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9,323,753 | 1 | 9 | 1. A method for generating a compressed representation of digital documents on a handheld device, the method comprising: periodically obtaining one or more digital documents stored in a memory of a handheld device; extracting one or more words from each of the one or more digital documents; and generating a compressed representation of the one or more digital documents stored in the memory of the handheld device using one or more balanced trees, wherein the one or more balanced trees include at least one of a word balanced tree including a plurality of nodes, each of the plurality of nodes representing a word from among the one or more extracted words, and a document balanced tree including a plurality of nodes, each of the plurality of nodes representing a digital document from among the one or more digital documents, wherein each node of the word balanced tree comprises a position of the represented word in the digital document, wherein the generating of the compressed representation of the one or more digital documents using the one or more balanced trees comprises: storing the one or more extracted words in the word balanced tree including the plurality of nodes, such that each of the plurality of nodes represents a word in the one or more extracted words, and such that a word is associated with a node and includes pointer information associated with a first digital document including the associated word from a set of digital documents, a position of the associated word in the first digital document, and number occurrences of the associated word in the set of digital documents; storing the one or more digital documents in the document balanced tree including the plurality of nodes, such that each of the plurality of nodes represents a digital document in the one or more digital documents and includes the document header information; and generating a document map table including at least one entry in at least one list of entries representing the digital documents, wherein each of the at least one entry in the list of entries includes pointer information associated with one of the digital documents corresponding to one of the plurality of nodes in the document balanced tree, wherein the at least one entry in the list of entries represents an ordered sequence of words associated with one of the one or more digital documents, and wherein the first digital document is one of the one or more digital documents. | 1. A method for generating a compressed representation of digital documents on a handheld device, the method comprising: periodically obtaining one or more digital documents stored in a memory of a handheld device; extracting one or more words from each of the one or more digital documents; and generating a compressed representation of the one or more digital documents stored in the memory of the handheld device using one or more balanced trees, wherein the one or more balanced trees include at least one of a word balanced tree including a plurality of nodes, each of the plurality of nodes representing a word from among the one or more extracted words, and a document balanced tree including a plurality of nodes, each of the plurality of nodes representing a digital document from among the one or more digital documents, wherein each node of the word balanced tree comprises a position of the represented word in the digital document, wherein the generating of the compressed representation of the one or more digital documents using the one or more balanced trees comprises: storing the one or more extracted words in the word balanced tree including the plurality of nodes, such that each of the plurality of nodes represents a word in the one or more extracted words, and such that a word is associated with a node and includes pointer information associated with a first digital document including the associated word from a set of digital documents, a position of the associated word in the first digital document, and number occurrences of the associated word in the set of digital documents; storing the one or more digital documents in the document balanced tree including the plurality of nodes, such that each of the plurality of nodes represents a digital document in the one or more digital documents and includes the document header information; and generating a document map table including at least one entry in at least one list of entries representing the digital documents, wherein each of the at least one entry in the list of entries includes pointer information associated with one of the digital documents corresponding to one of the plurality of nodes in the document balanced tree, wherein the at least one entry in the list of entries represents an ordered sequence of words associated with one of the one or more digital documents, and wherein the first digital document is one of the one or more digital documents. 9. The method of claim 1 , further comprising: receiving a search query including one or more words from a user of the handheld device for searching for one or more digital documents; determining whether the one or more words correspond to one or more nodes in the word balanced tree by traversing through the nodes in the word balanced tree based on the search query; retrieving the one or more digital documents including the one or more words by traversing through the digital document map table and providing a search result including the one or more retrieved digital documents on the display of the handheld device if it is determined that the one or more words correspond to the one or more nodes in the word balanced tree; and returning a search query error on the display of the handheld device if it is determined that the one or more words do not correspond to the one or more nodes in the word balanced tree. | 0.652568 |
9,058,317 | 11 | 14 | 11. A system, comprising: a processing unit; a memory operatively coupled to the processing unit; and a program module which executes in the processing unit from the memory and which, when executed by the processing unit, causes the system to perform machine learning management functions that include: receiving a first segment of text data, identifying data features corresponding to a sequence of characters in the first segment of text data, generating predictive annotations to the sequence of characters based at least in part on the identified data features, identifying inaccurate annotations generated according to the predictive annotations, correcting the identified inaccurate annotations, generating at least one set of model training data incorporating the corrected annotations, and monitoring progress of annotations made to a second segment of text data associated with the first segment of text data by a plurality of collaborating users of a plurality of managed computers, the monitoring including determining, based at least in part on a training descriptor corresponding to the second segment of text data, a state of completion of annotations made to the second segment of text data by a particular one of the plurality of collaborating users, wherein the training descriptor identifies types of annotations in the at least one set of model training data. | 11. A system, comprising: a processing unit; a memory operatively coupled to the processing unit; and a program module which executes in the processing unit from the memory and which, when executed by the processing unit, causes the system to perform machine learning management functions that include: receiving a first segment of text data, identifying data features corresponding to a sequence of characters in the first segment of text data, generating predictive annotations to the sequence of characters based at least in part on the identified data features, identifying inaccurate annotations generated according to the predictive annotations, correcting the identified inaccurate annotations, generating at least one set of model training data incorporating the corrected annotations, and monitoring progress of annotations made to a second segment of text data associated with the first segment of text data by a plurality of collaborating users of a plurality of managed computers, the monitoring including determining, based at least in part on a training descriptor corresponding to the second segment of text data, a state of completion of annotations made to the second segment of text data by a particular one of the plurality of collaborating users, wherein the training descriptor identifies types of annotations in the at least one set of model training data. 14. The system of claim 11 , wherein the training descriptor further identifies resource data corresponding to the at least one set of model training data, the resource data comprising a lexicon of associations between predefined sequences of characters and predefined labels. | 0.581818 |
8,660,960 | 1 | 4 | 1. A computer-implemented method comprising: receiving, by an electronic document reader, an electronic document that includes (a) a plurality of content items, (b) a set of rules that defines a set of allowed operations which are authorized to be performed on the plurality of content items included in the electronic document, and (c) a first selective digest generated by a document author; identifying, by a processor, one or more invariant content items from amongst the plurality of content items, wherein the invariant content items remain unchanged when the set of allowed operations are performed on the plurality of content items included in the electronic document; generating, by the processor, a second selective digest of the one or more invariant content items; performing, by the processor, a comparison of the first selective digest generated by the document author and the second selective digest generated by the processor, wherein the comparison results in validation information; disabling, by the electronic document reader, the allowed operations when the comparison of the first and second selective digests indicates that operations have been performed on the electronic document which are not allowed under the set of rules; and saving, on a computer readable storage device, a version of the electronic document that includes the set of rules and the validation information. | 1. A computer-implemented method comprising: receiving, by an electronic document reader, an electronic document that includes (a) a plurality of content items, (b) a set of rules that defines a set of allowed operations which are authorized to be performed on the plurality of content items included in the electronic document, and (c) a first selective digest generated by a document author; identifying, by a processor, one or more invariant content items from amongst the plurality of content items, wherein the invariant content items remain unchanged when the set of allowed operations are performed on the plurality of content items included in the electronic document; generating, by the processor, a second selective digest of the one or more invariant content items; performing, by the processor, a comparison of the first selective digest generated by the document author and the second selective digest generated by the processor, wherein the comparison results in validation information; disabling, by the electronic document reader, the allowed operations when the comparison of the first and second selective digests indicates that operations have been performed on the electronic document which are not allowed under the set of rules; and saving, on a computer readable storage device, a version of the electronic document that includes the set of rules and the validation information. 4. The method of claim 1 , wherein disabling the allowed operations further comprises providing, by the electronic document reader, an error message indicating that an unauthorized operation has been performed. | 0.805915 |
7,729,916 | 1 | 11 | 1. A method for providing conversational computing between a user and at least one application, the method comprising the steps of: engaging in dialog with the user; processing the dialog, by a processor executing the at least one application, to one of complete a query, disambiguate a query, summarize a query, correct a query, correct a result of an executed task, communicate the result of such execution, determine a target application of an input/output event, and a combination thereof based on one of past dialog history, context, user preferences, meta information, and a combination thereof; and presenting a unified and coordinated user interface across the plurality of applications; wherein presenting a unified and coordinated user interface across a plurality of applications comprises the steps of: registering, by each application, information comprising application state, application modes, arguments, context, modalities, engine resources, and a combination thereof; and managing the dialog across the plurality of applications based on their registered information. | 1. A method for providing conversational computing between a user and at least one application, the method comprising the steps of: engaging in dialog with the user; processing the dialog, by a processor executing the at least one application, to one of complete a query, disambiguate a query, summarize a query, correct a query, correct a result of an executed task, communicate the result of such execution, determine a target application of an input/output event, and a combination thereof based on one of past dialog history, context, user preferences, meta information, and a combination thereof; and presenting a unified and coordinated user interface across the plurality of applications; wherein presenting a unified and coordinated user interface across a plurality of applications comprises the steps of: registering, by each application, information comprising application state, application modes, arguments, context, modalities, engine resources, and a combination thereof; and managing the dialog across the plurality of applications based on their registered information. 11. The method of claim 1 , wherein the step of presenting a unified and coordinated user interface across the plurality of applications comprises dynamically negotiating a network topology among devices executing the applications based on registered information of the applications. | 0.746416 |
9,779,141 | 10 | 14 | 10. A computer-implemented method for querying a knowledge based database having documents that have been indexed, the computer-implemented method being performed by one or more processors, and the computer-implemented method comprising: receiving a query, the query containing a plurality of terms comprising at least a camel case term and a value type term; processing the query to obtain a modified query, the modified query including a constituent term at a position corresponding to the camel case term, and a generic term at a position corresponding to the value type term; identifying documents in a knowledge base database that proximately match the modified query; for each identified document, determining a distance for the one or more terms in the modified query; removing from the identified documents any documents which contain any of the one or more terms that have a distance that exceeds a predetermined distance; applying a scoring formula to the identified documents to obtain a score for each of the identified documents; ranking the identified documents based on the score obtained for each of the identified documents; and outputting the identified documents according to the ranking. | 10. A computer-implemented method for querying a knowledge based database having documents that have been indexed, the computer-implemented method being performed by one or more processors, and the computer-implemented method comprising: receiving a query, the query containing a plurality of terms comprising at least a camel case term and a value type term; processing the query to obtain a modified query, the modified query including a constituent term at a position corresponding to the camel case term, and a generic term at a position corresponding to the value type term; identifying documents in a knowledge base database that proximately match the modified query; for each identified document, determining a distance for the one or more terms in the modified query; removing from the identified documents any documents which contain any of the one or more terms that have a distance that exceeds a predetermined distance; applying a scoring formula to the identified documents to obtain a score for each of the identified documents; ranking the identified documents based on the score obtained for each of the identified documents; and outputting the identified documents according to the ranking. 14. The method of claim 10 further comprising: determining that the received query exists in a cache of preexisting queries; and outputting a ranking of documents for the query from the cache when the query exists in the cache. | 0.79326 |
10,102,195 | 8 | 12 | 8. A non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by a processor, configure the processor to perform operations comprising: identifying at least one first item of a plurality of items for which an attribute is unpopulated based at least in part on identifying a plurality of attributes inherited from at least one parent item category associated with the at least one first item and at least one second item, the at least one parent item category being a parent node to a child node associated with at least one first item and the at least one second item in a browse-node hierarchy; extracting a plurality of existing values for the attribute based at least in part on the at least one second item of the plurality of items, the at least one second item having the attribute populated; associating a set of priority indicators with the plurality of existing values, the set of priority indicators generated based at least in part on pre-determined rules that utilize a context associated with an existing value of the plurality of existing values to represent importance of the existing value in comparison to other existing values, the context based at least in part on a set of existing values of the plurality of existing values identified by the pre-determined rules that are associated with a position of a given existing value within text of the at least one first item; implementing a rule engine that implements a rule set specified by a user to iteratively alter the rule set after removing one or more existing values of the plurality of existing values to prioritize remaining existing values of the plurality of existing values based at least in part on the set of priority indicators; determining a potential value for the attribute from the text associated with the at least one first item based at least in part on filtering the plurality of existing values and the prioritized remaining existing values from the rule engine; and populating the attribute of the at least one first item of the plurality of items with the determined potential value. | 8. A non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by a processor, configure the processor to perform operations comprising: identifying at least one first item of a plurality of items for which an attribute is unpopulated based at least in part on identifying a plurality of attributes inherited from at least one parent item category associated with the at least one first item and at least one second item, the at least one parent item category being a parent node to a child node associated with at least one first item and the at least one second item in a browse-node hierarchy; extracting a plurality of existing values for the attribute based at least in part on the at least one second item of the plurality of items, the at least one second item having the attribute populated; associating a set of priority indicators with the plurality of existing values, the set of priority indicators generated based at least in part on pre-determined rules that utilize a context associated with an existing value of the plurality of existing values to represent importance of the existing value in comparison to other existing values, the context based at least in part on a set of existing values of the plurality of existing values identified by the pre-determined rules that are associated with a position of a given existing value within text of the at least one first item; implementing a rule engine that implements a rule set specified by a user to iteratively alter the rule set after removing one or more existing values of the plurality of existing values to prioritize remaining existing values of the plurality of existing values based at least in part on the set of priority indicators; determining a potential value for the attribute from the text associated with the at least one first item based at least in part on filtering the plurality of existing values and the prioritized remaining existing values from the rule engine; and populating the attribute of the at least one first item of the plurality of items with the determined potential value. 12. The non-transitory computer readable storage medium of claim 8 , wherein the potential value is determined by applying a rule from the rule set. | 0.890208 |
7,934,066 | 1 | 15 | 1. An archive method using a primary storage and a secondary storage comprising: receiving a backup request for a target dataset used by an application on a primary storage system to be backed up on a secondary storage system, wherein the primary storage system may have one or more different applications and each application having a corresponding one or more different proprietary application formats for storing their datasets; identifying an application translator module component to be loaded into an extensible backup manager that converts between a proprietary application format associated with the target dataset and a predetermined storage format used by the extensible backup manager; scheduling a baseline backup of entire target dataset from the primary storage to the secondary storage using the application translator module to convert from the proprietary application format into the predetermined storage format when the baseline backup of the target dataset has not yet been performed; performing an incremental backup of the target dataset in addition to the baseline backup of the entire target dataset, if the incremental backup is scheduled, wherein the incremental backup uses the application translator module to convert from the proprietary application format associated with the application into the predetermined storage format of the extensible backup manager; and invoking a data mover component from the extensible backup manager when the application translator module has completed converting from the proprietary application format into the predetermined storage format wherein the data mover component causes the incremental backup and the baseline backup of the entire target dataset, if scheduled, to be moved from the primary storage to the secondary storage as requested and stored in the predetermined storage format rather than the proprietary application format associated with the application. | 1. An archive method using a primary storage and a secondary storage comprising: receiving a backup request for a target dataset used by an application on a primary storage system to be backed up on a secondary storage system, wherein the primary storage system may have one or more different applications and each application having a corresponding one or more different proprietary application formats for storing their datasets; identifying an application translator module component to be loaded into an extensible backup manager that converts between a proprietary application format associated with the target dataset and a predetermined storage format used by the extensible backup manager; scheduling a baseline backup of entire target dataset from the primary storage to the secondary storage using the application translator module to convert from the proprietary application format into the predetermined storage format when the baseline backup of the target dataset has not yet been performed; performing an incremental backup of the target dataset in addition to the baseline backup of the entire target dataset, if the incremental backup is scheduled, wherein the incremental backup uses the application translator module to convert from the proprietary application format associated with the application into the predetermined storage format of the extensible backup manager; and invoking a data mover component from the extensible backup manager when the application translator module has completed converting from the proprietary application format into the predetermined storage format wherein the data mover component causes the incremental backup and the baseline backup of the entire target dataset, if scheduled, to be moved from the primary storage to the secondary storage as requested and stored in the predetermined storage format rather than the proprietary application format associated with the application. 15. The method of claim 1 further comprising: generating an additional application translator module for each restore request that operates to separately convert between a predetermined storage format and a proprietary application format; and identifying, by a single extensible backup manager, each additional application translator module in accordance with the target dataset and application and ensuring, by the single extensible backup manager, each application translator module completes conversion of the target dataset from the predetermined storage format into the proprietary application format. | 0.500824 |
9,711,137 | 1 | 7 | 1. A system, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: based on an analysis of conversation data transmitted within an audio communication session between a first communication device of a network and a second communication device of the network, determining, during the audio communication session, goal data indicative of a goal associated with the first communication device and the second communication device; based on data received from a network data store coupled to the first communication device and the second communication device, determining solution data indicative of solutions to accomplish the goal; and in response to the determining the solution data and determining that first speech data associated with the conversation data is not being transmitted between the first communication device and the second communication device during the audio communication session, generating second speech data based on the solution data and adding a network device that is coupled to the first communication device and the second communication device via the network as an additional participant in the audio communication session, and simultaneously transmitting the second speech data from the network device to the first communication device and the second communication device, wherein, in addition to the conversation data transmitted between the first communication device and the second communication device during the audio communication session, the second speech data is transmitted to the first communication device and the second communication device during the audio communication session, and third speech data is transmitted between the first communication device and the second communication device after receiving the second speech data associated with the solution data. | 1. A system, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: based on an analysis of conversation data transmitted within an audio communication session between a first communication device of a network and a second communication device of the network, determining, during the audio communication session, goal data indicative of a goal associated with the first communication device and the second communication device; based on data received from a network data store coupled to the first communication device and the second communication device, determining solution data indicative of solutions to accomplish the goal; and in response to the determining the solution data and determining that first speech data associated with the conversation data is not being transmitted between the first communication device and the second communication device during the audio communication session, generating second speech data based on the solution data and adding a network device that is coupled to the first communication device and the second communication device via the network as an additional participant in the audio communication session, and simultaneously transmitting the second speech data from the network device to the first communication device and the second communication device, wherein, in addition to the conversation data transmitted between the first communication device and the second communication device during the audio communication session, the second speech data is transmitted to the first communication device and the second communication device during the audio communication session, and third speech data is transmitted between the first communication device and the second communication device after receiving the second speech data associated with the solution data. 7. The system of claim 1 , wherein the conversation data comprises the first speech data and the operations further comprise: converting the first speech data to textual data to facilitate the analysis. | 0.841444 |
7,698,138 | 5 | 6 | 5. A first apparatus comprising a broadcasting part broadcasting additional information containing keyword information for specifying an object that appears in broadcast contents, and a scene code indicating a scene of the broadcast contents, wherein the additional information and the scene code are, simultaneously with the broadcast contents, received, a language model corresponding to the received scene code when the scene code is received is, out of the language models retained in advance, specified, speech recognition of a voice uttered by a viewing person is, by using the corrected specified language model, performed, the keyword information is specified based on the speech recognition result, and the additional information containing the specified keyword information is displayed. | 5. A first apparatus comprising a broadcasting part broadcasting additional information containing keyword information for specifying an object that appears in broadcast contents, and a scene code indicating a scene of the broadcast contents, wherein the additional information and the scene code are, simultaneously with the broadcast contents, received, a language model corresponding to the received scene code when the scene code is received is, out of the language models retained in advance, specified, speech recognition of a voice uttered by a viewing person is, by using the corrected specified language model, performed, the keyword information is specified based on the speech recognition result, and the additional information containing the specified keyword information is displayed. 6. The first apparatus according to claim 5 , wherein a synonym dictionary, in which a plurality of words are classified into word classes based on a synonymy between the words, is utilized to thereby correct a frequency of appearance of a predetermined combination of the word classes in an expression form of the specified language model and/or a frequency of appearance of a predetermined word with reference to a predetermined word class in the expression form of the specified language model, based on history information on speech recognition results of already performed speech recognition, and the speech recognition is performed by using the corrected language model. | 0.633803 |
6,044,387 | 1 | 3 | 1. A method for effecting an automatic editing operation on a plurality of web page files at one time using a computer, comprising the steps of: (a) enabling a user to specify the editing operation that is to be automatically effected on the plurality of files by the computer; (b) without requiring intervention by the user, automatically opening each of the plurality of files, if not already open, in order to identify each file for which the editing operation is applicable; and (c) implementing the editing operation on each file for which the editing operation is applicable. | 1. A method for effecting an automatic editing operation on a plurality of web page files at one time using a computer, comprising the steps of: (a) enabling a user to specify the editing operation that is to be automatically effected on the plurality of files by the computer; (b) without requiring intervention by the user, automatically opening each of the plurality of files, if not already open, in order to identify each file for which the editing operation is applicable; and (c) implementing the editing operation on each file for which the editing operation is applicable. 3. The method of claim 1, further comprising the step of creating a list of files from the plurality of files, said list indicating the files for which the editing operation is applicable. | 0.872283 |
8,688,696 | 14 | 15 | 14. The method of claim 12 , further comprising the steps of growing the bounding box by increasing the geographic region defined by the bounding box until either a maximum bounding box size is reached or until a minimum quantity of entities remain after the excluding. | 14. The method of claim 12 , further comprising the steps of growing the bounding box by increasing the geographic region defined by the bounding box until either a maximum bounding box size is reached or until a minimum quantity of entities remain after the excluding. 15. The method of claim 14 , wherein the minimum quantity of entities is based only on a quantity of entities divided into the first part. | 0.957643 |
9,766,784 | 1 | 9 | 1. A system, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: determining a first layout for a message comprising first message content comprising a message element, the message element associated with a first token value and a first device display area of a device display, to facilitate a first display of the message on the device display based on the first layout; determining a second token value of the message element, different from the first token value, from token values comprising a text-only token value associated with generating a textual representation of the message element, an icon-only token value associated with generating an icon representation of the message element, a reduced-size token value associated with generating a representation that is smaller than a 100% sized representation of the message element, a full-size token value associated with generating the 100% sized representation of the message element, and an increased-size token value associated with generating a representation that is larger than the 100% sized representation of the message element; in response to receiving a first indication related to transitioning the message element from the first device display area to a second device display area of the device display, determining a second layout of the message comprising the message element displayed based on the second token value and the second device display area, wherein, to enable presentation of at least a selectable minimum amount of second message content that does not comprise the message element, the determining the second layout comprises complying with a scaling rule that is related to a selectable ratio of a summed token area and a messaging environment area of the device display, wherein the summed token area corresponds to a first sum of the display area associated with the second token value and a third token value associated with the second message content; and facilitating a second display of the message on the device display based on the second layout. | 1. A system, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: determining a first layout for a message comprising first message content comprising a message element, the message element associated with a first token value and a first device display area of a device display, to facilitate a first display of the message on the device display based on the first layout; determining a second token value of the message element, different from the first token value, from token values comprising a text-only token value associated with generating a textual representation of the message element, an icon-only token value associated with generating an icon representation of the message element, a reduced-size token value associated with generating a representation that is smaller than a 100% sized representation of the message element, a full-size token value associated with generating the 100% sized representation of the message element, and an increased-size token value associated with generating a representation that is larger than the 100% sized representation of the message element; in response to receiving a first indication related to transitioning the message element from the first device display area to a second device display area of the device display, determining a second layout of the message comprising the message element displayed based on the second token value and the second device display area, wherein, to enable presentation of at least a selectable minimum amount of second message content that does not comprise the message element, the determining the second layout comprises complying with a scaling rule that is related to a selectable ratio of a summed token area and a messaging environment area of the device display, wherein the summed token area corresponds to a first sum of the display area associated with the second token value and a third token value associated with the second message content; and facilitating a second display of the message on the device display based on the second layout. 9. The system of claim 1 , wherein a mobile device comprises the device display. | 0.970631 |
8,305,632 | 15 | 16 | 15. A system for performing automated batch processing on hard copy documents, said system comprising: a sheet feeder; a scanner arranged to receive sheets from said sheet feeder; a processor coupled to said scanner; a plurality of output devices coupled to said processor; and wherein said processor is configured to: search said scanned sheets for flagging indicia, wherein said flagging indicia is one or more of a copyright notice or a security legend; in response to determining the presence of flagging indicia in one or more of said scanned sheets: flag one or more sheets having flagging indicia from said one or more scanned sheets of writing; block processing of only said flagged one or more sheets from said one or more scanned sheets of writing, wherein access to said flagged one or more sheets is secured with an authorization code; identify an individual that requested the processing of said document; store an identity of said individual that requested the processing of said flagged one or more sheets in association with said flagged one or more sheets; transmit only said flagged one or more sheets to an electronic mail address of a reviewer via an electronic mail; and in response to detecting said entry of said authorization code, remove said blocking of said flagged one or more sheets; and send documents to said output devices according to written information on said sheets scanned by said scanner, wherein said written information further includes additional processing instructions for causing said processor and said output devices to perform one or more functions from: collating said document, stapling said document, and two-side printing said document. | 15. A system for performing automated batch processing on hard copy documents, said system comprising: a sheet feeder; a scanner arranged to receive sheets from said sheet feeder; a processor coupled to said scanner; a plurality of output devices coupled to said processor; and wherein said processor is configured to: search said scanned sheets for flagging indicia, wherein said flagging indicia is one or more of a copyright notice or a security legend; in response to determining the presence of flagging indicia in one or more of said scanned sheets: flag one or more sheets having flagging indicia from said one or more scanned sheets of writing; block processing of only said flagged one or more sheets from said one or more scanned sheets of writing, wherein access to said flagged one or more sheets is secured with an authorization code; identify an individual that requested the processing of said document; store an identity of said individual that requested the processing of said flagged one or more sheets in association with said flagged one or more sheets; transmit only said flagged one or more sheets to an electronic mail address of a reviewer via an electronic mail; and in response to detecting said entry of said authorization code, remove said blocking of said flagged one or more sheets; and send documents to said output devices according to written information on said sheets scanned by said scanner, wherein said written information further includes additional processing instructions for causing said processor and said output devices to perform one or more functions from: collating said document, stapling said document, and two-side printing said document. 16. The system of claim 15 , wherein said processor is further configured to: determine a number of pages in said document; identify said operation and said additional processing instructions on said coversheet; control said system to perform said operation indicated in said cover sheet on said document; and in response to said cover sheet having additional processing instructions, control said system to perform said additional processing instructions on said document. | 0.501055 |
8,086,999 | 4 | 6 | 4. A computer disk comprising: a computer readable disk suitable for storage of computer programs; and one or more computer programs encoded by said disk and configured to perform: receiving a user command to enable automatic cutting-and-pasting in a destination first, source second sequence, with user enablement of automatic natural language translation; subsequent to receiving said command and enablement, receiving a user selection of one or more insertion points in the contents of a destination computer resource via a destination user interface, said computer resource consisting of an electronic document; subsequent to receiving said user-selected insertion points, receiving a user selection of one or more information elements via a source user interface; intercepting transfer of said information elements to said destination computer resource; determining which intercepted information elements are expressed in a natural language not matching a user-specified natural language; responsive to finding no existing natural language handling rule for an information element to be transferred: invoking a rule management user interface; and allowing via said rule management user interface a user to define an action to be taken selected from the list of invoking a natural language translation process, allowing transfer without modification, and isolating said information element; performing one or more natural language handling actions on said intercepted information elements which do not match said user specified natural language as defined by one or more natural language handling rules; and transferring information elements to said destination which have been translated to said user specified natural language as a result of said handling actions. | 4. A computer disk comprising: a computer readable disk suitable for storage of computer programs; and one or more computer programs encoded by said disk and configured to perform: receiving a user command to enable automatic cutting-and-pasting in a destination first, source second sequence, with user enablement of automatic natural language translation; subsequent to receiving said command and enablement, receiving a user selection of one or more insertion points in the contents of a destination computer resource via a destination user interface, said computer resource consisting of an electronic document; subsequent to receiving said user-selected insertion points, receiving a user selection of one or more information elements via a source user interface; intercepting transfer of said information elements to said destination computer resource; determining which intercepted information elements are expressed in a natural language not matching a user-specified natural language; responsive to finding no existing natural language handling rule for an information element to be transferred: invoking a rule management user interface; and allowing via said rule management user interface a user to define an action to be taken selected from the list of invoking a natural language translation process, allowing transfer without modification, and isolating said information element; performing one or more natural language handling actions on said intercepted information elements which do not match said user specified natural language as defined by one or more natural language handling rules; and transferring information elements to said destination which have been translated to said user specified natural language as a result of said handling actions. 6. The disk as set forth in claim 4 wherein said handling actions comprise determining an original natural language in which each intercepted information elements is expressed, and subsequently invoking a computer translation process to translate each item from said original natural language to said user-specified natural language. | 0.513158 |
9,547,420 | 6 | 7 | 6. The computer-implemented method of claim 5 , further comprising: determining at least one font characteristic for a suggestion of the spatial layout based at least in part upon the confidence score of the suggestion. | 6. The computer-implemented method of claim 5 , further comprising: determining at least one font characteristic for a suggestion of the spatial layout based at least in part upon the confidence score of the suggestion. 7. The computer-implemented method of claim 6 , wherein the at least one font characteristic includes at least one of font size, font style, font color, font bold level, font italicize level, font animation, or font angle. | 0.946429 |
7,882,500 | 1 | 4 | 1. A computer program product comprising a tangible computer usable medium having a computer readable program for managing granularity of a computing service infrastructure, wherein the computer readable program when executed on a computer causes the computer to: identify a group having a number of service requestors; identify a set of business functions that may be requested by the group of service requestors by either customized or non-customized service requests; create a value (n1) that represents the smallest number of customized service functions to realize all of the business functions; create a value (n2) that represents the smallest total number of non-customized service functions to realize all of the business functions; and iteratively determine an optimal number L of customized and non-customized service functions to realize the business functions, where L is between n1 and n2 and increases from n2 towards n1 as a number of each requestor is assigned a customized service request for each business function. | 1. A computer program product comprising a tangible computer usable medium having a computer readable program for managing granularity of a computing service infrastructure, wherein the computer readable program when executed on a computer causes the computer to: identify a group having a number of service requestors; identify a set of business functions that may be requested by the group of service requestors by either customized or non-customized service requests; create a value (n1) that represents the smallest number of customized service functions to realize all of the business functions; create a value (n2) that represents the smallest total number of non-customized service functions to realize all of the business functions; and iteratively determine an optimal number L of customized and non-customized service functions to realize the business functions, where L is between n1 and n2 and increases from n2 towards n1 as a number of each requestor is assigned a customized service request for each business function. 4. The computer program product as in claim 1 , wherein the computer program product further causes the computer to: characterize at least one rule and at least one constraint for determining an optimal number L wherein one of the constraints comprises a tolerance coefficient for output data of at least one of the service functions. | 0.501493 |
8,108,216 | 10 | 11 | 10. The method according to claim 9 , further comprising: preparing in advance a first storage unit including a plurality of storage mediums with different data acquisition speeds, which store a plurality of speech units, respectively; preparing in advance a second storage unit configured to store information indicating in which one of said plurality of storage mediums each of the speech units is stored; and acquiring the plurality of speech units from the first storage unit in accordance with the information before concatenating the plurality of speech units, and wherein the calculating the penalty coefficient including calculating the penalty coefficient for each of said plurality of third speech unit strings based on a restriction concerning quickness of data acquisition which is to be satisfied when the speech units included in the first speech unit string are acquired from the first storage unit by the concatenation unit and a statistic determined depending on which one of said plurality of storage mediums each of all speech units included in the third speech unit string is stored in. | 10. The method according to claim 9 , further comprising: preparing in advance a first storage unit including a plurality of storage mediums with different data acquisition speeds, which store a plurality of speech units, respectively; preparing in advance a second storage unit configured to store information indicating in which one of said plurality of storage mediums each of the speech units is stored; and acquiring the plurality of speech units from the first storage unit in accordance with the information before concatenating the plurality of speech units, and wherein the calculating the penalty coefficient including calculating the penalty coefficient for each of said plurality of third speech unit strings based on a restriction concerning quickness of data acquisition which is to be satisfied when the speech units included in the first speech unit string are acquired from the first storage unit by the concatenation unit and a statistic determined depending on which one of said plurality of storage mediums each of all speech units included in the third speech unit string is stored in. 11. The method according to claim 10 , wherein said plurality of storage mediums include a storage medium with a high data acquisition speed and a storage medium with a low data acquisition speed, and the restriction is an upper limit value of the number of times of acquisition of speech unit data included in the first speech unit string from the storage medium with the low data acquisition speed, and the statistic is a proportion of the number of speech units stored in the storage medium with the low data acquisition speed to the number of speech units included in the third speech unit string. | 0.860168 |
8,572,024 | 1 | 9 | 1. A computer-implemented method of extracting information from co-occurring Hyper Text Mark-up Language (HTML) structured documents, the method comprising: receiving one or more web sites selected by a user for data extraction; collecting a plurality of co-occurring different HTML structured documents for each of the selected web sites at a computer comprising a processor; forming a plurality of clusters comprising different subsets of the co-occurring HTML structured documents, wherein: each cluster comprises a different HTML structured document of the plurality of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the plurality of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster, and an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures, displaying the centroid document of a particular cluster selected from a list of clusters; and providing a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display. | 1. A computer-implemented method of extracting information from co-occurring Hyper Text Mark-up Language (HTML) structured documents, the method comprising: receiving one or more web sites selected by a user for data extraction; collecting a plurality of co-occurring different HTML structured documents for each of the selected web sites at a computer comprising a processor; forming a plurality of clusters comprising different subsets of the co-occurring HTML structured documents, wherein: each cluster comprises a different HTML structured document of the plurality of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the plurality of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster, and an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures, displaying the centroid document of a particular cluster selected from a list of clusters; and providing a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display. 9. The method of claim 1 , further comprising extracting data from the other HTML structured documents of the particular cluster based on the identified data element on each of the other HTML structured documents of the particular cluster. | 0.923788 |
9,697,867 | 1 | 4 | 1. An adaptive narrative presentation system, comprising: at least one optical sensor having a field-of-view; a communications interface; and an adaptive narration presentation circuit communicably coupled to the at least one optical sensor and the communications interface, the adaptive narration presentation circuit to: generate a narrative presentation output at the communications interface; optically identify an object added to the field-of-view of the at least one optical sensor, the optical identification based at least in part on at least one intrinsic parameter of the object; identify at least one aspect of the narrative presentation associated with the identified object; and modify the at least one aspect of the narrative presentation based at least in part on the identified object. | 1. An adaptive narrative presentation system, comprising: at least one optical sensor having a field-of-view; a communications interface; and an adaptive narration presentation circuit communicably coupled to the at least one optical sensor and the communications interface, the adaptive narration presentation circuit to: generate a narrative presentation output at the communications interface; optically identify an object added to the field-of-view of the at least one optical sensor, the optical identification based at least in part on at least one intrinsic parameter of the object; identify at least one aspect of the narrative presentation associated with the identified object; and modify the at least one aspect of the narrative presentation based at least in part on the identified object. 4. The system of claim 1 , the adaptive narration presentation circuit to further: generate an audio/visual narrative presentation output at the communications interface. | 0.903079 |
9,519,636 | 1 | 9 | 1. A method comprising: receiving text in a system that includes a processor; extracting, by the system, a plurality of linguistic entities and associated linguistic entity categories based on the text; determining, by the system, one or more semantic objects of a semantic layer based on the linguistic entity categories, wherein each of the one or more semantic objects of the semantic layer associates one or more physical entities stored in a data source with user-friendly names; determining, by the system, an analysis context based on the text, the linguistic entities, and the associated linguistic entity categories; after determination of the analysis context and the one or more semantic objects by the system, generating, by the system, a query of the semantic layer based on the analysis context determined by the system and the one or more semantic objects determined by the system, wherein the generating the query of the semantic layer comprises: determining, by the system, based on the linguistic entity categories that were extracted, whether the one or more semantic objects are to be filtered, and in response to determining to filter the one or more semantic objects, determining how to filter the semantic objects, wherein when a value from a first linguistic entity category matches a value for one of the one or more semantic objects, using the value from the first linguistic entity category as a query filter, and when only a single entity is mentioned for the first linguistic entity category, including the entity in the query filter and removing the first linguistic entity category from a result of the query of the semantic layer; and receiving a structured data result in response to the query of the semantic layer. | 1. A method comprising: receiving text in a system that includes a processor; extracting, by the system, a plurality of linguistic entities and associated linguistic entity categories based on the text; determining, by the system, one or more semantic objects of a semantic layer based on the linguistic entity categories, wherein each of the one or more semantic objects of the semantic layer associates one or more physical entities stored in a data source with user-friendly names; determining, by the system, an analysis context based on the text, the linguistic entities, and the associated linguistic entity categories; after determination of the analysis context and the one or more semantic objects by the system, generating, by the system, a query of the semantic layer based on the analysis context determined by the system and the one or more semantic objects determined by the system, wherein the generating the query of the semantic layer comprises: determining, by the system, based on the linguistic entity categories that were extracted, whether the one or more semantic objects are to be filtered, and in response to determining to filter the one or more semantic objects, determining how to filter the semantic objects, wherein when a value from a first linguistic entity category matches a value for one of the one or more semantic objects, using the value from the first linguistic entity category as a query filter, and when only a single entity is mentioned for the first linguistic entity category, including the entity in the query filter and removing the first linguistic entity category from a result of the query of the semantic layer; and receiving a structured data result in response to the query of the semantic layer. 9. The method according to claim 1 , wherein the linguistic entity categories include a subject type category, an analysis type category and a dimension type category; wherein the method further comprises: dividing the received text into a plurality of clauses; and wherein the determining an analysis context based on the text, the linguistic entities, and the associated linguistic entity categories comprises: determining an analysis context for a first one of the plurality of clauses, the analysis context for the first one of the plurality of clauses including the subject type category, the analysis type category and the dimension type category, wherein the subject type category included in the analysis context for the first one of the plurality of clauses specifies a subject of an analysis, said subject of the analysis being a numerical indicator of value, wherein the analysis type category included in the analysis context for the first one of the plurality of clauses is different than the subject type category and represents an intent of the analysis, wherein the dimension type category included in the analysis context for the first one of the plurality of clauses is different than both the subject type category and the analysis type category and represents an axis of the analysis, wherein values of a quantity are to be disposed along the axis of the analysis. | 0.650858 |
9,501,592 | 7 | 9 | 7. The computer implemented method of claim 1 , the process further comprising: migrating or porting a Verilog-AMS model, which is written in Verilog-AMS language, into the SystemVerilog modeling environment based at least in part upon the set of built-in nettypes; identifying a Verilog-AMS wreal net in the Verilog-AMS model; and coercing the Verilog-AMS wreal net to the at least one wire-real nettype in the SystemVerilog modeling environment. | 7. The computer implemented method of claim 1 , the process further comprising: migrating or porting a Verilog-AMS model, which is written in Verilog-AMS language, into the SystemVerilog modeling environment based at least in part upon the set of built-in nettypes; identifying a Verilog-AMS wreal net in the Verilog-AMS model; and coercing the Verilog-AMS wreal net to the at least one wire-real nettype in the SystemVerilog modeling environment. 9. The computer implemented method of claim 7 , the process further comprising: determining an option for migrating or porting the Verilog-AMS model; and determining whether one or more exceptions apply to migrating or porting the Verilog-AMS model. | 0.957968 |
9,984,054 | 16 | 17 | 16. The system according to claim 15 , wherein the web-based extensible markup language editor receives modification of the source content from at least one of a plurality of client nodes via the web-based interface, wherein the web-based extensible markup language editor is associated with the web-based interface. | 16. The system according to claim 15 , wherein the web-based extensible markup language editor receives modification of the source content from at least one of a plurality of client nodes via the web-based interface, wherein the web-based extensible markup language editor is associated with the web-based interface. 17. The system according to claim 16 , wherein the review module saves the modification of the source content of the document as tentative changes until the review module receives permission to incorporate the modification from at least one of the plurality of client nodes, the tentative changes being visually distinctive from the source content. | 0.932005 |
7,533,110 | 2 | 3 | 2. The method as recited in claim 1 , wherein reading the first file comprises receiving a compressed file and uncompressing the compressed file to yield the first file. | 2. The method as recited in claim 1 , wherein reading the first file comprises receiving a compressed file and uncompressing the compressed file to yield the first file. 3. The method as recited in claim 2 , further comprising compressing the third file. | 0.973231 |
9,085,303 | 23 | 32 | 23. A vehicle personal assistant embodied in one or more non-transitory machine readable storage media, the vehicle personal assistant executable by a computing system to: receive a human-generated spoken natural language phrase; execute a semantic interpretation process on the human-generated spoken natural language phrase to derive, from the human-generated spoken natural language phrase, a trigger condition, a search action, and a search parameter to be used in executing the search action if the trigger condition is met, the trigger condition comprising a data value; monitor one or more vehicle-related real-time sensor inputs; compare a first vehicle-related real-time sensor input to the data value to determine whether the vehicle-related trigger condition has occurred; and in response to determining that the trigger condition has occurred: determine a current value of a second real-time input associated with the occurrence of the trigger condition; and execute the search action using (i) the current value of the second real-time input and (ii) the search parameter derived from the human-generated spoken natural language phrase. | 23. A vehicle personal assistant embodied in one or more non-transitory machine readable storage media, the vehicle personal assistant executable by a computing system to: receive a human-generated spoken natural language phrase; execute a semantic interpretation process on the human-generated spoken natural language phrase to derive, from the human-generated spoken natural language phrase, a trigger condition, a search action, and a search parameter to be used in executing the search action if the trigger condition is met, the trigger condition comprising a data value; monitor one or more vehicle-related real-time sensor inputs; compare a first vehicle-related real-time sensor input to the data value to determine whether the vehicle-related trigger condition has occurred; and in response to determining that the trigger condition has occurred: determine a current value of a second real-time input associated with the occurrence of the trigger condition; and execute the search action using (i) the current value of the second real-time input and (ii) the search parameter derived from the human-generated spoken natural language phrase. 32. The vehicle personal assistant of claim 23 , executable by the computing system to present further system-generated output in response to the further human-generated input. | 0.858974 |
8,209,665 | 1 | 6 | 1. A method, implemented at least in part by a computing device, for identifying topics in source code using Latent Dirichlet Allocation (LDA), the method comprising: receiving software source code; identifying domain specific keywords from the software source code; generating a keyword matrix, wherein the keyword matrix comprises weighted sums of occurrences of the domain specific keywords in the software source code; processing, using LDA, the keyword matrix and the software source code; and outputting, from the processing, collections of domain specific keywords and probabilities, wherein the collections corresponds to respective topics identified by LDA in the software source code. | 1. A method, implemented at least in part by a computing device, for identifying topics in source code using Latent Dirichlet Allocation (LDA), the method comprising: receiving software source code; identifying domain specific keywords from the software source code; generating a keyword matrix, wherein the keyword matrix comprises weighted sums of occurrences of the domain specific keywords in the software source code; processing, using LDA, the keyword matrix and the software source code; and outputting, from the processing, collections of domain specific keywords and probabilities, wherein the collections corresponds to respective topics identified by LDA in the software source code. 6. The method of claim 1 wherein each of the domain specific keywords of the keyword matrix is weighted based upon a location type of the domain specific keyword. | 0.930887 |
9,400,549 | 5 | 10 | 5. The non-transitory computer readable storage medium as recited in claim 1 , wherein the electronic book includes a story theme and a non-story theme. | 5. The non-transitory computer readable storage medium as recited in claim 1 , wherein the electronic book includes a story theme and a non-story theme. 10. The non-transitory computer readable storage medium as recited in claim 5 , wherein the at least a portion of the content of the electronic book changed is the non-story theme. | 0.938398 |
7,739,247 | 1 | 3 | 1. A system comprising: a server at least in selective communication with a client machine, the server configured to: receive a query from the client machine; retrieve a data set based on the query, and organize the data set into subsets with at least a first pass and a second pass, wherein the first pass is statistic driven and the second pass is attribute driven, wherein the statistic driven first pass is selected from a set consisting essentially of organizational clustering and hierarchical clustering, and wherein the second pass is to partition a subset of the data set that results from the first pass, and name each of the subsets, based at least in part on a property shared by at least a majority of the data units of the subset. | 1. A system comprising: a server at least in selective communication with a client machine, the server configured to: receive a query from the client machine; retrieve a data set based on the query, and organize the data set into subsets with at least a first pass and a second pass, wherein the first pass is statistic driven and the second pass is attribute driven, wherein the statistic driven first pass is selected from a set consisting essentially of organizational clustering and hierarchical clustering, and wherein the second pass is to partition a subset of the data set that results from the first pass, and name each of the subsets, based at least in part on a property shared by at least a majority of the data units of the subset. 3. The system of claim 1 , wherein the server is further configured to use text from each of the subsets to name respective ones of the subsets. | 0.862333 |
8,925,057 | 1 | 11 | 1. A system for user verification, comprising: a security component comprising a test generation component for generating one or more automated tests that rely on a plurality of human vision properties comprising at least persistence of vision and simultaneous contrast wherein simultaneous contrast comprises enhancement or diminishment, relative to normal, of perception, cognition and related performance as a result of immediately previous or simultaneous exposure to a stimulus of lesser or greater value in the same dimension, to differentiate a human user from an automated entity, wherein the test generation component further comprises a segmenting component which segments a target image into a grid of segments of predetermined sizes, and a frameset generation component for generating at least one frameset for at least one of the automated test, wherein the frameset generation component further comprises one or more of a color mapping component that determines which pixels of the target image are positive and where to put negative whitespace data prior to generating the frameset or a noise generation component that introduces noise into each frame of the frameset; a communication component configured to execute one or more of transmission of the tests to one or more access requestors or reception of responses from the access requestors; and a nontransitory computer readable medium having stored thereon one or more of the security component or the communication component. | 1. A system for user verification, comprising: a security component comprising a test generation component for generating one or more automated tests that rely on a plurality of human vision properties comprising at least persistence of vision and simultaneous contrast wherein simultaneous contrast comprises enhancement or diminishment, relative to normal, of perception, cognition and related performance as a result of immediately previous or simultaneous exposure to a stimulus of lesser or greater value in the same dimension, to differentiate a human user from an automated entity, wherein the test generation component further comprises a segmenting component which segments a target image into a grid of segments of predetermined sizes, and a frameset generation component for generating at least one frameset for at least one of the automated test, wherein the frameset generation component further comprises one or more of a color mapping component that determines which pixels of the target image are positive and where to put negative whitespace data prior to generating the frameset or a noise generation component that introduces noise into each frame of the frameset; a communication component configured to execute one or more of transmission of the tests to one or more access requestors or reception of responses from the access requestors; and a nontransitory computer readable medium having stored thereon one or more of the security component or the communication component. 11. The system of claim 1 , wherein the test generation component generates the target image of size 104×44 pixels wherein the target image is divided into 26 vertical segments and 11 horizontal segments, resulting in the video being displayed at 60 FPS with 4 FPFS. | 0.542955 |
8,793,137 | 11 | 17 | 11. A system for processing speech, comprising: a port configured to receive natural language speech input; and at least one automated speech processor configured to: receive the natural language speech input from the port and store it in a memory; semantically parse the natural language speech input with respect to a plurality of predetermined command grammars; determine if the parsed natural language speech input unambiguously corresponds to a command and comprises information that permits context-dependent statistically reliable processing with respect to completeness, then storing the command for execution and exiting the determining; if the received natural language speech input ambiguously corresponds to a single command or does not comprise information that permits context-dependent statistically reliable processing with respect to completeness, then prompting a user for further natural language speech input to reduce ambiguity or increase completeness, in dependence on a relationship of previously received natural language speech input and at least one command grammar of the plurality of predetermined command grammars, reparsing the further natural language speech input in conjunction with previously parsed natural language speech input, and iterating the determining; and if an abort, fail or cancel condition is detected in the natural language speech input; generating a signal by the at least one automated processor in dependence on, said determining. | 11. A system for processing speech, comprising: a port configured to receive natural language speech input; and at least one automated speech processor configured to: receive the natural language speech input from the port and store it in a memory; semantically parse the natural language speech input with respect to a plurality of predetermined command grammars; determine if the parsed natural language speech input unambiguously corresponds to a command and comprises information that permits context-dependent statistically reliable processing with respect to completeness, then storing the command for execution and exiting the determining; if the received natural language speech input ambiguously corresponds to a single command or does not comprise information that permits context-dependent statistically reliable processing with respect to completeness, then prompting a user for further natural language speech input to reduce ambiguity or increase completeness, in dependence on a relationship of previously received natural language speech input and at least one command grammar of the plurality of predetermined command grammars, reparsing the further natural language speech input in conjunction with previously parsed natural language speech input, and iterating the determining; and if an abort, fail or cancel condition is detected in the natural language speech input; generating a signal by the at least one automated processor in dependence on, said determining. 17. The system according to claim 11 , wherein the automated processor comprises a plurality of virtual workspaces and a plurality of processing cores. | 0.823185 |
8,958,828 | 1 | 14 | 1. A computer-implemented method comprising: detecting, by a mobile computing device, a current context associated with the mobile computing device, the current context being external to the mobile computing device and indicating a current state of the mobile computing device in its surrounding environment, wherein the current context includes information that identifies a received signal strength, at the mobile computing device, of a short or medium-range wireless network that the mobile computing device is currently able to access, and wherein the current context further includes information from a scheduling application that identifies scheduled activities for a user who is associated with the mobile computing device; comparing the received signal strength to a plurality of values of received signal strengths for the short or medium-range wireless network, the plurality of values of received signal strengths being associated with a plurality of different physical locations; identifying, based on at least the comparison of the received signal strength to the plurality of values of received signal strengths, a particular physical location where the mobile computing device is currently located from among the plurality of different physical locations from which the mobile computing device is able to access the short or medium-range wireless network; determining, based on the current context, a current activity of the user; determining, based on the identified particular physical location and the determined current activity of the user, whether to switch the mobile computing device from operating using a current profile to operating using a second profile, wherein the current profile and the second profile each define one or more settings of the mobile computing device, and wherein determining whether to switch the mobile computing device to operating using the second profile is based on applying one or more learned rules to the identified particular physical location and the determined current activity of the user; and in response to determining whether to switch to the second profile, adjusting one or more setting of the mobile computing device based on the second profile, further comprising, over a period of time before determining whether to switch the mobile computing device to operating using the second profile, defining the rules based on user adjustment of the settings of the mobile computing device and a detected context or change in context of the mobile computing device at or around a time the settings were adjusted. | 1. A computer-implemented method comprising: detecting, by a mobile computing device, a current context associated with the mobile computing device, the current context being external to the mobile computing device and indicating a current state of the mobile computing device in its surrounding environment, wherein the current context includes information that identifies a received signal strength, at the mobile computing device, of a short or medium-range wireless network that the mobile computing device is currently able to access, and wherein the current context further includes information from a scheduling application that identifies scheduled activities for a user who is associated with the mobile computing device; comparing the received signal strength to a plurality of values of received signal strengths for the short or medium-range wireless network, the plurality of values of received signal strengths being associated with a plurality of different physical locations; identifying, based on at least the comparison of the received signal strength to the plurality of values of received signal strengths, a particular physical location where the mobile computing device is currently located from among the plurality of different physical locations from which the mobile computing device is able to access the short or medium-range wireless network; determining, based on the current context, a current activity of the user; determining, based on the identified particular physical location and the determined current activity of the user, whether to switch the mobile computing device from operating using a current profile to operating using a second profile, wherein the current profile and the second profile each define one or more settings of the mobile computing device, and wherein determining whether to switch the mobile computing device to operating using the second profile is based on applying one or more learned rules to the identified particular physical location and the determined current activity of the user; and in response to determining whether to switch to the second profile, adjusting one or more setting of the mobile computing device based on the second profile, further comprising, over a period of time before determining whether to switch the mobile computing device to operating using the second profile, defining the rules based on user adjustment of the settings of the mobile computing device and a detected context or change in context of the mobile computing device at or around a time the settings were adjusted. 14. The computer-implemented method of claim 1 , wherein the settings of the mobile computing device defined by the current profile and the second profile include one or more of the following: speaker activation, speaker volume, microphone activation, display activation, display brightness, ringer activation, ringer volume, vibrate activation, ringtone, communications network connection, and communications filter activation. | 0.501166 |
8,850,306 | 9 | 13 | 9. A method, comprising: presenting a document template with an enhanced repeating section content control having formatted content in a presentation field of the enhanced repeating section content control, wherein the enhanced repeating section content control is placed around at least one of a: paragraph, a row, and a table in a document part, and is operative to insert a cloned copy of the enhanced repeating section content control into the document part in response to receiving a control directive at the enhanced repeating section content control; receiving control directives to modify the formatted content; and synchronizing the modified formatted content between the content control and a data store associated with the enhanced repeating section content control. | 9. A method, comprising: presenting a document template with an enhanced repeating section content control having formatted content in a presentation field of the enhanced repeating section content control, wherein the enhanced repeating section content control is placed around at least one of a: paragraph, a row, and a table in a document part, and is operative to insert a cloned copy of the enhanced repeating section content control into the document part in response to receiving a control directive at the enhanced repeating section content control; receiving control directives to modify the formatted content; and synchronizing the modified formatted content between the content control and a data store associated with the enhanced repeating section content control. 13. The method of claim 9 , comprising communicating the modified formatted content between the enhanced repeating section content control and the data store using a data schema different from a data schema of the formatted content stored in the data store. | 0.866006 |
8,856,638 | 14 | 20 | 14. A method for a multimedia seek sequence using a synchronization index and a mobile computing device, said method comprising the steps: providing a mobile computing device comprising a viewing screen and a touch-sensitive input interface; providing a synchronization index that comprises an electronic transcript that indicates text corresponding to audio from the multimedia and indicates respective times within multimedia corresponding to when a word or range of words is audible in the multimedia; providing a receiving device; displaying on said mobile computing device text from the synchronization index, wherein said text is displayed other than as a web page; receiving, by the mobile computing device, information indicating a user's selected mobile computing device touch-sensitive input interface gesture performed on a portion of said viewing screen corresponding to a word, or range of words, from said synchronization index; wherein said gesture is recognized by said touch-sensitive input interface; performing a timecode lookup using the synchronization index, wherein said synchronization index is referenced to provide data for a time location t1 that corresponds to said word or range of words; seeking on said receiving device multimedia corresponding to said synchronization index, and, if found, accessing multimedia at t1. | 14. A method for a multimedia seek sequence using a synchronization index and a mobile computing device, said method comprising the steps: providing a mobile computing device comprising a viewing screen and a touch-sensitive input interface; providing a synchronization index that comprises an electronic transcript that indicates text corresponding to audio from the multimedia and indicates respective times within multimedia corresponding to when a word or range of words is audible in the multimedia; providing a receiving device; displaying on said mobile computing device text from the synchronization index, wherein said text is displayed other than as a web page; receiving, by the mobile computing device, information indicating a user's selected mobile computing device touch-sensitive input interface gesture performed on a portion of said viewing screen corresponding to a word, or range of words, from said synchronization index; wherein said gesture is recognized by said touch-sensitive input interface; performing a timecode lookup using the synchronization index, wherein said synchronization index is referenced to provide data for a time location t1 that corresponds to said word or range of words; seeking on said receiving device multimedia corresponding to said synchronization index, and, if found, accessing multimedia at t1. 20. The method of claim 14 , wherein the mobile computing device comprises an operating system selected from the group comprising iOS, Android, Windows Phone, BlackBerry OS, and Linux. | 0.906599 |
8,549,394 | 10 | 16 | 10. A method for helping in a reading of an electronic message exchanged between multiple users, the method comprising the steps of: a chat room or instant message utility sending an electronic message between users; extracting a word from the electronic message sent to a particular user; acquiring history information on the word being extracted, wherein the history information includes a viewing of the word by the particular user, a usage of the word by the particular user, and a consultation of an electronic dictionary for the meaning of the word by the particular user; determining, based on the acquired history information, whether a meaning of the extracted word needs to be presented to the particular user on a display, wherein the determining is based on a criteria related to a viewing of the word by the particular user, a criteria related to a usage of the word by the particular user, and a criteria related to a consultation of an electronic dictionary for the meaning of the word by the particular user; and displaying the meaning of the word in a case in which the determining results in a determination that the meaning of the word needs to be presented to the user. | 10. A method for helping in a reading of an electronic message exchanged between multiple users, the method comprising the steps of: a chat room or instant message utility sending an electronic message between users; extracting a word from the electronic message sent to a particular user; acquiring history information on the word being extracted, wherein the history information includes a viewing of the word by the particular user, a usage of the word by the particular user, and a consultation of an electronic dictionary for the meaning of the word by the particular user; determining, based on the acquired history information, whether a meaning of the extracted word needs to be presented to the particular user on a display, wherein the determining is based on a criteria related to a viewing of the word by the particular user, a criteria related to a usage of the word by the particular user, and a criteria related to a consultation of an electronic dictionary for the meaning of the word by the particular user; and displaying the meaning of the word in a case in which the determining results in a determination that the meaning of the word needs to be presented to the user. 16. The method according to claim 10 , wherein the acquiring step acquires the history information on the usage of the word, and if the history information on the usage of the word does not meet a criterion that is related to the usage of the word and predetermined as a criterion for presuming that the particular user knows the meaning of the word, the determining step determines that the meaning of the word needs to be presented to the particular user. | 0.782588 |
8,799,239 | 1 | 5 | 1. A method comprising: receiving a first query instruction; in response to receiving the first query instruction, determining a compression ratio of a first compression value for a first query result decision diagram and a second compression value for a compressed query result set, the first compression value being indicative of a data size of the first query result decision diagram and the second compression value being indicative of the data size of the compressed query result set; comparing the compression ratio to a threshold ratio; and causing transmission of the first query result decision diagram or causing transmission of the compressed query result set based upon a result of the comparison of the compression ratio to the threshold ratio. | 1. A method comprising: receiving a first query instruction; in response to receiving the first query instruction, determining a compression ratio of a first compression value for a first query result decision diagram and a second compression value for a compressed query result set, the first compression value being indicative of a data size of the first query result decision diagram and the second compression value being indicative of the data size of the compressed query result set; comparing the compression ratio to a threshold ratio; and causing transmission of the first query result decision diagram or causing transmission of the compressed query result set based upon a result of the comparison of the compression ratio to the threshold ratio. 5. A method according to claim 1 , wherein determining a compression ratio includes determining the compression ratio where the first query result decision diagram is a reduced ordered binary decision diagram. | 0.895709 |
9,965,209 | 10 | 11 | 10. The method of claim 7 , further comprising pushing, by the glue device, the update graph data from the real-time, in memory graph storage device to the scalable, distributed, fault-tolerant, in-memory graph storage device for assimilation into the at least one graph. | 10. The method of claim 7 , further comprising pushing, by the glue device, the update graph data from the real-time, in memory graph storage device to the scalable, distributed, fault-tolerant, in-memory graph storage device for assimilation into the at least one graph. 11. The method of claim 10 , wherein the update graph data is pushed to the scalable, distributed, fault-tolerant, in-memory graph storage device with respect to the time threshold. | 0.947567 |
10,109,217 | 5 | 8 | 5. A speech assessment method for using the speech assessment device for the multisyllabic-word learning machine as claimed in claim 1 , comprising the following steps: a step of starting the assessment mode including using the central processing system to let the displaying unit displays the playing interface; a step of selecting words to be assessed including using the playing interface to select the standard continuous audio files for multisyllabic words, or the standard audio files for each separate character of the multisyllabic words from the standard speech database; a step of choosing to play or record including choosing a step of playing or a step of recording; a step of recording including using the speech receiving unit to receive and convert the words to be assessed spoken by the learner into the learner's continuous audio files for multisyllabic words, and the learner's audio files for each separate character of the multisyllabic words, wherein the learner's continuous audio files, and the learner's audio files are stored in the learner's speech database, and also transmitted to the audio visualization unit to create the learner's monosyllabic reference polygonal line for each separate character and the learner's continuous multisyllabic reference polygonal line for multisyllabic words, by conducting a step of visualization; the step of visualization including: a step of picking out fundamental frequency, a step of defining analysis point, a step of transforming polygonal lines, and a step of simplifying the polygonal lines, wherein the step of visualization is capable of simultaneously converting standard audio file into the reference polygonal line and converting the learner's audio file into the learner's polygonal line; the step of picking out fundamental frequency including selecting the most stable section of the frequency of the words spoken by the learner, picking out the fundamental frequency of the stable section, and forming a learner's initial curve corresponding to the first character of the multisyllabic words spoken by the learner, wherein the horizontal and vertical axes of the graph of the learner's initial curve are defined as a time axis and a frequency axis, respectively, the step of visualization is performed character by character to form the learner's monosyllabic reference polygonal line of the learner's monosyllabic reference polygonal line for each separate character; the step of defining analysis points including defining that the learner's initial curve includes a plurality of analysis points; the step of transforming polygonal lines including forming at least one section of line by connecting consequently connecting the four analysis points to one another, defining the section of line as an initial comparison syllable, so that the learner's initial curve presents a line which consists of the at least one section of straight line formed by the initial comparison syllables; the step of simplifying the polygonal lines including comparing or checking the durations of the initial comparison syllables, and the total duration of the learner's initial curve, if the duration of the first initial comparison syllable is found to be less than 30% of the total duration of the learner's initial curve, the first initial comparison syllable is considered as unrepresentative and then combined with a neighboring second initial comparison syllable to form a combined initial comparison syllable, then the combined initial comparison syllable is connected to another representative initial comparison to form a learner's monosyllabic reference polygonal line for bi-syllabic words; a step of repeating including: repeating the step of picking out fundamental frequency, the step of defining analysis point, the step of transforming polygonal lines, and the step of simplifying the polygonal lines, so as to convert the rest characters into the learner's monosyllabic reference polygonal line for bi-syllabic words of the learner's monosyllabic reference polygonal line, and connect the learner's monosyllabic reference polygonal line to form the learner's continuous bi-syllabic reference polygonal line which is to be displayed on the displaying unit; a step of assessment including picking up the monosyllabic reference polygonal line for each separate character, and the continuous multisyllabic reference polygonal line for multisyllabic words, and comparing them with the learner's monosyllabic reference and the learner's continuous bi-syllabic reference to form a plurality of comparison parameters, and the step of assessment include one or more comparison parameters. | 5. A speech assessment method for using the speech assessment device for the multisyllabic-word learning machine as claimed in claim 1 , comprising the following steps: a step of starting the assessment mode including using the central processing system to let the displaying unit displays the playing interface; a step of selecting words to be assessed including using the playing interface to select the standard continuous audio files for multisyllabic words, or the standard audio files for each separate character of the multisyllabic words from the standard speech database; a step of choosing to play or record including choosing a step of playing or a step of recording; a step of recording including using the speech receiving unit to receive and convert the words to be assessed spoken by the learner into the learner's continuous audio files for multisyllabic words, and the learner's audio files for each separate character of the multisyllabic words, wherein the learner's continuous audio files, and the learner's audio files are stored in the learner's speech database, and also transmitted to the audio visualization unit to create the learner's monosyllabic reference polygonal line for each separate character and the learner's continuous multisyllabic reference polygonal line for multisyllabic words, by conducting a step of visualization; the step of visualization including: a step of picking out fundamental frequency, a step of defining analysis point, a step of transforming polygonal lines, and a step of simplifying the polygonal lines, wherein the step of visualization is capable of simultaneously converting standard audio file into the reference polygonal line and converting the learner's audio file into the learner's polygonal line; the step of picking out fundamental frequency including selecting the most stable section of the frequency of the words spoken by the learner, picking out the fundamental frequency of the stable section, and forming a learner's initial curve corresponding to the first character of the multisyllabic words spoken by the learner, wherein the horizontal and vertical axes of the graph of the learner's initial curve are defined as a time axis and a frequency axis, respectively, the step of visualization is performed character by character to form the learner's monosyllabic reference polygonal line of the learner's monosyllabic reference polygonal line for each separate character; the step of defining analysis points including defining that the learner's initial curve includes a plurality of analysis points; the step of transforming polygonal lines including forming at least one section of line by connecting consequently connecting the four analysis points to one another, defining the section of line as an initial comparison syllable, so that the learner's initial curve presents a line which consists of the at least one section of straight line formed by the initial comparison syllables; the step of simplifying the polygonal lines including comparing or checking the durations of the initial comparison syllables, and the total duration of the learner's initial curve, if the duration of the first initial comparison syllable is found to be less than 30% of the total duration of the learner's initial curve, the first initial comparison syllable is considered as unrepresentative and then combined with a neighboring second initial comparison syllable to form a combined initial comparison syllable, then the combined initial comparison syllable is connected to another representative initial comparison to form a learner's monosyllabic reference polygonal line for bi-syllabic words; a step of repeating including: repeating the step of picking out fundamental frequency, the step of defining analysis point, the step of transforming polygonal lines, and the step of simplifying the polygonal lines, so as to convert the rest characters into the learner's monosyllabic reference polygonal line for bi-syllabic words of the learner's monosyllabic reference polygonal line, and connect the learner's monosyllabic reference polygonal line to form the learner's continuous bi-syllabic reference polygonal line which is to be displayed on the displaying unit; a step of assessment including picking up the monosyllabic reference polygonal line for each separate character, and the continuous multisyllabic reference polygonal line for multisyllabic words, and comparing them with the learner's monosyllabic reference and the learner's continuous bi-syllabic reference to form a plurality of comparison parameters, and the step of assessment include one or more comparison parameters. 8. The speech assessment method as claimed in claim 5 , wherein in the step of transforming polygonal lines, the polygonal lines include a first line, a second line, a third line, a fourth line and a fifth line; a first analysis point and a third analysis point of the first line are the same point, while the line a second analysis point and a fourth analysis point of the first line are the same point, a first analysis point and a fourth analysis point of the second line are the same point, while a second analysis point and a third analysis point of the second line are the same point, both the first and second lines are a straight line consisted of a single initial comparison; a second analysis point and a third analysis point of the third line are the same point, a second analysis point and a fourth analysis point of the fourth line are the same point, both the third and fourth lines are a line with one turning point and consisted of two initial comparison syllables; the fifth line is a zigzag line with two turning points and consisted of three initial comparison syllables, and four analysis points of the fifth line are different and independent from one another. | 0.869156 |
8,732,097 | 15 | 21 | 15. An apparatus, comprising: a processor; a memory; an event-prediction module to compute a first set of activity probabilities based on contextual information for a first set of historical activities and an activity-prediction model for a target activity, wherein an activity probability indicates a likelihood that the target activity has occurred; a threshold-generating module to generate a first set of probability thresholds; a threshold-scoring module to: compare a first set of probability thresholds with the first set of activity probabilities to determine a prediction success rate for each probability threshold; compute a utility score for each probability threshold based on the prediction success rates and a utility function, wherein the utility function has the form:
U ( P th )= U 1 (TP)+ U 2 (FP)+ U 3 (FN)+ U 4 (TN); wherein P th is the threshold value used to determine whether a historical activity matches the target activity, wherein U 1 (TP) and U 4 (TN) compute a benefit of making a recommendation based on predicting a true positive and a true negative, respectively, and wherein U 2 (FP) and U 3 (FN) compute a cost of making a recommendation based on predicting a false positive and a false negative, respectively; and select a first probability threshold whose utility score is greater than or equal to a baseline utility score and other utility scores of the first set of thresholds; and a threshold-assigning module to assign the first probability threshold to the activity-prediction model. | 15. An apparatus, comprising: a processor; a memory; an event-prediction module to compute a first set of activity probabilities based on contextual information for a first set of historical activities and an activity-prediction model for a target activity, wherein an activity probability indicates a likelihood that the target activity has occurred; a threshold-generating module to generate a first set of probability thresholds; a threshold-scoring module to: compare a first set of probability thresholds with the first set of activity probabilities to determine a prediction success rate for each probability threshold; compute a utility score for each probability threshold based on the prediction success rates and a utility function, wherein the utility function has the form:
U ( P th )= U 1 (TP)+ U 2 (FP)+ U 3 (FN)+ U 4 (TN); wherein P th is the threshold value used to determine whether a historical activity matches the target activity, wherein U 1 (TP) and U 4 (TN) compute a benefit of making a recommendation based on predicting a true positive and a true negative, respectively, and wherein U 2 (FP) and U 3 (FN) compute a cost of making a recommendation based on predicting a false positive and a false negative, respectively; and select a first probability threshold whose utility score is greater than or equal to a baseline utility score and other utility scores of the first set of thresholds; and a threshold-assigning module to assign the first probability threshold to the activity-prediction model. 21. The apparatus of claim 15 , wherein the contextual information includes one or more of: a geographic location; a motion trajectory; a date range; a logical name associated with a geographic location; a logical name associated with an activity description; a list of participants of the historical activity; and a set of keywords associated with the historical activity. | 0.79816 |
8,269,773 | 11 | 12 | 11. The method of claim 1 , further comprising: determining a first format for plotting data based upon associations between variables and graph components, wherein the first format is used for default plotting. | 11. The method of claim 1 , further comprising: determining a first format for plotting data based upon associations between variables and graph components, wherein the first format is used for default plotting. 12. The method of claim 11 , further comprising: determining an additional plurality of acceptable formats based upon associations between variables and graph components, wherein additional acceptable formats are available for selection. | 0.92984 |
9,668,024 | 21 | 24 | 21. An electronic device comprising: a first display; one or more processors; and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for: receiving speech input from a user; determining a user intent of the speech input based on content displayed on the first display; determining media content based on the user intent; and playing the media content on a second device associated with a second display. | 21. An electronic device comprising: a first display; one or more processors; and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for: receiving speech input from a user; determining a user intent of the speech input based on content displayed on the first display; determining media content based on the user intent; and playing the media content on a second device associated with a second display. 24. The device of claim 21 , wherein the one or more programs further include instructions for: determining whether the determined media content should be displayed on the first display or the second display based on a media format, a user preference, or a default setting; wherein the media content is displayed on the second display in response to a determination that the determined media content should be displayed on the second display; and wherein the media content is displayed on the first display in response to a determination that the determined media content should be displayed on the first display. | 0.525542 |
9,449,598 | 1 | 3 | 1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain audio data regarding an utterance of a user; initiate speech recognition on the audio data using a grammar of a composite language model, the composite language model comprising the grammar and an n-gram model, wherein the composite language model comprises scores that bias speech recognition performed using the composite language model to use the grammar over the n-gram model, and wherein a first state of the grammar links to a first state of the n-gram model and to a second state of the grammar; generate at least a first portion of automatic speech recognition results using a portion of the grammar up to at least the first state of the grammar; determine a first score using (1) acoustic information derived from the audio data and (2) a first weight associated with a link from the first state of the grammar to the second state of the grammar; determine a second score using (1) acoustic information derived from the audio data and (2) a second weight associated with a link from the first state of the grammar to the first state of the n-gram model; if the first score is greater than the second score, continue speech recognition on the audio data using the grammar by generating a second portion of automatic speech recognition results using the second state of the grammar, wherein the second portion of automatic speech recognition results is based at least in part on the first score; if the second score is greater than the first score, continue speech recognition on the audio data using n-gram model by generating the second portion of automatic speech recognition results using the first state of the n-gram model, wherein the second portion of automatic speech recognition results is based at least in part on the second score; and generate automatic speech recognition results based at least on the first portion of automatic speech recognition results and the second portion of automatic speech recognition results. | 1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain audio data regarding an utterance of a user; initiate speech recognition on the audio data using a grammar of a composite language model, the composite language model comprising the grammar and an n-gram model, wherein the composite language model comprises scores that bias speech recognition performed using the composite language model to use the grammar over the n-gram model, and wherein a first state of the grammar links to a first state of the n-gram model and to a second state of the grammar; generate at least a first portion of automatic speech recognition results using a portion of the grammar up to at least the first state of the grammar; determine a first score using (1) acoustic information derived from the audio data and (2) a first weight associated with a link from the first state of the grammar to the second state of the grammar; determine a second score using (1) acoustic information derived from the audio data and (2) a second weight associated with a link from the first state of the grammar to the first state of the n-gram model; if the first score is greater than the second score, continue speech recognition on the audio data using the grammar by generating a second portion of automatic speech recognition results using the second state of the grammar, wherein the second portion of automatic speech recognition results is based at least in part on the first score; if the second score is greater than the first score, continue speech recognition on the audio data using n-gram model by generating the second portion of automatic speech recognition results using the first state of the n-gram model, wherein the second portion of automatic speech recognition results is based at least in part on the second score; and generate automatic speech recognition results based at least on the first portion of automatic speech recognition results and the second portion of automatic speech recognition results. 3. The system of claim 1 wherein the one or processors are further configured to: determine to transition from a second state of the n-gram model to a third state of the grammar based at least on a word associated with the third state of the grammar; and further continue speech recognition on the audio data using the third state of the grammar. | 0.606818 |
8,010,564 | 2 | 4 | 2. The non-transitory computer-readable recording medium according to claim 1 , further comprising evaluating a heading candidate when among the determined sets are a first set including a data item and the headings identifying the data item and a second set where among the headings, a single heading is positioned differently from the headings of the first set, wherein the evaluating includes selecting, as a proper determined set, the first set or the second set based on a position of the single heading and a position of the data item, and the outputting includes outputting the proper determined set. | 2. The non-transitory computer-readable recording medium according to claim 1 , further comprising evaluating a heading candidate when among the determined sets are a first set including a data item and the headings identifying the data item and a second set where among the headings, a single heading is positioned differently from the headings of the first set, wherein the evaluating includes selecting, as a proper determined set, the first set or the second set based on a position of the single heading and a position of the data item, and the outputting includes outputting the proper determined set. 4. The non-transitory computer-readable recording medium according to claim 2 , wherein the evaluating includes selecting the proper determined set based on an area of a region encompassing the data item and the single heading. | 0.906967 |
9,460,068 | 1 | 18 | 1. A computer system for a narrational media organizer to transform digital media into a personal, memorable story with minimal user input, the system comprising: a) one or more processors; b) a non-transitory machine readable medium coupled to the one or more processors; c) a set of computer instructions stored in the machine readable medium and operable on the one or more processors for creating a narrational media organizer (NMO) environment causing performance of operations comprising: displaying digital media files of a first set as graphical representations of each of the digital media files in an arrangement along a timeline in a work area; receiving from a first user, a first command to shift the arrangement, including a user selection of an annotation location between two of the displayed graphical representations of the digital media files and a textual annotation; in response to the first command, placing a graphical instance of the textual annotation at the selected annotation location and shifting the arrangement of graphical representations to make room for the textual annotation; obtaining one or more digital media files of a second set of a second user, each of the one or more digital media files of the second set associated with a timestamp, wherein a first digital media file of the one or more digital media files of the second set was non-destructively excluded from the NMO environment; and merging the digital media files of the second set with the first set of digital media files, wherein: a first graphical representation of at least one of the digital media files of the second set is automatically inserted between two of the displayed graphical representations of the digital media files of the first set into the arrangement along the timeline based on the timestamp associated with the at least one of the digital media files of the second set, and a second graphical representation of the first digital media file of the second set is automatically inserted along the timeline and the second graphical representation includes a minimized version of the first digital media file; d) a user interface operably connected to the one or more processors, the user interface effective to transmit one or more commands including the first command to the one or more processors; and e) a storage operably connected to the one or more processors, the storage effective for storing a data structure, wherein the data structure includes the digital media files of the first set, the digital media files of the second set, and the textual annotation. | 1. A computer system for a narrational media organizer to transform digital media into a personal, memorable story with minimal user input, the system comprising: a) one or more processors; b) a non-transitory machine readable medium coupled to the one or more processors; c) a set of computer instructions stored in the machine readable medium and operable on the one or more processors for creating a narrational media organizer (NMO) environment causing performance of operations comprising: displaying digital media files of a first set as graphical representations of each of the digital media files in an arrangement along a timeline in a work area; receiving from a first user, a first command to shift the arrangement, including a user selection of an annotation location between two of the displayed graphical representations of the digital media files and a textual annotation; in response to the first command, placing a graphical instance of the textual annotation at the selected annotation location and shifting the arrangement of graphical representations to make room for the textual annotation; obtaining one or more digital media files of a second set of a second user, each of the one or more digital media files of the second set associated with a timestamp, wherein a first digital media file of the one or more digital media files of the second set was non-destructively excluded from the NMO environment; and merging the digital media files of the second set with the first set of digital media files, wherein: a first graphical representation of at least one of the digital media files of the second set is automatically inserted between two of the displayed graphical representations of the digital media files of the first set into the arrangement along the timeline based on the timestamp associated with the at least one of the digital media files of the second set, and a second graphical representation of the first digital media file of the second set is automatically inserted along the timeline and the second graphical representation includes a minimized version of the first digital media file; d) a user interface operably connected to the one or more processors, the user interface effective to transmit one or more commands including the first command to the one or more processors; and e) a storage operably connected to the one or more processors, the storage effective for storing a data structure, wherein the data structure includes the digital media files of the first set, the digital media files of the second set, and the textual annotation. 18. The system of claim 1 , wherein the operations further comprise receiving from the user, a second command to position a cursor at a second annotation location between a second two of the displayed graphical representations, wherein the cursor position can be controlled by a return key to create a paragraph, and thereby cause the digital media files subsequent to the cursor position to be moved down and form a new paragraph. | 0.76778 |
9,356,940 | 3 | 4 | 3. A method as recited in claim 1 , further comprising the operation of establishing a token, wherein the token is a private session key. | 3. A method as recited in claim 1 , further comprising the operation of establishing a token, wherein the token is a private session key. 4. A method as recited in claim 3 , wherein the token is provided to other servers within a predefined proximity of a location hub server. | 0.955656 |
7,698,647 | 1 | 5 | 1. A portable dataport for document retrieving, inter-relating, annotating and management comprising: an electronic document storage device associated with said dataport, for storing a population of coded electronic documents; and, a view manager, having three dimensional grid for project document loading and retrieval, wherein a user selects a document in the grid for loading, said three dimensional grid corresponding to electronic document fields for navigation to related documents, wherein said view manager is electronically linked to said electronic document storage device to retrieve, inter-relate, annotate and manage said documents, wherein as an individual project document is loaded for viewing, said document is loaded within a main scrollable image viewer and related documents are loaded in the background, in their own scrollable image viewers to navigate to related project documents and project documents are accessible via cardinality keys, and wherein said view manager, in connection with document loading and retrieval; retrieves all coded documents associated with a project from said electronic document storage device; creates a data structure that contains coordinate data and navigations keys for each coded project document; creates scrollable image viewers for an identified project document and all related projects documents based upon the coordinate data for said project documents: creates a hash map for containing said scrollable image viewers; and creates a hash map for containing cardinality keys corresponding to the coordinate data for said identified and related project documents. | 1. A portable dataport for document retrieving, inter-relating, annotating and management comprising: an electronic document storage device associated with said dataport, for storing a population of coded electronic documents; and, a view manager, having three dimensional grid for project document loading and retrieval, wherein a user selects a document in the grid for loading, said three dimensional grid corresponding to electronic document fields for navigation to related documents, wherein said view manager is electronically linked to said electronic document storage device to retrieve, inter-relate, annotate and manage said documents, wherein as an individual project document is loaded for viewing, said document is loaded within a main scrollable image viewer and related documents are loaded in the background, in their own scrollable image viewers to navigate to related project documents and project documents are accessible via cardinality keys, and wherein said view manager, in connection with document loading and retrieval; retrieves all coded documents associated with a project from said electronic document storage device; creates a data structure that contains coordinate data and navigations keys for each coded project document; creates scrollable image viewers for an identified project document and all related projects documents based upon the coordinate data for said project documents: creates a hash map for containing said scrollable image viewers; and creates a hash map for containing cardinality keys corresponding to the coordinate data for said identified and related project documents. 5. The portable dataport of claim 1 , wherein said portable dataport retrieves said documents through a design grid view or a design tables view. | 0.94754 |
8,452,795 | 8 | 9 | 8. A system, comprising: one or more computers; a repository comprising one or more storage devices, the repository storing specialization data, the specialization data associating each of a plurality of text queries with one or more query specializations identified from the text query, wherein each query specialization is the text of one of the text queries modified so that an n-gram in the text of the text query is replaced by entity text from a class-instance pair having class text matching the n-gram, and wherein the class-instance pairs are generated by: obtaining a plurality of class instance pairs derived from a plurality of documents by applying one or more extraction patterns to the plurality of documents, each class-instance pair comprising class text naming an entity class and entity text naming a particular instance of the entity class; and calculating a weight for each class-instance pair according to a frequency score and a diversity score for the class-instance pair, wherein the frequency score of the class-instance pair is based on a number of times the class-instance pair was derived from the plurality of documents, and wherein the diversity score of the class-instance pair is based on a number of distinct extraction patterns used to extract the class-instance pair; and wherein each query specialization is generated from a respective text query by: extracting a plurality of n-grams from the text query and extracting a respective context for each extracted n-gram from the text query, the respective context for an extracted n-gram including a prefix context and a suffix context; comparing the extracted n-grams to the class text of the class-instance pairs; identifying an n-gram that matches class text of a first class-instance pair; and generating the query specialization from the entity text of the first class-instance pair and the respective context for the identified n-gram; and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a partial query entered by a user; obtaining one or more candidate queries that are completions of the partial query; identifying, in the specialization data, one or more query specializations for one or more of the obtained candidate queries; and presenting query suggestions to the user, the query suggestions that include one or more of the obtained candidate queries and one or more of the identified query specializations. | 8. A system, comprising: one or more computers; a repository comprising one or more storage devices, the repository storing specialization data, the specialization data associating each of a plurality of text queries with one or more query specializations identified from the text query, wherein each query specialization is the text of one of the text queries modified so that an n-gram in the text of the text query is replaced by entity text from a class-instance pair having class text matching the n-gram, and wherein the class-instance pairs are generated by: obtaining a plurality of class instance pairs derived from a plurality of documents by applying one or more extraction patterns to the plurality of documents, each class-instance pair comprising class text naming an entity class and entity text naming a particular instance of the entity class; and calculating a weight for each class-instance pair according to a frequency score and a diversity score for the class-instance pair, wherein the frequency score of the class-instance pair is based on a number of times the class-instance pair was derived from the plurality of documents, and wherein the diversity score of the class-instance pair is based on a number of distinct extraction patterns used to extract the class-instance pair; and wherein each query specialization is generated from a respective text query by: extracting a plurality of n-grams from the text query and extracting a respective context for each extracted n-gram from the text query, the respective context for an extracted n-gram including a prefix context and a suffix context; comparing the extracted n-grams to the class text of the class-instance pairs; identifying an n-gram that matches class text of a first class-instance pair; and generating the query specialization from the entity text of the first class-instance pair and the respective context for the identified n-gram; and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a partial query entered by a user; obtaining one or more candidate queries that are completions of the partial query; identifying, in the specialization data, one or more query specializations for one or more of the obtained candidate queries; and presenting query suggestions to the user, the query suggestions that include one or more of the obtained candidate queries and one or more of the identified query specializations. 9. The system of claim 8 , wherein the instructions further cause the one or more computers to perform operations comprising determining an order for the query suggestions and presenting the query suggestions according to the order. | 0.854637 |
7,565,647 | 23 | 25 | 23. A computer software product, comprising a computer-readable storage medium in which computer program instructions are stored, which instructions, when read by a computer, cause the computer to perform a method comprising the steps of: parsing a specification of a computing application for a mobile information device by using a descriptor element factory, said specification written in an extended markup language and comprising tags corresponding to functions of said application, to create a descriptor object model comprising objects that implement said functions, wherein the parsing comprises reading different ones of said tags with different readers registered in a factory to be instantiated; and processing said objects to generate executable code for said application, said processing step further comprising: (i) creating a generation object model according to said specification and (ii) dynamically generating source code based on said descriptor object model and said generation object model by using a generation object factory that produces generation objects, said generation objects being operable to generate class files of said source code; preverifying classes of said class files; packaging said executable code into an archive file, said packaging step comprising: preparing an application descriptor file; and including a portion of said application descriptor file in said archive file, said archive file being adapted to be downloaded to and run by the mobile information device. | 23. A computer software product, comprising a computer-readable storage medium in which computer program instructions are stored, which instructions, when read by a computer, cause the computer to perform a method comprising the steps of: parsing a specification of a computing application for a mobile information device by using a descriptor element factory, said specification written in an extended markup language and comprising tags corresponding to functions of said application, to create a descriptor object model comprising objects that implement said functions, wherein the parsing comprises reading different ones of said tags with different readers registered in a factory to be instantiated; and processing said objects to generate executable code for said application, said processing step further comprising: (i) creating a generation object model according to said specification and (ii) dynamically generating source code based on said descriptor object model and said generation object model by using a generation object factory that produces generation objects, said generation objects being operable to generate class files of said source code; preverifying classes of said class files; packaging said executable code into an archive file, said packaging step comprising: preparing an application descriptor file; and including a portion of said application descriptor file in said archive file, said archive file being adapted to be downloaded to and run by the mobile information device. 25. The computer software product according to claim 23 , wherein said tags and said objects belong to different tag types and different object types respectively, and wherein said step of parsing said tags comprises providing a first set of respective readers for said different tag types to populate said objects corresponding to said different object types, and wherein said step of processing said objects comprises providing a second set of respective generators for said different object types to generate elements of said executable code corresponding to said different object types. | 0.585674 |
8,819,812 | 10 | 11 | 10. The computer-implemented method of claim 7 , further comprising: enabling the user to assign a specific gesture as the input for performing a particular function by the application. | 10. The computer-implemented method of claim 7 , further comprising: enabling the user to assign a specific gesture as the input for performing a particular function by the application. 11. The computer-implemented method of claim 10 , wherein assigning the specific gesture includes training the computing device to recognize a new gesture. | 0.954142 |
8,140,504 | 3 | 4 | 3. The method of claim 2 , further comprising: presenting the answer to a user. | 3. The method of claim 2 , further comprising: presenting the answer to a user. 4. The method of claim 3 , wherein presenting the answer to the user includes: formatting the answer in accordance with the selected report template. | 0.962731 |
7,856,472 | 28 | 29 | 28. The method of claim 2 , wherein the second messages are associated with a second online forum that is different from the first online forum online forum relates to a first subject matter, and the second online forum relates to a second subject matter. | 28. The method of claim 2 , wherein the second messages are associated with a second online forum that is different from the first online forum online forum relates to a first subject matter, and the second online forum relates to a second subject matter. 29. The method of claim 28 , wherein the displaying the plurality of message summaries is carried out utilizing the website, and the first message and the second message are capable of being accessed utilizing the website. | 0.95018 |
8,934,278 | 1 | 3 | 1. A method within a hybrid ternary content addressable memory (TCAM), the method comprising: comparing a first portion of a search word to a first portion of a stored word in a first TCAM stage; and comparing a second portion of the search word to a second portion of the stored word in a second TCAM stage when the first portion of the search word matches the first portion of the stored word, the first portion of the search word being different than the second portion of the search word, and the first TCAM stage being configured as a first type TCAM and the second TCAM stage being configured as a second type TCAM, the first type TCAM being different than the second type TCAM. | 1. A method within a hybrid ternary content addressable memory (TCAM), the method comprising: comparing a first portion of a search word to a first portion of a stored word in a first TCAM stage; and comparing a second portion of the search word to a second portion of the stored word in a second TCAM stage when the first portion of the search word matches the first portion of the stored word, the first portion of the search word being different than the second portion of the search word, and the first TCAM stage being configured as a first type TCAM and the second TCAM stage being configured as a second type TCAM, the first type TCAM being different than the second type TCAM. 3. The method of claim 1 further comprising decoding mask bits and key bits at the second TCAM stage during a read operation, the decoding comprising translating the mask bits and the key bits from values used for the second TCAM stage to values used for the first TCAM stage. | 0.931103 |
7,870,087 | 59 | 63 | 59. A method of processing queries of databases, the method comprising: receiving a problem; parsing the problem into subproblems of suitable size to be processed by an analog processor; for each of the subproblems, setting a number of parameters of the analog processor to embed the subproblem into the analog processor; determining a subanswer to the subproblem from a final state of the analog processor. | 59. A method of processing queries of databases, the method comprising: receiving a problem; parsing the problem into subproblems of suitable size to be processed by an analog processor; for each of the subproblems, setting a number of parameters of the analog processor to embed the subproblem into the analog processor; determining a subanswer to the subproblem from a final state of the analog processor. 63. The method of claim 59 wherein parsing the problem into subproblems of suitable size to be processed by the analog processor includes optimizing the subproblems for processing on the analog processor. | 0.870064 |
8,949,256 | 16 | 17 | 16. The method of claim 15 , wherein the first portion of the web page comprises a copyright notice. | 16. The method of claim 15 , wherein the first portion of the web page comprises a copyright notice. 17. The method of claim 16 , wherein the second portion of the web page comprises a title block. | 0.954887 |
7,917,288 | 1 | 4 | 1. A computer-implemented navigation system, comprising: a segmentation component for grouping instructions into multiple segments, the instructions providing a route for navigating geographically from a starting location to an ending location; a decision component for processing one or more factors to determine suitability for abbreviating the instructions of the one or more of the segments; and an abbreviation component for abbreviating the instructions of the one or more segments based on the one or more factors. | 1. A computer-implemented navigation system, comprising: a segmentation component for grouping instructions into multiple segments, the instructions providing a route for navigating geographically from a starting location to an ending location; a decision component for processing one or more factors to determine suitability for abbreviating the instructions of the one or more of the segments; and an abbreviation component for abbreviating the instructions of the one or more segments based on the one or more factors. 4. The system of claim 1 , wherein the multiple segments include a start segment, end segment, and one or more middle segments. | 0.677665 |
9,396,167 | 1 | 2 | 1. A method for presenting content items comprising: receiving a plurality of content items; determining size constraints of each of the plurality of content items; selecting a plurality of candidate templates each having a number of slots, each slot defining a portion of a page within which a content item is displayed; for each candidate template of the plurality of candidate templates, determining a score for the candidate template by: determining a score for each slot of the candidate template based on a difference between a size of the slot and the size constraints of one or more of the plurality of content items, where a maximum score is assigned to the slot if the size difference between the size of the slot and size constraints of the content item is within a threshold difference, and determining the score for the candidate template based on aggregating the scores of the slots of the candidate template; selecting a template from the plurality of candidate templates based on the determined scores; and generating the page for presentation to a user, the page including one or more of the plurality of content items positioned based on slots in the selected template. | 1. A method for presenting content items comprising: receiving a plurality of content items; determining size constraints of each of the plurality of content items; selecting a plurality of candidate templates each having a number of slots, each slot defining a portion of a page within which a content item is displayed; for each candidate template of the plurality of candidate templates, determining a score for the candidate template by: determining a score for each slot of the candidate template based on a difference between a size of the slot and the size constraints of one or more of the plurality of content items, where a maximum score is assigned to the slot if the size difference between the size of the slot and size constraints of the content item is within a threshold difference, and determining the score for the candidate template based on aggregating the scores of the slots of the candidate template; selecting a template from the plurality of candidate templates based on the determined scores; and generating the page for presentation to a user, the page including one or more of the plurality of content items positioned based on slots in the selected template. 2. The method of claim 1 , wherein one or more of the plurality of content items comprise user-generated posts on social networks. | 0.85426 |
8,417,854 | 1 | 8 | 1. A computer-implemented method comprising: receiving, at an integration layer, a connection request from an auto-id component to be connected to an auto-id node, the connection request specifying one or more communication parameters of the auto-id component; instantiating a generic adaptor class for effecting communication between the auto-id node and the auto-id component, the generic adaptor implementing functionality common to multiple different, specific adaptor classes stored in a class repository of the integration layer; instantiating a generic communicator class for effecting a data transport aspect of the communication between the auto-id node and the auto-id component, the generic communicator class implementing functionality common to multiple different, specific communicator classes stored in the class repository, and the generic communicator class being a component of the generic adaptor class; instantiating a generic converter class for effecting a data conversion aspect of the communication between the auto-id node and the auto-id component, the generic converter class implementing functionality common to multiple different, specific converter classes stored in the class repository, and the generic converter class being a component of the generic adaptor class; identifying, from among the multiple different adaptor, communicator, and converter classes stored in the class repository, a specific adaptor, a specific communicator class, and a specific converter class, respectively, based on the specified communication parameters; instantiating the identified specific adaptor, communicator, and converter classes; adding the identified specific adaptor, communicator, and converter classes to an instance list and effecting the communication between the auto-id component and the auto-id node using the instantiated generic adaptor, communicator, and converter classes and the instantiated specific adaptor, communicator, and converter classes. | 1. A computer-implemented method comprising: receiving, at an integration layer, a connection request from an auto-id component to be connected to an auto-id node, the connection request specifying one or more communication parameters of the auto-id component; instantiating a generic adaptor class for effecting communication between the auto-id node and the auto-id component, the generic adaptor implementing functionality common to multiple different, specific adaptor classes stored in a class repository of the integration layer; instantiating a generic communicator class for effecting a data transport aspect of the communication between the auto-id node and the auto-id component, the generic communicator class implementing functionality common to multiple different, specific communicator classes stored in the class repository, and the generic communicator class being a component of the generic adaptor class; instantiating a generic converter class for effecting a data conversion aspect of the communication between the auto-id node and the auto-id component, the generic converter class implementing functionality common to multiple different, specific converter classes stored in the class repository, and the generic converter class being a component of the generic adaptor class; identifying, from among the multiple different adaptor, communicator, and converter classes stored in the class repository, a specific adaptor, a specific communicator class, and a specific converter class, respectively, based on the specified communication parameters; instantiating the identified specific adaptor, communicator, and converter classes; adding the identified specific adaptor, communicator, and converter classes to an instance list and effecting the communication between the auto-id component and the auto-id node using the instantiated generic adaptor, communicator, and converter classes and the instantiated specific adaptor, communicator, and converter classes. 8. The method of claim 1 , wherein the specific adaptor class further comprises an n on-line communication mode or an off-line communication mode adaptor class. | 0.847909 |
7,617,193 | 1 | 7 | 1. A search system for providing user controlled relevance ranking of search results received from an internet web based search engine, and operating in conjunction with a conventional browser, comprising: means for accepting keywords and at least one of different specific User Inputs from the search user to request search results; means for determining the size of the set of requested search results to be provided by the search engine to the search user, or for determining the size of the set of requested search results to be provided by the search engine to the search user by interactive action between a managing program and the web search engine, when the search results exceed a preset number; means for acquiring the size of the set of requested search results and for formatting and managing multiple parallel near simultaneous search requests of the search engine to increase the selected responses when they exceed said preset number; means for parsing the selected responses of the search results received from the search engine by removing duplicate and extraneous information to display parsed information; means for applying a scoring algorithm to the parsed search results received from the search engine to rank the search results, which incorporates search setting information supplied from the search user; means for dynamically or interactively focusing the search results, and causing the search results to be re-ranked, without going back to a search engine; and means for formatting the sorted search results into a display format for display on the user's computer operating in conjunction with a conventional browser. | 1. A search system for providing user controlled relevance ranking of search results received from an internet web based search engine, and operating in conjunction with a conventional browser, comprising: means for accepting keywords and at least one of different specific User Inputs from the search user to request search results; means for determining the size of the set of requested search results to be provided by the search engine to the search user, or for determining the size of the set of requested search results to be provided by the search engine to the search user by interactive action between a managing program and the web search engine, when the search results exceed a preset number; means for acquiring the size of the set of requested search results and for formatting and managing multiple parallel near simultaneous search requests of the search engine to increase the selected responses when they exceed said preset number; means for parsing the selected responses of the search results received from the search engine by removing duplicate and extraneous information to display parsed information; means for applying a scoring algorithm to the parsed search results received from the search engine to rank the search results, which incorporates search setting information supplied from the search user; means for dynamically or interactively focusing the search results, and causing the search results to be re-ranked, without going back to a search engine; and means for formatting the sorted search results into a display format for display on the user's computer operating in conjunction with a conventional browser. 7. A search system according to claim 1 , wherein the search system includes means for providing user-controllable relevance ranking of search results received from two or more internet web based search engines. | 0.754079 |
9,495,963 | 1 | 8 | 1. A method, comprising: analyzing, by at least one automatic speech recognition component, at least one voice interaction by at least one agent following at least one script in at least one of a plurality of panels; and determining whether the at least one agent has adequately followed the at least one script based on a score using confidence level thresholds of the least one automatic speech recognition component such that confidence level thresholds are assigned to each of the plurality of panels. | 1. A method, comprising: analyzing, by at least one automatic speech recognition component, at least one voice interaction by at least one agent following at least one script in at least one of a plurality of panels; and determining whether the at least one agent has adequately followed the at least one script based on a score using confidence level thresholds of the least one automatic speech recognition component such that confidence level thresholds are assigned to each of the plurality of panels. 8. The method of claim 1 , wherein the at least one voice interaction includes at least one voice interaction governed by at least one script that includes text corresponding to at least one offer of at least one of goods and services. | 0.70403 |
8,386,465 | 12 | 14 | 12. A system for decreasing the perceived end user latency while interacting with a media database comprising: the media database storing metadata associated with media; a media manager in communication with at least one media player and operable to access the media database via at least one of a plurality of connections between the at least one media player and the media manager; the at least one media player each having a user interface operable to display a first set of query results and receive user input based on the displayed first set of query results, wherein each query result in the displayed first set of query results representing a user selectable object that navigates to another set of query results displayable by the user interface; and a predictive module operable to generate at least one query based on the user input and to derive at least one predictive background query of the database displayed on the displayed first set of query results and prior to a user invoking any action within the user interface, the predictive module compares the at least one generated query to the at least one derived background query such that if the generated query corresponds to the at least one background query the user interface displays the another set of query results acquired from the at least one background query that correspond to the at least one generated query. | 12. A system for decreasing the perceived end user latency while interacting with a media database comprising: the media database storing metadata associated with media; a media manager in communication with at least one media player and operable to access the media database via at least one of a plurality of connections between the at least one media player and the media manager; the at least one media player each having a user interface operable to display a first set of query results and receive user input based on the displayed first set of query results, wherein each query result in the displayed first set of query results representing a user selectable object that navigates to another set of query results displayable by the user interface; and a predictive module operable to generate at least one query based on the user input and to derive at least one predictive background query of the database displayed on the displayed first set of query results and prior to a user invoking any action within the user interface, the predictive module compares the at least one generated query to the at least one derived background query such that if the generated query corresponds to the at least one background query the user interface displays the another set of query results acquired from the at least one background query that correspond to the at least one generated query. 14. The system of claim 12 , wherein the derived background queries comprise all queries that may be made by selecting the user selectable object displayed on the user interface. | 0.954429 |
8,229,933 | 1 | 13 | 1. A computer-implemented method for matching of contracts using a fixed-length complex predicate representation comprising: storing, in memory, an impression opportunity profile in the form of a Boolean expression; converting the impression opportunity profile into a list comprising at least one impression conjunct; retrieving, at a server, a set of candidate contracts that match the at least one impression conjunct; constructing, within a computer memory, a contract tree representation of at least one contract from among the set of candidate contracts, the contract tree comprising alternating AND/OR levels of a plurality of nodes, the plurality of nodes comprising at least one contract tree leaf node predicate, the contract tree leaf node predicates having a label representing a projection onto a discrete set of ordered symbols; and marking, for producing at least one marked contract tree leaf node predicate, the at least one contract tree leaf node predicate based on comparing the at least one contract tree leaf node predicate to the at least one impression conjunct. | 1. A computer-implemented method for matching of contracts using a fixed-length complex predicate representation comprising: storing, in memory, an impression opportunity profile in the form of a Boolean expression; converting the impression opportunity profile into a list comprising at least one impression conjunct; retrieving, at a server, a set of candidate contracts that match the at least one impression conjunct; constructing, within a computer memory, a contract tree representation of at least one contract from among the set of candidate contracts, the contract tree comprising alternating AND/OR levels of a plurality of nodes, the plurality of nodes comprising at least one contract tree leaf node predicate, the contract tree leaf node predicates having a label representing a projection onto a discrete set of ordered symbols; and marking, for producing at least one marked contract tree leaf node predicate, the at least one contract tree leaf node predicate based on comparing the at least one contract tree leaf node predicate to the at least one impression conjunct. 13. The method of claim 1 , wherein the retrieving operation prunes contracts containing any NOT-IN predicates violated by the impression opportunity profile. | 0.610837 |
9,626,959 | 9 | 12 | 9. A system for processing natural language utterances, comprising: one or more physical processors programmed to execute one or more computer program instructions which, when executed, cause the one or more physical processors to: receive a natural language command associated with a user; generate a first interpretation of the natural language command based on one or more recognized words of the natural language command; perform a first action specified by the natural language command based on the first interpretation; access, by the computer system, a personalized cognitive model to proactively select a second interpretation of the natural language command responsive to an indication from the user that the first interpretation is not correct; and proactively perform a second action specified by the natural language command based on the second interpretation. | 9. A system for processing natural language utterances, comprising: one or more physical processors programmed to execute one or more computer program instructions which, when executed, cause the one or more physical processors to: receive a natural language command associated with a user; generate a first interpretation of the natural language command based on one or more recognized words of the natural language command; perform a first action specified by the natural language command based on the first interpretation; access, by the computer system, a personalized cognitive model to proactively select a second interpretation of the natural language command responsive to an indication from the user that the first interpretation is not correct; and proactively perform a second action specified by the natural language command based on the second interpretation. 12. The system of claim 9 , wherein the one or more physical processors are further caused to: receive a user input associated with the user after the receipt of the natural language command, wherein the indication from the user that the first interpretation is not correct is based on a determination that the receipt of the user input is proximate in time to the receipt of the natural language command. | 0.798307 |
8,949,231 | 18 | 31 | 18. A user-interface system for selecting and presenting a collection of content items in which the presentation is ordered at least in part based on analyzing activity associated with content items having descriptive terms that describe the content items and promoting the presentation ranking of content items associated with descriptive terms that have an increased level of current activity, the system comprising: at least one non-transitory computer-readable media in at least one of a user device or a remote server system in communication with the user device, the computer-readable media comprising instructions that when executed cause a computer system to: provide access to a set of content items, each content item having at least one associated descriptive term to describe the content item; receive input entered by users for identifying desired content items; present corresponding subsets of content items to the users in response to the input entered by the users, receive actions from the users selecting content items from the corresponding subsets; analyze the selection actions received from the users to detect an increased level of current activity relative to an normal level of activity associated with the content items selected by the users; select and order a collection of content items from the provided set of content items based on promoting the ranking of content items associated with descriptive terms that are associated with content items that have the increased level of current activity relative to the normal activity level; and present the collection of content items to at least one user. | 18. A user-interface system for selecting and presenting a collection of content items in which the presentation is ordered at least in part based on analyzing activity associated with content items having descriptive terms that describe the content items and promoting the presentation ranking of content items associated with descriptive terms that have an increased level of current activity, the system comprising: at least one non-transitory computer-readable media in at least one of a user device or a remote server system in communication with the user device, the computer-readable media comprising instructions that when executed cause a computer system to: provide access to a set of content items, each content item having at least one associated descriptive term to describe the content item; receive input entered by users for identifying desired content items; present corresponding subsets of content items to the users in response to the input entered by the users, receive actions from the users selecting content items from the corresponding subsets; analyze the selection actions received from the users to detect an increased level of current activity relative to an normal level of activity associated with the content items selected by the users; select and order a collection of content items from the provided set of content items based on promoting the ranking of content items associated with descriptive terms that are associated with content items that have the increased level of current activity relative to the normal activity level; and present the collection of content items to at least one user. 31. The system of claim 18 , wherein the input comprises at least one prefix of a word for describing the desired content items. | 0.887719 |
7,587,667 | 25 | 31 | 25. A computer-readable volatile or non-volatile medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: after an XML processor, which is configured to send validated XML data to an application, starts performing a validation operation on an XML-based input stream, and before said XML processor completes performing said validation operation on said XML-based input stream, performing the steps of: after starting to validate a particular XML element in said XML-based input stream, and before completion of validating said particular XML element in said XML-based input stream, performing the computer-implemented step of said XML processor receiving one or more requests for particular information relating to said validation operation, wherein said one or more requests include at least one of: (a) a request for whether said particular XML element is defined in corresponding information that dictates the structure of said XML data in said XML-based input stream; (b) a request for the name of said particular XML element; (c) a request for the data type of said particular XML element; (d) a request for whether said particular XML element conforms to the corresponding information that dictates the structure of said XML data in said XML-based input stream; (e) a request for the current validation mode of said validation operation; (f) a request for the current state of said validation operation; or (g) a request for one or more annotations that are associated with said particular XML element; said XML processor generating one or more messages that include said particular information; and said XML processor responding to said one or more requests for said particular information by providing said one or more messages. | 25. A computer-readable volatile or non-volatile medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: after an XML processor, which is configured to send validated XML data to an application, starts performing a validation operation on an XML-based input stream, and before said XML processor completes performing said validation operation on said XML-based input stream, performing the steps of: after starting to validate a particular XML element in said XML-based input stream, and before completion of validating said particular XML element in said XML-based input stream, performing the computer-implemented step of said XML processor receiving one or more requests for particular information relating to said validation operation, wherein said one or more requests include at least one of: (a) a request for whether said particular XML element is defined in corresponding information that dictates the structure of said XML data in said XML-based input stream; (b) a request for the name of said particular XML element; (c) a request for the data type of said particular XML element; (d) a request for whether said particular XML element conforms to the corresponding information that dictates the structure of said XML data in said XML-based input stream; (e) a request for the current validation mode of said validation operation; (f) a request for the current state of said validation operation; or (g) a request for one or more annotations that are associated with said particular XML element; said XML processor generating one or more messages that include said particular information; and said XML processor responding to said one or more requests for said particular information by providing said one or more messages. 31. The computer-readable volatile or non-volatile medium of claim 25 , wherein said particular information, which is included in said one or more messages, comprises one or more of: first data indicating whether said particular XML element is defined in the corresponding information that dictates the structure of said XML data in said XML-based input stream; the name of the particular XML element that is currently being processed; the data type of the particular XML element that is currently being processed; second data indicating whether said particular XML element conforms to the corresponding information that dictates the structure of said XML data in said XML-based input stream; the current validation mode for the particular XML element that is currently being processed, wherein the current validation mode is one of strict mode, lax mode, and skip mode; the current state of said validation operation; or the one or more annotations that are associated with the particular XML element that is currently being processed. | 0.500482 |
9,224,149 | 22 | 28 | 22. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: obtaining identity information, with a portable program module, for a source of a webpage associated with a container document, the portable program module located in the container document; submitting, by the portable program module located in the container document, the identity information to a concept server storing keywords associated with the container document; receiving, by the portable program module located on the container document and from the concept server, in response to the submitted identity information, the keywords associated with the container document; selecting, by the portable program module located in the container document, a subset of the keywords received from the concept server based at least on one or more criteria specified by an author of the portable program module; submitting, by the portable program module located in the container document, a query to an item search server related to the subset of the keywords selected by the portable program module; and receiving, at the portable program module located in the container document, advertisements responsive to the query from the item search server for display. | 22. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: obtaining identity information, with a portable program module, for a source of a webpage associated with a container document, the portable program module located in the container document; submitting, by the portable program module located in the container document, the identity information to a concept server storing keywords associated with the container document; receiving, by the portable program module located on the container document and from the concept server, in response to the submitted identity information, the keywords associated with the container document; selecting, by the portable program module located in the container document, a subset of the keywords received from the concept server based at least on one or more criteria specified by an author of the portable program module; submitting, by the portable program module located in the container document, a query to an item search server related to the subset of the keywords selected by the portable program module; and receiving, at the portable program module located in the container document, advertisements responsive to the query from the item search server for display. 28. The medium of claim 22 , wherein the identity information for a source of a webpage comprises a URL associated with the container document. | 0.644279 |
8,194,983 | 7 | 8 | 7. The method of claim 1 , wherein the first set of characteristic parameters is at least one of a line height, a word spacing, a line spacing, a number of pixels corresponding to each component, a width of each component, a height of each component, coordinates of each component, density of each component, and aspect ratio of each component. | 7. The method of claim 1 , wherein the first set of characteristic parameters is at least one of a line height, a word spacing, a line spacing, a number of pixels corresponding to each component, a width of each component, a height of each component, coordinates of each component, density of each component, and aspect ratio of each component. 8. The method of claim 7 , wherein calculating the line height comprises: creating a histogram of heights corresponding to a height of each of the plurality of components; identifying a frequently occurring height from the histogram of heights; and computing line height based on the frequently occurring height. | 0.912261 |
7,673,283 | 1 | 4 | 1. A computer method of extending metaclasses in a metamodel, comprising the steps of: defining an extension of a metaclass in a metamodel, an instance of the metamodel being a user model having one or more model elements; applying the defined extension to one of the model elements of the user model, wherein the model element maintains a list of annotations to track and manage applied stereotypes; and during run time, dynamically (i) creating a metamodel object representing the defined extension such that requirement for intermediate code generation to extend the metamodel is removed, and (ii) linking the created metamodel object to the model element, including adding the created metamodel object as an annotation in the model element's list of annotations replacing direct references to stereotypes extending the metamodel. | 1. A computer method of extending metaclasses in a metamodel, comprising the steps of: defining an extension of a metaclass in a metamodel, an instance of the metamodel being a user model having one or more model elements; applying the defined extension to one of the model elements of the user model, wherein the model element maintains a list of annotations to track and manage applied stereotypes; and during run time, dynamically (i) creating a metamodel object representing the defined extension such that requirement for intermediate code generation to extend the metamodel is removed, and (ii) linking the created metamodel object to the model element, including adding the created metamodel object as an annotation in the model element's list of annotations replacing direct references to stereotypes extending the metamodel. 4. A method as claimed in claim 1 further comprising the step of providing an interface to the metamodel to support the steps of defining, applying and runtime steps. | 0.768156 |
9,355,140 | 7 | 8 | 7. A non-transitory computer readable storage medium storing computer instructions executable by a processor to perform a method comprising: creating a query suggestion associated with a single entity, wherein the query suggestion includes first terms and wherein the first terms of the query suggestion include a first group of one or more of the first terms and a second group of one or more of the first terms; wherein creating the query suggestion associated with the single entity includes: identifying a plurality of entities associated with the first group of the first terms based on a mapping of the first group of the first terms to the entities, the entities including the single entity, identifying the second group of the first terms based on at least one property of the single entity, and creating the query suggestion associated with the single entity by annotating the first group of the first terms with the second group of the first terms; identifying an entity search query associated with the single entity of the query suggestion, wherein the entity search query is identified based on a mapping of the single entity to the search query, and wherein the entity search query includes second terms, the second terms including at least one term that is not included in the query suggestion; associating the query suggestion with the second terms of the entity search query so that a user selection of the query suggestion issues a search based on the second terms of the entity search query, including the at least one term that is not included in the query suggestion; identifying a user selection of the query suggestion; and in response to the user selection of the query suggestion, submitting the second terms of the entity search query, including the at least one term that is not included in the query suggestion, to a search system. | 7. A non-transitory computer readable storage medium storing computer instructions executable by a processor to perform a method comprising: creating a query suggestion associated with a single entity, wherein the query suggestion includes first terms and wherein the first terms of the query suggestion include a first group of one or more of the first terms and a second group of one or more of the first terms; wherein creating the query suggestion associated with the single entity includes: identifying a plurality of entities associated with the first group of the first terms based on a mapping of the first group of the first terms to the entities, the entities including the single entity, identifying the second group of the first terms based on at least one property of the single entity, and creating the query suggestion associated with the single entity by annotating the first group of the first terms with the second group of the first terms; identifying an entity search query associated with the single entity of the query suggestion, wherein the entity search query is identified based on a mapping of the single entity to the search query, and wherein the entity search query includes second terms, the second terms including at least one term that is not included in the query suggestion; associating the query suggestion with the second terms of the entity search query so that a user selection of the query suggestion issues a search based on the second terms of the entity search query, including the at least one term that is not included in the query suggestion; identifying a user selection of the query suggestion; and in response to the user selection of the query suggestion, submitting the second terms of the entity search query, including the at least one term that is not included in the query suggestion, to a search system. 8. The non-transitory computer readable storage medium of claim 7 , further comprising receiving a query, wherein the query suggestion is based on the query. | 0.926152 |
4,771,401 | 41 | 42 | 41. An method according to claim 38 wherein said matching step comprises the step of responding to a differential coding of a first lexicon entry for generating a signal representative of a first linguistic expression, said differential encoding being representative of a difference in character content between the linguistic expression represented in said first lexicon entry and a second linguistic expression represented in a second said lexicon entry. | 41. An method according to claim 38 wherein said matching step comprises the step of responding to a differential coding of a first lexicon entry for generating a signal representative of a first linguistic expression, said differential encoding being representative of a difference in character content between the linguistic expression represented in said first lexicon entry and a second linguistic expression represented in a second said lexicon entry. 42. A method according to claim 41 wherein said responding step includes the steps of A. generating an alphanumeric character in response to an explicit differential coding representative of an alphanumeric character of said first linguistic expression, and B. generating an alphanumeric character sequence in response to an indirect differential code, said indirect differential code representing a character sequence common to said first linguistic expression and to a third linguistic expression represented in a third lexicon entry. | 0.851028 |
9,348,329 | 15 | 19 | 15. A distributed automation control device, comprising: a memory circuit storing a multi-Boolean function block configured to receive a plurality of inputs, to perform multiple Boolean logical operations based on the inputs, and to output any one of a plurality of logical outputs based upon the Boolean logical operations, wherein the plurality of inputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of inputs and as the plurality of individual inputs, and the plurality of logical outputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of logical outputs and as the plurality of individual logical outputs; a processor configured to execute the multiple Boolean logical operations; and an interface configured to output any of the plurality of logical outputs based upon the operations executed by the processor. | 15. A distributed automation control device, comprising: a memory circuit storing a multi-Boolean function block configured to receive a plurality of inputs, to perform multiple Boolean logical operations based on the inputs, and to output any one of a plurality of logical outputs based upon the Boolean logical operations, wherein the plurality of inputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of inputs and as the plurality of individual inputs, and the plurality of logical outputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of logical outputs and as the plurality of individual logical outputs; a processor configured to execute the multiple Boolean logical operations; and an interface configured to output any of the plurality of logical outputs based upon the operations executed by the processor. 19. The distributed automation control device of claim 15 , wherein the distributed automation control device is not a programmable logic controller. | 0.876246 |
8,949,079 | 27 | 41 | 27. A method for providing structured clinical information from patient records, the method comprising: (a) mining, by a processor, a patient record having at least one unstructured data source comprising unstructured patient information, the mining comprising mining unstructured free text information, the patient record being from a healthcare provider, the mining including extracting at least one of multiple pieces of information related to each of multiple variables; (b) creating, probabilistically by the processor, structured clinical data for each of the variables from the extracted multiple pieces of information, including the at least one piece of the unstructured patient information mined from the unstructured data source, the structured clinical data being stored for answering a question regarding patients; (c) providing (a) as a service to the healthcare provider; and (d) mining from the structured clinical data as a function of the question. | 27. A method for providing structured clinical information from patient records, the method comprising: (a) mining, by a processor, a patient record having at least one unstructured data source comprising unstructured patient information, the mining comprising mining unstructured free text information, the patient record being from a healthcare provider, the mining including extracting at least one of multiple pieces of information related to each of multiple variables; (b) creating, probabilistically by the processor, structured clinical data for each of the variables from the extracted multiple pieces of information, including the at least one piece of the unstructured patient information mined from the unstructured data source, the structured clinical data being stored for answering a question regarding patients; (c) providing (a) as a service to the healthcare provider; and (d) mining from the structured clinical data as a function of the question. 41. The method of claim 27 wherein (c) comprises communicating corrected information related to the patient record. | 0.945394 |
9,563,693 | 16 | 20 | 16. A computerized system comprising: one or more processors; and one or more computer storage media storing computer-useable instructions that, when used by the one or more processors, cause the one or more processors to: receive user feedback for each of one or more social posts presented to a user, each social post presented in association with a sentiment assigned to the social post, the user feedback for each social post regarding the sentiment assigned to the social post; generate sentiment tuning data from the user feedback; generate a new set of sentiment indicators from user provided sentiment indicators of the sentiment tuning data; apply the new set of sentiment indicators, generated from the sentiment tuning data, to new social posts to determine sentiments for the new social posts, wherein the applying comprises: identify designated expressive symbols of the new set of sentiment indicators in the new social posts, the new set of sentiment indicators comprising assignments between the designated expressive symbols and designated sentiments; and determine assignments of the sentiments to the new social posts based on the assignments between the designated expressive symbols and the designated sentiments; and present the new social posts in association with the sentiments assigned to the new social posts. | 16. A computerized system comprising: one or more processors; and one or more computer storage media storing computer-useable instructions that, when used by the one or more processors, cause the one or more processors to: receive user feedback for each of one or more social posts presented to a user, each social post presented in association with a sentiment assigned to the social post, the user feedback for each social post regarding the sentiment assigned to the social post; generate sentiment tuning data from the user feedback; generate a new set of sentiment indicators from user provided sentiment indicators of the sentiment tuning data; apply the new set of sentiment indicators, generated from the sentiment tuning data, to new social posts to determine sentiments for the new social posts, wherein the applying comprises: identify designated expressive symbols of the new set of sentiment indicators in the new social posts, the new set of sentiment indicators comprising assignments between the designated expressive symbols and designated sentiments; and determine assignments of the sentiments to the new social posts based on the assignments between the designated expressive symbols and the designated sentiments; and present the new social posts in association with the sentiments assigned to the new social posts. 20. The computerized system of claim 16 , wherein a first sentiment of the sentiments comprises a positive sentiment, a second sentiment of the sentiments comprises a negative sentiment, and a third sentiment of the sentiments comprises a neutral sentiment. | 0.721258 |
10,140,261 | 5 | 8 | 5. The non-transitory computer storage medium of claim 4 , wherein the finite set of undirected edges is represented by a size or appearance associated with the sample text. | 5. The non-transitory computer storage medium of claim 4 , wherein the finite set of undirected edges is represented by a size or appearance associated with the sample text. 8. The non-transitory computer storage medium of claim 5 , wherein an edge width of the finite set of undirected edges is proportional to the edge weight. | 0.946267 |
7,966,187 | 1 | 7 | 1. A method for evaluating compliance of at least one agent reading at least one script to at least one client, the method comprising at least the following: conducting at least one voice interaction between the at least one agent and the at least one client, wherein the at least one agent follows the at least one script at an agent workstation; evaluating the at least one voice interaction with at least one automatic speech recognition component adapted to analyze the at least one voice interaction, wherein the at least one voice interaction is divided into viewable panel-level segments and a panel-level time displacement stamp is assigned to each panel of the panel-level segments, wherein each panel-level segment is compared with a corresponding expected text, wherein a confidence level threshold of the automatic speech recognition component is used to evaluate the accuracy of each panel-level segment based on an output of a comparison between each panel-level segment and its corresponding expected text, wherein a score is assigned to each panel-level segment, each score indicating a match accuracy between the panel-level segment to which it is assigned and its assigned panel-level segment's corresponding expected text, wherein the scores are evaluated against a standard, the standard defining a required score for each of the panel-level segments to be declared as a match to their corresponding expected texts; and determining whether the at least one agent has adequately followed the at least one script wherein a set of action rules is applied to the output of the determining, wherein the set of action rules includes a quality assurance action to be taken. | 1. A method for evaluating compliance of at least one agent reading at least one script to at least one client, the method comprising at least the following: conducting at least one voice interaction between the at least one agent and the at least one client, wherein the at least one agent follows the at least one script at an agent workstation; evaluating the at least one voice interaction with at least one automatic speech recognition component adapted to analyze the at least one voice interaction, wherein the at least one voice interaction is divided into viewable panel-level segments and a panel-level time displacement stamp is assigned to each panel of the panel-level segments, wherein each panel-level segment is compared with a corresponding expected text, wherein a confidence level threshold of the automatic speech recognition component is used to evaluate the accuracy of each panel-level segment based on an output of a comparison between each panel-level segment and its corresponding expected text, wherein a score is assigned to each panel-level segment, each score indicating a match accuracy between the panel-level segment to which it is assigned and its assigned panel-level segment's corresponding expected text, wherein the scores are evaluated against a standard, the standard defining a required score for each of the panel-level segments to be declared as a match to their corresponding expected texts; and determining whether the at least one agent has adequately followed the at least one script wherein a set of action rules is applied to the output of the determining, wherein the set of action rules includes a quality assurance action to be taken. 7. The script compliance method of claim 1 , wherein conducting at least one voice interaction includes conducting the at least one voice interaction at least in part on at least one communications network having at least one wireless component. | 0.776051 |
9,959,318 | 2 | 3 | 2. The method of claim 1 , further comprising: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to the first user; and a plurality of second nodes corresponding to the plurality of entities, respectively. | 2. The method of claim 1 , further comprising: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to the first user; and a plurality of second nodes corresponding to the plurality of entities, respectively. 3. The method of claim 2 , wherein identifying the particular entity of the plurality of entities corresponding to the profile page comprises identifying a node of the plurality of nodes corresponding to the profile page. | 0.922402 |
8,145,256 | 35 | 37 | 35. A method comprising: receiving a request from a device through a communication system, the request comprising data representing an image of an object; accessing at least one of a database, a search engine, and a data network to find information related to the object, the information comprising at least one of an image, a video, an audio file, text, a hypertext link, and a web site; and sending titles of the found information through the communication system to the device. | 35. A method comprising: receiving a request from a device through a communication system, the request comprising data representing an image of an object; accessing at least one of a database, a search engine, and a data network to find information related to the object, the information comprising at least one of an image, a video, an audio file, text, a hypertext link, and a web site; and sending titles of the found information through the communication system to the device. 37. The method of claim 35 , further comprising performing at least one of enhancing, focusing, filtering, removing non-relevant objects, adjusting contrast between light and dark areas, adjusting brightness, adjusting color, adjusting focus, interpolating pixels to reduce the effects of blurs, reflections, and removing red eye. | 0.833333 |
8,379,830 | 9 | 10 | 9. A non-transitory computer readable medium storing computer executable instructions to configure a computer to determine when to transfer a user from an automated service to a live agent by performing steps comprising: a) predicting whether an interaction is good, based on a first classification model trained using records of one or more previous interactions classified as good, using P(x|LM good ); b) predicting whether the interaction is bad, based on a second classification model trained using records of one or more previous interactions classified as bad, using P(x|LM bad ); c) calculating a log likelihood ratio using log(P(x|LM good )/P(x|LM bad )); d) comparing said log likelihood ratio to a threshold value, such that if said log likelihood ratio falls below said threshold value, instructions are executed to transfer said user from automation to said live agent; wherein: i) x is a set of responses made by the user during the interaction; and ii) the one or more previous interactions classified as good and the one or more previous interactions classified as bad comprise, at least, prompts provided by an interactive voice response system, transcriptions of statements by a caller derived from an automatic speech recognizer, meanings ascribed to statements made by the caller, and confidence scores for the transcriptions. | 9. A non-transitory computer readable medium storing computer executable instructions to configure a computer to determine when to transfer a user from an automated service to a live agent by performing steps comprising: a) predicting whether an interaction is good, based on a first classification model trained using records of one or more previous interactions classified as good, using P(x|LM good ); b) predicting whether the interaction is bad, based on a second classification model trained using records of one or more previous interactions classified as bad, using P(x|LM bad ); c) calculating a log likelihood ratio using log(P(x|LM good )/P(x|LM bad )); d) comparing said log likelihood ratio to a threshold value, such that if said log likelihood ratio falls below said threshold value, instructions are executed to transfer said user from automation to said live agent; wherein: i) x is a set of responses made by the user during the interaction; and ii) the one or more previous interactions classified as good and the one or more previous interactions classified as bad comprise, at least, prompts provided by an interactive voice response system, transcriptions of statements by a caller derived from an automatic speech recognizer, meanings ascribed to statements made by the caller, and confidence scores for the transcriptions. 10. The non-transitory computer readable medium as claimed in claim 9 wherein said classification model is based on a boostexter classification. | 0.815385 |
5,544,257 | 21 | 23 | 21. The system of claim 17, wherein said updating means comprises: (1) means for determining a most probable path through said hidden Markov model for each training observation sequence; (2) means for updating said model parameters based on relative frequencies of state transitions and on observed values emitted during said state transitions, comprising: (I) means for updating said one or more output probability distributions; (II) means for updating said one or more mixture coefficients; and (III) means for updating state transition probabilities. | 21. The system of claim 17, wherein said updating means comprises: (1) means for determining a most probable path through said hidden Markov model for each training observation sequence; (2) means for updating said model parameters based on relative frequencies of state transitions and on observed values emitted during said state transitions, comprising: (I) means for updating said one or more output probability distributions; (II) means for updating said one or more mixture coefficients; and (III) means for updating state transition probabilities. 23. The system of claim 21, wherein said means for updating mixture coefficients comprises means for updating mixture coefficients according to an equation: ##EQU15## where "s.sub.j " is a state of said hidden markov model, and "g.sub.k " is one of one or more clusters of feature vectors. | 0.931419 |
8,517,739 | 1 | 3 | 1. A method of teaching a user to read, comprising the steps of: (a) providing a user, a processing unit, and a user vocabulary table; (b) selecting a source text, the source text being at least a portion of reading material that the user is expected to read; (c) the processing unit comparing each word in the source text with the vocabulary table and identifying lesson words, the lesson words being those words found in the source text, but not in the vocabulary table; (d) the processing unit adding the lesson words to the vocabulary table; (e) the processing unit presenting at least one word drill exercise for each word of the lesson words on a screen, the drill exercise for each lesson word combining textual presentation of the word together with an audible presentation of the pronunciation of the word; (f) the user exercising the lesson words using the word drill exercises; (g) presenting the source text to the user to read; and (h) Repeating steps (b) through (g) with a new source text sequentially expanding the reading vocabulary of the user. | 1. A method of teaching a user to read, comprising the steps of: (a) providing a user, a processing unit, and a user vocabulary table; (b) selecting a source text, the source text being at least a portion of reading material that the user is expected to read; (c) the processing unit comparing each word in the source text with the vocabulary table and identifying lesson words, the lesson words being those words found in the source text, but not in the vocabulary table; (d) the processing unit adding the lesson words to the vocabulary table; (e) the processing unit presenting at least one word drill exercise for each word of the lesson words on a screen, the drill exercise for each lesson word combining textual presentation of the word together with an audible presentation of the pronunciation of the word; (f) the user exercising the lesson words using the word drill exercises; (g) presenting the source text to the user to read; and (h) Repeating steps (b) through (g) with a new source text sequentially expanding the reading vocabulary of the user. 3. The method as set forth in claim 1 , wherein step (c) further includes the step of removing some of the unique words from the lesson words. | 0.579882 |
9,104,353 | 1 | 5 | 1. A printing system for printing documents over a network, the printing system comprising: a processor; and a memory storing machine readable instructions, which when executed by the processor cause the processor to: receive, from a user, a document including content to be printed; ascertain whether the document is confidential, based on a determination as to whether text indicating that the document is confidential is present in the content to be printed; in response to ascertaining that the document is confidential, generate an authentication code corresponding to the document to provide print control of the document to authorized users, wherein the authorized users includes the user, and wherein the authentication code is a code to ascertain that the authorized users are authorized to print the document; and provide the authentication code to the authorized users to provide the print control. | 1. A printing system for printing documents over a network, the printing system comprising: a processor; and a memory storing machine readable instructions, which when executed by the processor cause the processor to: receive, from a user, a document including content to be printed; ascertain whether the document is confidential, based on a determination as to whether text indicating that the document is confidential is present in the content to be printed; in response to ascertaining that the document is confidential, generate an authentication code corresponding to the document to provide print control of the document to authorized users, wherein the authorized users includes the user, and wherein the authentication code is a code to ascertain that the authorized users are authorized to print the document; and provide the authentication code to the authorized users to provide the print control. 5. The printing system as claimed in claim 1 , wherein the machine readable instructions are further to cause the processor to: receive a print request from the user to print the document; determine whether the document was marked confidential; request the user to provide the authentication code corresponding to the document in response to a determination that the document was marked confidential; and generate a print trigger to print the document in response to receiving the authentication code from the user. | 0.500969 |
8,996,517 | 10 | 11 | 10. The system of claim 9 , where the processor is further to: receive the information identifying the document; and provide an alternative document after receiving the information identifying the document, the alternative document including information regarding the selection. | 10. The system of claim 9 , where the processor is further to: receive the information identifying the document; and provide an alternative document after receiving the information identifying the document, the alternative document including information regarding the selection. 11. The system of claim 10 , where, when providing the alternative document, the processor is further to: determine that the remove list includes the information identifying the document, and provide the alternative document based on determining that the remove list includes the information identifying the document. | 0.904172 |
9,697,194 | 6 | 10 | 6. A computer program product for generating an auto-correct dictionary, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to analyze contents of information accessed by a user via a first application, wherein: the contents of information include at least one of words and phrases that appear in the first application; program instructions to identify at least one of the words and the phrases that appear in the first application and are not included in a first dictionary; program instructions to generate a temporary dictionary based, at least in part, on at least one of the words and the phrases identified in the first application that are not included in the first dictionary; and program instructions to use the temporary dictionary to carry out auto-correct operations on text included in a second application. | 6. A computer program product for generating an auto-correct dictionary, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to analyze contents of information accessed by a user via a first application, wherein: the contents of information include at least one of words and phrases that appear in the first application; program instructions to identify at least one of the words and the phrases that appear in the first application and are not included in a first dictionary; program instructions to generate a temporary dictionary based, at least in part, on at least one of the words and the phrases identified in the first application that are not included in the first dictionary; and program instructions to use the temporary dictionary to carry out auto-correct operations on text included in a second application. 10. The computer program product of claim 6 , the program instructions further comprising: program instructions to respond to a determination that the temporary dictionary is not to be used to carry out auto-correct operations by deleting the contents of the temporary dictionary. | 0.72167 |
8,825,639 | 7 | 8 | 7. The method of claim 1 , further comprising: determining, from among a plurality of different types or degrees of associations between the members in the member network, a particular type or degree of an association in the member network between the third member and the first member; and ranking the collection of articles responsive to the third search query based on the particular type or degree of the association in the member network between the first member and the third member; wherein providing the third member with information describing the collection of articles responsive to the third search query comprises formatting the information in an arrangement that corresponds to the ranking of the collection of articles responsive to the third search query. | 7. The method of claim 1 , further comprising: determining, from among a plurality of different types or degrees of associations between the members in the member network, a particular type or degree of an association in the member network between the third member and the first member; and ranking the collection of articles responsive to the third search query based on the particular type or degree of the association in the member network between the first member and the third member; wherein providing the third member with information describing the collection of articles responsive to the third search query comprises formatting the information in an arrangement that corresponds to the ranking of the collection of articles responsive to the third search query. 8. The method of claim 7 , wherein the degree of the association in the member network between the first member and the third member indicates a number of intermediate relationships that separate the first member and the third member. | 0.949742 |
9,159,316 | 1 | 5 | 1. A computer-implemented method, comprising: receiving, by a computing system and as having been transmitted by a first computing device, a textual search query that was specified by user input at the first computing device, the textual search query including a textual search term; causing, by the computing system and as a result of having received the textual search query, search results that correspond to the textual search query to be generated through a search that uses the textual search query and provided for receipt and presentation by the first computing device; determining, by the computing system and as a result of having received the textual search query, whether the textual search term exists in a dictionary of terms for a speech recognition system; adding, by the computing system and as a result of determining that the textual search term is not in the dictionary of terms for the speech recognition system and as a result of having received the textual search query, the textual search term to the dictionary of terms for the speech recognition system due to inclusion of the textual search term in the textual search query, in order to generate an updated dictionary of terms for the speech recognition system; identifying, by the computing system, acoustic model data for the textual search term; and providing, by the computing system, the acoustic model data for the textual search and the updated dictionary of terms for the speech recognition system for use in a verbal translation that includes: receiving a verbal query that was specified by user input at another computing device and that includes a verbal representation of the textual search term, and translating, using the acoustic model data for the textual search term and the updated dictionary of terms for the speech recognition system, the verbal query into a textual representation of the verbal query, the textual representation of the verbal query including the textual search term. | 1. A computer-implemented method, comprising: receiving, by a computing system and as having been transmitted by a first computing device, a textual search query that was specified by user input at the first computing device, the textual search query including a textual search term; causing, by the computing system and as a result of having received the textual search query, search results that correspond to the textual search query to be generated through a search that uses the textual search query and provided for receipt and presentation by the first computing device; determining, by the computing system and as a result of having received the textual search query, whether the textual search term exists in a dictionary of terms for a speech recognition system; adding, by the computing system and as a result of determining that the textual search term is not in the dictionary of terms for the speech recognition system and as a result of having received the textual search query, the textual search term to the dictionary of terms for the speech recognition system due to inclusion of the textual search term in the textual search query, in order to generate an updated dictionary of terms for the speech recognition system; identifying, by the computing system, acoustic model data for the textual search term; and providing, by the computing system, the acoustic model data for the textual search and the updated dictionary of terms for the speech recognition system for use in a verbal translation that includes: receiving a verbal query that was specified by user input at another computing device and that includes a verbal representation of the textual search term, and translating, using the acoustic model data for the textual search term and the updated dictionary of terms for the speech recognition system, the verbal query into a textual representation of the verbal query, the textual representation of the verbal query including the textual search term. 5. The computer-implemented method of claim 1 , further comprising: assigning a probability value to a dictionary entry for the textual search term within the updated dictionary of terms based on a number of times that the textual search term is received within search queries, such that at least three dictionary entries for corresponding terms within the updated dictionary of terms have three different assigned probability values based on respective number of times that the corresponding terms have been received within the search queries. | 0.804457 |
9,081,816 | 10 | 11 | 10. The non-transitory computer-readable medium as in claim 8 , wherein the mapping occurs prior to executing of the query. | 10. The non-transitory computer-readable medium as in claim 8 , wherein the mapping occurs prior to executing of the query. 11. The non-transitory computer-readable medium as in claim 10 , wherein the mapping comprises accessing an identity plug-in, that is registered on a search application based on a mapping attribute in an identity management (IDM) system. | 0.947075 |
8,880,495 | 1 | 14 | 1. A method for constructing an expanded search query at a computing device, the method comprising: receiving audio information via a microphone of the computing device; recording the audio information in an overwriteable circular buffer of the computing device, including recording at least some of the audio information during a period when the computing device is powered-on, but is in an inactive state or a sleep state in which a graphical display of the computing device is off or substantially dimmed, said recording initiated responsive to a triggering condition including detection of a sound level via the microphone that exceeds a sound level threshold, the overwriteable circular buffer having a limited data storage capacity in which older audio information is overwritten with newer audio information upon reaching the limited data storage capacity; initiating construction of a search query by receiving a user input via a text-based user interface of the computing device, the user input including one or more keywords forming a user-defined portion of the search query; processing at least a portion of the audio information recorded in the overwriteable circular buffer to obtain one or more additional keywords forming an expanded portion of the search query, the portion of the audio information containing the one or more additional keywords received and recorded in the overwriteable circular buffer prior to receiving the user input including the one or more keywords; supplying the search query including the user-defined portion and the expanded portion to a search engine; and receiving a response to the search query from the search engine, the response generated by the search engine based, at least in part, on the one or more keywords of the user-defined portion and the one or more additional keywords of the expanded portion of the search query. | 1. A method for constructing an expanded search query at a computing device, the method comprising: receiving audio information via a microphone of the computing device; recording the audio information in an overwriteable circular buffer of the computing device, including recording at least some of the audio information during a period when the computing device is powered-on, but is in an inactive state or a sleep state in which a graphical display of the computing device is off or substantially dimmed, said recording initiated responsive to a triggering condition including detection of a sound level via the microphone that exceeds a sound level threshold, the overwriteable circular buffer having a limited data storage capacity in which older audio information is overwritten with newer audio information upon reaching the limited data storage capacity; initiating construction of a search query by receiving a user input via a text-based user interface of the computing device, the user input including one or more keywords forming a user-defined portion of the search query; processing at least a portion of the audio information recorded in the overwriteable circular buffer to obtain one or more additional keywords forming an expanded portion of the search query, the portion of the audio information containing the one or more additional keywords received and recorded in the overwriteable circular buffer prior to receiving the user input including the one or more keywords; supplying the search query including the user-defined portion and the expanded portion to a search engine; and receiving a response to the search query from the search engine, the response generated by the search engine based, at least in part, on the one or more keywords of the user-defined portion and the one or more additional keywords of the expanded portion of the search query. 14. The method of claim 1 , wherein processing the portion of the audio information includes applying speech recognition to the portion of the audio information to obtain the one or more additional keywords. | 0.85443 |
9,710,699 | 1 | 6 | 1. An image processing appliance comprising a family of image processing functions instantiated on high thru put processor hardwares that accomplishes recognition of individuals of interest from analysis of images taken under real world lighting conditions, wherein the analysis functions accomplish a) extraction of indices of recognition from real work imagery sets containing the images of the individuals of interest, b) the construction of three dimensional morphable models of the individuals of interest based on data sets containing images of the individuals of interest, c) extraction of lighting conditions from the real world image data set containing images of the individual to be recognized, d) imposition of the extracted lighting conditions upon the three dimensional images of candidate individuals, and e) declaration of individual identify based on a high degree of correlation between the real world data set and the simulated data set extracted from the morphed three dimensional models with the lighting conditions of the real image rendered onto the three dimensional models morphed into the positional conditions of the individual to be recognized from the real world data set. | 1. An image processing appliance comprising a family of image processing functions instantiated on high thru put processor hardwares that accomplishes recognition of individuals of interest from analysis of images taken under real world lighting conditions, wherein the analysis functions accomplish a) extraction of indices of recognition from real work imagery sets containing the images of the individuals of interest, b) the construction of three dimensional morphable models of the individuals of interest based on data sets containing images of the individuals of interest, c) extraction of lighting conditions from the real world image data set containing images of the individual to be recognized, d) imposition of the extracted lighting conditions upon the three dimensional images of candidate individuals, and e) declaration of individual identify based on a high degree of correlation between the real world data set and the simulated data set extracted from the morphed three dimensional models with the lighting conditions of the real image rendered onto the three dimensional models morphed into the positional conditions of the individual to be recognized from the real world data set. 6. The host processing hardwares of claim 1 asFPGA-based, GPU-based, or analog ASIC-based processing units. | 0.869193 |
5,537,485 | 17 | 19 | 17. The method according to claim 16, wherein said step of area filtering comprises: defining plural structuring elements each having a size of at least two pixels; sequentially defining each pixel in the image after global thresholding as an operating pixel and sequentially overlaying each operating pixel with each structuring element; determining, for each operating pixel sequentially overlaid by each structuring element, the minimum pixel value of the pixels overlaid by each structuring element in relation to the same operating pixel; determining the maximum of the minimum pixel values determined in relation to the same operating pixel; and setting the value of each pixel in the output area-filtered image corresponding to the position of the operating pixel in the global thresholded image to the respective maximum of said minimum values determined in the preceding step. | 17. The method according to claim 16, wherein said step of area filtering comprises: defining plural structuring elements each having a size of at least two pixels; sequentially defining each pixel in the image after global thresholding as an operating pixel and sequentially overlaying each operating pixel with each structuring element; determining, for each operating pixel sequentially overlaid by each structuring element, the minimum pixel value of the pixels overlaid by each structuring element in relation to the same operating pixel; determining the maximum of the minimum pixel values determined in relation to the same operating pixel; and setting the value of each pixel in the output area-filtered image corresponding to the position of the operating pixel in the global thresholded image to the respective maximum of said minimum values determined in the preceding step. 19. The method of claim 17, wherein said step of defining plural structuring elements comprises: defining said structuring elements to include at least one subset of all possible combinations of two interconnected pixels. | 0.947406 |
9,009,040 | 7 | 9 | 7. One or more non-transitory computer readable media storing one or more instructions, when executed by one or more processors, configured to: access recorded voice data of a user from one or more sources, the recorded voice data comprising a plurality of voice samples; access a transcript of the recorded voice data, the transcript comprising text representing one or more words of each voice sample; identify an origin of a voice sample, the origin being a device used to input the voice sample; determine that the origin is associated with the user; determine that the voice sample matches a voice profile of the user, wherein the voice profile comprises voice signal characteristics to identify a voice of the user and user speech information to convert the voice sample to corresponding text; provide electronic mail and a text message generated by the user to identify one or more words commonly used by the user, the transcript, and the recorded voice data to a transcription system to generate an updated voice profile for the user; determine portions of the transcript that are transcribed at a low confidence of accuracy; flag the portions of the transcript that are transcribed at a low confidence of accuracy; and communicate the flagged portions of the transcript to a transcript refiner. | 7. One or more non-transitory computer readable media storing one or more instructions, when executed by one or more processors, configured to: access recorded voice data of a user from one or more sources, the recorded voice data comprising a plurality of voice samples; access a transcript of the recorded voice data, the transcript comprising text representing one or more words of each voice sample; identify an origin of a voice sample, the origin being a device used to input the voice sample; determine that the origin is associated with the user; determine that the voice sample matches a voice profile of the user, wherein the voice profile comprises voice signal characteristics to identify a voice of the user and user speech information to convert the voice sample to corresponding text; provide electronic mail and a text message generated by the user to identify one or more words commonly used by the user, the transcript, and the recorded voice data to a transcription system to generate an updated voice profile for the user; determine portions of the transcript that are transcribed at a low confidence of accuracy; flag the portions of the transcript that are transcribed at a low confidence of accuracy; and communicate the flagged portions of the transcript to a transcript refiner. 9. The media of claim 7 , the instructions configured to: determine that the voice sample records the voice of the user. | 0.755102 |
8,577,865 | 9 | 10 | 9. A computer program product, the computer program product comprising a set of instructions in a machine-readable storage device for use in searching for documents, said documents having searchable parameters, said searchable parameters stored in more than one different data sources, the set of instructions for causing at least one machine to: receive a search statement, said search statement comprising at least a first search query, said first search query comprising a first search value and at least a first search parameter specifying a first data source to search, and a second search query, said second search query comprising a second search value and at least a second search parameter specifying a second data source to search; determine a search strategy based on the search statement, the search strategy comprising a search activity for each data source to be searched such that a first search activity and a second search activity for searching said first data source and searching said second data source are created, respectively; assign weights to said search activities, said weights based upon a type of a data source to be searched and a specificity of search value; search the first data source and second data source using the first and second search activities respectively, wherein an order in which the first and second search activities are performed is dictated by the weights assigned to the first and second search activities; and returning a final document search result from said search activities. | 9. A computer program product, the computer program product comprising a set of instructions in a machine-readable storage device for use in searching for documents, said documents having searchable parameters, said searchable parameters stored in more than one different data sources, the set of instructions for causing at least one machine to: receive a search statement, said search statement comprising at least a first search query, said first search query comprising a first search value and at least a first search parameter specifying a first data source to search, and a second search query, said second search query comprising a second search value and at least a second search parameter specifying a second data source to search; determine a search strategy based on the search statement, the search strategy comprising a search activity for each data source to be searched such that a first search activity and a second search activity for searching said first data source and searching said second data source are created, respectively; assign weights to said search activities, said weights based upon a type of a data source to be searched and a specificity of search value; search the first data source and second data source using the first and second search activities respectively, wherein an order in which the first and second search activities are performed is dictated by the weights assigned to the first and second search activities; and returning a final document search result from said search activities. 10. The computer program product as set forth in claim 9 , wherein searching comprises: performing the first search activity to identify a first result set of documents; and performing the second search activity using the first result set of documents to identify a second result set of documents, said second result set comprising a sub set of said first result set. | 0.501359 |
8,175,872 | 1 | 16 | 1. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving geotagged audio signals that correspond to environmental audio recorded by multiple mobile devices in multiple geographic locations, receiving an audio signal that corresponds to an utterance recorded by a particular mobile device, determining a particular geographic location associated with the particular mobile device, selecting a subset of geotagged audio signals, and weighting each geotagged audio signal of the subset based on whether the respective audio signal was manually uploaded or automatically updated, generating a noise model for the particular geographic location using the subset of weighted geotagged audio signals, and performing noise compensation on the audio signal that corresponds to the utterance using the noise model that has been generated for the particular geographic location. | 1. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving geotagged audio signals that correspond to environmental audio recorded by multiple mobile devices in multiple geographic locations, receiving an audio signal that corresponds to an utterance recorded by a particular mobile device, determining a particular geographic location associated with the particular mobile device, selecting a subset of geotagged audio signals, and weighting each geotagged audio signal of the subset based on whether the respective audio signal was manually uploaded or automatically updated, generating a noise model for the particular geographic location using the subset of weighted geotagged audio signals, and performing noise compensation on the audio signal that corresponds to the utterance using the noise model that has been generated for the particular geographic location. 16. The system of claim 1 , wherein the operations further comprise selecting the noise model generated for the particular geographic location from among multiple noise models generated for the multiple geographic locations. | 0.812081 |
7,792,353 | 12 | 13 | 12. A method according to claim 10 , wherein the specified selection criterion further comprises calculating a score for each training sample and for each unlabeled sample using an active-learning technique. | 12. A method according to claim 10 , wherein the specified selection criterion further comprises calculating a score for each training sample and for each unlabeled sample using an active-learning technique. 13. A method according to claim 12 , wherein the selected sample is selected in step (c) based on calculated scores from among samples in the training set and samples in the set of unlabeled samples. | 0.919433 |
8,483,518 | 1 | 7 | 1. A method at least partially controlled by a computing device, the method comprising: segmenting an image into objects; assigning a value to each of the segmented objects, wherein the value is an estimation of a significance of an object being recognized by humans; identifying an object such that the image surrounding the object visually associates the object as being a part of the image; selecting the object for the object recognition; cropping the object from the image, wherein the object is expanded beyond a boundary of the image without conveying a contour of the object; filling a region on the image where the object has been cropped; and generating candidate objects that have similar low level features to the object cropped from the image, wherein the low level features are features that are defined without using human perception. | 1. A method at least partially controlled by a computing device, the method comprising: segmenting an image into objects; assigning a value to each of the segmented objects, wherein the value is an estimation of a significance of an object being recognized by humans; identifying an object such that the image surrounding the object visually associates the object as being a part of the image; selecting the object for the object recognition; cropping the object from the image, wherein the object is expanded beyond a boundary of the image without conveying a contour of the object; filling a region on the image where the object has been cropped; and generating candidate objects that have similar low level features to the object cropped from the image, wherein the low level features are features that are defined without using human perception. 7. The method as recited in claim 1 , further comprising scaling sizes of the image and the set of candidate objects in accordance with a corresponding scaling factor. | 0.930417 |
8,527,861 | 1 | 6 | 1. A mobile device having a display screen, comprising: a processor; and a processor readable storage medium having processor readable program code embodied in said processor readable storage medium, said processor readable program code for programming the device to: find links within a page character array and filter out of the page character array characters which are not links; create one or more link groups each having a plurality of links; lay out each link group for display in optimum form on the display screen of the mobile device at predetermined display screen locations based upon hardware of the mobile device, wherein the predetermined screen locations correspond to discrete user locations; display on the display screen of the mobile device a first portion of the link group layout, wherein the first portion does not include all links of the link group; logically map each of the displayed links of the first portion of the link group to a distinct user input, in which correspondence between links in the link group and keystrokes or voice commands is created; alter the display of the link groups to display a second portion of the link group layout; and logically map each of the displayed links of the second portion of the link group to a distinct user input; wherein the mapping of each of the displayed links of the second portion of the link group does not alter the mapping of the first portion of the link group such that the mapping of links of the first and the second portions of the link group are maintained concurrently. | 1. A mobile device having a display screen, comprising: a processor; and a processor readable storage medium having processor readable program code embodied in said processor readable storage medium, said processor readable program code for programming the device to: find links within a page character array and filter out of the page character array characters which are not links; create one or more link groups each having a plurality of links; lay out each link group for display in optimum form on the display screen of the mobile device at predetermined display screen locations based upon hardware of the mobile device, wherein the predetermined screen locations correspond to discrete user locations; display on the display screen of the mobile device a first portion of the link group layout, wherein the first portion does not include all links of the link group; logically map each of the displayed links of the first portion of the link group to a distinct user input, in which correspondence between links in the link group and keystrokes or voice commands is created; alter the display of the link groups to display a second portion of the link group layout; and logically map each of the displayed links of the second portion of the link group to a distinct user input; wherein the mapping of each of the displayed links of the second portion of the link group does not alter the mapping of the first portion of the link group such that the mapping of links of the first and the second portions of the link group are maintained concurrently. 6. A mobile device as in claim 1 , wherein the program code lays out an indication of a corresponding mapped keystroke along with each link name for each link in the link group. | 0.64881 |
10,013,479 | 1 | 2 | 1. An electronic apparatus comprising: a computer readable storage medium and program instructions stored on the computer readable storage medium; and a processor communicatively coupled to the computer readable storage medium and configured to execute the program instructions to perform a method comprising: receiving an input character string from a user; retrieving, in response to input of a character string by a user, conversion candidates associated with the input character string, each conversion candidate having a first rank, wherein the input character string is a mail address and each conversion candidate is a nickname or a name, wherein the first rank is based on a first count corresponding to a total number of users who transmitted mails to the mail address using each nickname or name, wherein the first rank is further based on a second count corresponding to a total number of mails transmitted to the mail address using each nickname or name by the user; displaying, when a plurality of the conversion candidates are present, the plurality of conversion candidates within a corresponding plurality of regions on a map, wherein conversion candidates that have a higher first count occupy larger regions on the map, wherein a first region associated with a conversion candidate having a highest first count comprises 50% of the map, wherein a second region associated with a conversion candidate having a second highest first count comprises 30% of the map, wherein a third region associated with a conversion candidate having a third highest first count comprises 20% of the map, and wherein the plurality of regions on the map are further colored with chroma ordered according to the second count; and displaying, in response to a user selecting a particular region of the plurality of regions on the map with a user input device, information associated with the conversion candidate corresponding to the particular selected region. | 1. An electronic apparatus comprising: a computer readable storage medium and program instructions stored on the computer readable storage medium; and a processor communicatively coupled to the computer readable storage medium and configured to execute the program instructions to perform a method comprising: receiving an input character string from a user; retrieving, in response to input of a character string by a user, conversion candidates associated with the input character string, each conversion candidate having a first rank, wherein the input character string is a mail address and each conversion candidate is a nickname or a name, wherein the first rank is based on a first count corresponding to a total number of users who transmitted mails to the mail address using each nickname or name, wherein the first rank is further based on a second count corresponding to a total number of mails transmitted to the mail address using each nickname or name by the user; displaying, when a plurality of the conversion candidates are present, the plurality of conversion candidates within a corresponding plurality of regions on a map, wherein conversion candidates that have a higher first count occupy larger regions on the map, wherein a first region associated with a conversion candidate having a highest first count comprises 50% of the map, wherein a second region associated with a conversion candidate having a second highest first count comprises 30% of the map, wherein a third region associated with a conversion candidate having a third highest first count comprises 20% of the map, and wherein the plurality of regions on the map are further colored with chroma ordered according to the second count; and displaying, in response to a user selecting a particular region of the plurality of regions on the map with a user input device, information associated with the conversion candidate corresponding to the particular selected region. 2. The electronic apparatus of claim 1 , wherein the first rank is further based on a third count corresponding to a number of mails transmitted for a respective sender-receiver pair of mail addresses; wherein the first rank is further based on a fourth count corresponding to a number of mails transmitted by senders belonging to a same organization as the user; and wherein the first rank is further based on a fifth count corresponding to a number of branches in a tree structure representing an organizational hierarchy between an organization of the user and an organization of a second user associated with the input character string. | 0.50078 |
8,965,761 | 13 | 15 | 13. The computer program product of claim 12 wherein means, recorded on the recording medium, for providing to a multiplicity of users a presentation including content from a session document further comprises: means, recorded on the recording medium, for providing a session document for the presentation, wherein the session document includes a session grammar and a session structured document; means, recorded on the recording medium, for selecting from the session structured document a classified structural element in dependence upon user classifications of a user participant in the presentation; and means, recorded on the recording medium, for presenting the selected structural element to the user. | 13. The computer program product of claim 12 wherein means, recorded on the recording medium, for providing to a multiplicity of users a presentation including content from a session document further comprises: means, recorded on the recording medium, for providing a session document for the presentation, wherein the session document includes a session grammar and a session structured document; means, recorded on the recording medium, for selecting from the session structured document a classified structural element in dependence upon user classifications of a user participant in the presentation; and means, recorded on the recording medium, for presenting the selected structural element to the user. 15. The computer program product of claim 13 further comprising means, recorded on the recording medium, for creating a session document from a presentation document, including: means, recorded on the recording medium, for identifying a presentation document for a presentation, the presentation document including a presentation grammar and a structured document having structural elements classified with classification identifiers; means, recorded on the recording medium, for identifying a user participant for the presentation, the user having a user profile comprising user classifications; and means, recorded on the recording medium, for filtering the structured document in dependence upon the user classifications and the classification identifiers. | 0.760568 |
8,914,283 | 7 | 10 | 7. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: identifying, in a database of utterances, transcribed utterances and un-transcribed utterances; ordering transcription candidate utterances from the un-transcribed utterances based on confidence scores of the transcription candidate utterances, to yield a selectively sampled order; transcribing, via a processor, a top n utterances from the selectively sampled order, to yield additional transcribed utterances and remainder un-transcribed utterances, wherein the remainder un-transcribed utterances are the un-transcribed utterances without the additional transcribed utterances; receiving human-transcribed utterances, wherein the human-transcribed utterances are selected from the remainder un-transcribed utterances for human transcription based on the confidence scores; and adding the additional transcribed utterances and the human-transcribed utterances to the database of utterances. | 7. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: identifying, in a database of utterances, transcribed utterances and un-transcribed utterances; ordering transcription candidate utterances from the un-transcribed utterances based on confidence scores of the transcription candidate utterances, to yield a selectively sampled order; transcribing, via a processor, a top n utterances from the selectively sampled order, to yield additional transcribed utterances and remainder un-transcribed utterances, wherein the remainder un-transcribed utterances are the un-transcribed utterances without the additional transcribed utterances; receiving human-transcribed utterances, wherein the human-transcribed utterances are selected from the remainder un-transcribed utterances for human transcription based on the confidence scores; and adding the additional transcribed utterances and the human-transcribed utterances to the database of utterances. 10. The system of claim 7 , the computer-readable storage medium having additional instruction stored which result in the operations further comprising: upon adding the additional transcribed utterances to the database of utterances, removing the additional utterances from the un-transcribed utterances. | 0.501639 |
7,526,504 | 1 | 3 | 1. A system for consuming job information stored on a spool storage by a spooling module, the system comprising: a processing unit; and memory accessible to the processing unit, the memory comprising: logic configured to consume a data structure that specifies the job information from the spool storage, wherein the data structure defines a plurality of nodes organized into a hierarchical arrangement representing different aspects of the job information; first filter logic configured to process the job information when the job information conforms to the data structure and generate a first output result that conforms to the data structure; second filter logic configured to process the job information when the job information conforms to the data structure and generate a second output result that partially conforms to the data structure; and third filter logic configured to process the job information when the job information is arranged according to a non-structured format; wherein the first filter logic processes the job information while maintaining the data structure specifying the job information to generate the first output result for a first target entity, the first target entity configured to recognize and process the job information when arranged according to the data structure, wherein the second filter logic processes the job information to generate the second output result for a second target entity, the second target entity configured to recognize and process the job information when arranged at least partially according to the data structure, and wherein the third filter logic processes the job information when the job information is arranged according to a non-structured format to generate a third output result for a third target entity, the third target entity configured to recognize and process the job information when arranged according to the non-structured format. | 1. A system for consuming job information stored on a spool storage by a spooling module, the system comprising: a processing unit; and memory accessible to the processing unit, the memory comprising: logic configured to consume a data structure that specifies the job information from the spool storage, wherein the data structure defines a plurality of nodes organized into a hierarchical arrangement representing different aspects of the job information; first filter logic configured to process the job information when the job information conforms to the data structure and generate a first output result that conforms to the data structure; second filter logic configured to process the job information when the job information conforms to the data structure and generate a second output result that partially conforms to the data structure; and third filter logic configured to process the job information when the job information is arranged according to a non-structured format; wherein the first filter logic processes the job information while maintaining the data structure specifying the job information to generate the first output result for a first target entity, the first target entity configured to recognize and process the job information when arranged according to the data structure, wherein the second filter logic processes the job information to generate the second output result for a second target entity, the second target entity configured to recognize and process the job information when arranged at least partially according to the data structure, and wherein the third filter logic processes the job information when the job information is arranged according to a non-structured format to generate a third output result for a third target entity, the third target entity configured to recognize and process the job information when arranged according to the non-structured format. 3. The system of claim 1 , wherein the logic for consuming comprises logic configured to consume at least one document node representing a document to be processed by the spooling module. | 0.541667 |
8,627,276 | 1 | 13 | 1. A method comprising: identifying a plurality of entities having relationships there between, the identifying being performed by a processor; accessing a first entity from the plurality of entities, the accessing the first entity being performed by the processor; accessing a second entity from the plurality of entities, the accessing the second entity being performed by the processor; mapping the first entity to the second entity, mapping the first entity to the second entity including bi-directionally mapping the first entity the second entity, and the mapping being performed by the processor; determining, based on the mapping, if a graphical affordance, associated with at least one of an intermediate representation of a graphical model or code associated with the graphical model, is selected, the determining being performed by the processor; and selectively identifying, based on the determining, one or more portions of the graphical model or one or more portions of the at least one of the intermediate representation of the graphical model or the code associated with the graphical model, when identifying the one or more portions of the graphical model, the method includes: receiving information associated with browsing the at least one of the intermediate representation of the graphical model or the code associated with the graphical model; and identifying the one or more portions of the graphical model based on the received information associated with browsing the at least one of the intermediate representation of the graphical model or the code associated with the graphical model, when identifying the one or more portions of the at least one of the intermediate representation of the graphical model or the code associated with the graphical model, the method includes: receiving information associated with selecting the graphical affordance of the graphical model; and identifying the one or more portions of the at least one of the intermediate representation of the graphical model or the code associated with the graphical model based on the received information associated with selecting the graphical affordance of the graphical model, and the selectively identifying being performed by the processor. | 1. A method comprising: identifying a plurality of entities having relationships there between, the identifying being performed by a processor; accessing a first entity from the plurality of entities, the accessing the first entity being performed by the processor; accessing a second entity from the plurality of entities, the accessing the second entity being performed by the processor; mapping the first entity to the second entity, mapping the first entity to the second entity including bi-directionally mapping the first entity the second entity, and the mapping being performed by the processor; determining, based on the mapping, if a graphical affordance, associated with at least one of an intermediate representation of a graphical model or code associated with the graphical model, is selected, the determining being performed by the processor; and selectively identifying, based on the determining, one or more portions of the graphical model or one or more portions of the at least one of the intermediate representation of the graphical model or the code associated with the graphical model, when identifying the one or more portions of the graphical model, the method includes: receiving information associated with browsing the at least one of the intermediate representation of the graphical model or the code associated with the graphical model; and identifying the one or more portions of the graphical model based on the received information associated with browsing the at least one of the intermediate representation of the graphical model or the code associated with the graphical model, when identifying the one or more portions of the at least one of the intermediate representation of the graphical model or the code associated with the graphical model, the method includes: receiving information associated with selecting the graphical affordance of the graphical model; and identifying the one or more portions of the at least one of the intermediate representation of the graphical model or the code associated with the graphical model based on the received information associated with selecting the graphical affordance of the graphical model, and the selectively identifying being performed by the processor. 13. The method of claim 1 , where, when mapping the first entity to the second entity, the method includes: generating tracing information that associates a first part of the first entity with a second part of the second entity. | 0.654545 |
9,400,559 | 1 | 5 | 1. A method for using a gesture shortcut in a system that takes user gestures as input to an application, comprising: receiving data captured by a capture device, the data corresponding to a user motion or pose; determining, based on the data, a first output identifying that the user motion or pose corresponds to the user performing a shortcut of a full gesture, a performance of the shortcut of the full gesture identifying an input to the application also identified by performance of the full gesture, the shortcut of the full gesture comprising a subset of a user motion or pose comprising the full gesture; sending the first output to the application; determining, based on the data, a second output identifying that the user motion or pose corresponds to the user performing the full gesture; sending the second output to the application; recognizing the first output and the second output as identifying the same intended gesture input to the application; and based at least on recognizing the shortcut of the full gesture and the full gesture within a predetermined amount of time as identifying the same intended gesture input to the application, the application using only either the shortcut of the full gesture or the full gesture as the intended gesture input to the application. | 1. A method for using a gesture shortcut in a system that takes user gestures as input to an application, comprising: receiving data captured by a capture device, the data corresponding to a user motion or pose; determining, based on the data, a first output identifying that the user motion or pose corresponds to the user performing a shortcut of a full gesture, a performance of the shortcut of the full gesture identifying an input to the application also identified by performance of the full gesture, the shortcut of the full gesture comprising a subset of a user motion or pose comprising the full gesture; sending the first output to the application; determining, based on the data, a second output identifying that the user motion or pose corresponds to the user performing the full gesture; sending the second output to the application; recognizing the first output and the second output as identifying the same intended gesture input to the application; and based at least on recognizing the shortcut of the full gesture and the full gesture within a predetermined amount of time as identifying the same intended gesture input to the application, the application using only either the shortcut of the full gesture or the full gesture as the intended gesture input to the application. 5. The method of claim 1 , wherein determining, based on the data, the first output identifying whether the user motion or pose corresponds to the user performing the shortcut of a full gesture further comprises: determining from the application to process the data to determine whether the shortcut of the full gesture has been performed before processing the data to determine the first output. | 0.768692 |
8,566,095 | 3 | 6 | 3. The method of claim 1 , wherein adjusting the initial probability of the first n-gram identifying a word based at least in part on the first number of atomic units comprises: identifying a scaling weight depending on the first number of atomic units; and applying the scaling weight to the initial probability of the first n-gram identifying a word to determine the scaled probability of the first n-gram identifying a word. | 3. The method of claim 1 , wherein adjusting the initial probability of the first n-gram identifying a word based at least in part on the first number of atomic units comprises: identifying a scaling weight depending on the first number of atomic units; and applying the scaling weight to the initial probability of the first n-gram identifying a word to determine the scaled probability of the first n-gram identifying a word. 6. The method of claim 3 , further comprising: identifying lesser order n-grams, the lesser order n-grams being derived from the first n-gram; receiving initial probabilities corresponding to each of the lesser order n-grams identifying words; comparing the initial probability of the first n-gram identifying a word to initial probabilities of combinations of the lesser order n-grams identifying words; and when an initial probability of a combination of lesser order n-grams identifying a word differs from the initial probability of the first n-gram identifying a word by a specified threshold amount, modifying the scaling weight that depends on the first number of atomic units. | 0.581395 |
8,315,924 | 15 | 18 | 15. An apparatus configured for automating accounting, comprising: a processor; a memory; a receiving mechanism configured to receive a check voucher at a system, wherein the check voucher corresponds to a check, wherein the check voucher is neither a check nor an invoice; a recognition mechanism configured to perform an optical character recognition (OCR) operation on the check voucher to identify a set of tokens printed on the check voucher; a search mechanism configured to search a dictionary of tokens for open invoices to identify a match between the set of tokens printed on the check voucher and tokens associated with an open invoice; a determination mechanism configured to determine an amount of the check by determining the value of an amount token printed on the check voucher; an accounting mechanism configured to apply a payment for the amount of the check to the open invoice; wherein the apparatus further determines a layout for the check voucher, wherein the layout indicates a position and a type of each token on the check voucher; saves the layout in a library to facilitate processing of subsequent check vouchers with the same layout; determines an identifying token on the check voucher; and uses the identifying token to retrieve the layout for the check voucher. | 15. An apparatus configured for automating accounting, comprising: a processor; a memory; a receiving mechanism configured to receive a check voucher at a system, wherein the check voucher corresponds to a check, wherein the check voucher is neither a check nor an invoice; a recognition mechanism configured to perform an optical character recognition (OCR) operation on the check voucher to identify a set of tokens printed on the check voucher; a search mechanism configured to search a dictionary of tokens for open invoices to identify a match between the set of tokens printed on the check voucher and tokens associated with an open invoice; a determination mechanism configured to determine an amount of the check by determining the value of an amount token printed on the check voucher; an accounting mechanism configured to apply a payment for the amount of the check to the open invoice; wherein the apparatus further determines a layout for the check voucher, wherein the layout indicates a position and a type of each token on the check voucher; saves the layout in a library to facilitate processing of subsequent check vouchers with the same layout; determines an identifying token on the check voucher; and uses the identifying token to retrieve the layout for the check voucher. 18. The apparatus of claim 15 , wherein the search mechanism is further configured to identify a match between the set of tokens printed on the check voucher and tokens associated with the open invoice by comparing amounts of the open invoices to the amount of the check. | 0.65869 |
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