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9,240,969 | 1 | 6 |
1. A method comprising: determining, by one or more processors, one or more topics associated with a message based at least in part on message data included in the message; determining, by the one or more processors, knowledge data describing the one or more topics associated with the message; determining, by the one or more processors, social activity data describing one or more user activities associated with a group of one or more social users based at least in part on the knowledge data, the one or more user activities describing the one or more topics; generating, by the one or more processors, a selectable tag based at least in part on the social activity data describing the one or more user activities, a selection of the selectable tag causing a display of the social activity data associated with the message; and generating, by the one or more processors, graphical user interface data for displaying the social activity data associated with the message in response to the selectable tag being selected.
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1. A method comprising: determining, by one or more processors, one or more topics associated with a message based at least in part on message data included in the message; determining, by the one or more processors, knowledge data describing the one or more topics associated with the message; determining, by the one or more processors, social activity data describing one or more user activities associated with a group of one or more social users based at least in part on the knowledge data, the one or more user activities describing the one or more topics; generating, by the one or more processors, a selectable tag based at least in part on the social activity data describing the one or more user activities, a selection of the selectable tag causing a display of the social activity data associated with the message; and generating, by the one or more processors, graphical user interface data for displaying the social activity data associated with the message in response to the selectable tag being selected. 6. The method of claim 1 further comprising: generating one or more tags based at least in part on the one or more topics associated with the message; and generating the graphical user interface data for displaying the one or more tags.
| 0.647761 |
8,304,642 | 3 | 5 |
3. A lyric display method comprising the steps of: loading a body of lyrics data from at least one file or stream comprising lyrics data of at least one music piece, where either or both of said file or stream and said body of lyrics data comprises symbols that each identify a Distinct Lyric Block of said body of lyrics data; acquiring a sequence of performance comprising a list of symbols that each specify one of said symbols that each identify, where said symbols that each specify are in a predetermined order of planned performance; advancing from one sequence step to a next sequence step within said sequence of performance; ascertaining a specified symbol of said symbols that each identify as that symbol which is specified by the symbol at said next sequence step within said sequence of performance; ascertaining an identified Distinct Lyric Block of said body of lyrics data as that Distinct Lyric Block which is identified by said specified symbol; ascertaining a displayable portion of Distinct Lyric Block as either that which is a totality of said identified Distinct Lyric Block or else one of a plurality of consecutively displayed portions of said identified Distinct Lyric Block, where said consecutively displayed portions are determined according to predetermined criteria for amount of material to simultaneously display; displaying said displayable portion of Distinct Lyric Block.
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3. A lyric display method comprising the steps of: loading a body of lyrics data from at least one file or stream comprising lyrics data of at least one music piece, where either or both of said file or stream and said body of lyrics data comprises symbols that each identify a Distinct Lyric Block of said body of lyrics data; acquiring a sequence of performance comprising a list of symbols that each specify one of said symbols that each identify, where said symbols that each specify are in a predetermined order of planned performance; advancing from one sequence step to a next sequence step within said sequence of performance; ascertaining a specified symbol of said symbols that each identify as that symbol which is specified by the symbol at said next sequence step within said sequence of performance; ascertaining an identified Distinct Lyric Block of said body of lyrics data as that Distinct Lyric Block which is identified by said specified symbol; ascertaining a displayable portion of Distinct Lyric Block as either that which is a totality of said identified Distinct Lyric Block or else one of a plurality of consecutively displayed portions of said identified Distinct Lyric Block, where said consecutively displayed portions are determined according to predetermined criteria for amount of material to simultaneously display; displaying said displayable portion of Distinct Lyric Block. 5. The method of claim 3 , further comprising the steps of: accessing a first lyric portion from a first relative position within a first Distinct Lyric Block of said body of lyrics data, where said first relative position is a position of said first lyric portion relative to a start of said first Distinct Lyric Block; displaying said first lyric portion; accessing a corresponding portion of music notation data appropriate to said first lyric portion; creating a first adjusted version comprising notes of said corresponding portion newly positioned horizontally to align horizontally with syllables of words of said first lyric portion; displaying said first adjusted version; accessing a second lyric portion from said first relative position within a second Distinct Lyric Block of said body of lyrics data; displaying said second lyric portion; creating a second adjusted version comprising notes of said corresponding portion newly positioned horizontally to align horizontally with syllables of words of said second lyric portion; displaying said second adjusted version.
| 0.5 |
7,606,782 | 1 | 6 |
1. A computer-based enterprise knowledge management system that represents and stores business knowledge in a natural language and generates program source code or rules to implement said business knowledge for use in business practices, comprising: at least one user interface for receiving said business knowledge in one or more sentences in a natural language; at least one user interface interactively presenting one or more statements from a knowledge manager and one or more production rules from a generator to the user via the user interface; at least one computer-readable memory, containing: (a) said knowledge manager programmed to represent said business knowledge as said at least one statement comprising at least one relationship, said relationship instantiating at least one relation having at least one role and at least one concept filling said role, wherein the relationships are defined using semantic modeling, wherein said representation of said business knowledge is accomplished using the Rete algorithm; and (b) said knowledge manager programmed to process said relationships semantically and syntactically; (c) said generator in communication with said knowledge manager to generate computer program code or production rules that combine syntactic and semantic constraints for implementing said business knowledge; and at least one tangible computer-readable storage medium selected from the group consisting of a temporary memory system and a permanent memory system for storing said statement and said computer program code or production rules to be integrated with external object models and databases.
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1. A computer-based enterprise knowledge management system that represents and stores business knowledge in a natural language and generates program source code or rules to implement said business knowledge for use in business practices, comprising: at least one user interface for receiving said business knowledge in one or more sentences in a natural language; at least one user interface interactively presenting one or more statements from a knowledge manager and one or more production rules from a generator to the user via the user interface; at least one computer-readable memory, containing: (a) said knowledge manager programmed to represent said business knowledge as said at least one statement comprising at least one relationship, said relationship instantiating at least one relation having at least one role and at least one concept filling said role, wherein the relationships are defined using semantic modeling, wherein said representation of said business knowledge is accomplished using the Rete algorithm; and (b) said knowledge manager programmed to process said relationships semantically and syntactically; (c) said generator in communication with said knowledge manager to generate computer program code or production rules that combine syntactic and semantic constraints for implementing said business knowledge; and at least one tangible computer-readable storage medium selected from the group consisting of a temporary memory system and a permanent memory system for storing said statement and said computer program code or production rules to be integrated with external object models and databases. 6. The system of claim 1 , wherein each of said roles specifies one relationship for each of said concepts filling said role.
| 0.822443 |
9,899,021 | 11 | 12 |
11. The computer-implemented method of claim 6 , wherein at least one of the first or second costs is based at least partly on contextual information.
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11. The computer-implemented method of claim 6 , wherein at least one of the first or second costs is based at least partly on contextual information. 12. The computer-implemented method of claim 11 , wherein the contextual information corresponds to background sound or user tendencies.
| 0.5 |
8,666,757 | 27 | 28 |
27. The computer program product according to claim 26 , wherein payment is determined according to a payment function associated with the PPS.
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27. The computer program product according to claim 26 , wherein payment is determined according to a payment function associated with the PPS. 28. The computer program product according to claim 27 , wherein a PPS comprises a plurality of classification levels defining the payment, the plurality of classification levels comprising: a driving element level including a set of driving elements used to encode the service provider activity at a transactional level; a group level including a set of groups, each group mapping one or more driving elements to a particular payment rate; and a category level including a set of categories, each category being mapped to one or more of the groups according to predetermined industry classification schemes.
| 0.5 |
9,576,210 | 3 | 6 |
3. A computing device comprising: at least one processor; and a memory storing instructions which when executed the at least one processor to: identify edges in an image using an edge detection filter; identify a plurality of edge points of the image using the identified edges; determine respective first edge transition widths at each edge point of the plurality of edge points; determine a first statistic based on the first edge transition widths; determine a sharpness of the image based on the first statistic; process the image to identify text; determine, from the plurality of edge points, a set of edge points that are proximate to the text; determine respective second edge transition widths for each edge point of the set of edge points; determine a second statistic using the respective second edge transition widths; and perform optical character recognition on the text based on the second statistic.
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3. A computing device comprising: at least one processor; and a memory storing instructions which when executed the at least one processor to: identify edges in an image using an edge detection filter; identify a plurality of edge points of the image using the identified edges; determine respective first edge transition widths at each edge point of the plurality of edge points; determine a first statistic based on the first edge transition widths; determine a sharpness of the image based on the first statistic; process the image to identify text; determine, from the plurality of edge points, a set of edge points that are proximate to the text; determine respective second edge transition widths for each edge point of the set of edge points; determine a second statistic using the respective second edge transition widths; and perform optical character recognition on the text based on the second statistic. 6. The computing device of claim 3 , wherein an output of the edge detection filter comprises a first intensity gradient in a first direction for each point of the image and a second intensity gradient in a second direction for each point of the image, the first and second directions being perpendicular to each other, and the instructions to identify the edges configure the at least one processor to: combine the first intensity gradient and the second intensity gradient for each point of the image; wherein the edges are identified based on the combined intensity gradients.
| 0.5 |
8,379,801 | 25 | 28 |
25. A method, comprising: displaying a text caption on a communication device, the text caption corresponding to a text transcription of at least a portion of a voice signal of a conversation between at least two parties; receiving a corrected block of text for at least one block of text within the text caption; displaying the corrected block of text within the text caption as an inline correction during the conversation, such that the corrected block of text appears within the text caption in place of the at least one block of text; and indicating that the corrected block of text replaced the at least one block of text.
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25. A method, comprising: displaying a text caption on a communication device, the text caption corresponding to a text transcription of at least a portion of a voice signal of a conversation between at least two parties; receiving a corrected block of text for at least one block of text within the text caption; displaying the corrected block of text within the text caption as an inline correction during the conversation, such that the corrected block of text appears within the text caption in place of the at least one block of text; and indicating that the corrected block of text replaced the at least one block of text. 28. The method of claim 25 , wherein the corrected block of text is selected from the group consisting of at least one word, at least one sentence, and at least one line of text.
| 0.814583 |
8,291,014 | 10 | 11 |
10. The device of claim 8 , where the information associated with the plurality of second documents includes respective identifiers of the plurality of second documents.
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10. The device of claim 8 , where the information associated with the plurality of second documents includes respective identifiers of the plurality of second documents. 11. The device of claim 10 , where each of the identifiers comprises a uniform resource locator (URL) associated with a corresponding one of the plurality of second documents.
| 0.5 |
9,087,090 | 19 | 21 |
19. A system, comprising: at least one processor and at least one associated memory; a query processor that executes on the at least one processor and receives the query, wherein the query applies one or more qualitative search terms to an attribute of data items in a set of data items; and while executing the query, the query processor processes each data item in the set of data items by, extracting an attribute value from the data item, using a concept-mapping to determine a compatibility index for the attribute value, wherein the concept-mapping associates each attribute value with a numerical compatibility index that indicates a compatibility between the attribute value and the one or more qualitative search terms, wherein the concept mapping is represented using an array containing X and Y coordinate pairs describing a shape of a concept-mapping function, wherein using the concept-mapping to determine the compatibility index includes using the attribute value to perform a lookup in the array to retrieve the compatibility index, and using the compatibility index as a factor in determining whether to include the data item in a set of query results; and wherein when the query includes multiple qualitative search terms, the query processor, determines compatibility indices for the multiple qualitative search terms for each data item, combines the determined compatibility indices into an aggregate compatibility index for each data item, wherein combining the determined compatibility indices involves one of computing an average for the multiple compatibility indices, and computing a weighted average for the multiple compatibility indices based on an ordering of associated qualitative search terms in the query, and determines whether to include each data item in the set of query results based on whether the aggregate compatibility index for the data item meets or exceeds a threshold.
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19. A system, comprising: at least one processor and at least one associated memory; a query processor that executes on the at least one processor and receives the query, wherein the query applies one or more qualitative search terms to an attribute of data items in a set of data items; and while executing the query, the query processor processes each data item in the set of data items by, extracting an attribute value from the data item, using a concept-mapping to determine a compatibility index for the attribute value, wherein the concept-mapping associates each attribute value with a numerical compatibility index that indicates a compatibility between the attribute value and the one or more qualitative search terms, wherein the concept mapping is represented using an array containing X and Y coordinate pairs describing a shape of a concept-mapping function, wherein using the concept-mapping to determine the compatibility index includes using the attribute value to perform a lookup in the array to retrieve the compatibility index, and using the compatibility index as a factor in determining whether to include the data item in a set of query results; and wherein when the query includes multiple qualitative search terms, the query processor, determines compatibility indices for the multiple qualitative search terms for each data item, combines the determined compatibility indices into an aggregate compatibility index for each data item, wherein combining the determined compatibility indices involves one of computing an average for the multiple compatibility indices, and computing a weighted average for the multiple compatibility indices based on an ordering of associated qualitative search terms in the query, and determines whether to include each data item in the set of query results based on whether the aggregate compatibility index for the data item meets or exceeds a threshold. 21. The system of claim 19 , wherein the concept-mapping is a class-specific concept-mapping; and wherein prior to using the concept-mapping, the query processor is configured to select the concept-mapping based on class information obtained from one or more fields in the set of data items.
| 0.675947 |
10,067,563 | 1 | 3 |
1. A device, comprising: a gaze detector adapted to generate gaze information; and a user-interface controller adapted to: in response to the gaze information indicating that the user is gazing at the device, recognize an audio command uttered by the user, and provide a response to the audio command via the device; and in response to the gaze information indicating that the user is not gazing at the device, recognize an audio command uttered by the user, and route response information to a second device for presentation to the user.
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1. A device, comprising: a gaze detector adapted to generate gaze information; and a user-interface controller adapted to: in response to the gaze information indicating that the user is gazing at the device, recognize an audio command uttered by the user, and provide a response to the audio command via the device; and in response to the gaze information indicating that the user is not gazing at the device, recognize an audio command uttered by the user, and route response information to a second device for presentation to the user. 3. The device of claim 1 , wherein the user-interface controller is further adapted to: activate a set of audio inputs recognizable by the device in response to the gaze information indicating that the user is gazing at the device.
| 0.591873 |
8,079,023 | 1 | 4 |
1. A computer implemented method, comprising: processing a source code representation of a computer program in an object-oriented language into a high-level intermediate representation; and translating the high-level intermediate representation into a typed medium-level intermediate representation, comprising combining a name-based class name and corresponding structure-based record type into a combined class type, using an exact class name to represent objects of that class but not those of subclasses and the combined class type as an encoding of an existential type to represent objects of the class and subclasses of the class, and translating interface method invocation of an object by calling an interface method on the object when open, testing whether an object can be cast to a class, to an interface, to a class vector.
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1. A computer implemented method, comprising: processing a source code representation of a computer program in an object-oriented language into a high-level intermediate representation; and translating the high-level intermediate representation into a typed medium-level intermediate representation, comprising combining a name-based class name and corresponding structure-based record type into a combined class type, using an exact class name to represent objects of that class but not those of subclasses and the combined class type as an encoding of an existential type to represent objects of the class and subclasses of the class, and translating interface method invocation of an object by calling an interface method on the object when open, testing whether an object can be cast to a class, to an interface, to a class vector. 4. The method of claim 1 wherein translating the high-level intermediate representation further comprises: translating object type casting, including performing type checking, wherein types include virtual table types, type variables, runtime types, or existential types, or any combination thereof.
| 0.681237 |
10,002,189 | 29 | 51 |
29. A non-transitory computer readable storage medium containing an executable program for constructing database queries for searching a database, wherein the program is configured to cause at least one processor to perform the steps of: receiving a user entered search string, the search string comprising one or more words; identifying a first node in an ontology based on the one or more words of the search string, the first node being related to at least one of the one or more words in the search string, wherein the ontology includes at least one node representing a concept and at least one node representing an attribute of the concept; constructing a first database query based on the identified first node in the ontology, the first database query comprising one or more attributes associated with the first node, and a respective value, from the search string, for each of the one or more attributes; after constructing the first database query, searching at least one database using the first database query; identifying, based on a frequency of occurrence of a pair of user events, a second node in the ontology, the second node associated with the first node, the second additional node representing a concept not represented by the received search string, wherein a first user event of the pair of user events corresponds to the first node and a second user event of the pair of user events corresponds to the second node, and wherein for each occurrence of the pair of user events, the first user event and the second user event occur within a predetermined time period; constructing a second database query based on the identified second; after constructing the second database query, searching at least one database using the second database query; and outputting results of the searching.
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29. A non-transitory computer readable storage medium containing an executable program for constructing database queries for searching a database, wherein the program is configured to cause at least one processor to perform the steps of: receiving a user entered search string, the search string comprising one or more words; identifying a first node in an ontology based on the one or more words of the search string, the first node being related to at least one of the one or more words in the search string, wherein the ontology includes at least one node representing a concept and at least one node representing an attribute of the concept; constructing a first database query based on the identified first node in the ontology, the first database query comprising one or more attributes associated with the first node, and a respective value, from the search string, for each of the one or more attributes; after constructing the first database query, searching at least one database using the first database query; identifying, based on a frequency of occurrence of a pair of user events, a second node in the ontology, the second node associated with the first node, the second additional node representing a concept not represented by the received search string, wherein a first user event of the pair of user events corresponds to the first node and a second user event of the pair of user events corresponds to the second node, and wherein for each occurrence of the pair of user events, the first user event and the second user event occur within a predetermined time period; constructing a second database query based on the identified second; after constructing the second database query, searching at least one database using the second database query; and outputting results of the searching. 51. The computer readable storage medium of claim 29 , wherein the first node and the second node are identified prior to searching any database with either the first database query or the second database query.
| 0.84576 |
8,291,509 | 14 | 15 |
14. A computer program product for performing data analytics on outsourced data, the computer program product being tangibly embodied on a non-transitory computer-readable medium and including executable code that, when executed, is configured to cause a data processing apparatus to: generate a binary tree representing data from a data owner, wherein each node of the binary tree is associated with an identity that represents a data element or an interval of data elements; compute an identity token and encrypting the identity token for each of the identities in the binary tree; generate a range query token using an identity selected by a data analyst and a secret key input by the data owner and compute a decryption key for the selected identity; and analyze the data by comparing the computed decryption key for the selected identity with each of the encrypted identities.
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14. A computer program product for performing data analytics on outsourced data, the computer program product being tangibly embodied on a non-transitory computer-readable medium and including executable code that, when executed, is configured to cause a data processing apparatus to: generate a binary tree representing data from a data owner, wherein each node of the binary tree is associated with an identity that represents a data element or an interval of data elements; compute an identity token and encrypting the identity token for each of the identities in the binary tree; generate a range query token using an identity selected by a data analyst and a secret key input by the data owner and compute a decryption key for the selected identity; and analyze the data by comparing the computed decryption key for the selected identity with each of the encrypted identities. 15. The computer program product of claim 14 embodied on the non-transitory computer-readable medium further comprising executable code that, when executed, causes the data processing engine to generate an identity query token using an encrypted constant selected by the data analyst and the secret key input by the data owner and compute the identity query token.
| 0.5 |
8,666,992 | 1 | 2 |
1. A method of querying a remote service without revealing a private document to the remote service, comprising: at a main computer, receiving from a client a signature generated from a user's private document, without receiving the document; querying an intermediate database with the signature of the private document to generate an intermediate result set comprising intermediate database documents, based on a computation of similarity of the signatures of the intermediate database documents to the signature of the private document; computing a relevance factor for each document of the intermediate result set; computing a reconstruction error based on the relevance factors of all the documents in the intermediate result set and determining a confidence in the intermediate result set based on the reconstruction error; querying the remote service with a query which is based on the intermediate result set, whereby the user's private document and the signature of the private document are not revealed to the remote service; receiving a final result set from the remote service based on the query; and weighting the final result set based on the relevance factors.
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1. A method of querying a remote service without revealing a private document to the remote service, comprising: at a main computer, receiving from a client a signature generated from a user's private document, without receiving the document; querying an intermediate database with the signature of the private document to generate an intermediate result set comprising intermediate database documents, based on a computation of similarity of the signatures of the intermediate database documents to the signature of the private document; computing a relevance factor for each document of the intermediate result set; computing a reconstruction error based on the relevance factors of all the documents in the intermediate result set and determining a confidence in the intermediate result set based on the reconstruction error; querying the remote service with a query which is based on the intermediate result set, whereby the user's private document and the signature of the private document are not revealed to the remote service; receiving a final result set from the remote service based on the query; and weighting the final result set based on the relevance factors. 2. The method of claim 1 , wherein the private document comprises at least one of an image, a sound recording, and text.
| 0.865169 |
8,272,009 | 1 | 28 |
1. A method for use in connection with delivering assets to users of a broadcast network, the broadcast network primarily involving synchronized distribution of broadcast content to multiple users, the method comprising: receiving a broadcast content stream at a UED of a network user; receiving a subset of assets at the UED in conjunction with the broadcast content stream, the subset of assets identified by a network interface upstream in the broadcast network with respect to the UED by: monitoring textual information associated with said broadcast content stream; calculating a goodness of fit value for each of the assets according to a matching between the textual information and textual constraints associated with the assets; and identifying the subset of assets as having the highest respective goodness of fit values; determining targeting criteria corresponding to each of the subset of assets; selecting, at the UED, one of the subset of assets for an asset delivery spot as a function of the targeting criteria; and delivering the selected one of the subset of assets via the UED during the asset delivery spot.
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1. A method for use in connection with delivering assets to users of a broadcast network, the broadcast network primarily involving synchronized distribution of broadcast content to multiple users, the method comprising: receiving a broadcast content stream at a UED of a network user; receiving a subset of assets at the UED in conjunction with the broadcast content stream, the subset of assets identified by a network interface upstream in the broadcast network with respect to the UED by: monitoring textual information associated with said broadcast content stream; calculating a goodness of fit value for each of the assets according to a matching between the textual information and textual constraints associated with the assets; and identifying the subset of assets as having the highest respective goodness of fit values; determining targeting criteria corresponding to each of the subset of assets; selecting, at the UED, one of the subset of assets for an asset delivery spot as a function of the targeting criteria; and delivering the selected one of the subset of assets via the UED during the asset delivery spot. 28. The method of claim 1 , further comprising: determining a current channel being watched via the UED; and determining at least one of said non-textual targeting criteria according to the determined current channel.
| 0.830997 |
8,464,234 | 26 | 35 |
26. A non-transitory computer readable storage medium having code stored thereon that, when executed by one or more processors, causes the one or more processors to perform operations comprising: scanning one or more header files on a computing device into a tokenized form and scanning the tokenized form for one or more symbols and creating one or more preprocessor symbol tables based upon the one or more symbols; parsing the tokenized form on the computing device into one or more abstract syntax trees; creating one or more pre-parsed headers for the one or more header files, by: serializing in a modular form, the one or more abstract syntax trees to a storage device; serializing in a modular form the tokenized form to the storage device; and serializing in a modular form the one or more preprocessor symbol tables to the storage device; locating the one or more pre-parsed headers from the storage device based upon directives in one or more source files; deserializing the one or more abstract syntax trees from the pre-parsed headers on the computing device; and compiling the one or more source files using the one or more abstract syntax trees on the computing device.
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26. A non-transitory computer readable storage medium having code stored thereon that, when executed by one or more processors, causes the one or more processors to perform operations comprising: scanning one or more header files on a computing device into a tokenized form and scanning the tokenized form for one or more symbols and creating one or more preprocessor symbol tables based upon the one or more symbols; parsing the tokenized form on the computing device into one or more abstract syntax trees; creating one or more pre-parsed headers for the one or more header files, by: serializing in a modular form, the one or more abstract syntax trees to a storage device; serializing in a modular form the tokenized form to the storage device; and serializing in a modular form the one or more preprocessor symbol tables to the storage device; locating the one or more pre-parsed headers from the storage device based upon directives in one or more source files; deserializing the one or more abstract syntax trees from the pre-parsed headers on the computing device; and compiling the one or more source files using the one or more abstract syntax trees on the computing device. 35. The non-transitory computer readable storage medium of claim 26 , wherein the operations further comprise: locating the one or more pre-parsed headers from the storage device based upon directives in one or more source files; deserializing the one or more abstract syntax trees from the pre-parsed headers on the computing device; deserializing the tokenized form from the pre-parsed headers on the computing device; deserializing the one or more preprocessor symbol tables from the pre-parsed headers on the computing device; and compiling the one or more source files using the one or more abstract syntax trees, the one or more preprocessor symbol tables, and the tokenized form on the computing device.
| 0.5 |
8,335,689 | 1 | 2 |
1. A method to improve the speed and efficiency of human and computerized speech transcription through an automated transcription management system comprising: monitoring automatically the queue of transcription jobs to be worked; allocating automatically the transcription jobs across a pool of at least one of human computerized transcribing resources; monitoring automatically the performance of the current pool of at least one of human and computerized transcribing resources; creating automatically forecasts of expected future transcribing resource needs and, re-adjusting, by a computing device, automatically the use of currently active transcribing resources, pools of reserve transcribing resources, and recruitment of potential future transcribing resources to meet the transcription job forecasts.
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1. A method to improve the speed and efficiency of human and computerized speech transcription through an automated transcription management system comprising: monitoring automatically the queue of transcription jobs to be worked; allocating automatically the transcription jobs across a pool of at least one of human computerized transcribing resources; monitoring automatically the performance of the current pool of at least one of human and computerized transcribing resources; creating automatically forecasts of expected future transcribing resource needs and, re-adjusting, by a computing device, automatically the use of currently active transcribing resources, pools of reserve transcribing resources, and recruitment of potential future transcribing resources to meet the transcription job forecasts. 2. The method of claim 1 wherein the transcription management system reacts to one of current or expected future drops in transcription jobs by placing at least one of human and computerized transcribing resources into an off-duty state.
| 0.573741 |
8,812,966 | 1 | 9 |
1. A method comprising: generating a first configurator for a customizable product, wherein the generating the first configurator comprises performing the operations of creating a customizable product, wherein the customizable product comprises a set of one or more attributes, and the set of one or more attributes is configured to define, at least in part, the customizable product, assigning the customizable product to a customizable product class, wherein the customizable product class is a parent class of a hierarchy defining the first configurator, adding a component product class to the customizable product class, wherein the component product class is a subclass of the customizable product, adding a customizable class rule to the customizable product class, wherein the customizable class rule comprises one or more expressions, and the one or more expressions are configured to define one or more constraints on one or more component products added to the customizable product, and mapping a customizable user interface (UI) to the customizable product class, wherein the customizable UI is configured to provide access structure to the first configurator; and generating a second configurator for another customizable product, wherein the generating the second configurator comprises performing at least one of the operations on the another customizable product.
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1. A method comprising: generating a first configurator for a customizable product, wherein the generating the first configurator comprises performing the operations of creating a customizable product, wherein the customizable product comprises a set of one or more attributes, and the set of one or more attributes is configured to define, at least in part, the customizable product, assigning the customizable product to a customizable product class, wherein the customizable product class is a parent class of a hierarchy defining the first configurator, adding a component product class to the customizable product class, wherein the component product class is a subclass of the customizable product, adding a customizable class rule to the customizable product class, wherein the customizable class rule comprises one or more expressions, and the one or more expressions are configured to define one or more constraints on one or more component products added to the customizable product, and mapping a customizable user interface (UI) to the customizable product class, wherein the customizable UI is configured to provide access structure to the first configurator; and generating a second configurator for another customizable product, wherein the generating the second configurator comprises performing at least one of the operations on the another customizable product. 9. The method of claim 1 , wherein the component product class comprises a static attribute, and the static attribute is not associated with a parent class.
| 0.922388 |
9,965,567 | 3 | 4 |
3. The method of claim 1 , wherein the single publication element is assigned to a single section of the first layout.
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3. The method of claim 1 , wherein the single publication element is assigned to a single section of the first layout. 4. The method of claim 3 , wherein the first publication template is configured to display only one of the two or more content components in the single section of the first layout.
| 0.5 |
7,849,496 | 1 | 2 |
1. Within a system comprising a processor and a memory, a method of administering online communities within an online community management system comprising: declaratively specifying, via the processor, a taxonomy of online community types; declaratively specifying, via the processor, a plurality of roles for members of online communities; declaratively specifying, via the processor, a security policy that associates permissions with roles and online community types; maintaining, via the processor, a plurality of online community profiles, wherein each online community profile represents an online community, specifies an online community type from the taxonomy, and specifies a list of members of the online community and an associated role for each member; and providing, via the processor, access to a selected online community according to the online community type of the selected online community, a role within the selected online community associated with a user attempting to access the selected online community, and the security policy.
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1. Within a system comprising a processor and a memory, a method of administering online communities within an online community management system comprising: declaratively specifying, via the processor, a taxonomy of online community types; declaratively specifying, via the processor, a plurality of roles for members of online communities; declaratively specifying, via the processor, a security policy that associates permissions with roles and online community types; maintaining, via the processor, a plurality of online community profiles, wherein each online community profile represents an online community, specifies an online community type from the taxonomy, and specifies a list of members of the online community and an associated role for each member; and providing, via the processor, access to a selected online community according to the online community type of the selected online community, a role within the selected online community associated with a user attempting to access the selected online community, and the security policy. 2. The method of claim 1 , further comprising linking, via the processor, a permission of a selected online community with a role defined by a system that is external to the selected online community.
| 0.692308 |
7,831,529 | 16 | 19 |
16. A method to facilitate communications in an automated communications system, comprising: receiving one or more items and processing the one or more items via learning algorithms to direct the one or more items to a user; receiving, via at least one user interface, one or more user inputs to at least one of control, adjust and tune values of a plurality of attributes associated with the one or more items representing user preferences regarding computing a priority score for directing the one or more items to the user, wherein the at least one user interface allows the user to adjust a value of the priority score based on adjusting the values of the plurality of attributes; and directing delivery of the one or more items to the user based on the priority score.
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16. A method to facilitate communications in an automated communications system, comprising: receiving one or more items and processing the one or more items via learning algorithms to direct the one or more items to a user; receiving, via at least one user interface, one or more user inputs to at least one of control, adjust and tune values of a plurality of attributes associated with the one or more items representing user preferences regarding computing a priority score for directing the one or more items to the user, wherein the at least one user interface allows the user to adjust a value of the priority score based on adjusting the values of the plurality of attributes; and directing delivery of the one or more items to the user based on the priority score. 19. The method of claim 16 , further comprising at least one selected from the group consisting of defining static groups, defining dynamic groups, defining groups by a relationship within an organizational structure, defining groups by communications history, defining groups by past associations, defining groups by frequency of contact, defining groups by meetings and appointments, and defining groups by projects.
| 0.5 |
7,490,092 | 25 | 56 |
25. A method of indexing and searching timed media files, as recited in claim 1 , wherein said calculation includes the processing of language contained within the timed media file.
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25. A method of indexing and searching timed media files, as recited in claim 1 , wherein said calculation includes the processing of language contained within the timed media file. 56. A method of indexing and searching timed media files, as recited in claim 25 , further comprising the step of calculating a centrality number for at least one occurrence of at least one information representation contained within the timed media file.
| 0.5 |
8,880,516 | 1 | 11 |
1. A computer-implemented method comprising: receiving a first search query from a first member of a member network; responding to the first search query with a first result set that is based on the first search query and that comprises a plurality of electronic articles and, for one or more electronic articles of the plurality of electronic articles, rating information that corresponds to the one or more electronic articles, and a rating system control that corresponds to a particular one of the plurality of electronic articles, wherein the rating system control is a selectable item adapted to receive an endorsement rating regarding the corresponding particular one of the plurality of electronic articles, and wherein the rating information comprises text or indicia that indicates a prior selection by one or more members of the member network of rating system controls corresponding to the one or more electronic articles of the plurality of electronic articles; receiving a selection, by the first member, of the rating system control that corresponds to the particular one of the plurality of electronic articles; updating, based on the received selection of the rating system control that corresponds to the particular one of the plurality of electronic articles, the rating information that corresponds to the particular one of the plurality of electronic articles; receiving a second search query from a second member of the member network; and responding to the second search query with a second result set based on the second search query, wherein the second result set comprises the particular one of the plurality of electronic articles and, based on the second member's membership in the member network, the second result set comprises the updated rating information that corresponds to the particular one of the plurality of electronic articles.
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1. A computer-implemented method comprising: receiving a first search query from a first member of a member network; responding to the first search query with a first result set that is based on the first search query and that comprises a plurality of electronic articles and, for one or more electronic articles of the plurality of electronic articles, rating information that corresponds to the one or more electronic articles, and a rating system control that corresponds to a particular one of the plurality of electronic articles, wherein the rating system control is a selectable item adapted to receive an endorsement rating regarding the corresponding particular one of the plurality of electronic articles, and wherein the rating information comprises text or indicia that indicates a prior selection by one or more members of the member network of rating system controls corresponding to the one or more electronic articles of the plurality of electronic articles; receiving a selection, by the first member, of the rating system control that corresponds to the particular one of the plurality of electronic articles; updating, based on the received selection of the rating system control that corresponds to the particular one of the plurality of electronic articles, the rating information that corresponds to the particular one of the plurality of electronic articles; receiving a second search query from a second member of the member network; and responding to the second search query with a second result set based on the second search query, wherein the second result set comprises the particular one of the plurality of electronic articles and, based on the second member's membership in the member network, the second result set comprises the updated rating information that corresponds to the particular one of the plurality of electronic articles. 11. The method of claim 1 , further comprising providing, with the second local result set presentation for the updated rating information, an identifier that corresponds to the first member.
| 0.685855 |
9,588,678 | 10 | 17 |
10. An electronic device for recognizing handwriting, comprising: at least one of a touch device configured to receive a handwriting strokes; a storage configured to store information comprising the at least one handwriting stroke; and a controller configured to: determine text regions corresponding to at least two handwriting strokes, calculate each size of text regions, determine whether the text regions overlap each other, select a specific text region among the text regions into an excluding strokes group based on at least one of the size of the specific text region, a ratio of an overlap region between the specific text region and other text regions to the specific text region, and a number of overlap regions between the specific text region and other text regions, and recognize characters of the text regions except for the excluding strokes group.
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10. An electronic device for recognizing handwriting, comprising: at least one of a touch device configured to receive a handwriting strokes; a storage configured to store information comprising the at least one handwriting stroke; and a controller configured to: determine text regions corresponding to at least two handwriting strokes, calculate each size of text regions, determine whether the text regions overlap each other, select a specific text region among the text regions into an excluding strokes group based on at least one of the size of the specific text region, a ratio of an overlap region between the specific text region and other text regions to the specific text region, and a number of overlap regions between the specific text region and other text regions, and recognize characters of the text regions except for the excluding strokes group. 17. The electronic device of claim 10 , wherein the controller is configured to: obtain time information on when overlapped handwriting strokes are written; and group the overlapped handwriting strokes based on the time information.
| 0.7277 |
9,483,591 | 1 | 4 |
1. A computer-implemented method for assuring a reliability of a chip comprising: retrieving a design netlist with a processor; identifying, via the processor, a logic structure in the design netlist; generating, via the processor, a driver based on the logic structure, wherein generating the driver based on the logic structure comprises: verifying a parity; traversing a netlist back from a plurality of netlist outputs; identifying one or more parity protected structures and one or more gates, wherein protected parity structures comprises a duplication protection; and generating an assertion indicative of a parity validity; applying, via the processor, a simulation and a formal model based on the driver; and testing, via the processor, an output of the simulation and the formal model.
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1. A computer-implemented method for assuring a reliability of a chip comprising: retrieving a design netlist with a processor; identifying, via the processor, a logic structure in the design netlist; generating, via the processor, a driver based on the logic structure, wherein generating the driver based on the logic structure comprises: verifying a parity; traversing a netlist back from a plurality of netlist outputs; identifying one or more parity protected structures and one or more gates, wherein protected parity structures comprises a duplication protection; and generating an assertion indicative of a parity validity; applying, via the processor, a simulation and a formal model based on the driver; and testing, via the processor, an output of the simulation and the formal model. 4. The computer-implemented method of claim 1 wherein traversing a netlist back from a plurality of netlist outputs; identifying one or more parity protected structures and one or more gates, wherein protected parity structures comprise a onehot protection.
| 0.547535 |
8,769,242 | 1 | 20 |
1. A system for translation map simplification, comprising: a processor; a translation engine operable on the processor, wherein the translation engine comprises: a module to determine a translation map based on a predetermined criterion in response to receiving input data, the translation map being configured for translating the input data from a first format or data model to a second format or data model that is presented in a new map; a module to load the translation map; a module to determine if the translation map extends another map, the other map comprising a referenced map; a module to determine if the translation map comprises at least one map fragment; a module to load the referenced map in response to a determination that the translation map comprises an extension of the referenced map; a module to load the at least one map fragment in response to a determination that the translation map comprises the at least one map fragment; and wherein the system further comprises a compiler operable on the processor to compile the new map based on combining at least the translation map, the referenced map and the at least one map fragment, in response to the translation map not including at least one of a new map reference and a modification to the translation map, and wherein the input data is processed based on the new map to produce translated data specific to the new map.
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1. A system for translation map simplification, comprising: a processor; a translation engine operable on the processor, wherein the translation engine comprises: a module to determine a translation map based on a predetermined criterion in response to receiving input data, the translation map being configured for translating the input data from a first format or data model to a second format or data model that is presented in a new map; a module to load the translation map; a module to determine if the translation map extends another map, the other map comprising a referenced map; a module to determine if the translation map comprises at least one map fragment; a module to load the referenced map in response to a determination that the translation map comprises an extension of the referenced map; a module to load the at least one map fragment in response to a determination that the translation map comprises the at least one map fragment; and wherein the system further comprises a compiler operable on the processor to compile the new map based on combining at least the translation map, the referenced map and the at least one map fragment, in response to the translation map not including at least one of a new map reference and a modification to the translation map, and wherein the input data is processed based on the new map to produce translated data specific to the new map. 20. The system of claim 1 , further comprising a module that links a component in the first format or data model to a corresponding component in the second format or data model by a line in the new map.
| 0.637993 |
9,607,081 | 6 | 7 |
6. The method of claim 1 , wherein the comparing includes determining a degree of similarity between a user-specific ontology of the one or more user-specific ontologies and the plurality of defined ontologies.
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6. The method of claim 1 , wherein the comparing includes determining a degree of similarity between a user-specific ontology of the one or more user-specific ontologies and the plurality of defined ontologies. 7. The method of claim 6 , further including: selecting a defined ontology of the plurality of ontologies having the highest degree of similarity to the user-specific ontology; and determining a category corresponding to the selected defined ontology, wherein the categorizing the user includes categorizing the user as a member of the determined category.
| 0.5 |
6,044,343 | 22 | 29 |
22. A speech recognition method comprising the steps of: processing first speech input signal data to preclassify the speech input signal and produce first preclassification output data, wherein the first speech input signal data represents a speech input signal; processing second speech input signal data to preclassify the speech input signal and produce second preclassification output data; determining when to include the first speech input signal, the second speech input signal, and a combination of the first and second speech input signals in a preferred mix of the preclassification output data by determining at least an appropriate balance between speech recognition accuracy and a speech recognition processing speed; mixing the first and second preclassification output data in accordance with the preferred mix; and classifying the speech input signal based on the preferred mix of preclassification output data.
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22. A speech recognition method comprising the steps of: processing first speech input signal data to preclassify the speech input signal and produce first preclassification output data, wherein the first speech input signal data represents a speech input signal; processing second speech input signal data to preclassify the speech input signal and produce second preclassification output data; determining when to include the first speech input signal, the second speech input signal, and a combination of the first and second speech input signals in a preferred mix of the preclassification output data by determining at least an appropriate balance between speech recognition accuracy and a speech recognition processing speed; mixing the first and second preclassification output data in accordance with the preferred mix; and classifying the speech input signal based on the preferred mix of preclassification output data. 29. The speech recognition method of claim 22 wherein second speech input signal data is an observation sequence of indices of relative closeness of a representation of the speech input signal to codewords in a reference codebook, and the step of processing second speech input signal data comprises the step of: determining with a fuzzy Viterbi algorithm a respective probability for each of u hidden Markov models that the hidden Markov model produced the observation sequence, wherein the second preclassification output data are the u determined respective probabilities.
| 0.713645 |
7,644,281 | 11 | 13 |
11. A method for extracting a digital watermark ŵ from textual and/or vector graphics documents of electronic and/or hard-copy form based on the modulation of luminance or grayscale values, of color values, or of halftone patterns of characters or of vector elements, wherein the watermarked and potentially distorted or attacked document {hacek over (y)}′ is segmented, processed and the watermark extracted as ŵ, the codeword ĉ estimated, and the message {circumflex over (m)} decoded, the method comprising the steps of (a) applying document segmentation to the watermarked document {hacek over (y)}′, including the selection of documents text and/or vector graphics components y text , (b) extracting the potentially modulated elements from the text and/or vector graphics components, including performing character and/or elements segmentation for text and/or vector graphics documents, (c) estimating the watermark signal ŵ from the modulated grayscale, color and/or halftone pattern attributes, (d) generating a pilot signal; estimating and compensating the extracted watermark ŵ state and desynchronization, based on the pilot signal, resulting into the estimated codeword ĉ; decoding the codeword ĉ resulting into the final message {circumflex over (m)}.
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11. A method for extracting a digital watermark ŵ from textual and/or vector graphics documents of electronic and/or hard-copy form based on the modulation of luminance or grayscale values, of color values, or of halftone patterns of characters or of vector elements, wherein the watermarked and potentially distorted or attacked document {hacek over (y)}′ is segmented, processed and the watermark extracted as ŵ, the codeword ĉ estimated, and the message {circumflex over (m)} decoded, the method comprising the steps of (a) applying document segmentation to the watermarked document {hacek over (y)}′, including the selection of documents text and/or vector graphics components y text , (b) extracting the potentially modulated elements from the text and/or vector graphics components, including performing character and/or elements segmentation for text and/or vector graphics documents, (c) estimating the watermark signal ŵ from the modulated grayscale, color and/or halftone pattern attributes, (d) generating a pilot signal; estimating and compensating the extracted watermark ŵ state and desynchronization, based on the pilot signal, resulting into the estimated codeword ĉ; decoding the codeword ĉ resulting into the final message {circumflex over (m)}. 13. The method of claim 11 wherein, if the watermarked and potentially distorted or attacked document is available only in hard-copy form {hacek over (y)}′ b , the method further comprises, first, the step of acquiring the printed document {hacek over (y)}′ b resulting into the document raw image y′, and/or the step of prefiltering this image y′ for better processing accuracy for the following steps; wherein it uses any acquisition device to acquire the hard-copy document including each member of the group formed of a flat-bedded or hand-held scanner, a camera, the camera of a mobile phone, or any other imaging acquisition device.
| 0.748224 |
8,135,675 | 4 | 5 |
4. The method of claim 3 , further comprising running the campaign query on one of the replication servers in each of the server groups in parallel so that the campaign query runs on all of the plurality of server groups.
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4. The method of claim 3 , further comprising running the campaign query on one of the replication servers in each of the server groups in parallel so that the campaign query runs on all of the plurality of server groups. 5. The method of claim 4 , further comprising sending a periodic batch progress update to the application server at each of the plurality of server groups.
| 0.5 |
9,940,933 | 1 | 6 |
1. A processor implemented speech recognition method, comprising: receiving a recognized sentence generated through speech recognition; evaluating the sentence by calculating a degree of suitability for each word in the sentence that takes into consideration a relationship of each word with other words in the sentence; selecting, by the processor and based on the calculated degrees of suitability, a target word to be corrected among words in the sentence; sampling candidate words, dependent on the selecting of the target word, considering relationships between the words of the sentence and a position of the target word; selecting, by the processor and dependent on the sampling of the candidate words, at least one of the sampled candidate words based on processor evaluated suitabilities of the sampled candidate words; and respectively revising the sentence by replacing the target word with the selected at least one sampled candidate word, wherein the respective revising of the sentence further includes evaluating the respectively revised sentence to determine whether to select another target word of the respectively revised sentence to be corrected before generating a final recognition sentence.
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1. A processor implemented speech recognition method, comprising: receiving a recognized sentence generated through speech recognition; evaluating the sentence by calculating a degree of suitability for each word in the sentence that takes into consideration a relationship of each word with other words in the sentence; selecting, by the processor and based on the calculated degrees of suitability, a target word to be corrected among words in the sentence; sampling candidate words, dependent on the selecting of the target word, considering relationships between the words of the sentence and a position of the target word; selecting, by the processor and dependent on the sampling of the candidate words, at least one of the sampled candidate words based on processor evaluated suitabilities of the sampled candidate words; and respectively revising the sentence by replacing the target word with the selected at least one sampled candidate word, wherein the respective revising of the sentence further includes evaluating the respectively revised sentence to determine whether to select another target word of the respectively revised sentence to be corrected before generating a final recognition sentence. 6. The method of claim 1 , further comprising performing the evaluating of the suitabilities of the sampled candidate words, including calculating a degree of suitability for each of the sampled candidate words based on either one or both of an acoustic model that considers a determined degree of similarity for each of the sampled candidate words with respect to a phoneme sequence of the target word and a context based linguistic model that considers respective bi-directional relationships of the sampled candidate words with the other words in the sentence exclusive of the target word.
| 0.5 |
9,613,267 | 1 | 4 |
1. A computer implemented method of extracting structural label and value pairwise data associated with a digital version of a document, the method comprising: a) performing a layout analysis of the digital version of the document to generate one or more layout structures associated with the document, each layout structure including a plurality of structural elements vertically or horizontally aligned where each structural element is defined as a typographical box including one or more lines of textual elements associated with the digital version of the document; b) processing the one or more lines of textual elements to identify and tag textual elements associated with label and value pairwise data; c) processing the one or more layout structures and associated tagged textual elements to generate one or more respective label:value sequences of tagged textual elements representative of a respective layout structure; and d) extracting label and value pairwise data from the one or more label:value sequences of tagged elements, wherein step c) generates the one or more respective label:value sequences of tagged textual element using a sequence-based method to hierarchically segment a sequence of elements associated with the generated one or more layout structures associated with the digital version of the document; and wherein the sequence-based method includes: generating a set of n-prams from the sequence of elements, an n-gram including an ordered sequence of n features provided by a sequence of n named elements; electing sequential n-grams from the set of n-grams, the sequential n-grams defined as similar contiguous n-grams; selecting a most frequent sequential n-pram from the elected sequential n-grams; and generating a new sequence of the elements by matching the selected most frequent sequential n-gram against the sequence of elements associated with the document, replacing matched elements of the sequence of elements with a respective node, and associating the matched elements of the sequence of elements as children of the respective node.
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1. A computer implemented method of extracting structural label and value pairwise data associated with a digital version of a document, the method comprising: a) performing a layout analysis of the digital version of the document to generate one or more layout structures associated with the document, each layout structure including a plurality of structural elements vertically or horizontally aligned where each structural element is defined as a typographical box including one or more lines of textual elements associated with the digital version of the document; b) processing the one or more lines of textual elements to identify and tag textual elements associated with label and value pairwise data; c) processing the one or more layout structures and associated tagged textual elements to generate one or more respective label:value sequences of tagged textual elements representative of a respective layout structure; and d) extracting label and value pairwise data from the one or more label:value sequences of tagged elements, wherein step c) generates the one or more respective label:value sequences of tagged textual element using a sequence-based method to hierarchically segment a sequence of elements associated with the generated one or more layout structures associated with the digital version of the document; and wherein the sequence-based method includes: generating a set of n-prams from the sequence of elements, an n-gram including an ordered sequence of n features provided by a sequence of n named elements; electing sequential n-grams from the set of n-grams, the sequential n-grams defined as similar contiguous n-grams; selecting a most frequent sequential n-pram from the elected sequential n-grams; and generating a new sequence of the elements by matching the selected most frequent sequential n-gram against the sequence of elements associated with the document, replacing matched elements of the sequence of elements with a respective node, and associating the matched elements of the sequence of elements as children of the respective node. 4. The computer implemented method of extracting structured label and value pairwise data according to claim 1 , wherein prior to step a) text extraction and graphical segment extraction are performed on the digital document.
| 0.700798 |
8,176,119 | 13 | 17 |
13. A system comprising: a computer; a content viewer operably installed on the computer; and a content object accessible to the computer via the content viewer, the content object including a content viewer readable code component, the content viewer readable code component including dynamically selectable characteristics, the content viewer readable code component being useable with a plurality of different content viewers, the content viewer readable code component changing a portion of the content object upon execution of the content viewer readable code component without altering the remainder of the content object.
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13. A system comprising: a computer; a content viewer operably installed on the computer; and a content object accessible to the computer via the content viewer, the content object including a content viewer readable code component, the content viewer readable code component including dynamically selectable characteristics, the content viewer readable code component being useable with a plurality of different content viewers, the content viewer readable code component changing a portion of the content object upon execution of the content viewer readable code component without altering the remainder of the content object. 17. The system as claimed in claim 13 wherein the portion of the content object changed upon execution of the content viewer readable code component includes an audio clip.
| 0.609091 |
9,465,996 | 15 | 16 |
15. A media device, comprising: a memory medium that stores a recording of a media content event as the media content event is being received in a media content stream by the media device; a system clock that outputs real time; a memory that stores at least a recording end time of the media content event that is being recorded; and a processor system that is communicatively coupled to the memory medium, the system clock, and the memory, wherein the processor system performs: determining a closing credits monitor time, wherein the closing credits monitor time is a predefined duration before the recording end time; comparing the real time output from the system clock with the closing credits monitor time; analyzing a plurality of received image frames after the real time reaches the closing credits monitor time to identify text presented in one of the analyzed image frames in response to detecting the real time reaches the closing credits monitor time; identifying at least one attribute pertaining to the identified text; comparing the at least one attribute with a corresponding predefined closing credits attribute stored in a closing credits database; determining that the identified text corresponds to closing credits of the media content event in response to the at least one attribute matches the corresponding predefined closing credits attribute; and initiating an end of the recording of the media content event in response to determining that the identified text corresponds to the closing credits of the media content event.
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15. A media device, comprising: a memory medium that stores a recording of a media content event as the media content event is being received in a media content stream by the media device; a system clock that outputs real time; a memory that stores at least a recording end time of the media content event that is being recorded; and a processor system that is communicatively coupled to the memory medium, the system clock, and the memory, wherein the processor system performs: determining a closing credits monitor time, wherein the closing credits monitor time is a predefined duration before the recording end time; comparing the real time output from the system clock with the closing credits monitor time; analyzing a plurality of received image frames after the real time reaches the closing credits monitor time to identify text presented in one of the analyzed image frames in response to detecting the real time reaches the closing credits monitor time; identifying at least one attribute pertaining to the identified text; comparing the at least one attribute with a corresponding predefined closing credits attribute stored in a closing credits database; determining that the identified text corresponds to closing credits of the media content event in response to the at least one attribute matches the corresponding predefined closing credits attribute; and initiating an end of the recording of the media content event in response to determining that the identified text corresponds to the closing credits of the media content event. 16. The media device of claim 15 , wherein the corresponding predefined closing credits attribute is based on the closing credits of the media content event being recorded, wherein the media content event being recorded is uniquely identifiable by an identifier, and further comprising: a communication system interface communicatively couples the media device to an electronic device having a remote closing credits database via a communication network, wherein the media device communicates a request to receive the corresponding predefined closing credits attribute, wherein the request from the media device includes the identifier of the media content event being recorded, wherein the electronic device accesses the corresponding predefined closing credits attribute from the remote closing credits database based on the unique identifier of the media content event being recorded, and wherein the media device receives the corresponding predefined closing credits attribute associated with the media content event being recorded from the electronic device.
| 0.5 |
8,838,605 | 29 | 30 |
29. The program storage device of claim 16 further comprising: specifying a weight for each node; and determining a weight for each of the plurality of communities.
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29. The program storage device of claim 16 further comprising: specifying a weight for each node; and determining a weight for each of the plurality of communities. 30. The program storage device of claim 29 , further comprising modifying the weight for each node, and determining a modified weight for each of the plurality of communities.
| 0.5 |
7,703,028 | 15 | 16 |
15. A computer-implemented method, said computer including a processor and having a graphical display that includes at least two objects, said graphical display showing a relationship between said at least two objects, said method comprising: splitting said graphical display into a left area forming a left rectangle, a center area forming a center rectangle, and a right area forming a right rectangle; displaying a star schema in said graphical display by displaying at least one dimension object including at least one dimension table that includes attribute data in said left area, a facts object including a facts table that includes measurement data in said center area, and at least one additional dimension object including at least one dimension table that includes attribute data in said right area, wherein said at least one object in each area is manipulated independently of said other objects in said each area and said at least one object in each other area; displaying in at least one area said at least two objects in said graphical display; accepting input that reduces at least one of said at least two objects in one area; and in response to reducing said at least one object in said one area; reducing said display of said one area that includes said reduced at least one object; moving and realigning vertically and horizontally at least one of said at least two objects that is not reduced relative to said reduced at least one object in said reduced area thereby showing said relationship between said at least two objects; moving said display of said each other area in response to reduction of the display of said reduced area on the graphical device; realigning said objects in said each other area with the realigned other objects within said reduced area, wherein positions of said objects in said each other area are adjusted in at least one of a horizontal direction and a vertical direction to accommodate movement and alignment of at least one of said at least two objects that is not reduced; and displaying said relationship on said graphical display by including at least one connecting line that connects said at least one object in said reduced area with said at least one object that is not included in said reduced area.
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15. A computer-implemented method, said computer including a processor and having a graphical display that includes at least two objects, said graphical display showing a relationship between said at least two objects, said method comprising: splitting said graphical display into a left area forming a left rectangle, a center area forming a center rectangle, and a right area forming a right rectangle; displaying a star schema in said graphical display by displaying at least one dimension object including at least one dimension table that includes attribute data in said left area, a facts object including a facts table that includes measurement data in said center area, and at least one additional dimension object including at least one dimension table that includes attribute data in said right area, wherein said at least one object in each area is manipulated independently of said other objects in said each area and said at least one object in each other area; displaying in at least one area said at least two objects in said graphical display; accepting input that reduces at least one of said at least two objects in one area; and in response to reducing said at least one object in said one area; reducing said display of said one area that includes said reduced at least one object; moving and realigning vertically and horizontally at least one of said at least two objects that is not reduced relative to said reduced at least one object in said reduced area thereby showing said relationship between said at least two objects; moving said display of said each other area in response to reduction of the display of said reduced area on the graphical device; realigning said objects in said each other area with the realigned other objects within said reduced area, wherein positions of said objects in said each other area are adjusted in at least one of a horizontal direction and a vertical direction to accommodate movement and alignment of at least one of said at least two objects that is not reduced; and displaying said relationship on said graphical display by including at least one connecting line that connects said at least one object in said reduced area with said at least one object that is not included in said reduced area. 16. The computer-implemented method of claim 15 , further comprising aligning said at least one moved object within said other area.
| 0.813559 |
8,261,196 | 1 | 2 |
1. A method of displaying search results and usage metrics for a search of one or more documents that a user has opened and had in focus, the method comprising: monitoring documents that the user has opened and had in focus, wherein a document being opened by the user and in focus of the user includes a document relative to which an operation has been performed by the user within a predetermined time interval; storing, on a workstation of a user, an index that includes entries for only monitored documents that the user has opened and had in focus, wherein an index entry is created or modified for each of the monitored documents only in response to the user having opened and had in focus that monitored document, wherein only the user has performed an operation relative to that monitored document within the predetermined time interval; receiving, from the user, a request to search said index; presenting a user interface, said user interface displaying search results including a listing of documents from the monitored documents and one or more graphical visualizations characterizing the search results in the listing of documents, wherein documents in the listing includes documents relative to each of which an operation has been performed by the user within the predetermined time interval; receiving, from the user, an input instruction to display usage metrics for a selected one of said documents in the listing of documents; and updating said user interface to display said usage metrics, wherein said usage metrics include a total amount of time the user had a selected document opened and in focus, wherein the total amount of time the user has spent on the selected document when the selected document is open and in focus includes one or more instances when the user has performed an operation relative to the selected document within the predetermined time interval.
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1. A method of displaying search results and usage metrics for a search of one or more documents that a user has opened and had in focus, the method comprising: monitoring documents that the user has opened and had in focus, wherein a document being opened by the user and in focus of the user includes a document relative to which an operation has been performed by the user within a predetermined time interval; storing, on a workstation of a user, an index that includes entries for only monitored documents that the user has opened and had in focus, wherein an index entry is created or modified for each of the monitored documents only in response to the user having opened and had in focus that monitored document, wherein only the user has performed an operation relative to that monitored document within the predetermined time interval; receiving, from the user, a request to search said index; presenting a user interface, said user interface displaying search results including a listing of documents from the monitored documents and one or more graphical visualizations characterizing the search results in the listing of documents, wherein documents in the listing includes documents relative to each of which an operation has been performed by the user within the predetermined time interval; receiving, from the user, an input instruction to display usage metrics for a selected one of said documents in the listing of documents; and updating said user interface to display said usage metrics, wherein said usage metrics include a total amount of time the user had a selected document opened and in focus, wherein the total amount of time the user has spent on the selected document when the selected document is open and in focus includes one or more instances when the user has performed an operation relative to the selected document within the predetermined time interval. 2. The method of claim 1 wherein receiving the input instruction further comprises receiving a mouse click action, from the user, and wherein updating said user interface further comprises: presenting a pop-up window displaying said usage metrics.
| 0.69125 |
9,558,267 | 14 | 18 |
14. A system comprising: at least a processor and a memory configured for: mining user related content information, wherein the information is mined from an information repository; filtering the mined user related content information from the information repository, wherein the filtering comprises identifying a subset of the mined user related content information comprising information related to a predetermined category; identifying, using a cosine similarity measure, a plurality of words having a similarity to a seed set of words by analyzing the subset using a plurality of analyzers, wherein each analyzer is configured to capture a plurality of representational variations, from the information repository, related to the seed set of words; classifying, based on the analyzing, the plurality of representational variations, wherein the classifying comprises ranking the filtered user related content information; combining the classified plurality of representational variations of the user content information from each of the plurality of analyzers, wherein the combining comprises identifying a relevancy of a representational variation to a user intent based upon the ranking of the filtered user related content information; and training a classifier for characterizing real-time intention content from information repositories using the combined plurality of representational variations.
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14. A system comprising: at least a processor and a memory configured for: mining user related content information, wherein the information is mined from an information repository; filtering the mined user related content information from the information repository, wherein the filtering comprises identifying a subset of the mined user related content information comprising information related to a predetermined category; identifying, using a cosine similarity measure, a plurality of words having a similarity to a seed set of words by analyzing the subset using a plurality of analyzers, wherein each analyzer is configured to capture a plurality of representational variations, from the information repository, related to the seed set of words; classifying, based on the analyzing, the plurality of representational variations, wherein the classifying comprises ranking the filtered user related content information; combining the classified plurality of representational variations of the user content information from each of the plurality of analyzers, wherein the combining comprises identifying a relevancy of a representational variation to a user intent based upon the ranking of the filtered user related content information; and training a classifier for characterizing real-time intention content from information repositories using the combined plurality of representational variations. 18. The system as claimed in claim 14 , wherein said analyzing comprises analyzing in parallel the mined user related content information from the information repository by each of a plurality of analyzers, and wherein said combining comprises assigning weights to the classified plurality of representational variations of the user related content information from each of the plurality of analyzers, and wherein said combining further comprises summing the weighted classified plurality of representational variations of the user related content information from each of the plurality of analyzers.
| 0.5 |
8,165,878 | 1 | 10 |
1. A computer system method for matching an utterance of a user to a template comprising the steps of: (a) receiving by a processor the utterance from an input device, wherein the utterance includes at least one word; (b) accessing a set of template hierarchies from a database, wherein the set includes at least one template; (c) comparing by the processor the at least one word of the utterance to the at least one term of a template hierarchy in the set of template hierarchies; (d) determining by the processor whether the at least one word of the utterance matches the at least one term of the template hierarchy; (e) calculating by the processor a score based on the match between the at least one word of the utterance and the at least one term of the template hierarchy; (f) repeating steps (c)-(e) until there are no more words of the utterance for said comparing step; (g) populating the at least one template with at least one data element corresponding to the at least one term of the template hierarchy to obtain a populated template; (h) computing a total score based on the match between all words of the utterance to the populated template; (i) selecting by the processor the at least one template with the highest total score; (j) recording the populated template; and (k) communicating the populated template to the user.
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1. A computer system method for matching an utterance of a user to a template comprising the steps of: (a) receiving by a processor the utterance from an input device, wherein the utterance includes at least one word; (b) accessing a set of template hierarchies from a database, wherein the set includes at least one template; (c) comparing by the processor the at least one word of the utterance to the at least one term of a template hierarchy in the set of template hierarchies; (d) determining by the processor whether the at least one word of the utterance matches the at least one term of the template hierarchy; (e) calculating by the processor a score based on the match between the at least one word of the utterance and the at least one term of the template hierarchy; (f) repeating steps (c)-(e) until there are no more words of the utterance for said comparing step; (g) populating the at least one template with at least one data element corresponding to the at least one term of the template hierarchy to obtain a populated template; (h) computing a total score based on the match between all words of the utterance to the populated template; (i) selecting by the processor the at least one template with the highest total score; (j) recording the populated template; and (k) communicating the populated template to the user. 10. The computer system method of claim 1 wherein the database is located on a memory of a remote computer.
| 0.912724 |
8,078,452 | 11 | 15 |
11. A system for identifying phrasal terms, the system comprising: a processor; and a memory, wherein the processor is configured to execute steps comprising: receiving a text having a plurality of words; determining a plurality of contexts, wherein a context comprises one or more words proximate to another word in the text; for each context, determining a first frequency based on a number of occurrences of the context within the text; assigning a first rank to at least one context based on the first frequency for the at least one context; determining multiple word-context pairs; for each word-context pair, determining a second frequency based on a number of occurrences of the word associated with the word-context pair being used in the context; assigning a second rank to at least one word-context pair based on the second frequency for the at least one word-context pair; determining a rank ratio for each word-context pair based on the first rank and the second rank associated with the word-context pair; determining a mutual rank ratio based on multiple rank ratios; and identifying a phrasal term based on the mutual rank ratio.
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11. A system for identifying phrasal terms, the system comprising: a processor; and a memory, wherein the processor is configured to execute steps comprising: receiving a text having a plurality of words; determining a plurality of contexts, wherein a context comprises one or more words proximate to another word in the text; for each context, determining a first frequency based on a number of occurrences of the context within the text; assigning a first rank to at least one context based on the first frequency for the at least one context; determining multiple word-context pairs; for each word-context pair, determining a second frequency based on a number of occurrences of the word associated with the word-context pair being used in the context; assigning a second rank to at least one word-context pair based on the second frequency for the at least one word-context pair; determining a rank ratio for each word-context pair based on the first rank and the second rank associated with the word-context pair; determining a mutual rank ratio based on multiple rank ratios; and identifying a phrasal term based on the mutual rank ratio. 15. The system of claim 11 , wherein the plurality of contexts comprises a bigram.
| 0.964067 |
9,966,072 | 1 | 8 |
1. A method for determining a language among a plurality of languages available for a voice to text transcription of phone calls between a caller and a recipient provided by an answering machine system, comprising: deriving a country code of said caller or said recipient; selecting three or more languages to be included in a list of languages, wherein each selected language is determined to be a preferred language in that each language is identified as satisfying an initial acceptable probability of being selected later for use; after the list of languages is generated, determining, for each language in the list, a subsequent probability of being selected for use, the subsequent probability being based at least partially on said derived country code and at least another technical option; organize the list of languages based on each language's determined subsequent probability so as to generate a prioritized list of languages, whereby a first language with a highest subsequent probability is placed at a top of the prioritized list of languages followed by a second language with a second highest subsequent probability followed by a third language with a third highest subsequent probability; presenting the prioritized list of languages to said caller; selecting, by said caller, said language from among the prioritized list of languages by interacting with said answering machine system; and transcribing a corresponding voice message into text of the selected language for forwarding to said recipient.
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1. A method for determining a language among a plurality of languages available for a voice to text transcription of phone calls between a caller and a recipient provided by an answering machine system, comprising: deriving a country code of said caller or said recipient; selecting three or more languages to be included in a list of languages, wherein each selected language is determined to be a preferred language in that each language is identified as satisfying an initial acceptable probability of being selected later for use; after the list of languages is generated, determining, for each language in the list, a subsequent probability of being selected for use, the subsequent probability being based at least partially on said derived country code and at least another technical option; organize the list of languages based on each language's determined subsequent probability so as to generate a prioritized list of languages, whereby a first language with a highest subsequent probability is placed at a top of the prioritized list of languages followed by a second language with a second highest subsequent probability followed by a third language with a third highest subsequent probability; presenting the prioritized list of languages to said caller; selecting, by said caller, said language from among the prioritized list of languages by interacting with said answering machine system; and transcribing a corresponding voice message into text of the selected language for forwarding to said recipient. 8. The method according to claim 1 , further comprising the steps of; receiving, by said caller, a text message for approval and/or modification before said forwarding to said recipient; and subsequently forwarding said text message to said recipient when said caller approves said text message.
| 0.629397 |
9,823,913 | 1 | 9 |
1. A computer implemented method of detecting global variables in JAVASCRIPT code, and adding local variables in place of said global variables, comprising: receiving by a processor a JAVASCRIPT code containing at least one of a plurality of globally defined functions; generating by the processor at least one call flow graph for each one of said at least one of globally defined functions; generating by the processor an inter-procedural control flow graph for each one of said call flow graph; generating by the processor an inter-procedural dominator graph for each one of said inter-procedural control flow graph; identifying by the processor each of referenced global variables within each of said inter-procedural dominator graph and determining a JAVASCRIPT scope of each of referenced global variables; identifying by the processor at least one of: one or more confined global variables which receive a value within a first JAVASCRIPT scope of each referenced global variable wherein said value is not referenced outside of said first JAVASCRIPT scope, and one or more repeating global variables accessed repeatedly within a second JAVASCRIPT scope of each referenced global variable; and automatically adding by the processor local variables in place of at least one of said confined global variables and said repeating global variables.
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1. A computer implemented method of detecting global variables in JAVASCRIPT code, and adding local variables in place of said global variables, comprising: receiving by a processor a JAVASCRIPT code containing at least one of a plurality of globally defined functions; generating by the processor at least one call flow graph for each one of said at least one of globally defined functions; generating by the processor an inter-procedural control flow graph for each one of said call flow graph; generating by the processor an inter-procedural dominator graph for each one of said inter-procedural control flow graph; identifying by the processor each of referenced global variables within each of said inter-procedural dominator graph and determining a JAVASCRIPT scope of each of referenced global variables; identifying by the processor at least one of: one or more confined global variables which receive a value within a first JAVASCRIPT scope of each referenced global variable wherein said value is not referenced outside of said first JAVASCRIPT scope, and one or more repeating global variables accessed repeatedly within a second JAVASCRIPT scope of each referenced global variable; and automatically adding by the processor local variables in place of at least one of said confined global variables and said repeating global variables. 9. The method of claim 1 , further comprising altering a definition of at least one confined global variable of said confined global variables such that said at least one confined global variable is defined as a local variable.
| 0.78381 |
9,251,524 | 3 | 4 |
3. The method of claim 1 , wherein the first term, value (vd1) equals the number of times the first term appears in the document.
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3. The method of claim 1 , wherein the first term, value (vd1) equals the number of times the first term appears in the document. 4. The method of claim 3 , wherein prior to step (iii), the user profile contains a value (vp) associated with the second term, and said determining step comprising determining a second value (v2) for said second term of the document and determining the second value (v2) for the second term of the document comprises calculating the second value (v2) using the values: vp, a, and vd2.
| 0.5 |
7,571,098 | 3 | 4 |
3. The speech processing method of claim 2 , wherein said converting comprises converting the word lattice into a word confusion network.
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3. The speech processing method of claim 2 , wherein said converting comprises converting the word lattice into a word confusion network. 4. The speech processing method of claim 3 , wherein posterior probabilities of the word confusion network are used as confidence scores.
| 0.5 |
9,106,979 | 13 | 15 |
13. A recommender system for associating a second media content item with a first media content item, wherein the first media content item comprises a first audio/video content and the second media content item comprises a second audio/video content, the recommender system comprising: a network interface configured for receiving a map of a first delimited segment of the first media content item, the map comprising a first sentiment-state keyword associated with the first segment and a first temporal delimitation of the first segment, and for receiving a map of a second delimited segment of the second media content item, the map comprising a second sentiment-state keyword associated with the second segment and a second temporal delimitation of the second segment; and a processor operatively connected to the network interface, the processor configured for: comparing the maps of the first and second delimited segments; and if a result of the comparison is a favorable result for a temporal extent associated with the first and second temporal delimitations, then associating the second media content item with the first media content item.
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13. A recommender system for associating a second media content item with a first media content item, wherein the first media content item comprises a first audio/video content and the second media content item comprises a second audio/video content, the recommender system comprising: a network interface configured for receiving a map of a first delimited segment of the first media content item, the map comprising a first sentiment-state keyword associated with the first segment and a first temporal delimitation of the first segment, and for receiving a map of a second delimited segment of the second media content item, the map comprising a second sentiment-state keyword associated with the second segment and a second temporal delimitation of the second segment; and a processor operatively connected to the network interface, the processor configured for: comparing the maps of the first and second delimited segments; and if a result of the comparison is a favorable result for a temporal extent associated with the first and second temporal delimitations, then associating the second media content item with the first media content item. 15. The system of claim 13 , wherein the second media content item is an advertisement, and the first media content item is not an advertisement.
| 0.879368 |
8,380,507 | 19 | 20 |
19. The computer readable media of claim 18 , further comprising additional computer readable instructions recorded thereon for: identifying a default language associated with an electronic device providing the speech content; determining that the identified languages are speakable in the default language; and selecting the default language for generating the speech content.
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19. The computer readable media of claim 18 , further comprising additional computer readable instructions recorded thereon for: identifying a default language associated with an electronic device providing the speech content; determining that the identified languages are speakable in the default language; and selecting the default language for generating the speech content. 20. The computer readable media of claim 19 , further comprising additional computer readable instructions recorded thereon for: determining whether a minimum amount of speech content generated in the default language from a particular text string in a language other than the default language is understandable.
| 0.5 |
8,200,695 | 9 | 10 |
9. The method according to claim 8 , wherein one of a first user interface where a query is input in sentence units, a second user interface where retrieved documents are used as a query, and a third user interface where a query is input by attaching or uploading a text file is provided to a user by an output unit providing a user interface, before the receiving of the query input by a user through the query input unit.
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9. The method according to claim 8 , wherein one of a first user interface where a query is input in sentence units, a second user interface where retrieved documents are used as a query, and a third user interface where a query is input by attaching or uploading a text file is provided to a user by an output unit providing a user interface, before the receiving of the query input by a user through the query input unit. 10. The method according to claim 9 , wherein, when a user attaches or uploads a predetermined file using the third user interface, the query input unit monitors a format of the attached or uploaded file to receive only a file of that is morphologically analyzable.
| 0.5 |
9,348,935 | 12 | 19 |
12. A system for delivering related video content for augmented keywords on a web page, the system comprising: a server comprising a processor, the server receiving from an agent executing within a browser, responsive to the agent detecting a mouse over a keyword currently displayed on a web page of a client, the keyword identified for augmentation via a user interface overlay and identifying a plurality of videos related to the keyword, the server configured to dynamically select, responsive to receiving the keyword at a time of the mouse over, one or more videos for the user interface overlay for the keyword; a content relevancy engine determining an order of relevance of the plurality of videos to the keyword; and wherein the server selects one or more videos of the plurality of videos with a higher order of relevance and transmits to the agent of the client, within a predetermined time period from receipt of the keyword from the agent responsive to the agent detecting the mouse over, the user interface overlay, to be displayed by the agent responsive to the mouse over, to include the selected one or more videos of the plurality of videos with a higher order of relevance for at least one of user selection or display in the user interface overlay, the predetermined time period comprising a time threshold within which the server is to complete the selection of the one or more videos and to complete delivery of the selected one or more videos to the client.
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12. A system for delivering related video content for augmented keywords on a web page, the system comprising: a server comprising a processor, the server receiving from an agent executing within a browser, responsive to the agent detecting a mouse over a keyword currently displayed on a web page of a client, the keyword identified for augmentation via a user interface overlay and identifying a plurality of videos related to the keyword, the server configured to dynamically select, responsive to receiving the keyword at a time of the mouse over, one or more videos for the user interface overlay for the keyword; a content relevancy engine determining an order of relevance of the plurality of videos to the keyword; and wherein the server selects one or more videos of the plurality of videos with a higher order of relevance and transmits to the agent of the client, within a predetermined time period from receipt of the keyword from the agent responsive to the agent detecting the mouse over, the user interface overlay, to be displayed by the agent responsive to the mouse over, to include the selected one or more videos of the plurality of videos with a higher order of relevance for at least one of user selection or display in the user interface overlay, the predetermined time period comprising a time threshold within which the server is to complete the selection of the one or more videos and to complete delivery of the selected one or more videos to the client. 19. The system of claim 12 , wherein the content relevancy engine determines the order of relevance of the plurality of videos based on information on recency of the plurality of videos provided by the one or more search results, the information on recency comprising one of a first time when a video was created or a second time when the video was uploaded, provided by one or more search results.
| 0.5 |
8,280,900 | 5 | 6 |
5. A non-transitory computer readable medium comprising instructions executed by a processor for returning search results based on speculative query expansion, the instructions comprising: receiving an initial query; retrieving a set of documents based on the initial query, the set of documents comprising documents judged either as relevant or non-relevant to the initial query, and unjudged documents; executing a speculative query expansion process based on the retrieved set of documents, comprising: a. generating a list of query expansion terms based on the judged documents; b. assigning a weight for each of the query expansion terms in the generated list; c. selecting at least one term from the list of query expansion terms; d. adding the selected at least one term to the initial query to create a speculatively expanded query, wherein the speculatively expanded query is indicative of a query possibility; e. generating a list of documents from the set of documents based on the speculatively expanded query; f. assigning a pseudo metric score for the speculatively expanded query based on the order of marked documents within the generated list, wherein the pseudo metric score is indicative of an application of a metric on the judged documents; g. if no termination condition is met to terminate the speculative query process is received, returning to step c; and h. returning the speculatively expanded query with the highest metric score; returning search results based on the speculative query expansion process.
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5. A non-transitory computer readable medium comprising instructions executed by a processor for returning search results based on speculative query expansion, the instructions comprising: receiving an initial query; retrieving a set of documents based on the initial query, the set of documents comprising documents judged either as relevant or non-relevant to the initial query, and unjudged documents; executing a speculative query expansion process based on the retrieved set of documents, comprising: a. generating a list of query expansion terms based on the judged documents; b. assigning a weight for each of the query expansion terms in the generated list; c. selecting at least one term from the list of query expansion terms; d. adding the selected at least one term to the initial query to create a speculatively expanded query, wherein the speculatively expanded query is indicative of a query possibility; e. generating a list of documents from the set of documents based on the speculatively expanded query; f. assigning a pseudo metric score for the speculatively expanded query based on the order of marked documents within the generated list, wherein the pseudo metric score is indicative of an application of a metric on the judged documents; g. if no termination condition is met to terminate the speculative query process is received, returning to step c; and h. returning the speculatively expanded query with the highest metric score; returning search results based on the speculative query expansion process. 6. The non-transitory computer readable medium of claim 5 , wherein the instruction to terminate the speculative query process is based on a preset number of iterations.
| 0.545699 |
8,925,108 | 16 | 18 |
16. A machine-implemented method comprising: receiving, by a document archive server, a client request relating to an electronic document stored at the document archive server, wherein (a) the client request is for generation of an audit-enabled document, (b) the electronic document is associated with actions-taken information that exists separately from the electronic document, and (c) the actions-taken information describes actions taken with respect to the electronic document; retrieving, by the document archive server, from an audit information server and in response to the client request, the actions-taken information associated with the electronic document; generating, by the document archive server, an audit-enabled electronic document that includes the actions-taken information and the electronic document; and providing, by the document archive server, the audit-enabled electronic document.
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16. A machine-implemented method comprising: receiving, by a document archive server, a client request relating to an electronic document stored at the document archive server, wherein (a) the client request is for generation of an audit-enabled document, (b) the electronic document is associated with actions-taken information that exists separately from the electronic document, and (c) the actions-taken information describes actions taken with respect to the electronic document; retrieving, by the document archive server, from an audit information server and in response to the client request, the actions-taken information associated with the electronic document; generating, by the document archive server, an audit-enabled electronic document that includes the actions-taken information and the electronic document; and providing, by the document archive server, the audit-enabled electronic document. 18. The method of claim 16 , wherein the client request is triggered by attaching the electronic document to an email.
| 0.839237 |
10,037,280 | 1 | 5 |
1. A method of pre-fetching address translations in a memory management unit (MMU) of a device, comprising: detecting a triggering condition related to one or more translation caches associated with the MMU, the triggering condition associated with a trigger address; generating a sequence descriptor describing a sequence of address translations to pre-fetch into the one or more translation caches, wherein the sequence of address translations comprises a plurality of address translations corresponding to a plurality of address ranges adjacent to an address range containing the trigger address; issuing an address translation request to the one or more translation caches for each of the plurality of address translations in the sequence of address translations, wherein the one or more translation caches pre-fetch at least one address translation of the plurality of address translations into the one or more translation caches based on the at least one address translation not being present in the one or more translation caches; setting a pre-fetch flag in a first translation cache entry corresponding to the trigger address to ensure that pre-fetch is performed for an address range corresponding to the first translation cache entry only once; and setting the pre-fetch flag in a second translation cache entry corresponding to at least one of the plurality of address ranges adjacent to the address range containing the trigger address to ensure that pre-fetch is not triggered on subsequent hits to the second translation cache entry.
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1. A method of pre-fetching address translations in a memory management unit (MMU) of a device, comprising: detecting a triggering condition related to one or more translation caches associated with the MMU, the triggering condition associated with a trigger address; generating a sequence descriptor describing a sequence of address translations to pre-fetch into the one or more translation caches, wherein the sequence of address translations comprises a plurality of address translations corresponding to a plurality of address ranges adjacent to an address range containing the trigger address; issuing an address translation request to the one or more translation caches for each of the plurality of address translations in the sequence of address translations, wherein the one or more translation caches pre-fetch at least one address translation of the plurality of address translations into the one or more translation caches based on the at least one address translation not being present in the one or more translation caches; setting a pre-fetch flag in a first translation cache entry corresponding to the trigger address to ensure that pre-fetch is performed for an address range corresponding to the first translation cache entry only once; and setting the pre-fetch flag in a second translation cache entry corresponding to at least one of the plurality of address ranges adjacent to the address range containing the trigger address to ensure that pre-fetch is not triggered on subsequent hits to the second translation cache entry. 5. The method of claim 1 , further comprising: determining whether or not the trigger address is contained in a sequence descriptor of an active address translation request, wherein the sequence descriptor describing the sequence of address translations to pre-fetch is not generated based on the trigger address being contained in the sequence descriptor of the active address translation request.
| 0.621673 |
8,903,719 | 9 | 11 |
9. The media of claim 8 , wherein the one or more dictionaries are selected using a communication profile for the specific recipient that maintains the communication style for the specific recipient on a per-communication-medium basis.
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9. The media of claim 8 , wherein the one or more dictionaries are selected using a communication profile for the specific recipient that maintains the communication style for the specific recipient on a per-communication-medium basis. 11. The media of claim 9 , wherein the method further comprises building the communication profile based on words used in one or more messages communicated to the specific recipient from the user, wherein the one or more messages are in the specific communication medium.
| 0.5 |
8,719,282 | 1 | 8 |
1. A computer-implemented method comprising: receiving a search query including a query term; receiving a document identified as being responsive to the search query; obtaining a synonym that a synonym rule identifies as a substitute for the query term in the search query; receiving an indication that the synonym of the query term in the search query is designated as a restricted-locality synonym; in response to receiving the indication that the synonym is designated as a restricted-locality synonym, selecting a first scoring model that specifies how to score occurrences of restricted-locality synonyms in documents, wherein the first scoring model is different than a second scoring model that specifies how to score occurrences of query terms or synonyms that are not designated as a restricted-locality synonym in documents, wherein the first scoring model specifies that a document score for the document depends on whether occurrences of the restricted-locality synonym in the document co-occur in the document with one or more query terms or one or more synonyms of the query term; and determining a document score for the document using the first scoring model.
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1. A computer-implemented method comprising: receiving a search query including a query term; receiving a document identified as being responsive to the search query; obtaining a synonym that a synonym rule identifies as a substitute for the query term in the search query; receiving an indication that the synonym of the query term in the search query is designated as a restricted-locality synonym; in response to receiving the indication that the synonym is designated as a restricted-locality synonym, selecting a first scoring model that specifies how to score occurrences of restricted-locality synonyms in documents, wherein the first scoring model is different than a second scoring model that specifies how to score occurrences of query terms or synonyms that are not designated as a restricted-locality synonym in documents, wherein the first scoring model specifies that a document score for the document depends on whether occurrences of the restricted-locality synonym in the document co-occur in the document with one or more query terms or one or more synonyms of the query term; and determining a document score for the document using the first scoring model. 8. The method of claim 1 , wherein determining a document score for the document using the first scoring model comprises: determining that the restricted-locality synonym does not occur adjacent to a query term; and based on determining that the restricted-locality synonym does not occur adjacent to a query term, demoting a score associated with each occurrence of the restricted-locality synonym in the document.
| 0.604762 |
9,628,620 | 18 | 19 |
18. A method for providing captioned telephone service, the method comprising: initiating a first captioned telephone service call; during the first captioned telephone service call, creating a first set of captions using a human captioner; simultaneous with creating the first set of captions using a human captioner, creating a second set of captions using an automated speech recognition captioner; comparing the first set of captions and the second set of captions using a scoring algorithm; determining whether the first set of captions is outside of a predetermined range of scores; and in response to the score of first set of captions being outside of a predetermined range of scores, setting an electronic flag indicative of the human captioner being in need of corrective action.
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18. A method for providing captioned telephone service, the method comprising: initiating a first captioned telephone service call; during the first captioned telephone service call, creating a first set of captions using a human captioner; simultaneous with creating the first set of captions using a human captioner, creating a second set of captions using an automated speech recognition captioner; comparing the first set of captions and the second set of captions using a scoring algorithm; determining whether the first set of captions is outside of a predetermined range of scores; and in response to the score of first set of captions being outside of a predetermined range of scores, setting an electronic flag indicative of the human captioner being in need of corrective action. 19. The method of claim 18 , further comprising transmitting an electronic communication to a person responsible for initiating the corrective action.
| 0.5 |
8,412,512 | 2 | 6 |
2. The method of claim 1 , further comprising: identifying a second portion of the first social feed that is associated with a third user, the third user having a different relationship with the first user than the particular relationship; and excluding the second portion from translation based at least in part on the different relationship.
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2. The method of claim 1 , further comprising: identifying a second portion of the first social feed that is associated with a third user, the third user having a different relationship with the first user than the particular relationship; and excluding the second portion from translation based at least in part on the different relationship. 6. The method of claim 2 , wherein the particular relationship between the first user and the second user in the social graph is closer than the different relationship between the first user and the third user in the social graph.
| 0.5 |
8,417,721 | 20 | 21 |
20. The computer-readable medium of claim 17 , wherein the geographic data set is a tree structure wherein different positions in the tree structure that share a same level correspond to different geographic locations that share a same geographic region type.
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20. The computer-readable medium of claim 17 , wherein the geographic data set is a tree structure wherein different positions in the tree structure that share a same level correspond to different geographic locations that share a same geographic region type. 21. The computer-readable medium of claim 20 , wherein determining that the geographic entity name and the second geographic entity name have a particular relationship in a geographic data set comprises determining that a first position for the first geographic entity name in the tree structure and a second position for the second geographic entity name in the tree structure share a parent in the tree structure.
| 0.505952 |
9,405,186 | 1 | 2 |
1. A computer-implemented method for automatically creating a target sample plan for optical proximity correction (OPC) calibration with a minimal number of clips, the method comprising using a computing device to perform actions including: defining a sample plan including a plurality of clips, each of the plurality of clips representing portions of an integrated circuit (IC) layout; calculating a total relevancy score of a projected sample plan for the IC layout, wherein the projected sample plan includes a candidate clip representing an additional portion of the IC layout, and wherein the relevancy score is derived from at least one relevancy criterion and a relevancy weight for the at least one relevancy criterion, the at least one relevancy criterion being one of a topology type of a clip, a printing difficulty of a clip, and a dimensional ratio between clips in the projected sample plan; calculating a relevancy score difference between the total relevancy score of the projected sample plan and a total relevancy score of the sample plan without the candidate clip; adding the candidate clip to the sample plan for the IC layout and removing the candidate clip from the plurality of clips in response to the relevancy score difference substantially fitting a non-linear relevancy score function; removing the candidate clip from the plurality of clips without adding the clip to the sample plan for the IC layout in response to the relevancy score difference substantially fitting a linear relevancy score function, wherein the candidate clip not being added to the sample plan indicates that the sample plan includes the minimal number of clips; and generating an OPC model using the sample plan with the minimal number of clips, wherein the sample plan with the minimal number of clips represents the target sample plan, and wherein the OPC model is used to manufacture at least one IC.
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1. A computer-implemented method for automatically creating a target sample plan for optical proximity correction (OPC) calibration with a minimal number of clips, the method comprising using a computing device to perform actions including: defining a sample plan including a plurality of clips, each of the plurality of clips representing portions of an integrated circuit (IC) layout; calculating a total relevancy score of a projected sample plan for the IC layout, wherein the projected sample plan includes a candidate clip representing an additional portion of the IC layout, and wherein the relevancy score is derived from at least one relevancy criterion and a relevancy weight for the at least one relevancy criterion, the at least one relevancy criterion being one of a topology type of a clip, a printing difficulty of a clip, and a dimensional ratio between clips in the projected sample plan; calculating a relevancy score difference between the total relevancy score of the projected sample plan and a total relevancy score of the sample plan without the candidate clip; adding the candidate clip to the sample plan for the IC layout and removing the candidate clip from the plurality of clips in response to the relevancy score difference substantially fitting a non-linear relevancy score function; removing the candidate clip from the plurality of clips without adding the clip to the sample plan for the IC layout in response to the relevancy score difference substantially fitting a linear relevancy score function, wherein the candidate clip not being added to the sample plan indicates that the sample plan includes the minimal number of clips; and generating an OPC model using the sample plan with the minimal number of clips, wherein the sample plan with the minimal number of clips represents the target sample plan, and wherein the OPC model is used to manufacture at least one IC. 2. The method of claim 1 , wherein in the case that the at least one relevancy criterion includes the topology type, the calculating of the total relevancy score of the projected sample plan further includes: calculating a polygon count for the IC layout, wherein the polygon count includes a total number of shapes for each clip; and calculating an area density for the IC layout, wherein the area density includes a percentage of area in the projected sample plan occupied by polygons in each clip.
| 0.5 |
9,081,463 | 5 | 6 |
5. The method of claim 4 further comprising: receiving run-time edits to the first and second regions that revise the output presentation of the web page; and publishing the revised web page for access by clients.
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5. The method of claim 4 further comprising: receiving run-time edits to the first and second regions that revise the output presentation of the web page; and publishing the revised web page for access by clients. 6. The method of claim 5 wherein said publishing comprises: publishing the revised web page in place of the web page whose source code was received in the receiving step.
| 0.5 |
8,387,029 | 14 | 18 |
14. A method for parsing and executing a software program, the method comprising: receiving a portion of the software program in an original linguistic form in a high level language, wherein the portion of the software program includes a nonlinear program element having a body; and tokenizing the portion of the software program to generate an input stream of tokens representing the portion of the software program; while retaining the original linguistic form of the software program, using a set of one or more production rules by a parser to directly execute the nonlinear program element by manipulating a parse state and the input stream of tokens representing the body of the nonlinear program element, wherein the one or more production rules include a type conversion production rule useable by the parser to perform type conversion and production rules useable by the parser to insert an expression into the input stream of tokens to skip tokens in the input stream of tokens during execution of the nonlinear program element, and wherein directly executing comprises executing tokens until the dynamic end of the nonlinear program element is reached, and wherein manipulating the input stream of tokens comprises using the type conversion production rule to perform type conversion on at least one token of the input stream of tokens and using the one or more production rules to insert expressions to skip tokens during execution of the nonlinear program element.
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14. A method for parsing and executing a software program, the method comprising: receiving a portion of the software program in an original linguistic form in a high level language, wherein the portion of the software program includes a nonlinear program element having a body; and tokenizing the portion of the software program to generate an input stream of tokens representing the portion of the software program; while retaining the original linguistic form of the software program, using a set of one or more production rules by a parser to directly execute the nonlinear program element by manipulating a parse state and the input stream of tokens representing the body of the nonlinear program element, wherein the one or more production rules include a type conversion production rule useable by the parser to perform type conversion and production rules useable by the parser to insert an expression into the input stream of tokens to skip tokens in the input stream of tokens during execution of the nonlinear program element, and wherein directly executing comprises executing tokens until the dynamic end of the nonlinear program element is reached, and wherein manipulating the input stream of tokens comprises using the type conversion production rule to perform type conversion on at least one token of the input stream of tokens and using the one or more production rules to insert expressions to skip tokens during execution of the nonlinear program element. 18. The method as recited in claim 14 , wherein the nonlinear program element comprises a loop construct containing one or more of a conditional statement, a BREAK statement, a CONTINUE statement, or a RETURN statement.
| 0.738038 |
10,162,893 | 14 | 19 |
14. A method for transmitting and displaying electronic media from a service provider to a subscriber comprising: providing, via a service provider computer, access to a web page that is used to log onto web page, the service provider computer communicatively coupled to a controller of the subscriber via a network connection, the service provider computer communicatively coupled to an electronic media library that is searchable by key word; prior to initiating a search from the subscriber via the web page, displaying an index of key words available for searching and a number count for each of the key words, the number count indicating the number of different media content associated with each of the respective key words; wherein when the electronic media library is searched by a user-selected key word from the index, presenting a plurality of pre-assembled media content associated with the selected key word, and upon receiving a user-selected one of the plurality of pre-assembled media content presented, presenting the selected content thereby allowing the subscriber to view the selected pre-assembled media content prior to the content being added to the electronic media collection; and transmitting, to a display of the subscriber, the pre-assembled media content that is added to the electronic media collection; wherein a value specifying a number of discrete media for presentment as a preview at one time, and both prior to selection of any of the plurality of pre-assembled media content and prior to being added to the electronic media collection as the plurality of pre-assembled media content, is selectable by the user via the web page.
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14. A method for transmitting and displaying electronic media from a service provider to a subscriber comprising: providing, via a service provider computer, access to a web page that is used to log onto web page, the service provider computer communicatively coupled to a controller of the subscriber via a network connection, the service provider computer communicatively coupled to an electronic media library that is searchable by key word; prior to initiating a search from the subscriber via the web page, displaying an index of key words available for searching and a number count for each of the key words, the number count indicating the number of different media content associated with each of the respective key words; wherein when the electronic media library is searched by a user-selected key word from the index, presenting a plurality of pre-assembled media content associated with the selected key word, and upon receiving a user-selected one of the plurality of pre-assembled media content presented, presenting the selected content thereby allowing the subscriber to view the selected pre-assembled media content prior to the content being added to the electronic media collection; and transmitting, to a display of the subscriber, the pre-assembled media content that is added to the electronic media collection; wherein a value specifying a number of discrete media for presentment as a preview at one time, and both prior to selection of any of the plurality of pre-assembled media content and prior to being added to the electronic media collection as the plurality of pre-assembled media content, is selectable by the user via the web page. 19. The method according to claim 14 , further comprising: storing the the key word of the subscriber in a memory device of the service provider computer; adding additional pre-assembled content to the service provider computer; and notifying the subscriber when additional pre-assembled content related to the subscriber's saved key word search is available.
| 0.5 |
9,824,128 | 20 | 24 |
20. A method for querying a schema-less database, comprising: instantiating an instance of search query object corresponding to a search session using an API processing computer operatively coupled to a user interface; connecting to an information grid using an API processing computer, wherein said information grid comprises a plurality of heterogeneous databases that each are accessible via a URL; updating said search query object with at least two user-defined schemas values entered into said user interface representing a context field stored in a global context field database operatively coupled to said information grid; mapping said search query object to a mapped database corresponding to said user-defined schema values representing a context field stored in a global context field database operatively coupled to said information grid; updating said query object entered into said user interface with user-defined schema values representing a search term; querying said information grid using said search term by submitting a search query to said information grid without translating said search query into a common markup language format; updating in real time during the search session said user interface to display search results in a table format; and relating the search results of the mapped database to search results in another heterogeneous database, wherein one of the mapped database and said another database is a schema-less database that stores data without using any schema relationships and the other is a database that stores data using a schema relationship.
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20. A method for querying a schema-less database, comprising: instantiating an instance of search query object corresponding to a search session using an API processing computer operatively coupled to a user interface; connecting to an information grid using an API processing computer, wherein said information grid comprises a plurality of heterogeneous databases that each are accessible via a URL; updating said search query object with at least two user-defined schemas values entered into said user interface representing a context field stored in a global context field database operatively coupled to said information grid; mapping said search query object to a mapped database corresponding to said user-defined schema values representing a context field stored in a global context field database operatively coupled to said information grid; updating said query object entered into said user interface with user-defined schema values representing a search term; querying said information grid using said search term by submitting a search query to said information grid without translating said search query into a common markup language format; updating in real time during the search session said user interface to display search results in a table format; and relating the search results of the mapped database to search results in another heterogeneous database, wherein one of the mapped database and said another database is a schema-less database that stores data without using any schema relationships and the other is a database that stores data using a schema relationship. 24. The method of claim 20 , further comprising: successively updating said user-defined context field property.
| 0.602837 |
5,559,969 | 31 | 56 |
31. A data processing system having a first bus wherein the first bus has a first bus width, the first bus for sequentially transmitting a plurality of first data packets wherein the plurality of first data packets have a first data width, the data processing system further having a second bus wherein the second bus has a second width, the second bus for sequentially transmitting a plurality of second data packets wherein the plurality of second data packets have a second data width, the width of the first bus being less than the width of the second bus, comprising: a. a memory processor coupled to the first bus and further coupled to the second bus for programming one of a plurality of formatting functions and formatting the plurality of first data packets into a plurality of groups, said memory processor assembling the plurality of first data packets into the plurality of groups as the plurality of first data packets are sequentially transmitted over the first bus, each of the plurality of groups forming a corresponding one of the plurality of second data packets for sequential transmission over the second bus; the memory processor further controlling which of the plurality of first data packets are assembled into each of the plurality of groups.
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31. A data processing system having a first bus wherein the first bus has a first bus width, the first bus for sequentially transmitting a plurality of first data packets wherein the plurality of first data packets have a first data width, the data processing system further having a second bus wherein the second bus has a second width, the second bus for sequentially transmitting a plurality of second data packets wherein the plurality of second data packets have a second data width, the width of the first bus being less than the width of the second bus, comprising: a. a memory processor coupled to the first bus and further coupled to the second bus for programming one of a plurality of formatting functions and formatting the plurality of first data packets into a plurality of groups, said memory processor assembling the plurality of first data packets into the plurality of groups as the plurality of first data packets are sequentially transmitted over the first bus, each of the plurality of groups forming a corresponding one of the plurality of second data packets for sequential transmission over the second bus; the memory processor further controlling which of the plurality of first data packets are assembled into each of the plurality of groups. 56. A data processing system according to claim 31 wherein the memory processor further formats a plurality of second data packets, said memory processor disassembling the plurality of second data packets into a plurality of first data packets as the plurality of second data packets are sequentially transmitted over the second bus, each of the plurality of first data packets being sequential transmitted over the first bus; said memory processor further controlling which of the plurality of second data packets are disassembled into each of the plurality of first data packets.
| 0.5 |
6,065,026 | 26 | 44 |
26. A textual document authoring system, comprising: means for storing in storage a library of textual components and a database of marks identifying each of the components that is part of a first textual document, means for displaying in a word processor window on a display responsive to the storage the first textual document including a first plurality of the textual components, and a user interface for responding to user input by a first user to an interface of the word processor to edit the first textual document while the document is displayed by the means for displaying in the word processor window; for responding to user input by a second user to the interface of the word processor to edit a second textual document including a second plurality of the textual components, the first plurality including one or more textual components from the second plurality; for detecting when one of the textual components that belongs to both the first plurality and the second plurality is updated in one of the first and second textual documents; for prompting the user of the other of the first and second textual documents to accept or reject changes made to the one of the textual components, in response to updating of the one of the textual components; for responding to user input to the interface of the word processor to generate a second version of the first textual document that includes updated textual components; and means for responding to user input to the interface of the word processor to generate a second version of the second textual document that includes updated textual components.
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26. A textual document authoring system, comprising: means for storing in storage a library of textual components and a database of marks identifying each of the components that is part of a first textual document, means for displaying in a word processor window on a display responsive to the storage the first textual document including a first plurality of the textual components, and a user interface for responding to user input by a first user to an interface of the word processor to edit the first textual document while the document is displayed by the means for displaying in the word processor window; for responding to user input by a second user to the interface of the word processor to edit a second textual document including a second plurality of the textual components, the first plurality including one or more textual components from the second plurality; for detecting when one of the textual components that belongs to both the first plurality and the second plurality is updated in one of the first and second textual documents; for prompting the user of the other of the first and second textual documents to accept or reject changes made to the one of the textual components, in response to updating of the one of the textual components; for responding to user input to the interface of the word processor to generate a second version of the first textual document that includes updated textual components; and means for responding to user input to the interface of the word processor to generate a second version of the second textual document that includes updated textual components. 44. The apparatus of claim 26 further including means for maintaining information on each of the component's name, description, and classifications.
| 0.768025 |
9,342,605 | 16 | 17 |
16. The system of claim 15 , wherein for one or more of the identified network resources that the second users have interacted with within the particular period of time, the popularity ranking is based at least in part on a number of times one or more edges have been generated, based at least in part on the interactions, between nodes respectively associated with the second users and nodes respectively associated with the identified network resources.
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16. The system of claim 15 , wherein for one or more of the identified network resources that the second users have interacted with within the particular period of time, the popularity ranking is based at least in part on a number of times one or more edges have been generated, based at least in part on the interactions, between nodes respectively associated with the second users and nodes respectively associated with the identified network resources. 17. The system of claim 16 , wherein the edge comprises one or more of a number of times viewed, a number of times liked, or a number of times the search results posted to a social-networking system comprising the data store of social-graph information.
| 0.5 |
8,135,716 | 1 | 3 |
1. A computer-implemented method associated with a programming language in an application server that includes access to different database server implementations, wherein the programming language accesses content of database tables via work areas derived from the database tables, comprising: defining mapping of a database table, having columns to store content, each column is associated with a column type, to a work area such that, at a database server, each column in the database table is mapped to a corresponding component of the work area, the corresponding component having a default component type based on the column type of the associated column in the database table; determining that a particular column in the database table is to store large object data content; and in response to the determination, automatically defining a new mapping to a work area such that the particular column maps to a corresponding component having a component type other than the default component type, wherein, as a result of said new mapping, the programming language accesses a sub-portion of the large object data content by changing the content of the large object data content via a locator and the programming language reads a sub-portion of the large object data content via the work area with a SELECT statement associated with an interface IF_ABAP_DB_LOB_HANDLE implemented with at least one of: (i) CL_ABAP_DB_C_LOCATOR and CL_ABAP_DB_X_LOCATOR for a locator; or (ii) CL_ABAP_DB_C_READER, CL_ABAP_DB_X_READER for a stream reader.
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1. A computer-implemented method associated with a programming language in an application server that includes access to different database server implementations, wherein the programming language accesses content of database tables via work areas derived from the database tables, comprising: defining mapping of a database table, having columns to store content, each column is associated with a column type, to a work area such that, at a database server, each column in the database table is mapped to a corresponding component of the work area, the corresponding component having a default component type based on the column type of the associated column in the database table; determining that a particular column in the database table is to store large object data content; and in response to the determination, automatically defining a new mapping to a work area such that the particular column maps to a corresponding component having a component type other than the default component type, wherein, as a result of said new mapping, the programming language accesses a sub-portion of the large object data content by changing the content of the large object data content via a locator and the programming language reads a sub-portion of the large object data content via the work area with a SELECT statement associated with an interface IF_ABAP_DB_LOB_HANDLE implemented with at least one of: (i) CL_ABAP_DB_C_LOCATOR and CL_ABAP_DB_X_LOCATOR for a locator; or (ii) CL_ABAP_DB_C_READER, CL_ABAP_DB_X_READER for a stream reader. 3. The method of claim 1 , wherein the application server is associated with the programming language ABAP.
| 0.865915 |
9,325,568 | 10 | 11 |
10. The method of claim 6 , wherein the event message reported by the network element includes at least one first context identifier relating to a first communication entity of the reporting network element, and further comprising determining in response to receipt of the event message at least one second context identifier relating to a second communication entity of the network element on a peer side based on stored configuration information.
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10. The method of claim 6 , wherein the event message reported by the network element includes at least one first context identifier relating to a first communication entity of the reporting network element, and further comprising determining in response to receipt of the event message at least one second context identifier relating to a second communication entity of the network element on a peer side based on stored configuration information. 11. The method of claim 10 , wherein the second context identifier is determined by a look-up process in a configuration database based on the first context identifier.
| 0.5 |
8,285,699 | 1 | 2 |
1. A search engine comprising: a ranking function used in part to rank snippets based in part on a number of ranking coefficients, a number of words in each snippet, one or more of a number of punctuation symbols and numbers in each snippet, and a score of a proximity feature associated with each snippet, the proximity feature being associated with a snippet span to provide a summary based in part on output of the ranking function, wherein the search engine uses the ranking function to rank the snippets using a first ranking coefficient with the number of words in each snippet, a second ranking coefficient with the number of punctuation symbols in each snippet, a third ranking coefficient with the number of numbers in each snippet, and a fourth ranking coefficient with the score of the proximity feature associated with each snippet.
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1. A search engine comprising: a ranking function used in part to rank snippets based in part on a number of ranking coefficients, a number of words in each snippet, one or more of a number of punctuation symbols and numbers in each snippet, and a score of a proximity feature associated with each snippet, the proximity feature being associated with a snippet span to provide a summary based in part on output of the ranking function, wherein the search engine uses the ranking function to rank the snippets using a first ranking coefficient with the number of words in each snippet, a second ranking coefficient with the number of punctuation symbols in each snippet, a third ranking coefficient with the number of numbers in each snippet, and a fourth ranking coefficient with the score of the proximity feature associated with each snippet. 2. The search engine of claim 1 , further configured to search one or more of local and networked information repositories.
| 0.865721 |
9,471,566 | 42 | 47 |
42. A non-transitory computer-readable storage medium storing program instructions, wherein the program instructions are computer-executable to implement a language input mechanism for converting a phonetic language text to a written language text, wherein the language input mechanism is configured to: generate a plurality of possible phonetic language syllable segmentations for a phonetic language input text string; generate a plurality of possible written language sentences each including one or more written language words, wherein each sentence corresponds to one of the syllable segmentations, and wherein each word in each sentence corresponds to one or more of the syllables in the corresponding syllable segmentation; determine probability scores for the words and for sequences of two or more words in the sentences according to a language model comprising written language words and a history cache of previously selected written language words; generate a list of candidate output words for a current selection position in the phonetic language input text string from the sentences, wherein the list of candidate output words is sorted according to the probability scores; determine one of the possible written language sentences as a most probable candidate output sentence for the phonetic language input text string according to the probability scores; and output at least a portion of the list of sorted candidate output words and the candidate output sentence.
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42. A non-transitory computer-readable storage medium storing program instructions, wherein the program instructions are computer-executable to implement a language input mechanism for converting a phonetic language text to a written language text, wherein the language input mechanism is configured to: generate a plurality of possible phonetic language syllable segmentations for a phonetic language input text string; generate a plurality of possible written language sentences each including one or more written language words, wherein each sentence corresponds to one of the syllable segmentations, and wherein each word in each sentence corresponds to one or more of the syllables in the corresponding syllable segmentation; determine probability scores for the words and for sequences of two or more words in the sentences according to a language model comprising written language words and a history cache of previously selected written language words; generate a list of candidate output words for a current selection position in the phonetic language input text string from the sentences, wherein the list of candidate output words is sorted according to the probability scores; determine one of the possible written language sentences as a most probable candidate output sentence for the phonetic language input text string according to the probability scores; and output at least a portion of the list of sorted candidate output words and the candidate output sentence. 47. The non-transitory computer-readable storage medium as recited in claim 42 , wherein, to generate a plurality of possible phonetic language syllable segmentations for a phonetic language input text string, the language input mechanism is further configured to include possible syllables determined from partial syllables in the input text string in one or more of the possible phonetic language syllable segmentations.
| 0.558577 |
8,684,746 | 1 | 8 |
1. A method, comprising: receiving, from a first user at a first educational institution through a first user electronic interface adapter, a first set of questions; receiving, from a second user at a second educational institution through a second user electronic interface adapter, a second set of questions; combining, in a data storage, the first set of questions and the second set of questions into a global question bank; displaying, to the first user through a first display adapter, questions from the global question bank; receiving, from the first user through the first user electronic interface adapter, a selection of questions from the global question bank and a difficulty for each question of the selection of questions; generating, in the data storage, a proficiency examination from the selection of questions; displaying, to a student through a second display adapter, a first random question of a first question type from the proficiency examination; receiving, from the student through a third user electronic interface adapter, a first answer corresponding to the first random question; determining, in a processor, if the first answer is a correct answer for the first random question; if the first answer is the correct answer, increasing a current difficulty; if the first answer is not the correct answer, decreasing the current difficulty; and calculating, in the processor, a number of questions displayed to the student of the first question type; if the number of first question types displayed exceeds a first question type threshold then displaying, to the student through the second display adapter, a second random question of a second question type at the current difficulty; and if the number of first question types displayed does not exceed the first question type threshold then displaying, to the student through the second display adapter, a second random question of the first question type at the current difficulty.
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1. A method, comprising: receiving, from a first user at a first educational institution through a first user electronic interface adapter, a first set of questions; receiving, from a second user at a second educational institution through a second user electronic interface adapter, a second set of questions; combining, in a data storage, the first set of questions and the second set of questions into a global question bank; displaying, to the first user through a first display adapter, questions from the global question bank; receiving, from the first user through the first user electronic interface adapter, a selection of questions from the global question bank and a difficulty for each question of the selection of questions; generating, in the data storage, a proficiency examination from the selection of questions; displaying, to a student through a second display adapter, a first random question of a first question type from the proficiency examination; receiving, from the student through a third user electronic interface adapter, a first answer corresponding to the first random question; determining, in a processor, if the first answer is a correct answer for the first random question; if the first answer is the correct answer, increasing a current difficulty; if the first answer is not the correct answer, decreasing the current difficulty; and calculating, in the processor, a number of questions displayed to the student of the first question type; if the number of first question types displayed exceeds a first question type threshold then displaying, to the student through the second display adapter, a second random question of a second question type at the current difficulty; and if the number of first question types displayed does not exceed the first question type threshold then displaying, to the student through the second display adapter, a second random question of the first question type at the current difficulty. 8. The method of claim 1 , in which generating a proficiency examination comprises generating a language proficiency examination.
| 0.770463 |
8,630,857 | 1 | 2 |
1. A speech synthesizing apparatus comprising: a storage unit that stores speech segments; and a segment selection unit that selects a segment suited to a target segment environment from among a plurality of candidate segments selected from the storage unit, wherein the segment selection unit performs control to exclude, from the candidate segment which is a candidate of the selection, a segment having a prosody change amount less than a selection criterion that is determined based on a prosody change amount of the candidate segments.
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1. A speech synthesizing apparatus comprising: a storage unit that stores speech segments; and a segment selection unit that selects a segment suited to a target segment environment from among a plurality of candidate segments selected from the storage unit, wherein the segment selection unit performs control to exclude, from the candidate segment which is a candidate of the selection, a segment having a prosody change amount less than a selection criterion that is determined based on a prosody change amount of the candidate segments. 2. The speech synthesizing apparatus according to claim 1 , wherein the segment selection unit comprises: a prosody change amount calculation unit that calculates a prosody change amount of each candidate segment, based on prosody information of the target segment environment and the candidate segments; a selection criterion calculation unit that calculates a selection criterion, based on the prosody change amount; a candidate selection unit that narrows down selection candidates, based on the prosody change amount and the selection criterion; and an optimum segment search unit that searches for an optimum segment from among the narrowed-down candidate segments; wherein the candidate selection unit excludes, from selection candidates, a segment having a prosody change amount less than the selection criterion, and excludes the segment from a target of search for an optimum segment by the optimum segment search unit.
| 0.894617 |
9,373,155 | 17 | 18 |
17. 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: determining an initial height and an initial width of an image that is associated with a search result, wherein the image is to be displayed in the search result in line with text associated with the search result, and wherein the search result includes an in-line image region for displaying the image in line with the text, and a text region for displaying the text; determining an initial height of the text region of the search result based at least on (i) the text associated with the search result, and (ii) an initial width of the text region; determining an initial width of the in-line image region of the search result based at least on (i) the initial height of the text region of the search result, (ii) the initial height of the image, and (iii) the initial width of the image; determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region; and in response to determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region: determining an adjusted height of the text region of the search result based at least on the initial width of the in-line image region of the search result; determining an adjusted width of the in-line image region of the search result based at least on the adjusted height of the text region of the search result; determining an adjusted height and an adjusted width of the image based at least on the adjusted width of the in-line image region of the search result; scaling at least a portion of the image based at least on the adjusted height and the adjusted width of the image; and outputting the scaled image for display in the search result in line with the text.
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17. 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: determining an initial height and an initial width of an image that is associated with a search result, wherein the image is to be displayed in the search result in line with text associated with the search result, and wherein the search result includes an in-line image region for displaying the image in line with the text, and a text region for displaying the text; determining an initial height of the text region of the search result based at least on (i) the text associated with the search result, and (ii) an initial width of the text region; determining an initial width of the in-line image region of the search result based at least on (i) the initial height of the text region of the search result, (ii) the initial height of the image, and (iii) the initial width of the image; determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region; and in response to determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region: determining an adjusted height of the text region of the search result based at least on the initial width of the in-line image region of the search result; determining an adjusted width of the in-line image region of the search result based at least on the adjusted height of the text region of the search result; determining an adjusted height and an adjusted width of the image based at least on the adjusted width of the in-line image region of the search result; scaling at least a portion of the image based at least on the adjusted height and the adjusted width of the image; and outputting the scaled image for display in the search result in line with the text. 18. The medium of claim 17 , wherein the operations comprise: determining that the initial width of the in-line image region exceeds a maximum in-line image region width, wherein the adjusted height of the text region is further based on the maximum in-line image region width.
| 0.868095 |
8,762,836 | 1 | 2 |
1. A method comprising: creating a design environment for a user, said design environment configured to display a design, and said design environment allowing said user to apply a design font to a portion of text in said design; providing said user with the ability to define a mapping from said design font to a target font; receiving said mapping from said user while said user is creating said design; generating a markup language representation of said design; and applying said mapping to said design; wherein said design font is linked to said portion of text in said design: (i) continuously before and after said mapping is received from said user, and (ii) using an encoding prior to said generating step; said portion of text in said design is not displayed using said target font while said design is edited in said design environment; said target font is linked to said portion of text in said markup language representation using a different encoding; and said portion of text in said markup language representation is displayed using said target font while said design is rendered outside of the design environment in an external player or inside the design environment in a virtual external player instantiated within the design environment.
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1. A method comprising: creating a design environment for a user, said design environment configured to display a design, and said design environment allowing said user to apply a design font to a portion of text in said design; providing said user with the ability to define a mapping from said design font to a target font; receiving said mapping from said user while said user is creating said design; generating a markup language representation of said design; and applying said mapping to said design; wherein said design font is linked to said portion of text in said design: (i) continuously before and after said mapping is received from said user, and (ii) using an encoding prior to said generating step; said portion of text in said design is not displayed using said target font while said design is edited in said design environment; said target font is linked to said portion of text in said markup language representation using a different encoding; and said portion of text in said markup language representation is displayed using said target font while said design is rendered outside of the design environment in an external player or inside the design environment in a virtual external player instantiated within the design environment. 2. The method of claim 1 , wherein: said mapping maps a full published version of said design font to said target font; and said mapping is applied during said generating step.
| 0.5 |
9,946,708 | 8 | 14 |
8. A computer program product for identifying word-senses, 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 identify a frequency of occurrence value of a received word from each of a plurality of domain tables, wherein each of the plurality of domain tables comprises a frequency of occurrence value corresponding to the received word, a word-sense corresponding to the received word, and temporal properties corresponding to the received word, wherein the frequency of occurrence value is determined using an n-gram viewer; program instructions to associate the received word with a domain table from the plurality of domain tables based on the frequency of occurrence value corresponding to the received word meeting a threshold value; and program instructions to identify a word-sense of the received word based on the corresponding word-sense from the associated domain table.
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8. A computer program product for identifying word-senses, 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 identify a frequency of occurrence value of a received word from each of a plurality of domain tables, wherein each of the plurality of domain tables comprises a frequency of occurrence value corresponding to the received word, a word-sense corresponding to the received word, and temporal properties corresponding to the received word, wherein the frequency of occurrence value is determined using an n-gram viewer; program instructions to associate the received word with a domain table from the plurality of domain tables based on the frequency of occurrence value corresponding to the received word meeting a threshold value; and program instructions to identify a word-sense of the received word based on the corresponding word-sense from the associated domain table. 14. The computer program product of claim 8 , wherein each of the plurality of domain tables comprises one or more of: medical frequency of occurrence domain table; medical frequency of co-occurrence domain table; veterinary frequency of occurrence domain table; veterinary frequency of co-occurrence domain table; temporal frequency of occurrence domain table; colloquial word-sense domain table; cultural word-sense domain table; and regional word-sense domain table.
| 0.579749 |
4,751,740 | 10 | 11 |
10. In the document structure of claim 9 and wherein: the means for representing the text of a document includes a string of information including text codes.
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10. In the document structure of claim 9 and wherein: the means for representing the text of a document includes a string of information including text codes. 11. In the document structure of claim 10 and wherein the means for representing the text of a document further includes an attribute for supplying information concerning a portion of the string.
| 0.5 |
10,157,233 | 16 | 19 |
16. The method of claim 12 , wherein the relevance formula is derived using a machine learning technique.
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16. The method of claim 12 , wherein the relevance formula is derived using a machine learning technique. 19. The method of claim 16 , wherein the machine learning technique uses a conjugate gradient descent.
| 0.556522 |
8,538,687 | 1 | 6 |
1. A system for guidance and navigation in a building, comprising: a module for obtaining locations of one or more people in the building; a module for selecting a route based on the locations in a building; a module for processing the route into waypoints and segments; a module for associating semantic information with waypoints; a module for processing the waypoints and segments into navigation commands formed from a sentence template; and a module for providing and associating audio tones with waypoints; and wherein: the system comprising the modules is implemented on non-transitory computer readable media; and the audio tones are for distinguishing waypoints from one another and pulse rates for indicating various distances of the recipient of the audio from a waypoint.
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1. A system for guidance and navigation in a building, comprising: a module for obtaining locations of one or more people in the building; a module for selecting a route based on the locations in a building; a module for processing the route into waypoints and segments; a module for associating semantic information with waypoints; a module for processing the waypoints and segments into navigation commands formed from a sentence template; and a module for providing and associating audio tones with waypoints; and wherein: the system comprising the modules is implemented on non-transitory computer readable media; and the audio tones are for distinguishing waypoints from one another and pulse rates for indicating various distances of the recipient of the audio from a waypoint. 6. The system of claim 1 , wherein: semantic information is attached to waypoints and segments; and semantic information comprises landmarks.
| 0.794461 |
8,027,867 | 15 | 16 |
15. The system of claim 1 further comprising a membership module that creates a membership for the author prior to literary work submission that includes a contract in which the member/submitter agrees to pay a percentage of royalties earned from the literary work when it is published.
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15. The system of claim 1 further comprising a membership module that creates a membership for the author prior to literary work submission that includes a contract in which the member/submitter agrees to pay a percentage of royalties earned from the literary work when it is published. 16. The system of claim 15 wherein the membership module also collects a fee for each submission of a literary work for review from the member.
| 0.5 |
4,868,879 | 8 | 14 |
8. A method of recognizing speech, comprising the steps of: providing a plurality of reference templates composed of spectrally normalized data in a plurality of frames and a plurality of channels; analyzing the frequencies of an input speech periodically at each input frame, which is a predetermined time interval, to extract an input pattern composed of time series information of frequency components in a plurality of channels; spectrally normalizing said components of said input pattern in each of the channels in each frame to generate spectrally normalized data; starting counting of a speech frame number j of the input pattern after a start point of the input speech is detected; updating said speech frame number j every input frame while the input speech is in the speech sound condition; holding said speech frame number j while the input speech is in a silent condition; restarting to update said speech frame number j every input frame when the input speech is again in the speech sound condition before the end point of the input speech is detected; setting plural substantially linear matching paths, cash having different slopes, between said input pattern and said reference templates by generating plural path-related frame numbers lp, each of which is related to each of said matching paths, in substantially a linear relationship to said speech frame number j according to the equation ##EQU8## where the denominators C.sub.p are plural positive real constants each of which is predetermined with respect to each of said matching paths and where [] represents a Gaussian symbol, each time said speech frame number j is updated; generating plural reference template frame numbers kp, each of which is related to each of said matching paths, based on said path-related frame number lp and the frame length SL(n) of each reference template each time said speech frame number j is updated, according to the following equation; EQU kp=lp (if lp.ltoreq.SL(n)) EQU SL(n) (if lp>(SL(n)) calculating the distance between the spectrally normalized data W(i,j) of said speech frame number j of said input pattern and the spectrally normalized data Sn(i,kp) of said reference template frame number kp of each reference template in each matching path each time said speech frame number j is updated; calculating a dissimilarity relating to each of the matching paths for each of the reference templates by accumulating said distances each time said speech frame number j is updated; detecting a minimum dissimilarity each time said speech frame number j is updated and storing the number of the reference template corresponding to said minimum dissimilarity; and determining the number of said reference template relating to said minimum dissimilarity stored correspondingly to the speech frame number at the end point of the input speech as the recognized result of the input speech when said end point is detected.
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8. A method of recognizing speech, comprising the steps of: providing a plurality of reference templates composed of spectrally normalized data in a plurality of frames and a plurality of channels; analyzing the frequencies of an input speech periodically at each input frame, which is a predetermined time interval, to extract an input pattern composed of time series information of frequency components in a plurality of channels; spectrally normalizing said components of said input pattern in each of the channels in each frame to generate spectrally normalized data; starting counting of a speech frame number j of the input pattern after a start point of the input speech is detected; updating said speech frame number j every input frame while the input speech is in the speech sound condition; holding said speech frame number j while the input speech is in a silent condition; restarting to update said speech frame number j every input frame when the input speech is again in the speech sound condition before the end point of the input speech is detected; setting plural substantially linear matching paths, cash having different slopes, between said input pattern and said reference templates by generating plural path-related frame numbers lp, each of which is related to each of said matching paths, in substantially a linear relationship to said speech frame number j according to the equation ##EQU8## where the denominators C.sub.p are plural positive real constants each of which is predetermined with respect to each of said matching paths and where [] represents a Gaussian symbol, each time said speech frame number j is updated; generating plural reference template frame numbers kp, each of which is related to each of said matching paths, based on said path-related frame number lp and the frame length SL(n) of each reference template each time said speech frame number j is updated, according to the following equation; EQU kp=lp (if lp.ltoreq.SL(n)) EQU SL(n) (if lp>(SL(n)) calculating the distance between the spectrally normalized data W(i,j) of said speech frame number j of said input pattern and the spectrally normalized data Sn(i,kp) of said reference template frame number kp of each reference template in each matching path each time said speech frame number j is updated; calculating a dissimilarity relating to each of the matching paths for each of the reference templates by accumulating said distances each time said speech frame number j is updated; detecting a minimum dissimilarity each time said speech frame number j is updated and storing the number of the reference template corresponding to said minimum dissimilarity; and determining the number of said reference template relating to said minimum dissimilarity stored correspondingly to the speech frame number at the end point of the input speech as the recognized result of the input speech when said end point is detected. 14. An method according to claim 8, wherein said counting up of a speech frame number continues to update said speech frame number even in the silent condition after the start point of the input speech has been detected until the end point thereof is detected; and said detecting a minimum dissimilarity and storing the number of the corresponding reference template, stops the detection of the minimum dissimilarity under the silent condition.
| 0.5 |
9,571,660 | 1 | 2 |
1. A communication system for managing a multimedia conference call comprising: a microprocessor; and a computer readable medium, coupled with the microprocessor and comprising microprocessor readable and executable instructions that cause the microprocessor to execute: a conference manager that receives a plurality of questions for the multimedia conference call, wherein the plurality of questions are electronically submitted by one or more of a plurality of conference participants, wherein at least one of the plurality of questions is received in real-time during the multimedia conference call, and wherein the multimedia conference call is initially only broadcast, via a network, to the plurality of conference participants at a plurality of communication endpoints; a clustering module that clusters, in real-time, the plurality of questions into one or more categories for presentation in the multimedia conference call; and a presentation module that sends, via the network, in a video media of the multimedia conference call, the clustered plurality of questions in the one or more categories to the plurality of communication endpoints of the plurality of conference participants, wherein the video media comprises a visual presentation of a presenter and wherein sending the clustered plurality of questions comprises electronically inserting, in real-time, at least one of the clustered plurality of questions received during the multimedia conference call into the video media of the multimedia conference call.
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1. A communication system for managing a multimedia conference call comprising: a microprocessor; and a computer readable medium, coupled with the microprocessor and comprising microprocessor readable and executable instructions that cause the microprocessor to execute: a conference manager that receives a plurality of questions for the multimedia conference call, wherein the plurality of questions are electronically submitted by one or more of a plurality of conference participants, wherein at least one of the plurality of questions is received in real-time during the multimedia conference call, and wherein the multimedia conference call is initially only broadcast, via a network, to the plurality of conference participants at a plurality of communication endpoints; a clustering module that clusters, in real-time, the plurality of questions into one or more categories for presentation in the multimedia conference call; and a presentation module that sends, via the network, in a video media of the multimedia conference call, the clustered plurality of questions in the one or more categories to the plurality of communication endpoints of the plurality of conference participants, wherein the video media comprises a visual presentation of a presenter and wherein sending the clustered plurality of questions comprises electronically inserting, in real-time, at least one of the clustered plurality of questions received during the multimedia conference call into the video media of the multimedia conference call. 2. The system of claim 1 , wherein the one or more categories comprises a plurality of categories, and wherein: the conference manager receives a selection, from the communication endpoint of the presenter, of one of the plurality of categories and identifies a group of conference participants who submitted questions in the selected one of the plurality of categories; and a conferencing system that selects one or more communication endpoints of the group of conference participants who submitted questions to communicate in the multimedia conference call.
| 0.535714 |
8,909,810 | 36 | 38 |
36. The method of claim 33 , comprising providing one or more items of content to the shared content server from one or more of the nodes.
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36. The method of claim 33 , comprising providing one or more items of content to the shared content server from one or more of the nodes. 38. The method of claim 36 , comprising (i) acquiring an item of multimedia content from any of a web site, networked computer, hard drive, memory stick, DVD, CD or other device or system, and (ii) transmitting that item of content to one or more of the nodes via any of steps (A) and (B).
| 0.5 |
8,015,051 | 1 | 6 |
1. An automated method comprising: storing, using a computer processor, semantic information in a database, the semantic information being related to steps of business processes and describing the steps of the business processes in natural language expressions, the semantic information including functionality metadata, service metadata and instance descriptor metadata, wherein the functionality metadata provides a semantic context containing various levels of specificity and arranged in a hierarchical structure, the service metadata includes technical aspects relating to services implemented in software applications, and the instance descriptor metadata contains data transformation information relating to a transform of data between software applications and cross-references between the functionality metadata and runtime instances of the services; storing, using the computer processor, syntactic information for the services in the database, the syntactic information being cross-referenced to semantic information and related to the software applications each implementing a step of the business processes; comparing, by the computer processor, user input relating to business process with the semantic information and syntactic information, and associations therebetween on a match between the input and the semantic information, identifying, by the computer processor, corresponding syntactic information based on the associations; and from the corresponding syntactic information, identifying, by the computer processor, a software application that implements the step of the business process specified in the user input; identifying, by the computer processor, the data transformation information corresponding to the identified software application; and generating, by the computer processor, an integrated sequence of runtime instances of identified software applications to implement the business process by repeating the above comparing, identifying corresponding syntactic information and identifying a software application steps, wherein each runtime instance in the sequence implements a respective step of the business process and communicates with adjacent runtime instances via adapters created based on the identified data transformation information.
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1. An automated method comprising: storing, using a computer processor, semantic information in a database, the semantic information being related to steps of business processes and describing the steps of the business processes in natural language expressions, the semantic information including functionality metadata, service metadata and instance descriptor metadata, wherein the functionality metadata provides a semantic context containing various levels of specificity and arranged in a hierarchical structure, the service metadata includes technical aspects relating to services implemented in software applications, and the instance descriptor metadata contains data transformation information relating to a transform of data between software applications and cross-references between the functionality metadata and runtime instances of the services; storing, using the computer processor, syntactic information for the services in the database, the syntactic information being cross-referenced to semantic information and related to the software applications each implementing a step of the business processes; comparing, by the computer processor, user input relating to business process with the semantic information and syntactic information, and associations therebetween on a match between the input and the semantic information, identifying, by the computer processor, corresponding syntactic information based on the associations; and from the corresponding syntactic information, identifying, by the computer processor, a software application that implements the step of the business process specified in the user input; identifying, by the computer processor, the data transformation information corresponding to the identified software application; and generating, by the computer processor, an integrated sequence of runtime instances of identified software applications to implement the business process by repeating the above comparing, identifying corresponding syntactic information and identifying a software application steps, wherein each runtime instance in the sequence implements a respective step of the business process and communicates with adjacent runtime instances via adapters created based on the identified data transformation information. 6. The method of claim 1 , wherein the instance descriptor metadata further contains a runtime descriptor that stores an association between functionality metadata and a runtime instance.
| 0.5 |
9,946,709 | 8 | 11 |
8. A computer system for identifying word-senses, the computer system comprising: one or more computer processors, one or more computer-readable storage media, and program instructions stored on the one or more of the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to identify a frequency of occurrence value of a received word from each of a plurality of domain tables, wherein each of the plurality of domain tables comprises a frequency of occurrence value corresponding to the received word, a word-sense corresponding to the received word, and temporal properties corresponding to the received word, wherein the frequency of occurrence value is determined using an n-gram viewer; program instructions to associate the received word with a domain table from the plurality of domain tables based on the frequency of occurrence value corresponding to the received word meeting a threshold value; and program instructions to identify a word-sense of the received word based on the corresponding word-sense from the associated domain table.
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8. A computer system for identifying word-senses, the computer system comprising: one or more computer processors, one or more computer-readable storage media, and program instructions stored on the one or more of the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to identify a frequency of occurrence value of a received word from each of a plurality of domain tables, wherein each of the plurality of domain tables comprises a frequency of occurrence value corresponding to the received word, a word-sense corresponding to the received word, and temporal properties corresponding to the received word, wherein the frequency of occurrence value is determined using an n-gram viewer; program instructions to associate the received word with a domain table from the plurality of domain tables based on the frequency of occurrence value corresponding to the received word meeting a threshold value; and program instructions to identify a word-sense of the received word based on the corresponding word-sense from the associated domain table. 11. The computer system of claim 8 , further comprising: program instructions to receive an additional word; and program instructions to identify one or more word-senses corresponding to the additional word based on one or more corresponding word-senses in the associated domain tables, based on the frequency of occurrence value of the additional word in the domain table meeting the threshold value, and the one or more corresponding word-senses in a corresponding domain dictionary.
| 0.558288 |
8,271,506 | 17 | 20 |
17. A computing device comprising: a processor; at least one communication channel connected to the processor, the at least one communication channel further connected to a plurality of computing devices transmitting a plurality of information objects (IOs) over the at least one communication channel to the processor, the plurality of IOs comprising social data, spatial data, temporal data and logical data relating to a plurality of real-world entities (RWEs); a storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: correlation logic executed by the processor for correlating associations between the plurality of IOs and the plurality of RWEs based upon analysis of social data, spatial data, temporal data and logical data associated with the plurality of IOs and the plurality of RWEs; and relationship identification logic executed by the processor for identifing POV relationships between the RWEs based upon the correlations made by the correlation logic.
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17. A computing device comprising: a processor; at least one communication channel connected to the processor, the at least one communication channel further connected to a plurality of computing devices transmitting a plurality of information objects (IOs) over the at least one communication channel to the processor, the plurality of IOs comprising social data, spatial data, temporal data and logical data relating to a plurality of real-world entities (RWEs); a storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: correlation logic executed by the processor for correlating associations between the plurality of IOs and the plurality of RWEs based upon analysis of social data, spatial data, temporal data and logical data associated with the plurality of IOs and the plurality of RWEs; and relationship identification logic executed by the processor for identifing POV relationships between the RWEs based upon the correlations made by the correlation logic. 20. The computing device of claim 17 such that the relationship identification logic further comprises logic for identifying the POV relationships as explicit if the POV relationships between the RWEs are based upon identified correlations between the RWEs.
| 0.536101 |
5,524,179 | 6 | 8 |
6. A fuzzy inference processing apparatus according to claim 5, wherein said calculators comprises a predetermined number of calculators for respectively storing the then-part membership functions defined in the then-part of the rules; said first synthesizing means comprises the predetermined number of synthesizers respectively connected to said predetermined number of calculators; and said CPU comprises a central processing unit for supplying the grades of if-part membership functions for each rule to a synthesizer connected to a calculator storing the then-part membership function of the rule.
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6. A fuzzy inference processing apparatus according to claim 5, wherein said calculators comprises a predetermined number of calculators for respectively storing the then-part membership functions defined in the then-part of the rules; said first synthesizing means comprises the predetermined number of synthesizers respectively connected to said predetermined number of calculators; and said CPU comprises a central processing unit for supplying the grades of if-part membership functions for each rule to a synthesizer connected to a calculator storing the then-part membership function of the rule. 8. A fuzzy inference processing apparatus according to claim 6, wherein said predetermined number of synthesizers comprises multipliers; and said second synthesizing means comprises an adder.
| 0.547393 |
7,567,957 | 5 | 7 |
5. A computer-implemented method for providing an information navigation system for searching a set of materials having navigation states, the method comprising: providing information including: the set of materials, a plurality of attributes characterizing the materials, a plurality of values describing the materials, each value of the values having an association with at least one attribute of the attributes, each association defining an attribute-value pair, and a plurality of navigation states, each navigation state corresponding to a particular set of attribute-value pairs and to a particular subset of materials, wherein the particular subset of materials consists of materials in the information navigation system that are described by every attribute-value pair in the particular set of attribute-value pairs corresponding to said each navigation state, such that each material of materials in the particular subset of materials is described by every attribute-value pair in the particular set of attribute-value pairs corresponding to said each navigation state; generating a partial set of pre-computed navigation states by using a computer, wherein a first navigation state of the partial set of pre-computed navigation states includes a first attribute-value pair having a first attribute, in which the first attribute-value pair does not describe all the materials in the information navigation system that the first attribute characterizes, wherein a second navigation state of the partial set of pre-computed navigation states includes a second attribute-value pair having the first attribute, in which the second attribute-value pair refines the first attribute-value pair, and wherein at least one of the first navigation state and the second navigation state includes a third attribute-value pair having a third attribute, which is not the same as the first attribute, wherein the third attribute-value pair is mutually incomparable with the first attribute-value pair and is mutually incomparable with the second attribute-value pair, and the third attribute-value pair does not describe all the materials in the information navigation system that the third attribute characterizes; storing the partial set of pre-computed navigation states in a data structure in a memory, the partial set of pre-computed navigation states stored in the data structure including at least one of the first navigation state and the second navigation state; providing an interface to the information navigation system, the interface including a free-text search tool for and the interface providing a plurality of transitions, each transition providing a direct path, with no intervening navigation states, between two of the navigation states, wherein said each transition represents a change from a set of attribute-value pairs corresponding to an originating navigation to the set of attribute-value pairs corresponding to a destination navigation state, wherein a series of one or more transitions provides a path between any two navigation states, wherein the interface provides a direct path, with no intervening navigation states, between the first navigation state and the second navigation state, wherein the interface includes a guided search tool for enabling navigation from a current navigation state based on the plurality of transitions among the plurality of navigation states, and wherein the interface operates in an XML-based environment; searching, by using the computer, descriptive information associated with the set of materials, based at least in part on a free-text query accepted from the free-text search tool of the provided interface, to produce a set of free-text query interpretations; accepting a query to the navigation system based at least in part on the free-text query interpretations; and returning, to a user, a responsive navigation state by retrieving a pre-computed navigation state from the data structure based on the query.
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5. A computer-implemented method for providing an information navigation system for searching a set of materials having navigation states, the method comprising: providing information including: the set of materials, a plurality of attributes characterizing the materials, a plurality of values describing the materials, each value of the values having an association with at least one attribute of the attributes, each association defining an attribute-value pair, and a plurality of navigation states, each navigation state corresponding to a particular set of attribute-value pairs and to a particular subset of materials, wherein the particular subset of materials consists of materials in the information navigation system that are described by every attribute-value pair in the particular set of attribute-value pairs corresponding to said each navigation state, such that each material of materials in the particular subset of materials is described by every attribute-value pair in the particular set of attribute-value pairs corresponding to said each navigation state; generating a partial set of pre-computed navigation states by using a computer, wherein a first navigation state of the partial set of pre-computed navigation states includes a first attribute-value pair having a first attribute, in which the first attribute-value pair does not describe all the materials in the information navigation system that the first attribute characterizes, wherein a second navigation state of the partial set of pre-computed navigation states includes a second attribute-value pair having the first attribute, in which the second attribute-value pair refines the first attribute-value pair, and wherein at least one of the first navigation state and the second navigation state includes a third attribute-value pair having a third attribute, which is not the same as the first attribute, wherein the third attribute-value pair is mutually incomparable with the first attribute-value pair and is mutually incomparable with the second attribute-value pair, and the third attribute-value pair does not describe all the materials in the information navigation system that the third attribute characterizes; storing the partial set of pre-computed navigation states in a data structure in a memory, the partial set of pre-computed navigation states stored in the data structure including at least one of the first navigation state and the second navigation state; providing an interface to the information navigation system, the interface including a free-text search tool for and the interface providing a plurality of transitions, each transition providing a direct path, with no intervening navigation states, between two of the navigation states, wherein said each transition represents a change from a set of attribute-value pairs corresponding to an originating navigation to the set of attribute-value pairs corresponding to a destination navigation state, wherein a series of one or more transitions provides a path between any two navigation states, wherein the interface provides a direct path, with no intervening navigation states, between the first navigation state and the second navigation state, wherein the interface includes a guided search tool for enabling navigation from a current navigation state based on the plurality of transitions among the plurality of navigation states, and wherein the interface operates in an XML-based environment; searching, by using the computer, descriptive information associated with the set of materials, based at least in part on a free-text query accepted from the free-text search tool of the provided interface, to produce a set of free-text query interpretations; accepting a query to the navigation system based at least in part on the free-text query interpretations; and returning, to a user, a responsive navigation state by retrieving a pre-computed navigation state from the data structure based on the query. 7. The method of claim 5 , wherein the descriptive information includes text distinct from attribute-value pairs associated with the set of materials.
| 0.590164 |
9,836,511 | 17 | 24 |
17. A non-transitory computer-readable storage medium including instructions that, when executed by one or more processors, cause the one or more processors to: receive text obtained from a data source on a network, wherein the text includes unstructured data, wherein the text is associated with an item, wherein the item is associated with a plurality of attributes; search the text, wherein the text is searched using the plurality of attributes, wherein searching includes determining whether the text includes an attribute from the plurality of attributes; determine a plurality of subsets of the text that are associated with a particular attribute from the plurality of attributes, wherein the plurality of subsets of the text include a qualitative assessment of the particular attribute; normalize the plurality of subsets of the text, wherein normalizing includes reducing the plurality of subsets of the text to a common form; determine a plurality of scores for the particular attribute, wherein determining includes using the normalized subsets of the text and a source of the text, and wherein the scores associate the qualitative assessment from each of the normalized subsets of text with a numerical value; determine a resolved score for the particular attribute, wherein the resolved score is determined using the plurality of scores; determine an attribute format for displaying the plurality of attributes associated with the item, wherein determining includes using the resolved score for the particular attribute; display the plurality of attributes using the attribute format; determine a score for the item, wherein determining includes aggregating a plurality of scores associated with the plurality of attributes including the resolved score; generate an index, wherein the index includes the resolved score and the subsets of the text; display the subsets of the text using the index.
|
17. A non-transitory computer-readable storage medium including instructions that, when executed by one or more processors, cause the one or more processors to: receive text obtained from a data source on a network, wherein the text includes unstructured data, wherein the text is associated with an item, wherein the item is associated with a plurality of attributes; search the text, wherein the text is searched using the plurality of attributes, wherein searching includes determining whether the text includes an attribute from the plurality of attributes; determine a plurality of subsets of the text that are associated with a particular attribute from the plurality of attributes, wherein the plurality of subsets of the text include a qualitative assessment of the particular attribute; normalize the plurality of subsets of the text, wherein normalizing includes reducing the plurality of subsets of the text to a common form; determine a plurality of scores for the particular attribute, wherein determining includes using the normalized subsets of the text and a source of the text, and wherein the scores associate the qualitative assessment from each of the normalized subsets of text with a numerical value; determine a resolved score for the particular attribute, wherein the resolved score is determined using the plurality of scores; determine an attribute format for displaying the plurality of attributes associated with the item, wherein determining includes using the resolved score for the particular attribute; display the plurality of attributes using the attribute format; determine a score for the item, wherein determining includes aggregating a plurality of scores associated with the plurality of attributes including the resolved score; generate an index, wherein the index includes the resolved score and the subsets of the text; display the subsets of the text using the index. 24. The non-transitory computer-readable storage medium of claim 17 , further includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including: determining an aggregate score for the particular attribute, wherein determining the aggregate score uses the resolved score and one or more scores determined using one or more additional texts.
| 0.559957 |
8,533,680 | 8 | 12 |
8. One or more nonvolatile computer-readable storage media containing instructions which, when executed by a computer, cause the computer to perform a method, the method comprising: passing a symbolic parameter to a function of a program in a symbolic state representation of a program, the symbolic parameter comprising a symbolic sub-parameter that comprises a variable term; examining a set of value constraints for a pre-defined approximation of possible values associated with the symbolic parameter; as a result of not finding the pre-defined approximation of possible values in the set of value constraints, generating a domain of possible solutions for the symbolic parameter, the generating comprising: determining properties of the symbolic parameter, the properties of the symbolic parameter comprising a term type; determining possible values for the variable term, the determining the possible values for the variable term comprises walking over field maps of a representation of a given state and extracting one or more object terms appearing in the given state which match a type of the variable term; and selecting and applying one or more of a plurality of domain computation techniques according to the properties of the symbolic parameter comprising the term type; and performing the symbolic execution of the function using one or more solutions of the domain of possible solutions to generate a set of one or more actual solutions.
|
8. One or more nonvolatile computer-readable storage media containing instructions which, when executed by a computer, cause the computer to perform a method, the method comprising: passing a symbolic parameter to a function of a program in a symbolic state representation of a program, the symbolic parameter comprising a symbolic sub-parameter that comprises a variable term; examining a set of value constraints for a pre-defined approximation of possible values associated with the symbolic parameter; as a result of not finding the pre-defined approximation of possible values in the set of value constraints, generating a domain of possible solutions for the symbolic parameter, the generating comprising: determining properties of the symbolic parameter, the properties of the symbolic parameter comprising a term type; determining possible values for the variable term, the determining the possible values for the variable term comprises walking over field maps of a representation of a given state and extracting one or more object terms appearing in the given state which match a type of the variable term; and selecting and applying one or more of a plurality of domain computation techniques according to the properties of the symbolic parameter comprising the term type; and performing the symbolic execution of the function using one or more solutions of the domain of possible solutions to generate a set of one or more actual solutions. 12. The one or more nonvolatile computer-readable storage media of claim 8 , wherein the method further comprises simplifying the symbolic parameter.
| 0.607895 |
9,251,791 | 11 | 22 |
11. A system comprising: a data processing apparatus; and a data store coupled to the data processing apparatus, in which is stored: an application-independent input method editor configured to receive input for a plurality of applications executable by an electronic device, the application-independent input method editor operable to: receive spoken input from a user of the electronic device in an application of the plurality of applications; determine a category for the application; provide the spoken input and data that indicates the application category to a server that includes a speech recognition system configured to select one or more language models to generate text based on the spoken input, wherein the one or more language models are selected based on the data that indicates the application category; receive text from the server, wherein the text represents a transcription of the spoken input; and provide the text as input to the application.
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11. A system comprising: a data processing apparatus; and a data store coupled to the data processing apparatus, in which is stored: an application-independent input method editor configured to receive input for a plurality of applications executable by an electronic device, the application-independent input method editor operable to: receive spoken input from a user of the electronic device in an application of the plurality of applications; determine a category for the application; provide the spoken input and data that indicates the application category to a server that includes a speech recognition system configured to select one or more language models to generate text based on the spoken input, wherein the one or more language models are selected based on the data that indicates the application category; receive text from the server, wherein the text represents a transcription of the spoken input; and provide the text as input to the application. 22. The system of claim 11 , wherein the one or more language models are further selected based on one or more utterances in the spoken input.
| 0.828916 |
8,751,239 | 22 | 23 |
22. An apparatus comprising: means for training, at a user terminal, a first voice conversion model with respect to a training source speech of a first speaker and a second voice conversion model with respect to a training target speech of a second speaker; wherein training the first voice conversion model further comprises determining a first conversion function for transforming any source speech into corresponding synthetic speech, the first conversion function receiving the training source speech of the first speaker and a training source synthetic speech of the first speaker as inputs, and wherein training the second voice conversion model further comprises determining a second conversion function for transforming synthetic speech into corresponding target speech, the second conversion function receiving the training target speech of the second speaker and a training target synthetic speech of the second speaker as inputs; and wherein said training targets synthetic speech is produced from said training target speech; means for processing, at the user terminal, source speech of the first speaker using the first voice conversion model to convert the source speech to synthetic speech; and means for processing, at a user terminal, an output of the first voice conversion model at the second voice conversion model to produce target speech corresponding to the source speech.
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22. An apparatus comprising: means for training, at a user terminal, a first voice conversion model with respect to a training source speech of a first speaker and a second voice conversion model with respect to a training target speech of a second speaker; wherein training the first voice conversion model further comprises determining a first conversion function for transforming any source speech into corresponding synthetic speech, the first conversion function receiving the training source speech of the first speaker and a training source synthetic speech of the first speaker as inputs, and wherein training the second voice conversion model further comprises determining a second conversion function for transforming synthetic speech into corresponding target speech, the second conversion function receiving the training target speech of the second speaker and a training target synthetic speech of the second speaker as inputs; and wherein said training targets synthetic speech is produced from said training target speech; means for processing, at the user terminal, source speech of the first speaker using the first voice conversion model to convert the source speech to synthetic speech; and means for processing, at a user terminal, an output of the first voice conversion model at the second voice conversion model to produce target speech corresponding to the source speech. 23. The apparatus of claim 22 , wherein utterances of the training source speech are not parallel to utterances of the training target speech.
| 0.5 |
8,086,548 | 12 | 13 |
12. The computer-readable storage medium of claim 10 , wherein the method further comprises generating fingerprints for the first set of passages, and wherein at least one fingerprint corresponds to a state of the HMM.
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12. The computer-readable storage medium of claim 10 , wherein the method further comprises generating fingerprints for the first set of passages, and wherein at least one fingerprint corresponds to a state of the HMM. 13. The computer-readable storage medium of claim 12 , wherein the method further comprises generating fingerprints for the second set of passages, and wherein the fingerprints for the second set of passages correspond to an observation sequence of the HMM.
| 0.5 |
4,737,922 | 1 | 4 |
1. A character data output apparatus, comprising: input means for inputting sentence data, and for inputting certain groups of character data with associated special format data which format data enables the corresponding group of character data to be printed in a desired format; first memory means for storing the certain groups of character data and the associated special format data inputted by said input means; second memory means for storing the sentence data inputted by said input means excluding the special format data; processing means for discriminating if the sentence data stored in said second memory means includes character data groups coinciding with the certain groups of character data stored in said first memory means; and output means for automatically outputting, when said processing means discriminates that a character data group coinciding with the certain groups of character data stored in said first memory means is included in the sentence data, all the coinciding character data groups in the sentence data stored in said second memory means in accordance with the associated special format data as stored in said first memory means.
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1. A character data output apparatus, comprising: input means for inputting sentence data, and for inputting certain groups of character data with associated special format data which format data enables the corresponding group of character data to be printed in a desired format; first memory means for storing the certain groups of character data and the associated special format data inputted by said input means; second memory means for storing the sentence data inputted by said input means excluding the special format data; processing means for discriminating if the sentence data stored in said second memory means includes character data groups coinciding with the certain groups of character data stored in said first memory means; and output means for automatically outputting, when said processing means discriminates that a character data group coinciding with the certain groups of character data stored in said first memory means is included in the sentence data, all the coinciding character data groups in the sentence data stored in said second memory means in accordance with the associated special format data as stored in said first memory means. 4. An apparatus according to claim 1, wherein said input means comrises a predetermined key which is operative to initiate the discrimination operation by said processing means.
| 0.673432 |
8,296,124 | 1 | 5 |
1. A method for detecting incorrectly translated text in a translated document, comprising: identifying a target language for the translated document; identifying a set of one or more terms in the translated document that are invalid terms in the target language; analyzing, as performed by a processor, the set of invalid terms to determine a distribution of invalid terms in the translated document; and determining from the distribution of invalid terms whether one or more of the invalid terms comprise incorrectly translated text.
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1. A method for detecting incorrectly translated text in a translated document, comprising: identifying a target language for the translated document; identifying a set of one or more terms in the translated document that are invalid terms in the target language; analyzing, as performed by a processor, the set of invalid terms to determine a distribution of invalid terms in the translated document; and determining from the distribution of invalid terms whether one or more of the invalid terms comprise incorrectly translated text. 5. The method of claim 1 , wherein determining the distribution of invalid terms further comprises detecting contiguous invalid terms in the translated document.
| 0.768012 |
5,495,605 | 13 | 14 |
13. The tool of claim 88, wherein said first set of information has nodes and said syntactical graph also has nodes and said means for comparing comprises means for associating said nodes of said first set of information with said nodes of said syntactical graph and placing projections and tests on nodes of said first set of information.
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13. The tool of claim 88, wherein said first set of information has nodes and said syntactical graph also has nodes and said means for comparing comprises means for associating said nodes of said first set of information with said nodes of said syntactical graph and placing projections and tests on nodes of said first set of information. 14. The tool of claim 13, wherein the RDBMS performs operations in a predetermined order and said means for association of said nodes of said first information with said nodes of said syntactical graph comprises means for distinguishing between predictable operations and unpredictable operations from said operations performed by the RDBMS, means for associating predictable nodes of said first set of information with said predictable nodes of said syntactical graph, with unpredictable nodes constituting links between said associated predictable nodes.
| 0.5 |
9,953,085 | 7 | 8 |
7. A system for matching a content item in a data file to a search entity comprising one or more processors and a memory configured to: maintain a plurality of entity-action pairs and bidding parameters specific to each entity-action pair of the plurality of entity-action pairs; receive a first search query from a client device, the first search query including a query term indicative of a first search entity; identify, from the plurality of entity-action pairs, a first entity-action pair comprising the first search entity and a first online action and a second entity-action pair comprising the first search entity and a second online action that is different from the first online action responsive to the query term indicative of the first search entity in the received first search query; identify a second search entity not included in the first search query and identified using the first search entity and a knowledge graph of search entities; conduct a first content auction for the first entity-action pair based on bidding parameters specific to the first entity-action pair and a second content auction for the second entity-action pair based on bidding parameters specific to the second entity-action pair and responsive to identifying the first entity-action pair and the second entity-action pair; determine a first set of third-party content items associated with the first entity-action pair for participating in the first content auction, each third-party content item of the first set of third-party content items including executable instructions for causing an application of the client device to automatically perform the first online action upon actuating that third-party content item by the client device; determine a second set of third-party content items associated with the first entity-action pair for participating in the second content auction, each third-party content item of the second set of third-party content items including executable instructions for causing the application of the client device to automatically perform the second online action upon actuating that third-party content item by the client device; select, responsive to the first content auction, a first content item of a first third-party content provider based on a first bidding parameter of the first third-party content provider specific to the first entity-action pair and select, responsive to the second content auction, a second content item of a second third-party content provider based on a second bidding parameter of the second third-party content provider specific to the second entity-action pair, the first and second content items for presenting with search results corresponding to the first search query on the client device; and select a link associated with the second search entity for presenting with the search results corresponding to the first search query on the client device, wherein actuation of the link by the client device causes the first search query to be replaced with a second search query associated with the second search entity and new content items to be selected instead of the first and second content items.
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7. A system for matching a content item in a data file to a search entity comprising one or more processors and a memory configured to: maintain a plurality of entity-action pairs and bidding parameters specific to each entity-action pair of the plurality of entity-action pairs; receive a first search query from a client device, the first search query including a query term indicative of a first search entity; identify, from the plurality of entity-action pairs, a first entity-action pair comprising the first search entity and a first online action and a second entity-action pair comprising the first search entity and a second online action that is different from the first online action responsive to the query term indicative of the first search entity in the received first search query; identify a second search entity not included in the first search query and identified using the first search entity and a knowledge graph of search entities; conduct a first content auction for the first entity-action pair based on bidding parameters specific to the first entity-action pair and a second content auction for the second entity-action pair based on bidding parameters specific to the second entity-action pair and responsive to identifying the first entity-action pair and the second entity-action pair; determine a first set of third-party content items associated with the first entity-action pair for participating in the first content auction, each third-party content item of the first set of third-party content items including executable instructions for causing an application of the client device to automatically perform the first online action upon actuating that third-party content item by the client device; determine a second set of third-party content items associated with the first entity-action pair for participating in the second content auction, each third-party content item of the second set of third-party content items including executable instructions for causing the application of the client device to automatically perform the second online action upon actuating that third-party content item by the client device; select, responsive to the first content auction, a first content item of a first third-party content provider based on a first bidding parameter of the first third-party content provider specific to the first entity-action pair and select, responsive to the second content auction, a second content item of a second third-party content provider based on a second bidding parameter of the second third-party content provider specific to the second entity-action pair, the first and second content items for presenting with search results corresponding to the first search query on the client device; and select a link associated with the second search entity for presenting with the search results corresponding to the first search query on the client device, wherein actuation of the link by the client device causes the first search query to be replaced with a second search query associated with the second search entity and new content items to be selected instead of the first and second content items. 8. The system of claim 7 , wherein the one or more processors and the memory are configured to: receive a data file from a computing device of a first third-party content provider comprising one or more content items including the first content item, each of the one or more content items comprising identification data, a respective content item type, and a respective online action, each of the one or more content items associated with a product or service of the first third-party content provider; identify the first search entity based on identification data and a content item type for the first content item in the data file, the first search entity corresponding to a named physical entity; generate, based on the data file, the first entity-action pair comprising the first search entity and the first online action, the first online action associated with the first content item in the data file; and associate the first entity-action pair with the first bidding parameter specific to the first entity-action pair.
| 0.5 |
9,400,919 | 1 | 13 |
1. A computer-implemented method for training a pyramid convolutional neural network (CNN) comprising at least N shared layers where N≧2 and at least one unshared network coupled to the Nth shared layer, the method comprising: training CNN levels 1 to N in that order, wherein CNN level n comprises an input for receiving face images, the first n shared layers of the pyramid CNN, the unshared network of the pyramid CNN, and an output producing representations of the face images; wherein the input is coupled to a first of the n shared layers; each shared layer includes convolution, non-linearity and down-sampling; an nth of the n shared layers is coupled to the unshared network; and the unshared network is coupled to the output; wherein training CNN level n comprises: presenting face images to the input, each face image producing a corresponding representation at the output; processing the representations to produce estimates of a metric, for which actual values of the metric are known; and adapting the nth shared layer and the unshared network based on the estimates of the metric compared to the actual values of the metric.
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1. A computer-implemented method for training a pyramid convolutional neural network (CNN) comprising at least N shared layers where N≧2 and at least one unshared network coupled to the Nth shared layer, the method comprising: training CNN levels 1 to N in that order, wherein CNN level n comprises an input for receiving face images, the first n shared layers of the pyramid CNN, the unshared network of the pyramid CNN, and an output producing representations of the face images; wherein the input is coupled to a first of the n shared layers; each shared layer includes convolution, non-linearity and down-sampling; an nth of the n shared layers is coupled to the unshared network; and the unshared network is coupled to the output; wherein training CNN level n comprises: presenting face images to the input, each face image producing a corresponding representation at the output; processing the representations to produce estimates of a metric, for which actual values of the metric are known; and adapting the nth shared layer and the unshared network based on the estimates of the metric compared to the actual values of the metric. 13. The computer-implemented method of claim 1 wherein the trained pyramid CNN is more than 97% accurate on an LFW benchmark (labeled faces wild).
| 0.87193 |
8,392,352 | 18 | 19 |
18. The computer-implemented method of claim 17 , wherein at least one of the first layer, and the second layer is automatically generated.
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18. The computer-implemented method of claim 17 , wherein at least one of the first layer, and the second layer is automatically generated. 19. The computer-implemented method of claim 18 , further comprising: presenting to a user of at least one result representing information embedded in a plurality of parameters and in at least one structure of the neuro-fuzzy expert system which has been trained.
| 0.5 |
10,013,414 | 25 | 26 |
25. The management entity of claim 21 , wherein the processor executes the instructions to extract the context tokens from the parsed request, to map the context tokens to a first set of model elements, to extract the content tokens from the parsed request, and to map the content tokens to a second set of model elements.
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25. The management entity of claim 21 , wherein the processor executes the instructions to extract the context tokens from the parsed request, to map the context tokens to a first set of model elements, to extract the content tokens from the parsed request, and to map the content tokens to a second set of model elements. 26. The management entity of claim 25 , wherein the processor executes the instructions to combine the first set of model elements and the second set of model elements into a combined set of model elements, to optimize the combined set of model elements to produce an optimized set of model elements, and to convert the optimized set of model elements into the platform-neutral description of the results.
| 0.5 |
8,560,531 | 8 | 9 |
8. The method of claim 1 , wherein one of the search parameters is a geospatial parameter, and wherein calculating the proximity score comprises calculating a geospatial proximity score.
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8. The method of claim 1 , wherein one of the search parameters is a geospatial parameter, and wherein calculating the proximity score comprises calculating a geospatial proximity score. 9. The method of claim 8 , wherein calculating the geospatial proximity score further comprises: determining a geospatial distance, d Gdist , from a central point of the user-entered geospatial search parameter for the dataset using the following formula or a variation or derivative thereof: d Gdist = { 0 d Gmax ≤ r ( d Gmax / r - 1 ) 2 2 ( d Gmax - d Gmin ) / r d Gmin ≤ r , d Gmax ≥ r ( d Gmin + d Gmax ) / r - 1 d Gmin > r , wherein r is the radius of the range expressed by the user-entered geospatial search parameter and d Gmin and d Gmax are the minimum and maximum distances within the dataset from the central point.
| 0.5 |
9,402,057 | 10 | 19 |
10. An avatar portal service providing an online editor to one or more IP clients wherein each of said IP clients create and customize digital avatars based on detected key facial features detected from at least one uploaded photograph of one or more subscribers associated with said IP clients, said portal service comprising: an avatar web server storing data corresponding to digital avatars associated with said IP clients and preferences associated with subscribers associated with each of said IP clients and rendering an avatar portal interface to subscribers; a photofit server creating the 3D model of uploaded photographs of said subscribers; an avatar editor server rendering said user's avatars according to a plurality of customization operations; a video renderer creating pre-encoded stock footages of said avatars; an avatar repository receiving said pre-encoded stock footages and storing said uploaded photographs, avatars and pre-encoded stock footages of said subscribers; and said pre-encoded stock footages created by said video renderer being used in said avatar-calling service for lip, face and body movement synchronization operations.
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10. An avatar portal service providing an online editor to one or more IP clients wherein each of said IP clients create and customize digital avatars based on detected key facial features detected from at least one uploaded photograph of one or more subscribers associated with said IP clients, said portal service comprising: an avatar web server storing data corresponding to digital avatars associated with said IP clients and preferences associated with subscribers associated with each of said IP clients and rendering an avatar portal interface to subscribers; a photofit server creating the 3D model of uploaded photographs of said subscribers; an avatar editor server rendering said user's avatars according to a plurality of customization operations; a video renderer creating pre-encoded stock footages of said avatars; an avatar repository receiving said pre-encoded stock footages and storing said uploaded photographs, avatars and pre-encoded stock footages of said subscribers; and said pre-encoded stock footages created by said video renderer being used in said avatar-calling service for lip, face and body movement synchronization operations. 19. The portal service of claim 10 , avatars are based on at least one uploaded photograph, by detecting and calculating key facial features automatically.
| 0.75 |
8,965,926 | 4 | 6 |
4. The system of claim 1 , further comprising: an external application, the external application being processed to request collection information regarding at least a portion of the persistent document collections from the content management application to enable at least one of the plurality of users to download the one or more of the documents that are represented by the collection information.
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4. The system of claim 1 , further comprising: an external application, the external application being processed to request collection information regarding at least a portion of the persistent document collections from the content management application to enable at least one of the plurality of users to download the one or more of the documents that are represented by the collection information. 6. The system of claim 4 , wherein the external application is processed to modify the one or more of the documents that are represented by the collection information.
| 0.505917 |
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