structure wherein said associated signature for said visual data structure represents at least a semantic composition of said hierarchy of components of said visual data structure; a signature comparer to match a signature of said visual data structure to an associated signature of at least one visual data structure stored in said database and to present multiple versions of alternate visual data structures for said hierarchy of components for selection by a user; a visual data structure adapter and applier to adapt at least the attributes, said component types and content of said visual data structure to a selected visual data structure; and wherein said alternate visual data structures are visually different and semantically similar to each other; and wherein said processor activates said page analyzer, said signature comparer and said adapter and applier. 21. The system according to claim 1 and wherein said visual design system is a page analyzing visual editor. | 0.853659 |
10,043,069 | 20 | 21 | 20. The non-transitory computer-readable storage medium of claim 16 , wherein the computer-readable medium is encoded with additional instructions which, when executed by the at least one processor, further cause the computing system to determine a category of the text data, and wherein determination of the first user-selectable function is based at least in part on a previously selected user function associated with the category of the text data. | 20. The non-transitory computer-readable storage medium of claim 16 , wherein the computer-readable medium is encoded with additional instructions which, when executed by the at least one processor, further cause the computing system to determine a category of the text data, and wherein determination of the first user-selectable function is based at least in part on a previously selected user function associated with the category of the text data. 21. The non-transitory computer-readable storage medium of claim 20 , wherein the previously selected user function is a function selected by the user associated with the image data. | 0.947671 |
8,667,051 | 5 | 9 | 5. The method, as set forth in claim 1 , further comprising at least one of detecting or recognizing that said one or more broadcasted keywords includes at least one identifier. | 5. The method, as set forth in claim 1 , further comprising at least one of detecting or recognizing that said one or more broadcasted keywords includes at least one identifier. 9. The method, as set forth in claim 5 , wherein said at least one identifier comprises at least one zip code and storing contact information further comprises extracting a postal address preceding said zip code to store said postal address in an address book. | 0.924242 |
8,856,167 | 7 | 8 | 7. A method comprising: receiving a request for a suggested question, by a computing device over a network, from a requesting user using an online question and answer site, the question and answer site comprising questions posed by users and answers submitted by other users, the question comprising an identification of a user; formulating, by the computing device in the online question and answer site and based on the identification of the user, a first query so as to search, via the network, using a global index that relates entities known to the network with one another, for knowledge data, user profile data, social network data, spatial data, temporal data and topical data available to the network that relates to the user identification so as to identify knowledge data relevant to a current context of the identified user, wherein the knowledge data comprises questions and answers entered by a first plurality of users and the knowledge data for each question and answer additionally comprises an identification of one of a second plurality of users who consumed the knowledge data, a selection by the questioning user of a best answer from among posted answers, and consumption popularity data; transmitting, by the computing device over the network, the identified knowledge data to the requesting user. | 7. A method comprising: receiving a request for a suggested question, by a computing device over a network, from a requesting user using an online question and answer site, the question and answer site comprising questions posed by users and answers submitted by other users, the question comprising an identification of a user; formulating, by the computing device in the online question and answer site and based on the identification of the user, a first query so as to search, via the network, using a global index that relates entities known to the network with one another, for knowledge data, user profile data, social network data, spatial data, temporal data and topical data available to the network that relates to the user identification so as to identify knowledge data relevant to a current context of the identified user, wherein the knowledge data comprises questions and answers entered by a first plurality of users and the knowledge data for each question and answer additionally comprises an identification of one of a second plurality of users who consumed the knowledge data, a selection by the questioning user of a best answer from among posted answers, and consumption popularity data; transmitting, by the computing device over the network, the identified knowledge data to the requesting user. 8. The method of claim 7 wherein the request is automatically submitted on behalf of the requesting user in response to a trigger event. | 0.914033 |
8,756,185 | 32 | 33 | 32. The method of claim 30 , further comprising: generating a first personal semantic network associated with a first user; generating a second personal semantic network associated with a second user; establishing one or more connections between the first personal semantic network and the second personal semantic network, wherein the one or more connections are determined by the semantic similarity between the first personal semantic network and the second personal semantic network; and producing a personal output representation of a given document based on the one or more connections, thereby enabling sharing of information associated with the given document between the first user and the second user. | 32. The method of claim 30 , further comprising: generating a first personal semantic network associated with a first user; generating a second personal semantic network associated with a second user; establishing one or more connections between the first personal semantic network and the second personal semantic network, wherein the one or more connections are determined by the semantic similarity between the first personal semantic network and the second personal semantic network; and producing a personal output representation of a given document based on the one or more connections, thereby enabling sharing of information associated with the given document between the first user and the second user. 33. The method of claim 32 , wherein producing a personal output representation based on the one or more connections comprises: generating the personal output representation for the first user based on the first user's input commands for generation of a given representation associated with the given document; and presenting to the second user the personal output representation in response to the second user's request, thereby enabling information sharing without having to allow the second user access to the given document. | 0.794872 |
9,460,086 | 10 | 11 | 10. The method of claim 7 , wherein the local list generation unit is configured to perform an expanding operation to each word alignment in the pending list, and add new word alignments that satisfy the inversion transduction grammar constraint to the local list; wherein if a number of the new word alignments in the local list is more than b, then b word alignments are kept in the local list according to a measured quality. | 10. The method of claim 7 , wherein the local list generation unit is configured to perform an expanding operation to each word alignment in the pending list, and add new word alignments that satisfy the inversion transduction grammar constraint to the local list; wherein if a number of the new word alignments in the local list is more than b, then b word alignments are kept in the local list according to a measured quality. 11. The apparatus of claim 10 , wherein performing the expanding operation, includes: for each word alignment A in the pending list and link l in L, if l is not in A, adding l to A to produce a new word alignment, where L is a set of links having positive gains. | 0.90431 |
8,213,709 | 28 | 29 | 28. The computer program product of claim 27 , further comprising computer-readable instruction means for iteratively repeating the search using the refined classifier and feature/attention model until the search goal is accomplished. | 28. The computer program product of claim 27 , further comprising computer-readable instruction means for iteratively repeating the search using the refined classifier and feature/attention model until the search goal is accomplished. 29. The computer program product of claim 28 , wherein in a case where the domain knowledge database contains no feature/attention models relating to the search goal, searching is performed using unbiased, center-surround type saliency algorithms. | 0.918374 |
9,984,069 | 1 | 4 | 1. An input method for completing a missing text or a phrase on a display of a device terminal, comprising: receiving an input of a plurality of words as a first phrase or a first sentence through key entries for displaying on the device terminal; receiving an input of a first punctuation, wherein the first punctuation follows after the first phrase or the first sentence; receiving an input of a plurality of words as a second phrase or a second sentence through key entries for displaying on the device terminal, wherein the second phrase or the second sentence follows after the first punctuation; detecting a first location of a cursor on the display of the device terminal, wherein the first location of the cursor is positioned after an end of the second phrase or the second sentence; identifying by the device terminal, one or more words within only the second phrase or the second sentence which is located between the first punctuation and the first location of the cursor; using the identified one or more words within only the second phrase or the second sentence as a first previous text or a first previous phrase, querying for a first next text or a first next phrase from a word library in a memory of the device terminal, wherein the first next text or the first next phrase is associated in context with the first previous text or the first previous phrase; outputting on the display of the device terminal, the associated first next text or first next phrase which appends after the end of the second phrase or the second sentence; detecting a second location of the cursor on the display of the device terminal after the associated first next text or first next phrase is outputted, wherein the second location of the cursor is positioned before the first location of the cursor, and wherein the second location of the cursor is positioned after the first punctuation; identifying by the device terminal, one or more words within only a third phrase or a third sentence which is located between the first punctuation and the second location of the cursor; using the identified one or more words within only the third phrase or the third sentence as a second previous text or a second previous phrase, querying for a second next text or a second next phrase from the word library in the memory of the device terminal, wherein the second next text or the second next phrase is associated in context with the second previous text or the second previous phrase; and outputting on the display of the device terminal, the associated second next text or second next phrase which appends after the end of the third phrase or the third sentence. | 1. An input method for completing a missing text or a phrase on a display of a device terminal, comprising: receiving an input of a plurality of words as a first phrase or a first sentence through key entries for displaying on the device terminal; receiving an input of a first punctuation, wherein the first punctuation follows after the first phrase or the first sentence; receiving an input of a plurality of words as a second phrase or a second sentence through key entries for displaying on the device terminal, wherein the second phrase or the second sentence follows after the first punctuation; detecting a first location of a cursor on the display of the device terminal, wherein the first location of the cursor is positioned after an end of the second phrase or the second sentence; identifying by the device terminal, one or more words within only the second phrase or the second sentence which is located between the first punctuation and the first location of the cursor; using the identified one or more words within only the second phrase or the second sentence as a first previous text or a first previous phrase, querying for a first next text or a first next phrase from a word library in a memory of the device terminal, wherein the first next text or the first next phrase is associated in context with the first previous text or the first previous phrase; outputting on the display of the device terminal, the associated first next text or first next phrase which appends after the end of the second phrase or the second sentence; detecting a second location of the cursor on the display of the device terminal after the associated first next text or first next phrase is outputted, wherein the second location of the cursor is positioned before the first location of the cursor, and wherein the second location of the cursor is positioned after the first punctuation; identifying by the device terminal, one or more words within only a third phrase or a third sentence which is located between the first punctuation and the second location of the cursor; using the identified one or more words within only the third phrase or the third sentence as a second previous text or a second previous phrase, querying for a second next text or a second next phrase from the word library in the memory of the device terminal, wherein the second next text or the second next phrase is associated in context with the second previous text or the second previous phrase; and outputting on the display of the device terminal, the associated second next text or second next phrase which appends after the end of the third phrase or the third sentence. 4. The input method according to claim 1 , wherein the querying for the second next text or the second next phrase from the word library in the memory of the device terminal, comprises: querying from the word library for all expressions and sentences comprising the second previous text or the second previous phrase, and using an expression or a sentence that exists in the found expressions and sentences but does not exist in the second previous text or the second previous phrase as the second next text or the second next phrase. | 0.600897 |
7,962,507 | 10 | 19 | 10. A method for web mining at least one couplet part, the method comprising: processing, by a computer, a search term of a query, wherein the search term comprises a first sentence of a Chinese couplet using a search engine resulting in a search result, and wherein the Chinese couplet comprises the first sentence and a second sentence; parsing, by the computer, the search result resulting from the processing, wherein the parsing results in a snippet set that is selected from at least one sentence that matches the query and information associated with the query and a suggested new search term for a subsequent query; filtering, by the computer, the snippet set resulting in at least one candidate sentence for the Chinese couplet; and generating, by at least a support vector machine classifier, at least one new sentence suitable for the Chinese couplet from the at least one candidate sentence. | 10. A method for web mining at least one couplet part, the method comprising: processing, by a computer, a search term of a query, wherein the search term comprises a first sentence of a Chinese couplet using a search engine resulting in a search result, and wherein the Chinese couplet comprises the first sentence and a second sentence; parsing, by the computer, the search result resulting from the processing, wherein the parsing results in a snippet set that is selected from at least one sentence that matches the query and information associated with the query and a suggested new search term for a subsequent query; filtering, by the computer, the snippet set resulting in at least one candidate sentence for the Chinese couplet; and generating, by at least a support vector machine classifier, at least one new sentence suitable for the Chinese couplet from the at least one candidate sentence. 19. The method as recited in claim 10 , further comprising repeating the processing, the parsing, the filtering, and the generating with the second sentence of the Chinese couplet. | 0.719626 |
10,152,588 | 11 | 15 | 11. A method, comprising: receiving, by one or more hardware processors, a proposed password from a user; accessing, by the one or more hardware processors, a previous password of the user; decomposing, by the one or more hardware processors, the proposed password and the previous password into a first plurality of components and a second plurality of components, respectively; determining, by the one or more hardware processors, that the proposed password is formed by the first plurality of components using a first set of formation rules; determining, by the one or more hardware processors, that the previous password is formed by the second plurality of components using a second set of formation rules; and determining, by the one or more hardware processors, to accept the proposed password based on a comparison between the first formation rules and the second formation rules. | 11. A method, comprising: receiving, by one or more hardware processors, a proposed password from a user; accessing, by the one or more hardware processors, a previous password of the user; decomposing, by the one or more hardware processors, the proposed password and the previous password into a first plurality of components and a second plurality of components, respectively; determining, by the one or more hardware processors, that the proposed password is formed by the first plurality of components using a first set of formation rules; determining, by the one or more hardware processors, that the previous password is formed by the second plurality of components using a second set of formation rules; and determining, by the one or more hardware processors, to accept the proposed password based on a comparison between the first formation rules and the second formation rules. 15. The method of claim 11 , wherein determining that the proposed password is formed by the first plurality of components using the first set of formation rules comprises analyzing the first plurality of components in relation to the proposed password to detect a presence of one or more operations selected from the group of operations comprising insertion, concatenation, and replacement, used to form the proposed password from the first plurality of components. | 0.501071 |
9,818,448 | 1 | 2 | 1. A media editing method comprising: on a first media editing system: storing a track of time-based media; storing time-based metadata that pertains to and is temporally synchronized with the track of time-based media; while playing back the stored time-based media track and the stored time-based metadata on the first media editing system: receiving media and time-based metadata from a second media editing system, wherein the received media and metadata includes at least one of an edited version of the time-based media track and an edited version of the time-based metadata; enabling a user of the first media editing system to: actuate a first single control of the first media editing system to toggle between: (i) monitoring playback of the stored time-based media track and the stored time-based metadata; and (ii) monitoring playback of the media and time-based metadata received from the second media editing system; and actuate a second single control of the first media editing system to start and stop recording the media and time-based metadata received from the second media editing system, wherein recording the media and time-based metadata received from the second media editing system overwrites a temporally corresponding portion of the media track and the time-based metadata stored on the first system. | 1. A media editing method comprising: on a first media editing system: storing a track of time-based media; storing time-based metadata that pertains to and is temporally synchronized with the track of time-based media; while playing back the stored time-based media track and the stored time-based metadata on the first media editing system: receiving media and time-based metadata from a second media editing system, wherein the received media and metadata includes at least one of an edited version of the time-based media track and an edited version of the time-based metadata; enabling a user of the first media editing system to: actuate a first single control of the first media editing system to toggle between: (i) monitoring playback of the stored time-based media track and the stored time-based metadata; and (ii) monitoring playback of the media and time-based metadata received from the second media editing system; and actuate a second single control of the first media editing system to start and stop recording the media and time-based metadata received from the second media editing system, wherein recording the media and time-based metadata received from the second media editing system overwrites a temporally corresponding portion of the media track and the time-based metadata stored on the first system. 2. The method of claim 1 , wherein the time-based media tracks of the first and second media editing systems are audio tracks; and the time-based metadata of the first media editing systems comprise panning automation data that define an apparent location of a source of audio data on the audio track stored on the first media editing system in a space within a venue for playing back the audio track stored on the first media editing system; and the time-based metadata of the second media editing systems comprise panning automation data that define an apparent spatial location of a source of audio data on the audio track received from the second media editing system within a venue for playing back the audio track received from the second media editing system. | 0.500652 |
8,595,370 | 4 | 5 | 4. A method comprising: receiving, from a process associated with a particular webpage, a request to display a clickable item on said particular webpage; providing, to said process, said clickable item to be displayed on said particular webpage; after providing said clickable item to said process, receiving an indication that the clickable item has been selected; and in response to said indication, providing a new page to be displayed that contains at least one of (a) URLs corresponding to a subset of linking webpages that each contains a link to said particular webpage, wherein the linking webpages are determined to contain a link to said particular webpage by an automated web crawler or (b) a subset of tags that have been associated with said particular webpage by a plurality of users who have visited said particular webpage, wherein each tag is one or more words and is created, by a user of the plurality of users who has visited said particular webpage to describe content of said particular webpage, subsequent to the creation of said particular webpage. | 4. A method comprising: receiving, from a process associated with a particular webpage, a request to display a clickable item on said particular webpage; providing, to said process, said clickable item to be displayed on said particular webpage; after providing said clickable item to said process, receiving an indication that the clickable item has been selected; and in response to said indication, providing a new page to be displayed that contains at least one of (a) URLs corresponding to a subset of linking webpages that each contains a link to said particular webpage, wherein the linking webpages are determined to contain a link to said particular webpage by an automated web crawler or (b) a subset of tags that have been associated with said particular webpage by a plurality of users who have visited said particular webpage, wherein each tag is one or more words and is created, by a user of the plurality of users who has visited said particular webpage to describe content of said particular webpage, subsequent to the creation of said particular webpage. 5. The method of claim 4 , wherein: if the new page contains the URLs corresponding to the subset of linking webpages, then the URLs are ordered based on linking webpages that most recently added a link to said particular webpage; and if the new page contains the subset of tags that have been associated with said particular webpage, then the subset of tags are ordered based on the most recently created tags. | 0.785042 |
9,207,860 | 1 | 2 | 1. A method comprising: receiving a swipe gesture from an initial touch location on a touch-sensitive display of an electronic device; determining touch attributes for the swipe gesture, the touch attributes comprising a touch location of the swipe gesture; performing a first lock function when the swipe gesture progresses to a first touch location on the touch-sensitive display that is beyond a first threshold from the initial touch location, wherein the first lock function locks a first set of functionalities of the electronic device; and performing a second lock function when the swipe gesture progresses to a second touch location on the touch-sensitive display that is beyond a second threshold from the initial touch location, wherein the second lock function locks a second, different set of functionalities of the electronic device and the second threshold is beyond the first threshold. | 1. A method comprising: receiving a swipe gesture from an initial touch location on a touch-sensitive display of an electronic device; determining touch attributes for the swipe gesture, the touch attributes comprising a touch location of the swipe gesture; performing a first lock function when the swipe gesture progresses to a first touch location on the touch-sensitive display that is beyond a first threshold from the initial touch location, wherein the first lock function locks a first set of functionalities of the electronic device; and performing a second lock function when the swipe gesture progresses to a second touch location on the touch-sensitive display that is beyond a second threshold from the initial touch location, wherein the second lock function locks a second, different set of functionalities of the electronic device and the second threshold is beyond the first threshold. 2. The method of claim 1 , wherein the initial touch location is substantially at or substantially adjacent to an edge of the touch-sensitive display. | 0.876238 |
8,738,486 | 19 | 27 | 19. A computer system for discovering patterns in financial transaction card transaction data for the purpose of determining, for individual merchants, a membership of the merchant within one or more merchant groupings utilizing the transaction data, said computer comprising: a processing device; and a memory, said processing device operable to execute instructions stored in said memory causing said computer to: store transaction data within said memory, wherein the transaction data includes data relating to merchants accepting transaction cards for payment; run a plurality of prediction algorithms stored within said memory with the transaction data, each prediction algorithm predicting a membership for a merchant within the one or more merchant groupings based on the transaction data, at least one of the prediction algorithms generating meta-data describing the predictions; input the meta-data and predicted group memberships into a data mining application; assign a confidence score to each predicted group membership for the merchant based on a result provided by the data mining application, wherein the confidence score represents a likelihood the merchant is actually associated with the corresponding predicted group membership; and output the group membership prediction with the highest confidence score as a final membership prediction for the merchant. | 19. A computer system for discovering patterns in financial transaction card transaction data for the purpose of determining, for individual merchants, a membership of the merchant within one or more merchant groupings utilizing the transaction data, said computer comprising: a processing device; and a memory, said processing device operable to execute instructions stored in said memory causing said computer to: store transaction data within said memory, wherein the transaction data includes data relating to merchants accepting transaction cards for payment; run a plurality of prediction algorithms stored within said memory with the transaction data, each prediction algorithm predicting a membership for a merchant within the one or more merchant groupings based on the transaction data, at least one of the prediction algorithms generating meta-data describing the predictions; input the meta-data and predicted group memberships into a data mining application; assign a confidence score to each predicted group membership for the merchant based on a result provided by the data mining application, wherein the confidence score represents a likelihood the merchant is actually associated with the corresponding predicted group membership; and output the group membership prediction with the highest confidence score as a final membership prediction for the merchant. 27. A computer system according to claim 19 wherein to run a plurality of prediction algorithms with the transaction data, said computer system is programmed to utilize third party provided data that has been matched to a database of financial transaction card transactions by merchant location, where location is based on a calculated similarity, the similarity based on field values and field tokenized values within the database. | 0.73399 |
9,756,439 | 10 | 11 | 10. The device of claim 9 , wherein the pre-specified parameter further comprises at least one of a mute setting parameter, a media playback parameter, and a setting parameter of an application acquiring the audio file. | 10. The device of claim 9 , wherein the pre-specified parameter further comprises at least one of a mute setting parameter, a media playback parameter, and a setting parameter of an application acquiring the audio file. 11. The device of claim 10 , wherein when the pre-specified parameter comprises the mute setting parameter, the processor is further configured to: detect a current value of the mute setting parameter; if the current value of the mute setting parameter meets the preset condition indicating a mute status, output the text file; and if the current value of the mute setting parameter meets the preset condition indicating a non-mute status, output the audio file. | 0.844235 |
9,031,379 | 1 | 6 | 1. A device, comprising: a memory that stores instructions; and a processor coupled to the memory, wherein responsive to executing the instructions, the processor performs operations comprising: receiving, at a first time, a first signal from a first communication device to start a first media evaluation session of media content, wherein the first time is during a theatrical release of the media content; receiving, in a first message, first comments from the first communication device during the first evaluation session; receiving, at a second time, a second signal from a second communication device to start a second media evaluation session of the media content, wherein the second time occurs after the theatrical release of the media content; receiving, in a second message, second comments from the second communication device during the second media evaluation session, wherein the first media evaluation session and the second media evaluation session are asynchronous with each other; synchronizing the first comments and the second comments into a single commentary timeline to substantially reduce asynchronicity between the first media evaluation session and the second media evaluation session; inserting the synchronized first and second comments in an overlay for playback with the media content by a media device, wherein the overlay comprises the single commentary timeline in which the first comments and the second comments are presented on the commentary timeline and temporally associated with the media content; and identifying a cluster of frequent comments, as an identified cluster, comprising one of the first comments, the second comments, or any combination thereof. | 1. A device, comprising: a memory that stores instructions; and a processor coupled to the memory, wherein responsive to executing the instructions, the processor performs operations comprising: receiving, at a first time, a first signal from a first communication device to start a first media evaluation session of media content, wherein the first time is during a theatrical release of the media content; receiving, in a first message, first comments from the first communication device during the first evaluation session; receiving, at a second time, a second signal from a second communication device to start a second media evaluation session of the media content, wherein the second time occurs after the theatrical release of the media content; receiving, in a second message, second comments from the second communication device during the second media evaluation session, wherein the first media evaluation session and the second media evaluation session are asynchronous with each other; synchronizing the first comments and the second comments into a single commentary timeline to substantially reduce asynchronicity between the first media evaluation session and the second media evaluation session; inserting the synchronized first and second comments in an overlay for playback with the media content by a media device, wherein the overlay comprises the single commentary timeline in which the first comments and the second comments are presented on the commentary timeline and temporally associated with the media content; and identifying a cluster of frequent comments, as an identified cluster, comprising one of the first comments, the second comments, or any combination thereof. 6. The device of claim 1 , wherein the media content comprises one of video content, audio-only content, or video with no audio content. | 0.832512 |
8,949,878 | 9 | 10 | 9. The method as recited in claim 1 , wherein: the filter criteria comprises first and second filter criteria; the generating step comprises generating first and second numeric rankings for respective first and second filter criteria for each of the segments; the method further comprising the steps of: when the respective first numeric ranking for the segment exceeds a first threshold, processing the segment to thereby eliminate material corresponding to the first filter criteria; when the respective second numeric ranking for the segment exceeds a second threshold, processing the segment to thereby eliminate material corresponding to the second filter criteria. | 9. The method as recited in claim 1 , wherein: the filter criteria comprises first and second filter criteria; the generating step comprises generating first and second numeric rankings for respective first and second filter criteria for each of the segments; the method further comprising the steps of: when the respective first numeric ranking for the segment exceeds a first threshold, processing the segment to thereby eliminate material corresponding to the first filter criteria; when the respective second numeric ranking for the segment exceeds a second threshold, processing the segment to thereby eliminate material corresponding to the second filter criteria. 10. The method recited in claim 9 , wherein the first filter criteria is associated with a first passive user and wherein the second filter criteria is associated with a second passive user. | 0.91063 |
9,135,240 | 1 | 2 | 1. A method for estimating similarity between concepts, the method comprising: receiving a set of concepts related to a corpus of text documents; creating a representative graph structure having graph nodes each representing a latent semantic analysis (LSA) vector associated with a concept, and a node having one or more graph edges, each graph edge representing a strength of a relation between concepts based on an ontology; and deriving, for a concept, a new or modified vector represented by a node in the graph by propagating the LSA vectors against said graph structure, said new or modified vector representing a modified estimated similarity between concepts, wherein a programmed processor device is configured to perform said receiving, creating and deriving. | 1. A method for estimating similarity between concepts, the method comprising: receiving a set of concepts related to a corpus of text documents; creating a representative graph structure having graph nodes each representing a latent semantic analysis (LSA) vector associated with a concept, and a node having one or more graph edges, each graph edge representing a strength of a relation between concepts based on an ontology; and deriving, for a concept, a new or modified vector represented by a node in the graph by propagating the LSA vectors against said graph structure, said new or modified vector representing a modified estimated similarity between concepts, wherein a programmed processor device is configured to perform said receiving, creating and deriving. 2. The method as claimed in claim 1 , wherein said propagating a vector of a concept against said graph structure includes averaging the LSA vectors neighboring said concept. | 0.546875 |
9,282,289 | 1 | 8 | 1. A method for generating a summary document of an online meeting, the method comprising: storing, in computer memory, at least a portion of screen data representing a previously presented portion of an ongoing online meeting; capturing a plurality of screenshots in response to trigger events, each screenshot i) being based at least in part on the stored screen data and ii) being representable as an image thumbnail, wherein capturing each screenshot of the screen data includes associating a timestamp with the screenshot, the timestamp indicating a point in time in the previously presented portion of the meeting; combining the plurality of screenshots, thereby dynamically generating a summary document summarizing the ongoing online meeting, wherein the image thumbnails representing the plurality of screenshots are for facilitating navigating through the summary document while the ongoing online meeting is still ongoing; and signaling for presenting, at a viewer computing device attending the meeting, simultaneously and while the ongoing online meeting is still ongoing, first screen data corresponding to a currently presented portion of the ongoing online meeting and second screen data corresponding to one of the plurality of screenshots in the summary document, wherein the second screen data includes stored screen data from a previously presented portion of the ongoing online meeting, and wherein the first screen data is presented picture-in-picture inside the second screen data or the second screen data is presented picture-in-picture inside the first screen data, wherein signaling for presenting the first screen data corresponding to the currently presented portion of the ongoing online meeting includes presenting live screen and audio data of the ongoing online meeting, and wherein signaling for presenting the second screen data corresponding to the screenshot includes displaying screen data from the previously presented portion of the online meeting corresponding to the point in time in the previously presented portion of the meeting indicated by the timestamp associated with the one of the plurality of screenshots in the summary document. | 1. A method for generating a summary document of an online meeting, the method comprising: storing, in computer memory, at least a portion of screen data representing a previously presented portion of an ongoing online meeting; capturing a plurality of screenshots in response to trigger events, each screenshot i) being based at least in part on the stored screen data and ii) being representable as an image thumbnail, wherein capturing each screenshot of the screen data includes associating a timestamp with the screenshot, the timestamp indicating a point in time in the previously presented portion of the meeting; combining the plurality of screenshots, thereby dynamically generating a summary document summarizing the ongoing online meeting, wherein the image thumbnails representing the plurality of screenshots are for facilitating navigating through the summary document while the ongoing online meeting is still ongoing; and signaling for presenting, at a viewer computing device attending the meeting, simultaneously and while the ongoing online meeting is still ongoing, first screen data corresponding to a currently presented portion of the ongoing online meeting and second screen data corresponding to one of the plurality of screenshots in the summary document, wherein the second screen data includes stored screen data from a previously presented portion of the ongoing online meeting, and wherein the first screen data is presented picture-in-picture inside the second screen data or the second screen data is presented picture-in-picture inside the first screen data, wherein signaling for presenting the first screen data corresponding to the currently presented portion of the ongoing online meeting includes presenting live screen and audio data of the ongoing online meeting, and wherein signaling for presenting the second screen data corresponding to the screenshot includes displaying screen data from the previously presented portion of the online meeting corresponding to the point in time in the previously presented portion of the meeting indicated by the timestamp associated with the one of the plurality of screenshots in the summary document. 8. The method of claim 1 , wherein at least one of the plurality of screenshots is encrypted. | 0.920784 |
10,007,712 | 7 | 14 | 7. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors of a computing device, cause the one or more processors to perform acts comprising: receiving, at the computing device, a plurality of phrases, individual ones of the plurality of phrases being associated with one or more user-specified communication rules identifying different sets of one or more destination computer devices that are external to the computing device; storing the plurality of phrases and the one or more user-specified communication rules in a memory of the computing device; receiving, at the computing device from a user device over a network, a message having a syntax that includes a phrase, a user created content category, and a piece of content or an identification of the piece of content; interpreting the message to extract the phrase, the user created content category, and the piece of content or the identification of the piece of content; identifying, in the memory, the phrase within the plurality of phrases; determining that the piece of content or the identification of the piece of content is associated with one of a plurality of storage categories that are associated with a first combination of the phrase and the user created content category; identifying, from the memory, a particular user-specified communication rule that is associated with a second combination of the phrase and a storage category of the plurality of storage categories associated with the piece of content or the identification of the piece of content; and causing the piece of content, the identification of the piece of content, or information associated with the piece of content, to be sent over the network to the one or more destinations identified by the particular user-specified communication rule. | 7. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors of a computing device, cause the one or more processors to perform acts comprising: receiving, at the computing device, a plurality of phrases, individual ones of the plurality of phrases being associated with one or more user-specified communication rules identifying different sets of one or more destination computer devices that are external to the computing device; storing the plurality of phrases and the one or more user-specified communication rules in a memory of the computing device; receiving, at the computing device from a user device over a network, a message having a syntax that includes a phrase, a user created content category, and a piece of content or an identification of the piece of content; interpreting the message to extract the phrase, the user created content category, and the piece of content or the identification of the piece of content; identifying, in the memory, the phrase within the plurality of phrases; determining that the piece of content or the identification of the piece of content is associated with one of a plurality of storage categories that are associated with a first combination of the phrase and the user created content category; identifying, from the memory, a particular user-specified communication rule that is associated with a second combination of the phrase and a storage category of the plurality of storage categories associated with the piece of content or the identification of the piece of content; and causing the piece of content, the identification of the piece of content, or information associated with the piece of content, to be sent over the network to the one or more destinations identified by the particular user-specified communication rule. 14. One or more non-transitory computer-readable media as recited in claim 7 , wherein the message further includes an identification of a destination to send the piece of content, the identification of the piece of content, or the information associated with the piece of content, and wherein the particular user-specified communication rule directs the computing device to send the piece of content, the identification of the piece of content, or the information associated with the piece of content, to the destination identified in the message. | 0.704423 |
9,594,951 | 16 | 17 | 16. A motor vehicle having an input apparatus as claimed in claim 15 . | 16. A motor vehicle having an input apparatus as claimed in claim 15 . 17. The motor vehicle as claimed in claim 16 , wherein the input apparatus operates at least one of a navigation device, an infotainment system and a mobile radio system in the motor vehicle. | 0.957309 |
5,567,159 | 1 | 2 | 1. A kit for teaching reading skills comprising: a first set of six visual indicator members representing vowel letters wherein said visual indicator members of said first set all have a common height dimension; a second set of seven visual indicator members representing consonant letters extending above a middle line on ruled penmanship paper wherein said visual indicator members of said second set all have a common height dimension; a third set of four, visual indicator members representing consonant letters extending below a lower line on ruled penmanship paper wherein said visual indicator members of said third set all have a common height dimension; a fourth set of nine visual indicator members representing consonant letters not represented by said second and third sets of visual indicator members wherein said visual indicator members of said fourth set all have a common height dimension; and wherein said height dimension of said visual indicator members of said first set is different from said height dimension of said visual indicator members of said second, third and fourth sets, said height dimension of said visual indicator members of said second set is different from said height dimension of said visual indicator members of said fourth set, and said height dimension of said visual indicator members of said third set is different from said height dimension of said visual indicator members of said fourth set. | 1. A kit for teaching reading skills comprising: a first set of six visual indicator members representing vowel letters wherein said visual indicator members of said first set all have a common height dimension; a second set of seven visual indicator members representing consonant letters extending above a middle line on ruled penmanship paper wherein said visual indicator members of said second set all have a common height dimension; a third set of four, visual indicator members representing consonant letters extending below a lower line on ruled penmanship paper wherein said visual indicator members of said third set all have a common height dimension; a fourth set of nine visual indicator members representing consonant letters not represented by said second and third sets of visual indicator members wherein said visual indicator members of said fourth set all have a common height dimension; and wherein said height dimension of said visual indicator members of said first set is different from said height dimension of said visual indicator members of said second, third and fourth sets, said height dimension of said visual indicator members of said second set is different from said height dimension of said visual indicator members of said fourth set, and said height dimension of said visual indicator members of said third set is different from said height dimension of said visual indicator members of said fourth set. 2. The kit as recited in claim 1 wherein each of the members of each set has a distinguishing member characteristic for distinguishing members within each of said sets from each other. | 0.864905 |
8,122,069 | 11 | 12 | 11. A computer system, comprising: a display; a memory that stores an algorithm; and a processor that executes the algorithm to: store user interface events and file system events to capture text snippets visible on the display; pair the text snippets with related files; and use a context graph that includes the text snippets and the related files to locate a document from a query. | 11. A computer system, comprising: a display; a memory that stores an algorithm; and a processor that executes the algorithm to: store user interface events and file system events to capture text snippets visible on the display; pair the text snippets with related files; and use a context graph that includes the text snippets and the related files to locate a document from a query. 12. The computer system of claim 11 , wherein a link weight between a text snippet and a file in the context graph is increased when the text snippet is seen in close temporal proximity to an event on the file. | 0.786151 |
9,720,967 | 1 | 5 | 1. One or more storage media storing instructions which, when executed by one or more processors, cause: in response to receiving a query, identifying an execution plan that comprises a plurality of sub-plans that includes a first sub-plan and a second sub-plan; wherein the first sub-plan comprises a first operation, of a first type, that can be performed during execution of the execution plan; wherein the second sub-plan comprises a second operation, of a second type that is different than the first type, that can be performed during execution of the execution plan; wherein no sub-plan in the plurality of sub-plans contains all operations that are required to generate a valid result of the query; wherein the execution plan comprises one or more operations that are not in the first sub-plan or the second sub-plan; after determining the execution plan, executing a portion of the execution plan, wherein executing the portion of the execution plan comprises storing, in a buffer associated with a particular size, temporary results of executing the portion, wherein the particular size is less than a size of a table from which the temporary results are generated; in response to determining that an amount of data in the buffer has reached the particular size, determining whether one or more criteria are satisfied; if the one or more criteria are satisfied, then executing the first sub-plan of the plurality of sub-plans without executing the second sub-plan; if the one or more criteria are not satisfied, then executing the second sub-plan of the plurality of sub-plans without executing the first sub-plan; generating a result of the query by completing execution of the execution plan and without reoptimizing the query. | 1. One or more storage media storing instructions which, when executed by one or more processors, cause: in response to receiving a query, identifying an execution plan that comprises a plurality of sub-plans that includes a first sub-plan and a second sub-plan; wherein the first sub-plan comprises a first operation, of a first type, that can be performed during execution of the execution plan; wherein the second sub-plan comprises a second operation, of a second type that is different than the first type, that can be performed during execution of the execution plan; wherein no sub-plan in the plurality of sub-plans contains all operations that are required to generate a valid result of the query; wherein the execution plan comprises one or more operations that are not in the first sub-plan or the second sub-plan; after determining the execution plan, executing a portion of the execution plan, wherein executing the portion of the execution plan comprises storing, in a buffer associated with a particular size, temporary results of executing the portion, wherein the particular size is less than a size of a table from which the temporary results are generated; in response to determining that an amount of data in the buffer has reached the particular size, determining whether one or more criteria are satisfied; if the one or more criteria are satisfied, then executing the first sub-plan of the plurality of sub-plans without executing the second sub-plan; if the one or more criteria are not satisfied, then executing the second sub-plan of the plurality of sub-plans without executing the first sub-plan; generating a result of the query by completing execution of the execution plan and without reoptimizing the query. 5. The one or more storage media of claim 1 , wherein the first sub-plan corresponds to a bitmap join. | 0.964997 |
8,751,231 | 4 | 5 | 4. The method of claim 3 , further comprising: identifying, by the audio cue generator, gaps between the utterances in the audio data, wherein each of the gaps comprise a gap length; assigning a gap identifier to each of the gaps; and computing summary statistics on the gaps. | 4. The method of claim 3 , further comprising: identifying, by the audio cue generator, gaps between the utterances in the audio data, wherein each of the gaps comprise a gap length; assigning a gap identifier to each of the gaps; and computing summary statistics on the gaps. 5. The method of claim 4 , further comprising: generating an utterance vector comprising the utterance identifiers and corresponding utterance lengths; generating a gap vector comprising the gap identifiers and corresponding gap lengths; and computing a ratio of utterance length to gap length using the utterance vector and the gap vector. | 0.873981 |
9,448,915 | 6 | 9 | 6. A method for modular script design comprising: receiving, at a modular script designer component, script information for a modular script from a user, where the script information comprises user submitted script information; analyzing a database including a plurality of modules and a plurality of scripts to determine a list of popular first modules based on the script information, and displaying the list of popular first modules to the user; receiving, at the modular script designer component, a selection of a selected first module from the user, where the selected first module is selected from among the list of the popular first modules; adding the selected first module to the modular script; determining a last module listed in the modular script; generating a list of suggested next modules based on the last module listed in the modular script responsive to determining the last module listed in the modular script, wherein the generating includes the modular script designer component determining a commonly added next module that commonly follows the last module, based on the order of modules in other existing scripts, and displaying the list of suggested next modules to the user; receiving, at the modular script designer component, a selection of a selected next module from the user, the selection of the selected next module comprising: selecting the selected next module from among the list of suggested next modules or a request to create a new module; generating the new module if the selection of the selected next module includes the request to create the new module; receiving, from the user, a modification to the new module; obtaining manual approval of the modification from an approver, the approver being a peer of the user, where the obtained manual approval of the modification corresponds to a subset of the plurality of scripts; and adding the selected next module to the modular script as a new last module listed in the script. | 6. A method for modular script design comprising: receiving, at a modular script designer component, script information for a modular script from a user, where the script information comprises user submitted script information; analyzing a database including a plurality of modules and a plurality of scripts to determine a list of popular first modules based on the script information, and displaying the list of popular first modules to the user; receiving, at the modular script designer component, a selection of a selected first module from the user, where the selected first module is selected from among the list of the popular first modules; adding the selected first module to the modular script; determining a last module listed in the modular script; generating a list of suggested next modules based on the last module listed in the modular script responsive to determining the last module listed in the modular script, wherein the generating includes the modular script designer component determining a commonly added next module that commonly follows the last module, based on the order of modules in other existing scripts, and displaying the list of suggested next modules to the user; receiving, at the modular script designer component, a selection of a selected next module from the user, the selection of the selected next module comprising: selecting the selected next module from among the list of suggested next modules or a request to create a new module; generating the new module if the selection of the selected next module includes the request to create the new module; receiving, from the user, a modification to the new module; obtaining manual approval of the modification from an approver, the approver being a peer of the user, where the obtained manual approval of the modification corresponds to a subset of the plurality of scripts; and adding the selected next module to the modular script as a new last module listed in the script. 9. The method of claim 6 , wherein generating the new module comprises: receiving a selection of a stored module from the user, and generating the new module by cloning the selected stored module and editing the cloned selected stored module; and the method further comprises: obtaining approval of the new module from the approver, and updating, when approval is obtained from the approver, the database to include the new module. | 0.550104 |
7,729,913 | 33 | 40 | 33. A method for generating and using fault-tolerant speech recognition grammars, the method comprising: generating a master grammar set that contains textual representations of valid search query utterances; subdividing the master grammar set according to the first N characters of the textual representations of valid search query utterances to generate multiple speech recognition grammars, such that different speech recognition grammars correspond to different N-character sequences; storing said multiple speech recognition grammars in a data repository in association with the N-character sequences to which they correspond; and subsequently, via execution of software by a computerized system, interpreting a sequence of N character utterances of a user to generate a sequence of N characters; selecting from said data repository the speech recognition grammar corresponding to said sequence of N characters; and using the selected speech recognition grammar to interpret an utterance by the user of a search query; wherein N is less than the number of characters in the uttered search query, and wherein subdividing the master grammar set comprises treating a set of two or more similar sounding characters as the same character so that multiple N-character sequences map to the same speech recognition grammar. | 33. A method for generating and using fault-tolerant speech recognition grammars, the method comprising: generating a master grammar set that contains textual representations of valid search query utterances; subdividing the master grammar set according to the first N characters of the textual representations of valid search query utterances to generate multiple speech recognition grammars, such that different speech recognition grammars correspond to different N-character sequences; storing said multiple speech recognition grammars in a data repository in association with the N-character sequences to which they correspond; and subsequently, via execution of software by a computerized system, interpreting a sequence of N character utterances of a user to generate a sequence of N characters; selecting from said data repository the speech recognition grammar corresponding to said sequence of N characters; and using the selected speech recognition grammar to interpret an utterance by the user of a search query; wherein N is less than the number of characters in the uttered search query, and wherein subdividing the master grammar set comprises treating a set of two or more similar sounding characters as the same character so that multiple N-character sequences map to the same speech recognition grammar. 40. The method of claim 33 , wherein generating the master grammar set comprises extracting search terms and phrases from a query log reflective of search queries submitted by a population of users. | 0.748092 |
8,396,742 | 12 | 15 | 12. The method of claim 1 , further comprising: determining a value of the first change based at least in part on the first synergy score, a revenue associated with the paid portion, and a cost associated with the paid portion. | 12. The method of claim 1 , further comprising: determining a value of the first change based at least in part on the first synergy score, a revenue associated with the paid portion, and a cost associated with the paid portion. 15. The method of claim 12 , further comprising: determining, based on the value, an adjustment to be made to the paid portion. | 0.972511 |
9,298,692 | 15 | 17 | 15. The information handling device of claim 11 , wherein to provide an indication of the tag comprises providing a visual indication of the tag in a display device. | 15. The information handling device of claim 11 , wherein to provide an indication of the tag comprises providing a visual indication of the tag in a display device. 17. The information handling device of claim 15 , wherein the instructions are further executable by the processor to: determine user interaction with the indication of the tag; and provide output containing contextual data of the tag to the user; wherein providing output containing contextual data of the tag to the user comprises rendering, in the display device, the contextual data of the tag. | 0.682109 |
7,814,054 | 15 | 16 | 15. The computer implemented method of claim 12 , further comprising the steps of: (a) providing a plurality of uncommon commands mapped to a plurality of uncommon operations associated with said first source application; (b) including said plurality of uncommon commands within said first source operations list; (c) dynamically generating a list of said plurality of uncommon commands; and (d) displaying said list of said plurality of uncommon commands on said display. | 15. The computer implemented method of claim 12 , further comprising the steps of: (a) providing a plurality of uncommon commands mapped to a plurality of uncommon operations associated with said first source application; (b) including said plurality of uncommon commands within said first source operations list; (c) dynamically generating a list of said plurality of uncommon commands; and (d) displaying said list of said plurality of uncommon commands on said display. 16. The computer implemented method of claim 15 , further comprising the steps of: (a) selecting a first uncommon command from said list of uncommon commands with said input device; and (b) executing in said first source application, in response to said selecting of said first source command with said input device, a first uncommon operation associated by said first source operations list with said first uncommon command. | 0.931782 |
7,559,052 | 4 | 6 | 4. The method of claim 2 , wherein said logical model is an extensible Markup Language (XML) schema, and wherein said logical entity components are logical message components comprising XML schema components. | 4. The method of claim 2 , wherein said logical model is an extensible Markup Language (XML) schema, and wherein said logical entity components are logical message components comprising XML schema components. 6. The method of claim 4 wherein said base classes further comprise a message collection class for containing one or more logical message definitions and one or more corresponding physical message definitions. | 0.932362 |
10,003,507 | 1 | 7 | 1. A computer system for facilitating an efficient transmission of content using a transport protocol, the system comprising: a processor; and a storage device storing instructions that when executed by the processor cause the processor to perform a method, the method comprising: receiving a first interest which indicates a query for optimal transport parameters, wherein a name for an interest is a hierarchically structured variable length identifier that includes contiguous name components ordered from a most general level to a most specific level, wherein the query is based on a name prefix that includes one or more contiguous name components; computing the optimal transport parameters based on historical information associated with the name prefix; and transmitting a first response which includes computed optimal parameters to a requesting entity, thereby facilitating a transport protocol which increases network efficiency. | 1. A computer system for facilitating an efficient transmission of content using a transport protocol, the system comprising: a processor; and a storage device storing instructions that when executed by the processor cause the processor to perform a method, the method comprising: receiving a first interest which indicates a query for optimal transport parameters, wherein a name for an interest is a hierarchically structured variable length identifier that includes contiguous name components ordered from a most general level to a most specific level, wherein the query is based on a name prefix that includes one or more contiguous name components; computing the optimal transport parameters based on historical information associated with the name prefix; and transmitting a first response which includes computed optimal parameters to a requesting entity, thereby facilitating a transport protocol which increases network efficiency. 7. The computer system of claim 1 , wherein the method further comprises: including in the first response a set of values for available resources and an option to pay for the resources; in response to the first response, receiving a second interest that indicates a bid or payment for the resources; determining an allocation of the resources based on the bid or based on the bid and bids indicated in interests from other requesting entities; and generating for the requesting entity or entities a second response that includes a result of the resource allocation determination. | 0.605586 |
9,519,682 | 1 | 2 | 1. A method comprising: identifying, for a given action by one or more network computing devices, a trusted group of user accounts from a plurality of user accounts using a respective trustworthiness score for the given action assigned to each user account of the plurality, wherein the given action refers to an online activity that is performed by one or more users associated with respective user accounts, each user account's trustworthiness score being determined using inputs received from the each user account for the given action, the trustworthiness score being used to identify the trusted group of user accounts whose input is to be used to classify an item, wherein the item refers to an article on the internet that can have an action performed on it, and to identify other user accounts whose input is to be excluded from classifying the item, the identifying comprising generating an initial trustworthiness score for a user account of the plurality using a trained trustworthiness classifier and a feature set about the user account, the trained trustworthiness classifier comprising a number of machine-implemented algorithms used to evolve behaviors based on input data, the feature set comprising online user behavioral features and static profile features about the user account, wherein the online user behavioral features comprise online activity features and the static profile features comprise user registration features, the initial trustworthiness score for the user account is used at least initially to determine whether or not to include the user account in the trusted group of user accounts for the given action; monitoring, by the one or more network computing devices, inputs for the given action and about the item, the inputs about the item from the trusted group for the given action are used to classify the item as one of spam and non-spam, such that any input about the item from other than the trusted group of user accounts formed for the given action is excluded from being used to classify the item; and evolving, by the one or more network computing devices, the trusted group based on modified trustworthiness scores of the plurality of user accounts for the given action, each modified trustworthiness score is determined, in part, by a comparison of an input about the item from a corresponding user account and inputs about the item from other user accounts in the plurality of user accounts, wherein evolving the trusted group further comprises at least one of moving at least one user account into the trusted group that previously was not in the trusted group and moving at least one user account out of the trusted group that was previously in the trusted group. | 1. A method comprising: identifying, for a given action by one or more network computing devices, a trusted group of user accounts from a plurality of user accounts using a respective trustworthiness score for the given action assigned to each user account of the plurality, wherein the given action refers to an online activity that is performed by one or more users associated with respective user accounts, each user account's trustworthiness score being determined using inputs received from the each user account for the given action, the trustworthiness score being used to identify the trusted group of user accounts whose input is to be used to classify an item, wherein the item refers to an article on the internet that can have an action performed on it, and to identify other user accounts whose input is to be excluded from classifying the item, the identifying comprising generating an initial trustworthiness score for a user account of the plurality using a trained trustworthiness classifier and a feature set about the user account, the trained trustworthiness classifier comprising a number of machine-implemented algorithms used to evolve behaviors based on input data, the feature set comprising online user behavioral features and static profile features about the user account, wherein the online user behavioral features comprise online activity features and the static profile features comprise user registration features, the initial trustworthiness score for the user account is used at least initially to determine whether or not to include the user account in the trusted group of user accounts for the given action; monitoring, by the one or more network computing devices, inputs for the given action and about the item, the inputs about the item from the trusted group for the given action are used to classify the item as one of spam and non-spam, such that any input about the item from other than the trusted group of user accounts formed for the given action is excluded from being used to classify the item; and evolving, by the one or more network computing devices, the trusted group based on modified trustworthiness scores of the plurality of user accounts for the given action, each modified trustworthiness score is determined, in part, by a comparison of an input about the item from a corresponding user account and inputs about the item from other user accounts in the plurality of user accounts, wherein evolving the trusted group further comprises at least one of moving at least one user account into the trusted group that previously was not in the trusted group and moving at least one user account out of the trusted group that was previously in the trusted group. 2. The method of claim 1 , wherein the online activity features of the online user behavioral features comprising at least one of online browsing activity, electronic mail transactions and address book entries, and the user registration features of the static profile features comprising at least one of user preferences, age, gender and occupation. | 0.801705 |
9,866,394 | 1 | 2 | 1. A method of signing a document by a plurality of contracting users, wherein said contracting users are pre-registered users and have associated electronic pen devices such that each contracting user among the contracting users has an associated electronic pen device among the electronic pen devices, the method comprising the following steps: a) receiving at a secure server, from a first user, an invitation request of signing the document for the purpose of approving content of the document by a plurality of contracting users; b) receiving, at the secure sever, user identification information associated with the contracting users; c) generating, by the secure server, a unique document identifier in connection with said document to be signed; d) transmitting, by the secure server, an invitation to sign the document to the contracting users through their associated electronic pen devices along with the unique document identifier such that each contracting user among the contracting users receives said invitation to sign the document at an electronic pen device associated therewith; wherein the electronic pen devices are configured for receiving signature requests from the contracting users for signing the document, for the purpose of approving the content of the document, the signature requests comprising first authentication information associated with said contracting users, and wherein the electronic pen devices are configured for transmitting the first authentication information to the secure server for authenticating the contracting users; e) authenticating by the secure server the contracting users using said first authentication information comprising inquiring an authentication database at the secure sever storing second authentication information in connection with the contracting users for determining if there is a match between the first authentication information and the second authentication information; f) rejecting, by the secure server, signature requests associated with unsuccessfully authenticated contracting users; g) for successfully authenticated contracting users, automatically transmitting by the secure server to electronic pen devices associated with said successfully authenticated contracting users notifications of successful authentication and said associated electronic pen devices accepting signature requests from their respective contracting users to sign the document, receiving by the associated electronic pen devices and transmitting to the secure server handwritten signatures of the authenticated contracting users approving content of the document, automatically storing by the secure server said handwritten signatures inside a signature registration database, automatically generating by said secure server a unique signature identifier and associating said unique signature identifier to said handwritten signatures, and automatically communicating said unique signature identifier to said associated electronic pen devices, and communicating said unique signature identifier by the associated electronic pen devices to the successfully authenticated contracting users for indication on the document in order to be used as a reference during future authentication of said document; and h) during authentication of the document, providing access to said signature registration database for enabling an authenticating party to authenticate said document, where said authentication of said document comprises obtaining the unique signature identifier as indicated on the document; querying the secure server using this unique signature identifier to retrieve the stored signature associated with the unique signature identifier and determining if there is an exact match between the signature stored in the server and the signature appearing on said document. | 1. A method of signing a document by a plurality of contracting users, wherein said contracting users are pre-registered users and have associated electronic pen devices such that each contracting user among the contracting users has an associated electronic pen device among the electronic pen devices, the method comprising the following steps: a) receiving at a secure server, from a first user, an invitation request of signing the document for the purpose of approving content of the document by a plurality of contracting users; b) receiving, at the secure sever, user identification information associated with the contracting users; c) generating, by the secure server, a unique document identifier in connection with said document to be signed; d) transmitting, by the secure server, an invitation to sign the document to the contracting users through their associated electronic pen devices along with the unique document identifier such that each contracting user among the contracting users receives said invitation to sign the document at an electronic pen device associated therewith; wherein the electronic pen devices are configured for receiving signature requests from the contracting users for signing the document, for the purpose of approving the content of the document, the signature requests comprising first authentication information associated with said contracting users, and wherein the electronic pen devices are configured for transmitting the first authentication information to the secure server for authenticating the contracting users; e) authenticating by the secure server the contracting users using said first authentication information comprising inquiring an authentication database at the secure sever storing second authentication information in connection with the contracting users for determining if there is a match between the first authentication information and the second authentication information; f) rejecting, by the secure server, signature requests associated with unsuccessfully authenticated contracting users; g) for successfully authenticated contracting users, automatically transmitting by the secure server to electronic pen devices associated with said successfully authenticated contracting users notifications of successful authentication and said associated electronic pen devices accepting signature requests from their respective contracting users to sign the document, receiving by the associated electronic pen devices and transmitting to the secure server handwritten signatures of the authenticated contracting users approving content of the document, automatically storing by the secure server said handwritten signatures inside a signature registration database, automatically generating by said secure server a unique signature identifier and associating said unique signature identifier to said handwritten signatures, and automatically communicating said unique signature identifier to said associated electronic pen devices, and communicating said unique signature identifier by the associated electronic pen devices to the successfully authenticated contracting users for indication on the document in order to be used as a reference during future authentication of said document; and h) during authentication of the document, providing access to said signature registration database for enabling an authenticating party to authenticate said document, where said authentication of said document comprises obtaining the unique signature identifier as indicated on the document; querying the secure server using this unique signature identifier to retrieve the stored signature associated with the unique signature identifier and determining if there is an exact match between the signature stored in the server and the signature appearing on said document. 2. The method as claimed in claim 1 , wherein the contracting users are located within a same physical location at the same moment for signing the document. | 0.835789 |
8,706,713 | 1 | 5 | 1. A method of searching for desired information, the method comprising: receiving, from a user having user profile data associated therewith, a search request comprising a search argument; providing, to a first search engine, the received search argument for correlation with first contextual information in a database of network related information; providing, to a second search engine, the received search argument and the user profile data for correlation with a first advertisement in an advertisement database; providing the first contextual information and the first advertisement to the user as a first search result; updating the user profile data based on at least one of the first contextual information, the first advertisement, selection of the first advertisement by the user, and non-selection of the first advertisement by the user; receiving refinement information comprising a refined search argument from the user; providing, to the first search engine, the refined search argument for correlation with second contextual information in the database of network related information; providing, to the second search engine, the refined search argument and the updated user profile data for correlation with a second advertisement in the advertisement database; and providing the second contextual information and the second advertisement to the user. | 1. A method of searching for desired information, the method comprising: receiving, from a user having user profile data associated therewith, a search request comprising a search argument; providing, to a first search engine, the received search argument for correlation with first contextual information in a database of network related information; providing, to a second search engine, the received search argument and the user profile data for correlation with a first advertisement in an advertisement database; providing the first contextual information and the first advertisement to the user as a first search result; updating the user profile data based on at least one of the first contextual information, the first advertisement, selection of the first advertisement by the user, and non-selection of the first advertisement by the user; receiving refinement information comprising a refined search argument from the user; providing, to the first search engine, the refined search argument for correlation with second contextual information in the database of network related information; providing, to the second search engine, the refined search argument and the updated user profile data for correlation with a second advertisement in the advertisement database; and providing the second contextual information and the second advertisement to the user. 5. The method of claim 1 , wherein the refinement information comprises at least one additional search argument. | 0.776892 |
9,330,139 | 1 | 5 | 1. A method implemented at a communication device, the method comprising: receiving a first input comprising a first search keyword and at least one explicitly specified parameter value for use in a query to be transmitted to a first online service; in response to receiving a search command, generating a first query comprising the first search keyword and the at least one explicitly specified parameter value; transmitting the first query to the first online service; and storing the at least one explicitly specified parameter value in association with the first search keyword at the communication device; receiving a second input comprising a second search keyword for use in a query to be transmitted to the first online service or to another online service; and in response to receiving a further search command, generating a second query comprising the second search keyword; in response to determining that the second search keyword matches the first search keyword and that the second input does not include any explicitly specified parameter values, using one or more of the at least one explicitly specified parameter values associated with the first search keyword to modify the second query; transmitting the modified second query to the first or other online service. | 1. A method implemented at a communication device, the method comprising: receiving a first input comprising a first search keyword and at least one explicitly specified parameter value for use in a query to be transmitted to a first online service; in response to receiving a search command, generating a first query comprising the first search keyword and the at least one explicitly specified parameter value; transmitting the first query to the first online service; and storing the at least one explicitly specified parameter value in association with the first search keyword at the communication device; receiving a second input comprising a second search keyword for use in a query to be transmitted to the first online service or to another online service; and in response to receiving a further search command, generating a second query comprising the second search keyword; in response to determining that the second search keyword matches the first search keyword and that the second input does not include any explicitly specified parameter values, using one or more of the at least one explicitly specified parameter values associated with the first search keyword to modify the second query; transmitting the modified second query to the first or other online service. 5. The method of claim 1 , wherein the first online service and the other online service comprise shopping e-commerce websites. | 0.942534 |
8,248,632 | 1 | 5 | 1. A computer-implemented method for inserting dividers in a print job, said method comprising: compiling a plurality of individual files wherein said plurality of files comprises more than one file format by executing a program instruction in a data-processing system; and inserting at least one divider in-between each individual file among said plurality of files, wherein said file format of said individual files is preserved by executing a program instruction in a data-processing system, in order to thereafter generate a template comprising a print layout associated with said at least one divider and render a complete document comprising said individual files among said plurality of individual files in a preferred order with said at least one divider automatically inserted therein and including text strings thereof. | 1. A computer-implemented method for inserting dividers in a print job, said method comprising: compiling a plurality of individual files wherein said plurality of files comprises more than one file format by executing a program instruction in a data-processing system; and inserting at least one divider in-between each individual file among said plurality of files, wherein said file format of said individual files is preserved by executing a program instruction in a data-processing system, in order to thereafter generate a template comprising a print layout associated with said at least one divider and render a complete document comprising said individual files among said plurality of individual files in a preferred order with said at least one divider automatically inserted therein and including text strings thereof. 5. The method of claim 1 further comprising inserting said at least one divider in-between sections within each individual file among said plurality of files, by executing a program instruction in a data-processing system. | 0.74186 |
9,081,919 | 14 | 15 | 14. The method of claim 1 , further comprising: generating a report on one or more results from the extracting. | 14. The method of claim 1 , further comprising: generating a report on one or more results from the extracting. 15. The method of claim 14 , wherein the performing analysis on the extracted information comprises matching information in the report to information stored in the knowledge database. | 0.904389 |
7,814,404 | 1 | 19 | 1. A method for representing a workflow for a plurality of components transformed from a pre-existing page-based application, the plurality of components for configuring as a component based application to assist with messaging over a network between a device and a schema-defined service of a data source, the page-based application configured as a series of presentation pages including embedded data, messaging and presentation elements for interaction with a user interface, the method comprising the steps of: selecting the plurality of components transformed from the page-based application, the plurality of components comprising a data component having data descriptors representing the data elements and a message component having message descriptors representing the message elements and a presentation component having presentation descriptors representing the presentation elements, at least two of the plurality of components being operatively coupled to one another, the descriptors expressed in a structured definition language; selecting a plurality of dependency links associated with events corresponding to the embedded elements, the dependency links for describing the workflow of the plurality of components in respect to operation of the component based application when executed on the device; generating in an instructional language a set of instructions based on the dependency links, the set of instructions for coordinating the operation of the plurality of components; and inserting the set of instructions in a workflow component; wherein the plurality of components and the workflow component are subsequently packaged as the component based application. | 1. A method for representing a workflow for a plurality of components transformed from a pre-existing page-based application, the plurality of components for configuring as a component based application to assist with messaging over a network between a device and a schema-defined service of a data source, the page-based application configured as a series of presentation pages including embedded data, messaging and presentation elements for interaction with a user interface, the method comprising the steps of: selecting the plurality of components transformed from the page-based application, the plurality of components comprising a data component having data descriptors representing the data elements and a message component having message descriptors representing the message elements and a presentation component having presentation descriptors representing the presentation elements, at least two of the plurality of components being operatively coupled to one another, the descriptors expressed in a structured definition language; selecting a plurality of dependency links associated with events corresponding to the embedded elements, the dependency links for describing the workflow of the plurality of components in respect to operation of the component based application when executed on the device; generating in an instructional language a set of instructions based on the dependency links, the set of instructions for coordinating the operation of the plurality of components; and inserting the set of instructions in a workflow component; wherein the plurality of components and the workflow component are subsequently packaged as the component based application. 19. The method of claim 1 , wherein the message component descriptors represent the message element associated communication between the device and the data source. | 0.745342 |
7,873,631 | 6 | 7 | 6. The computer-readable storage medium of claim 1 , further comprising: formatting data accessed by a physical data field according to a display property specified by the physical data field. | 6. The computer-readable storage medium of claim 1 , further comprising: formatting data accessed by a physical data field according to a display property specified by the physical data field. 7. The computer-readable storage medium of claim 6 , wherein the formatting comprises redacting at least a portion of the data associated with a physical data field referenced by the access method of a logical field included in an abstract query. | 0.922884 |
7,822,765 | 10 | 18 | 10. A method comprising: a. Receiving first search information from a first user, wherein the first user is assigned a first role, the first role being associated with a task; b. Receiving second search information from a second user, wherein the second user is assigned a second role, the second role being similar to or different from the first role, the second role being associated with a task; c. Aggregating the first search information and the second search information based at least on the task associated with the first role and the task associated with the second role; d. Providing the aggregated search information to at least one search engine; e. Receiving responsive search results from the search engine; f. Routing the search results based at least on the task associated with the first role and the task associated with the second role; and g. Providing the routed search results to at least the first user and second user. | 10. A method comprising: a. Receiving first search information from a first user, wherein the first user is assigned a first role, the first role being associated with a task; b. Receiving second search information from a second user, wherein the second user is assigned a second role, the second role being similar to or different from the first role, the second role being associated with a task; c. Aggregating the first search information and the second search information based at least on the task associated with the first role and the task associated with the second role; d. Providing the aggregated search information to at least one search engine; e. Receiving responsive search results from the search engine; f. Routing the search results based at least on the task associated with the first role and the task associated with the second role; and g. Providing the routed search results to at least the first user and second user. 18. The method of claim 10 , wherein the first role of the first user comprises metadata filtering of the search results, the metadata comprising at least one of: a location of a document, an author of the document, a creation time of the document, access permissions of the document, identities of persons who reviewed the document, title of the document, language of the document, content type or types of the document, file format of the document, tag data embedded in the document; or a word count of the document. | 0.657407 |
9,002,817 | 1 | 2 | 1. A computer-implemented method comprising: receiving in a search engine system a query, the query comprising query text submitted by a user; searching a first collection of resources to obtain one or more first search results, wherein each of the one or more first search results has a respective first search result score; searching a second collection of web resources to obtain one or more second search results, wherein each of the one or more second search results has a respective second search result score, wherein the resources of the first collection of resources are different from the resources of the second collection of web resources; determining from historical user click data that resources from the first collection of resources are more likely to be selected by users than resources from other collections of data when presented by the search engine in a response to the query text; generating enhanced first search result scores for the first search results as a consequence of the determining, the enhanced first search result scores being greater than the respective first search result scores for the first search results; generating a presentation order of first search results and second search results in order of the enhanced first search result scores and the second search result scores; generating a presentation of highest-ranked first search results and second search results in the presentation order; and providing the presentation in a response to the query. | 1. A computer-implemented method comprising: receiving in a search engine system a query, the query comprising query text submitted by a user; searching a first collection of resources to obtain one or more first search results, wherein each of the one or more first search results has a respective first search result score; searching a second collection of web resources to obtain one or more second search results, wherein each of the one or more second search results has a respective second search result score, wherein the resources of the first collection of resources are different from the resources of the second collection of web resources; determining from historical user click data that resources from the first collection of resources are more likely to be selected by users than resources from other collections of data when presented by the search engine in a response to the query text; generating enhanced first search result scores for the first search results as a consequence of the determining, the enhanced first search result scores being greater than the respective first search result scores for the first search results; generating a presentation order of first search results and second search results in order of the enhanced first search result scores and the second search result scores; generating a presentation of highest-ranked first search results and second search results in the presentation order; and providing the presentation in a response to the query. 2. The method of claim 1 , wherein the historical click data represents resource collections of search results selected by users after submitting the query. | 0.894022 |
5,583,762 | 6 | 7 | 6. The method of claim 1 in which said step for deriving matched tags further includes the steps of: acquiring a given tag from a sequence of tags of said tag list; determining whether said given tag is a start tag; locating said given tag at the top of a first-in-first-out stack when it is determined to be a start tag; acquiring a next tag which is next in sequence to said given tag; determining whether said next tag is an end tag or a start tag; determining when said next tag is an end tag, whether said next tag is a match with said given tag at a said stack in the relationship of end tag to start tag; and removing said given tag from said stack in the presence of a said match and identifying its relation to said next tag. | 6. The method of claim 1 in which said step for deriving matched tags further includes the steps of: acquiring a given tag from a sequence of tags of said tag list; determining whether said given tag is a start tag; locating said given tag at the top of a first-in-first-out stack when it is determined to be a start tag; acquiring a next tag which is next in sequence to said given tag; determining whether said next tag is an end tag or a start tag; determining when said next tag is an end tag, whether said next tag is a match with said given tag at a said stack in the relationship of end tag to start tag; and removing said given tag from said stack in the presence of a said match and identifying its relation to said next tag. 7. The method of claim 6 including the steps of: providing a hierarchical root list; and adding said next tag to said root list when said next tag is determined to be a start tag and no said given tag is located at the top of said stack. | 0.956257 |
7,831,911 | 1 | 12 | 1. A computer-implemented method of ranking replacement target strings for a misspelled source string, the computer-implemented method comprising: converting the misspelled source string into a source phoneme sequence using a letter-to-sound system; utilizing a computer processor that is a component of the computer to traverse at least one phoneme-based trie structure so as to select a plurality of different candidate phoneme sequences based on a comparison of phonemes in the phoneme-based trie structure to the source phoneme sequence but without doing a direct comparison of every component of the plurality of different candidate phoneme sequences to a component of the source phoneme sequence; generating a count for each different candidate phoneme sequence in said plurality of different candidate phoneme sequences, the count being indicative of a quantity of edit operations required to transform the candidate phoneme sequence into the source phoneme sequence; utilizing the computer processor to select a limited number of the plurality of different candidate phoneme sequences based at least in part on said counts, the limited number being less than all of the different candidate phoneme sequences included in said plurality of different candidate phoneme sequences; utilizing the computer processor to select a first set of replacement target strings, each replacement target string in the first set being selected based on direct correspondence to a candidate phoneme sequences in said limited number of different candidate phoneme sequences; utilizing the computer processor to traverse at least one letter-based trie structure so as to select a plurality of different candidate letter sequences, wherein selecting the plurality of different candidate letter sequences comprises traversing the letter-based trie structure so as to identify the plurality of different candidate letter sequences without doing a direct comparison of every component of the plurality of different candidate letter sequences with every component of the misspelled source string; utilizing the computer processor to select a limited number of the plurality of different candidate letter sequences based at least in part on a count of a quantity of edit operations required to transform each different candidate letter sequence included in the limited number of different candidate letter sequences into the misspelled source string, the limited number of different candidate letter sequences being less than all of the different candidate letter sequences included in said plurality of different candidate letter sequences; utilizing the computer processor to select a second set of replacement target strings, each replacement target string in the second set being one of the candidate letter sequences in said limited number of the plurality of different candidate letter sequences; and utilizing the computer processor to rank the replacement strings in the first and/or second sets based on a summation of the count of the quantity of edit operations required to transform a particular different candidate phoneme sequence included in the limited number of the plurality of different candidate phoneme sequences into the source phoneme sequence plus the count of the quantity of edit operations required to transform a particular different candidate letter sequence included in the limited number of the plurality of different candidate letter sequences into the misspelled source string. | 1. A computer-implemented method of ranking replacement target strings for a misspelled source string, the computer-implemented method comprising: converting the misspelled source string into a source phoneme sequence using a letter-to-sound system; utilizing a computer processor that is a component of the computer to traverse at least one phoneme-based trie structure so as to select a plurality of different candidate phoneme sequences based on a comparison of phonemes in the phoneme-based trie structure to the source phoneme sequence but without doing a direct comparison of every component of the plurality of different candidate phoneme sequences to a component of the source phoneme sequence; generating a count for each different candidate phoneme sequence in said plurality of different candidate phoneme sequences, the count being indicative of a quantity of edit operations required to transform the candidate phoneme sequence into the source phoneme sequence; utilizing the computer processor to select a limited number of the plurality of different candidate phoneme sequences based at least in part on said counts, the limited number being less than all of the different candidate phoneme sequences included in said plurality of different candidate phoneme sequences; utilizing the computer processor to select a first set of replacement target strings, each replacement target string in the first set being selected based on direct correspondence to a candidate phoneme sequences in said limited number of different candidate phoneme sequences; utilizing the computer processor to traverse at least one letter-based trie structure so as to select a plurality of different candidate letter sequences, wherein selecting the plurality of different candidate letter sequences comprises traversing the letter-based trie structure so as to identify the plurality of different candidate letter sequences without doing a direct comparison of every component of the plurality of different candidate letter sequences with every component of the misspelled source string; utilizing the computer processor to select a limited number of the plurality of different candidate letter sequences based at least in part on a count of a quantity of edit operations required to transform each different candidate letter sequence included in the limited number of different candidate letter sequences into the misspelled source string, the limited number of different candidate letter sequences being less than all of the different candidate letter sequences included in said plurality of different candidate letter sequences; utilizing the computer processor to select a second set of replacement target strings, each replacement target string in the second set being one of the candidate letter sequences in said limited number of the plurality of different candidate letter sequences; and utilizing the computer processor to rank the replacement strings in the first and/or second sets based on a summation of the count of the quantity of edit operations required to transform a particular different candidate phoneme sequence included in the limited number of the plurality of different candidate phoneme sequences into the source phoneme sequence plus the count of the quantity of edit operations required to transform a particular different candidate letter sequence included in the limited number of the plurality of different candidate letter sequences into the misspelled source string. 12. The computer-implemented method of claim 1 , wherein said step of ranking the replacement strings in the first and/or second sets comprises ranking so as to account for assignment of a weighted bias scheme wherein a weighted bias is assigned to favor some edit operations required to transform a particular different candidate letter string included in the limited number of different candidate letter sequences into the misspelled source string over others. | 0.623779 |
8,442,985 | 9 | 10 | 9. The organization analysis system of claim 8 , wherein the textual analysis system is further configured to: generate a respective score, for each unique combination, based on the level of similarity between a single capability and a single requirement; compare the respective score for each unique combination to a predetermined scoring threshold; and determine, for each unique combination, a respective level of correspondence between the single capability and the single requirement based on comparison of the respective score to the predetermined scoring threshold, wherein the at least one visual presentation is generated to visually indicate the respective level of correspondence for each unique combination. | 9. The organization analysis system of claim 8 , wherein the textual analysis system is further configured to: generate a respective score, for each unique combination, based on the level of similarity between a single capability and a single requirement; compare the respective score for each unique combination to a predetermined scoring threshold; and determine, for each unique combination, a respective level of correspondence between the single capability and the single requirement based on comparison of the respective score to the predetermined scoring threshold, wherein the at least one visual presentation is generated to visually indicate the respective level of correspondence for each unique combination. 10. The organization analysis system of claim 9 , wherein the textual analysis system is further configured to determine direct correspondence based on the respective level of correspondence for each unique combination, wherein the visual presentation is configured to visually indicate direct correspondence between the single capability and the single requirement of each unique combination. | 0.861814 |
9,563,699 | 7 | 11 | 7. A non-transitory computer-readable storage medium storing instructions for identifying an audio content sample, the instructions which when executed by a processor cause the processor to: monitor a plurality of broadcast stations, fingerprint and save the fingerprints of broadcast audio content in a database of unidentified broadcast content as it is received; access playlists, comprising portions of identified broadcast audio content from the plurality of monitored broadcast stations, and fingerprints corresponding to the identified broadcast audio content; receive data representing sampled audio content from a portable device and search for a match between fingerprints of the sampled audio content and the fingerprints corresponding to at least parts of multiple playlists, further including: upon finding a fingerprint match against the fingerprints corresponding to a particular playlist for a particular monitored broadcast station, report the particular monitored broadcast station as a source of the sampled audio content, and identification of the sampled audio content back to the portable device; and upon not finding a fingerprint match against the fingerprints corresponding to any of the multiple playlists, further search for a match the fingerprints of sampled audio content, against at least one of: parts of the database of unidentified broadcast content from the monitored broadcast stations, to identify a source of the sampled audio content; and a reference database of identified audio content not associated with a particular broadcast station, to identify the sampled audio content; and report back to the portable device at least one of the source of the sampled audio content and the identity of the sampled audio content. | 7. A non-transitory computer-readable storage medium storing instructions for identifying an audio content sample, the instructions which when executed by a processor cause the processor to: monitor a plurality of broadcast stations, fingerprint and save the fingerprints of broadcast audio content in a database of unidentified broadcast content as it is received; access playlists, comprising portions of identified broadcast audio content from the plurality of monitored broadcast stations, and fingerprints corresponding to the identified broadcast audio content; receive data representing sampled audio content from a portable device and search for a match between fingerprints of the sampled audio content and the fingerprints corresponding to at least parts of multiple playlists, further including: upon finding a fingerprint match against the fingerprints corresponding to a particular playlist for a particular monitored broadcast station, report the particular monitored broadcast station as a source of the sampled audio content, and identification of the sampled audio content back to the portable device; and upon not finding a fingerprint match against the fingerprints corresponding to any of the multiple playlists, further search for a match the fingerprints of sampled audio content, against at least one of: parts of the database of unidentified broadcast content from the monitored broadcast stations, to identify a source of the sampled audio content; and a reference database of identified audio content not associated with a particular broadcast station, to identify the sampled audio content; and report back to the portable device at least one of the source of the sampled audio content and the identity of the sampled audio content. 11. The non-transitory computer-readable storage medium of claim 7 , further including instructions, which when executed by the processor, cause the processor to: save playlists of the broadcast audio content from the broadcast stations monitored; and send the portable device at least a recent portion of a playlist that identifies a plurality of recent items broadcast by a monitored broadcast station source. | 0.540268 |
9,530,415 | 2 | 6 | 2. The method of claim 1 , further comprising, upon a second indication from a user, processing the transcription in the specific field. | 2. The method of claim 1 , further comprising, upon a second indication from a user, processing the transcription in the specific field. 6. The method of claim 2 , wherein processing the text in the specific field is performed as though the user typed the text in the specific field. | 0.942474 |
8,600,954 | 18 | 19 | 18. A method comprising: receiving a model from a user device, the receiving the model being performed by a computing device; processing the model to obtain information that is used for executing the model, the model being processed without executing the model, the processing being performed by the computing device; determining whether the model is functional based on the information that is used for executing the model, the determining being performed by the computing device; causing information to be presented at the user device when the model is not functional, the information, presented at the user device, indicating that the model is not functional, the causing the information to be presented at the user device being performed by the computing device; receiving, from the user device, a response to the information indicating that the model is not functional, the response indicating that the model, that is not functional, is to be made available to the one or more users, the receiving the response being performed by the computing device; and causing the model, that is not functional, to be made available to the one or more users based on receiving the response indicating that the model, that is not functional, is to be made available to the one or more users, the causing the model to be made available when the model is not functional being performed by the computing device. | 18. A method comprising: receiving a model from a user device, the receiving the model being performed by a computing device; processing the model to obtain information that is used for executing the model, the model being processed without executing the model, the processing being performed by the computing device; determining whether the model is functional based on the information that is used for executing the model, the determining being performed by the computing device; causing information to be presented at the user device when the model is not functional, the information, presented at the user device, indicating that the model is not functional, the causing the information to be presented at the user device being performed by the computing device; receiving, from the user device, a response to the information indicating that the model is not functional, the response indicating that the model, that is not functional, is to be made available to the one or more users, the receiving the response being performed by the computing device; and causing the model, that is not functional, to be made available to the one or more users based on receiving the response indicating that the model, that is not functional, is to be made available to the one or more users, the causing the model to be made available when the model is not functional being performed by the computing device. 19. The method of claim 18 , where processing the model includes compiling the model, and where the information related to executing the model includes information identifying a sample rate associated with blocks of the model. | 0.874025 |
8,335,694 | 8 | 14 | 8. The method of claim 1 , further comprising: storing results of said procedure in a database, using said computer system. | 8. The method of claim 1 , further comprising: storing results of said procedure in a database, using said computer system. 14. The method of claim 8 , further comprising: searching said database, using said computer system, in accordance with pre-defined user preferences. | 0.959066 |
8,527,529 | 1 | 5 | 1. A method for displaying search results for a search query comprising a plurality of search terms, said method comprising: receiving said search query; obtaining at least one document satisfying said search query; determining a relative position of at least two of said search terms in said at least one document; and presenting at least a portion of said at least one document with a visual indication of said relative position of said at least two search terms in said at least one document, wherein said visual indication indicates a count of one or more intervening elements between said at least two search terms and wherein one or more steps of said method are performed by one or more hardware devices, wherein said relative position is indicated using a predefined character to indicate said one or more intervening elements between said at least two search terms and wherein said one or more intervening elements indicated by each predefined character comprises a given one of a character, word, line, paragraph and page. | 1. A method for displaying search results for a search query comprising a plurality of search terms, said method comprising: receiving said search query; obtaining at least one document satisfying said search query; determining a relative position of at least two of said search terms in said at least one document; and presenting at least a portion of said at least one document with a visual indication of said relative position of said at least two search terms in said at least one document, wherein said visual indication indicates a count of one or more intervening elements between said at least two search terms and wherein one or more steps of said method are performed by one or more hardware devices, wherein said relative position is indicated using a predefined character to indicate said one or more intervening elements between said at least two search terms and wherein said one or more intervening elements indicated by each predefined character comprises a given one of a character, word, line, paragraph and page. 5. The method of claim 1 , wherein said search query comprises one or more constraints on a relative position of at least two search terms. | 0.847253 |
9,632,997 | 18 | 19 | 18. The method according to claim 17 , further comprising executing at least one parse of transcription information to generate the plurality of elements. | 18. The method according to claim 17 , further comprising executing at least one parse of transcription information to generate the plurality of elements. 19. The method according to claim 18 , wherein identifying the at least one element sequence as meeting predetermined criteria includes identifying an element including more complex grammatical structures over an element including less complex grammatical structures. | 0.932337 |
8,843,364 | 16 | 20 | 16. A method, comprising: for each source of a plurality of sources, generating a plurality of word level models, each word level model corresponding to a respective one word of a plurality of words, each word level model including: a plurality of dictionaries, each of the plurality of dictionaries including one or more spectral components, and probabilities of transition between the dictionaries; for each source, combining the word level models into a single source specific model; and constraining the single source specific models according to high level information that defines valid transitions, the constrained single source specific models being usable to perform source separation on a sound mixture that includes multiple sources. | 16. A method, comprising: for each source of a plurality of sources, generating a plurality of word level models, each word level model corresponding to a respective one word of a plurality of words, each word level model including: a plurality of dictionaries, each of the plurality of dictionaries including one or more spectral components, and probabilities of transition between the dictionaries; for each source, combining the word level models into a single source specific model; and constraining the single source specific models according to high level information that defines valid transitions, the constrained single source specific models being usable to perform source separation on a sound mixture that includes multiple sources. 20. The method of claim 16 , wherein said constraining the single source specific models includes constraining transitions between word level models in the single source dependent model according to the high level information. | 0.887 |
7,497,778 | 1 | 10 | 1. A method of conducting a word based lottery game having a plurality of players, comprising the steps of: for each game, the players wagering on an entry defined by a set of words; in a random draw process, randomly generating an outcome that is a concatenation of characters, the draw being such that each outcome can be assigned a probability of occurrence; defining a rule that confers the words in the player entry a win status based on the outcome of the draw producing characters that are used to form the respective words in the player entry; selecting winning entries based on the words in an entry that are conferred a win status; and assigning a prize for each winning entry as a function of a value assigned to each of the words in the player entry formed by the randomly drawn characters, the value based on the commonality of the characters that form the words in the player entry. | 1. A method of conducting a word based lottery game having a plurality of players, comprising the steps of: for each game, the players wagering on an entry defined by a set of words; in a random draw process, randomly generating an outcome that is a concatenation of characters, the draw being such that each outcome can be assigned a probability of occurrence; defining a rule that confers the words in the player entry a win status based on the outcome of the draw producing characters that are used to form the respective words in the player entry; selecting winning entries based on the words in an entry that are conferred a win status; and assigning a prize for each winning entry as a function of a value assigned to each of the words in the player entry formed by the randomly drawn characters, the value based on the commonality of the characters that form the words in the player entry. 10. The method of claim 1 , wherein the draw applies to an individual entry. | 0.834061 |
6,122,661 | 37 | 46 | 37. A computer-readable storage medium holding code for facilitating information transfer between a host computer and a client computer via a server computer, comprising: a host computer comprising a memory within which a presentation space buffer storing computer display information is configured and a communications interface enabling information exchanges using data streams, including transmission of the presentation space buffer as a presentation space data stream; a client computer comprising a web browser application displaying a markup language document and forwarding user inputs; and a server computer topologically intermediate to the host computer and the client computer and comprising: a server application framework comprising a display control interfacing to the host computer via a communications medium over which data streams are exchanged, including the transmitted presentation space data stream, and a host extension converting the transmitted presentation space data stream into a markup language document having instructions that identify position information for a cursor on a Web page and for modifying the presentation space buffer in the host; and a web server application interfacing to the client computer via a network medium over which the markup language document is served and the forwarded user inputs received. | 37. A computer-readable storage medium holding code for facilitating information transfer between a host computer and a client computer via a server computer, comprising: a host computer comprising a memory within which a presentation space buffer storing computer display information is configured and a communications interface enabling information exchanges using data streams, including transmission of the presentation space buffer as a presentation space data stream; a client computer comprising a web browser application displaying a markup language document and forwarding user inputs; and a server computer topologically intermediate to the host computer and the client computer and comprising: a server application framework comprising a display control interfacing to the host computer via a communications medium over which data streams are exchanged, including the transmitted presentation space data stream, and a host extension converting the transmitted presentation space data stream into a markup language document having instructions that identify position information for a cursor on a Web page and for modifying the presentation space buffer in the host; and a web server application interfacing to the client computer via a network medium over which the markup language document is served and the forwarded user inputs received. 46. A storage medium according to claim 37, wherein the network medium comprises a member of the group consisting of a wide area network, a local area network, an intranetwork, or a TCP/IP-based network. | 0.871843 |
9,841,895 | 11 | 16 | 11. A non-transitory computer-readable storage medium encoded with instructions that, when executed, cause at least one processor to: output, for display, a graphical keyboard comprising a plurality of keys; in response to detecting a first portion of a gesture at a presence-sensitive input device, generate a word prefix comprising a plurality of characters; in response to detecting, during the gesture, a second portion of the gesture at the presence-sensitive input device: update, based on a word in a dictionary, the word prefix to include an additional character; responsive to determining that an alignment score of the gesture matching the word prefix with the additional character does not satisfy a threshold, determine, using correction data that indicates at least one alternative word prefix that is based at least in part on a misspelling of the word in the dictionary, an alternative alignment score, wherein the alternative word prefix comprises at least a portion of the word prefix; determine, based on the alternative alignment score for the alternative word prefix, a candidate word; and output, for display, the candidate word. | 11. A non-transitory computer-readable storage medium encoded with instructions that, when executed, cause at least one processor to: output, for display, a graphical keyboard comprising a plurality of keys; in response to detecting a first portion of a gesture at a presence-sensitive input device, generate a word prefix comprising a plurality of characters; in response to detecting, during the gesture, a second portion of the gesture at the presence-sensitive input device: update, based on a word in a dictionary, the word prefix to include an additional character; responsive to determining that an alignment score of the gesture matching the word prefix with the additional character does not satisfy a threshold, determine, using correction data that indicates at least one alternative word prefix that is based at least in part on a misspelling of the word in the dictionary, an alternative alignment score, wherein the alternative word prefix comprises at least a portion of the word prefix; determine, based on the alternative alignment score for the alternative word prefix, a candidate word; and output, for display, the candidate word. 16. The non-transitory computer-readable storage medium of claim 11 , wherein the alternative word prefix includes an alternative character, wherein the alternative character is not based on a distance that the alignment point is away from a neighboring key that is associated with the alternative character. | 0.71215 |
9,269,097 | 19 | 20 | 19. The method of claim 1 , further comprising: facilitating, by the computer system, delivery of the product or service responsive to determining that the pronoun refers to one or more of the product or service or the provider of the product or service. | 19. The method of claim 1 , further comprising: facilitating, by the computer system, delivery of the product or service responsive to determining that the pronoun refers to one or more of the product or service or the provider of the product or service. 20. The method of claim 19 , wherein facilitating delivery of the product or service includes performing a purchase transaction for the product or service. | 0.935038 |
9,613,007 | 14 | 15 | 14. A system comprising: an element anchoring module implemented at least partially in hardware, the element anchoring module configured to perform operations comprising: determining how far below text, that is located in a non-rectangular frame, to position, in the non-rectangular frame, one or more anchored text elements that are referenced in the text, the determining including: initially positioning the one or more anchored text elements within the non-rectangular frame; and iteratively repositioning the one or more anchored text elements until both: the one or more anchored text elements fit entirely within the non-rectangular frame; and there is no space between a bottom of the one or more anchored text elements and a bottom boundary of the non-rectangular frame. | 14. A system comprising: an element anchoring module implemented at least partially in hardware, the element anchoring module configured to perform operations comprising: determining how far below text, that is located in a non-rectangular frame, to position, in the non-rectangular frame, one or more anchored text elements that are referenced in the text, the determining including: initially positioning the one or more anchored text elements within the non-rectangular frame; and iteratively repositioning the one or more anchored text elements until both: the one or more anchored text elements fit entirely within the non-rectangular frame; and there is no space between a bottom of the one or more anchored text elements and a bottom boundary of the non-rectangular frame. 15. A system as described in claim 14 , wherein the one or more anchored text elements, once finally positioned according to the determining, do not extend outside boundaries of the non-rectangular frame. | 0.857542 |
9,582,823 | 1 | 7 | 1. A method comprising: receiving user behavioral data for search results of a search query, the user behavioral data comprising clickstream data indicating that a user selected the search results including an untagged item and a plurality of tagged items during a single search event; determining that the selected plurality of tagged items corresponds to a first type of metadata and the untagged items are selected during the single search event that includes the plurality of tagged items, the selected plurality of tagged items transgressing a threshold number of selected tagged items that corresponds to the first type of metadata; identifying, by a machine having a memory and at least one processor, the untagged item as a candidate to be tagged with the first type of metadata corresponding to the tagged items based on the determined plurality of tagged items corresponding to the first type of metadata and transgressing the threshold number of selected tagged items; and assigning data corresponding to the first type of metadata for the tagged items to the untagged item in response to the identifying the untagged item as the candidate to be tagged with the first type of metadata. | 1. A method comprising: receiving user behavioral data for search results of a search query, the user behavioral data comprising clickstream data indicating that a user selected the search results including an untagged item and a plurality of tagged items during a single search event; determining that the selected plurality of tagged items corresponds to a first type of metadata and the untagged items are selected during the single search event that includes the plurality of tagged items, the selected plurality of tagged items transgressing a threshold number of selected tagged items that corresponds to the first type of metadata; identifying, by a machine having a memory and at least one processor, the untagged item as a candidate to be tagged with the first type of metadata corresponding to the tagged items based on the determined plurality of tagged items corresponding to the first type of metadata and transgressing the threshold number of selected tagged items; and assigning data corresponding to the first type of metadata for the tagged items to the untagged item in response to the identifying the untagged item as the candidate to be tagged with the first type of metadata. 7. The method of claim 1 , further comprising providing a notification to an administrator in response to the identification of the untagged item as a candidate to be tagged with the first type of metadata assigned to the tagged items, the notification indicating that data corresponding to the first type of metadata for the tagged items should be assigned to the untagged item. | 0.710245 |
5,574,826 | 29 | 30 | 29. A memory section for an electronic controller which performs inference operations according to rules, each rule comprising at least one preposition and at least one implication, wherein a membership function, defined for a finite number of points of a universe of discourse, appears in the preposition of at least one of the rules, the membership function having a value for each of the finite number of points, which value is indicative of a degree of membership, wherein the memory section has a size defined by a number of nonzero values of the membership functions associated with a selected one of the finite number of points, the selected point having the largest number of nonzero values. | 29. A memory section for an electronic controller which performs inference operations according to rules, each rule comprising at least one preposition and at least one implication, wherein a membership function, defined for a finite number of points of a universe of discourse, appears in the preposition of at least one of the rules, the membership function having a value for each of the finite number of points, which value is indicative of a degree of membership, wherein the memory section has a size defined by a number of nonzero values of the membership functions associated with a selected one of the finite number of points, the selected point having the largest number of nonzero values. 30. The memory section of claim 29, wherein a length L of a memory word of the memory section is dependent on the largest number of non-zero values. | 0.929591 |
7,483,832 | 9 | 15 | 9. A text-to-speech translation voice customization system, comprising: means for receiving text content for translation to speech; means for correlating the text content to textual phrases of multiple words; means for converting each textual phrase into a corresponding string of phonemes; means for retrieving a phoneme identifier that uniquely represents each phoneme in the string of phonemes; means for concatenating each phoneme identifier of each phoneme in the string of phonemes to produce a sequence of phoneme identifiers with each phoneme identifier separated by a comma; means for creating a corresponding sequence of phoneme identifiers for each string of phonemes that corresponds to each textual phrase in the text content; means for concatenating each sequence of phoneme identifiers and separating each sequence of phone identifiers by a semi-colon; means for accessing a voice file storing recorded phrases in a speaker's voice; means for mapping each sequence of phoneme identifiers to a corresponding recorded phrase in the speaker's voice file; means for retrieving the recorded phrase from the voice file that corresponds to each sequence of phoneme identifiers; means for concatenating together the recorded phases from the speaker's voice file to form a sequence of the recorded phrases as a speech translation of the text content; and means for outputting the speech translation as a translation of the text content to speech. | 9. A text-to-speech translation voice customization system, comprising: means for receiving text content for translation to speech; means for correlating the text content to textual phrases of multiple words; means for converting each textual phrase into a corresponding string of phonemes; means for retrieving a phoneme identifier that uniquely represents each phoneme in the string of phonemes; means for concatenating each phoneme identifier of each phoneme in the string of phonemes to produce a sequence of phoneme identifiers with each phoneme identifier separated by a comma; means for creating a corresponding sequence of phoneme identifiers for each string of phonemes that corresponds to each textual phrase in the text content; means for concatenating each sequence of phoneme identifiers and separating each sequence of phone identifiers by a semi-colon; means for accessing a voice file storing recorded phrases in a speaker's voice; means for mapping each sequence of phoneme identifiers to a corresponding recorded phrase in the speaker's voice file; means for retrieving the recorded phrase from the voice file that corresponds to each sequence of phoneme identifiers; means for concatenating together the recorded phases from the speaker's voice file to form a sequence of the recorded phrases as a speech translation of the text content; and means for outputting the speech translation as a translation of the text content to speech. 15. The system of claim 9 , further comprising means for applying a combination of different voice files to create a new voice file. | 0.714286 |
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