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1. A computer implemented method for multimodal cross-vocabulary mapping, the computer implemented method comprising: annotating a corpus of multimodal content simultaneously using annotations from a plurality of vocabularies to form a set of common annotations; identifying relationships between a first vocabulary associated with a first modality and a second vocabulary associated with a second modality using the set of common annotations to form a multimodal vocabulary mapping; and mapping with a computing device items in the first vocabulary associated with the first modality to items in the second vocabulary associated with the second modality using the multimodal vocabulary mapping. | 1. A computer implemented method for multimodal cross-vocabulary mapping, the computer implemented method comprising: annotating a corpus of multimodal content simultaneously using annotations from a plurality of vocabularies to form a set of common annotations; identifying relationships between a first vocabulary associated with a first modality and a second vocabulary associated with a second modality using the set of common annotations to form a multimodal vocabulary mapping; and mapping with a computing device items in the first vocabulary associated with the first modality to items in the second vocabulary associated with the second modality using the multimodal vocabulary mapping. 2. The computer implemented method of claim 1 further comprising: responsive to receiving a query to search for content that includes query items associated with the first vocabulary, identifying a set of items in the second vocabulary that are mapped to the query items associated with the first vocabulary to form a set of mapped items in a second modality; and adding the set of mapped items in the second modality to the query to form an expanded query, wherein the expanded query can be used to search for content in the first modality and the second modality simultaneously. | 0.593317 |
1. A method implemented at least in part by a computing system, the method comprising: by the computing system: presenting a first user interface implementing a subscriber-identity-module-separated user interface paradigm; presenting a second user interface implementing a subscriber-identity-module-aggregated user interface paradigm; receiving user input via at least one of the user interfaces; and responsive to the user input, navigating to another user interface or performing one or more communications actions. | 1. A method implemented at least in part by a computing system, the method comprising: by the computing system: presenting a first user interface implementing a subscriber-identity-module-separated user interface paradigm; presenting a second user interface implementing a subscriber-identity-module-aggregated user interface paradigm; receiving user input via at least one of the user interfaces; and responsive to the user input, navigating to another user interface or performing one or more communications actions. 2. The method of claim 1 wherein: the second user interface implementing the subscriber-identity-module-aggregated user interface paradigm comprises an interface showing information regarding at least one communication transmitted or received via a first subscriber identity module card and information regarding at least one communication transmitted or received via a second, different subscriber identity module card. | 0.713333 |
1. A method comprising: receiving, using a presence-sensitive display coupled to a computing device, a first user input comprising a first drawing gesture associated with a first area for user input defined at the presence-sensitive display, wherein the first user input specifies one or more characters to be displayed at the presence-sensitive display, and wherein the first drawing gesture includes a drawn representation of the one or more characters; receiving, using the presence-sensitive display, a second user input comprising a second drawing gesture, wherein the second drawing gesture spans only the first area and a second area for user input defined at the presence-sensitive display, and wherein the second user input specifies a first editing operation associated with the one or more characters; applying, by the computing device, the first editing operation to the one or more characters in response to receiving the second user input; receiving, using the presence-sensitive display, a third user input comprising a third drawing gesture, wherein the third drawing gesture spans the first area, the second area, and a third area for user input defined at the presence-sensitive display, and wherein the third user input specifies a second editing operation associated with the one or more characters; and applying, by the computing device, the second editing operation to the one or more characters in response to receiving the third user input. | 1. A method comprising: receiving, using a presence-sensitive display coupled to a computing device, a first user input comprising a first drawing gesture associated with a first area for user input defined at the presence-sensitive display, wherein the first user input specifies one or more characters to be displayed at the presence-sensitive display, and wherein the first drawing gesture includes a drawn representation of the one or more characters; receiving, using the presence-sensitive display, a second user input comprising a second drawing gesture, wherein the second drawing gesture spans only the first area and a second area for user input defined at the presence-sensitive display, and wherein the second user input specifies a first editing operation associated with the one or more characters; applying, by the computing device, the first editing operation to the one or more characters in response to receiving the second user input; receiving, using the presence-sensitive display, a third user input comprising a third drawing gesture, wherein the third drawing gesture spans the first area, the second area, and a third area for user input defined at the presence-sensitive display, and wherein the third user input specifies a second editing operation associated with the one or more characters; and applying, by the computing device, the second editing operation to the one or more characters in response to receiving the third user input. 3. The method of claim 1 , wherein the second area comprises a subset of the first area, and wherein the second area is defined by a first graphical boundary that partitions the first area. | 0.561652 |
1. A method comprising: using a computing system having at least one processor to perform a process, the process comprising: creating a voice command mapping in response to loading a user interface page at the computing system by: identifying a markup language description of the user interface page loaded at the computing system, the identification of the markup language description occurring after loading the user interface page at the computing system; and generating the voice command mapping for the user interface page loaded at the computing system, wherein the voice command mapping maps a recognized word or phrase associated with at least one operation to one or more voice commands by parsing the markup language description identified from the user interface page to identify at least one user interface object specified by the markup language description configured to perform at least one operation responsive to a keyboard, mouse, or pointing device, the parsing of the markup language description being performed after loading the user interface page at the computing system, and the parsing does not create a modified version of the user interface page, wherein the voice command mapping uses a hash map data structure to store a relationship between at least one respective word or phrase to the at least one operation; processing an utterance in response to receiving the utterance at the computing system, the computing system displaying the user interface page, by: converting the utterance into a text representation of the utterance; determining a plurality of matches between the text representation of the utterance and multiple matching voice commands based on the voice command mapping for the user interface page loaded at the computing system; and performing a confirmation of a single matching voice command from among the plurality of matches. | 1. A method comprising: using a computing system having at least one processor to perform a process, the process comprising: creating a voice command mapping in response to loading a user interface page at the computing system by: identifying a markup language description of the user interface page loaded at the computing system, the identification of the markup language description occurring after loading the user interface page at the computing system; and generating the voice command mapping for the user interface page loaded at the computing system, wherein the voice command mapping maps a recognized word or phrase associated with at least one operation to one or more voice commands by parsing the markup language description identified from the user interface page to identify at least one user interface object specified by the markup language description configured to perform at least one operation responsive to a keyboard, mouse, or pointing device, the parsing of the markup language description being performed after loading the user interface page at the computing system, and the parsing does not create a modified version of the user interface page, wherein the voice command mapping uses a hash map data structure to store a relationship between at least one respective word or phrase to the at least one operation; processing an utterance in response to receiving the utterance at the computing system, the computing system displaying the user interface page, by: converting the utterance into a text representation of the utterance; determining a plurality of matches between the text representation of the utterance and multiple matching voice commands based on the voice command mapping for the user interface page loaded at the computing system; and performing a confirmation of a single matching voice command from among the plurality of matches. 2. The method of claim 1 , wherein a user interface object of the at least one user interface object is at least one of, a button, a textbox, or a checkbox. | 0.551819 |
1. A method executed by a processor for performing static analysis on source code having a low level language source code embedded in a high level language source code, wherein the high level language source code is represented in a high level representation that the static analysis can be performed on, the method comprising the steps of: transforming the embedded low level language source code to a high level representation that does not retain the full semantics of the low level language source code and that the static analysis can be performed on, by identifying a set of instructions in the low level language source code that represents a single high level statement in the high level representation, and transforming the set of instructions to represent the single high level statement in the high level representation; and performing static analysis on the high level representation of the high level language source code and the high level representation of the low level source code. | 1. A method executed by a processor for performing static analysis on source code having a low level language source code embedded in a high level language source code, wherein the high level language source code is represented in a high level representation that the static analysis can be performed on, the method comprising the steps of: transforming the embedded low level language source code to a high level representation that does not retain the full semantics of the low level language source code and that the static analysis can be performed on, by identifying a set of instructions in the low level language source code that represents a single high level statement in the high level representation, and transforming the set of instructions to represent the single high level statement in the high level representation; and performing static analysis on the high level representation of the high level language source code and the high level representation of the low level source code. 10. The method according to claim 1 , wherein the source code forms part of an embedded system. | 0.701672 |
6. A sound processing method applied to a sound processor, the sound processing method comprising: creating first and second resonance tube models based on a frequency characteristic that represents an acoustic property of an object to be measured, the first resonance tube model being modeled based on resonance properties of a first resonance peak with respect to a frequency band enclosing a first resonance frequency at the first resonance peak represented as the frequency characteristic, the second resonance tube model being modeled based on resonance properties of a second resonance peak with respect to a frequency band enclosing a high order resonance frequency which is not an integer multiple of the first resonance frequency at the second resonance peak represented as the frequency characteristic; extracting frequency component in the frequency band enclosing the first resonance frequency from the first resonance tube model to create a first partial acoustic model, and extract frequency component in the frequency band enclosing the second resonance frequency from the second resonance tube model to create a second partial acoustic model; and combining the first partial acoustic model and the second partial acoustic model to create an entire acoustic model. | 6. A sound processing method applied to a sound processor, the sound processing method comprising: creating first and second resonance tube models based on a frequency characteristic that represents an acoustic property of an object to be measured, the first resonance tube model being modeled based on resonance properties of a first resonance peak with respect to a frequency band enclosing a first resonance frequency at the first resonance peak represented as the frequency characteristic, the second resonance tube model being modeled based on resonance properties of a second resonance peak with respect to a frequency band enclosing a high order resonance frequency which is not an integer multiple of the first resonance frequency at the second resonance peak represented as the frequency characteristic; extracting frequency component in the frequency band enclosing the first resonance frequency from the first resonance tube model to create a first partial acoustic model, and extract frequency component in the frequency band enclosing the second resonance frequency from the second resonance tube model to create a second partial acoustic model; and combining the first partial acoustic model and the second partial acoustic model to create an entire acoustic model. 7. The sound processing method of claim 6 , wherein the creating is performed by a creating module, the extracting is performed by a filter, and the combining is performed by a combining module. | 0.516579 |
1. A method for creating digitized text for a record from an image of the record, comprising: obtaining one or more digital images of a record; evaluating the digital images in order to locate each of multiple word images; for each located word image, identifying multiple word features of that word image; assigning, to one group of word images, designated ones of the multiple word images based on the distance between the multiple word images, the distance representing the similarity of word features between at least two of the word images; selecting a representative word image in the one group of word images, by calculating, at a word clustering system, word feature values for the word features of each of the multiple word images assigned to the one group of word images, and using the word feature values to determine, at the word clustering system, a word image that is representative of the word images in the one group of word images; selecting digitized text for the representative word image; and assigning the selected digitized text to each of the word images in the one group of word images. | 1. A method for creating digitized text for a record from an image of the record, comprising: obtaining one or more digital images of a record; evaluating the digital images in order to locate each of multiple word images; for each located word image, identifying multiple word features of that word image; assigning, to one group of word images, designated ones of the multiple word images based on the distance between the multiple word images, the distance representing the similarity of word features between at least two of the word images; selecting a representative word image in the one group of word images, by calculating, at a word clustering system, word feature values for the word features of each of the multiple word images assigned to the one group of word images, and using the word feature values to determine, at the word clustering system, a word image that is representative of the word images in the one group of word images; selecting digitized text for the representative word image; and assigning the selected digitized text to each of the word images in the one group of word images. 7. The method of claim 1 , further comprising: calculating a mean of values for word features of the multiple word images assigned to the one group of word images, wherein the step of selecting a representative word image comprises selecting a word image in the one group of word images that is closest to the mean. | 0.564821 |
17. The system of claim 16 wherein the processing device comprises a coprocessor. | 17. The system of claim 16 wherein the processing device comprises a coprocessor. 18. The system of claim 17 wherein the coprocessor comprises a reconfigurable logic device. | 0.973758 |
9. A system for providing an extensible macro language, comprising: a macro handler comprising a macro processor operable to maintain, in a repository, a predefined macro language comprising a plurality of keywords and a plurality of associated commands for execution; a parser operable to parse a macro language expression to identify a new keyword in the macro language expression that is not within the plurality of keywords in the predefined macro language; and a registry of keywords and associated executable codes, including one or more keywords and one or more executable codes that are not included in the predefined macro language, each keyword being associated with a respective one of the executable codes, each executable code corresponding to a procedure that is not performed by the execution of the predefined macro language alone, wherein the macro handler is further operable to receive the new keyword from the parser, retrieve, from the registry of keywords and associated executable codes, the executable code associated with the new keyword identified within the macro language expression, and execute the retrieved executable code to run the extended macro command associated with the new keyword without recompiling the macro language, the executable code associated with the new keyword not included in the predefined macro language and resulting in the performance of a procedure that is not performed by execution of the predefined macro language alone. | 9. A system for providing an extensible macro language, comprising: a macro handler comprising a macro processor operable to maintain, in a repository, a predefined macro language comprising a plurality of keywords and a plurality of associated commands for execution; a parser operable to parse a macro language expression to identify a new keyword in the macro language expression that is not within the plurality of keywords in the predefined macro language; and a registry of keywords and associated executable codes, including one or more keywords and one or more executable codes that are not included in the predefined macro language, each keyword being associated with a respective one of the executable codes, each executable code corresponding to a procedure that is not performed by the execution of the predefined macro language alone, wherein the macro handler is further operable to receive the new keyword from the parser, retrieve, from the registry of keywords and associated executable codes, the executable code associated with the new keyword identified within the macro language expression, and execute the retrieved executable code to run the extended macro command associated with the new keyword without recompiling the macro language, the executable code associated with the new keyword not included in the predefined macro language and resulting in the performance of a procedure that is not performed by execution of the predefined macro language alone. 12. The system of claim 9 , wherein the parser is further operable to break the macro language expression down into a plurality of elements, at least one of the plurality of elements comprising a pointer to the extended macro command. | 0.617778 |
1. A method comprising: providing, by a processor over a network, a plurality of content items to a user at a user device; monitoring, via the processor over the network, interactions of the user with the provided content items at the user device; receiving, by the processor over the network, the monitored interactions comprising selections of the content items made by the user; recording, by the processor, information associated with each of the user selected content items in a user profile, the information comprising at least a content category of each of the user selected content items; analyzing, by the processor, the information recorded in the user profile, comprising: detecting different categories of the content items reviewed by the user, the number of the content items reviewed by the user for each category, and frequencies at which the user accesses the content items; calculating a read score based on at least the detected number of content items reviewed by the user for each category and a target number of content items to be reviewed for the same category; calculating a diversity score based on at least the number of the detected different categories; and calculating a frequency score based on at least the detected frequencies; determining, by the processor based on the calculated read score, diversity score, and frequency score, a final score associated with the user's reading habits, the final score is indicative of a diversity of content consumed by the user; generating, by the processor, a dashboard of the user's reading habits, the dashboard comprises the final score, a frequency of the user's consumption of content and the different categories associated with the user's content consumption; and transmitting, by the processor over the network, the dashboard to the user. | 1. A method comprising: providing, by a processor over a network, a plurality of content items to a user at a user device; monitoring, via the processor over the network, interactions of the user with the provided content items at the user device; receiving, by the processor over the network, the monitored interactions comprising selections of the content items made by the user; recording, by the processor, information associated with each of the user selected content items in a user profile, the information comprising at least a content category of each of the user selected content items; analyzing, by the processor, the information recorded in the user profile, comprising: detecting different categories of the content items reviewed by the user, the number of the content items reviewed by the user for each category, and frequencies at which the user accesses the content items; calculating a read score based on at least the detected number of content items reviewed by the user for each category and a target number of content items to be reviewed for the same category; calculating a diversity score based on at least the number of the detected different categories; and calculating a frequency score based on at least the detected frequencies; determining, by the processor based on the calculated read score, diversity score, and frequency score, a final score associated with the user's reading habits, the final score is indicative of a diversity of content consumed by the user; generating, by the processor, a dashboard of the user's reading habits, the dashboard comprises the final score, a frequency of the user's consumption of content and the different categories associated with the user's content consumption; and transmitting, by the processor over the network, the dashboard to the user. 7. The method of claim 1 , further comprising: including in the dashboard, by the processor, a comparison of the users' score with an average score of the user's social network. | 0.630497 |
7. A machine-implemented, non-abstract and automated process that provides for adaptive social networking between plural users of a machine system, where the machine system is used in implementing the process and where the process comprises: empowering a first user and/or one or more data processing devices proximate to the first user to cause one or more other data processors of the machine system, which other data processors are operatively coupled to the one or more proximate devices, to home in on one or more of at least one plurality of points, nodes or subregions in a maintained one of plural Communal Cognitions-representing Spaces maintained by the machine system, where the homed-in on points, nodes or subregions are ones determined by the machine system to more likely than others cross-correlate to apparent individualized current cognitions of the first user, wherein the Communal Cognitions-representing Spaces include a Context Space whose points, nodes or subregions include ones representing different user-adoptable roles; wherein said empowering includes machine-implemented identification of the first user; wherein said system-maintained plural Communal Cognitions-representing Spaces each includes stored data-objects representing hierarchically and/or spatially organized at least one plurality of points, nodes or subregions and wherein the hierarchical and/or spatial organizations in the respective Communal Cognitions-representing Space of at least one plurality of the points, nodes or subregions thereof are determined and are modifiable, at least in part, by over-a-network reported actions of a corresponding community formed by at least a subset of the plural users of the machine system; and wherein the empowering of the first user includes: automatically repeatedly carrying out one or more automated informational resource lookup operations on behalf of the first user without need for diverting focusing of attention by the first user for aiding the one or more automated informational resource lookup operations, at least one of the automated informational resource lookup operations being based on an identifying by the machine system of a likely context of the first user among plural contexts represented by the points, nodes or subregions of the Context Space; and providing the first user with an opportunity to access one or more informational resources identified by the machine system based on the one or more automated informational resource lookup operations. | 7. A machine-implemented, non-abstract and automated process that provides for adaptive social networking between plural users of a machine system, where the machine system is used in implementing the process and where the process comprises: empowering a first user and/or one or more data processing devices proximate to the first user to cause one or more other data processors of the machine system, which other data processors are operatively coupled to the one or more proximate devices, to home in on one or more of at least one plurality of points, nodes or subregions in a maintained one of plural Communal Cognitions-representing Spaces maintained by the machine system, where the homed-in on points, nodes or subregions are ones determined by the machine system to more likely than others cross-correlate to apparent individualized current cognitions of the first user, wherein the Communal Cognitions-representing Spaces include a Context Space whose points, nodes or subregions include ones representing different user-adoptable roles; wherein said empowering includes machine-implemented identification of the first user; wherein said system-maintained plural Communal Cognitions-representing Spaces each includes stored data-objects representing hierarchically and/or spatially organized at least one plurality of points, nodes or subregions and wherein the hierarchical and/or spatial organizations in the respective Communal Cognitions-representing Space of at least one plurality of the points, nodes or subregions thereof are determined and are modifiable, at least in part, by over-a-network reported actions of a corresponding community formed by at least a subset of the plural users of the machine system; and wherein the empowering of the first user includes: automatically repeatedly carrying out one or more automated informational resource lookup operations on behalf of the first user without need for diverting focusing of attention by the first user for aiding the one or more automated informational resource lookup operations, at least one of the automated informational resource lookup operations being based on an identifying by the machine system of a likely context of the first user among plural contexts represented by the points, nodes or subregions of the Context Space; and providing the first user with an opportunity to access one or more informational resources identified by the machine system based on the one or more automated informational resource lookup operations. 13. The automated process of claim 7 and further wherein the respective points, nodes or subregions (PNOS's) of at least one of the Communal Cognitions-representing Spaces of the machine system are distributed among: a primitives portion that contains primitive ones of the PNOS's; and a composites portion that contains operator nodes which each define a composite point, node or subregion based on two or more of the primitive PNOS's contained in the primitives portion. | 0.832239 |
23. A dual hash method for use with a pattern search engine said method comprising: using said pattern search engine comprising a programmable state machine comprising a balanced routing table search (BaRT)-based finite state machine (BFSM), said BFSM being implemented in hardware, or a combination of hardware and software; an initial rule bank, a default rule bank and a transition rule bank, each said rule having a test portion to determine if there is a match to a current rule, and a result portion which defines the next state targeted by said rule; storing default rules and dual hash rules that apply to a pattern context search in a default; rule bank that is indexed independently; storing transition rules that apply to said pattern context search in a transition rule bank; utilizing a rule entry in said default rule bank as an extension of a transition rule hash, said rule entry comprising a dual hash rule applicable to said pattern context search; and utilizing said dual hash rule when the default rule lookup is not required for a state; said transition rules having a higher priority than the rules on said default side, which is used for said dual hash; and when there is no match on either one of said default rules or said transition rules, said search engine reverts to said initial state; said dual hash being used (1) for any state for which input values covered by said transition rules are a super-set of said input values covered by said default rules; (2) wherein previous coverage can also be enforced by adding the missing uncovered input values of one or more default rules to a given state; and (3) wherein dual hash can always be used for anchored matching after a first character. | 23. A dual hash method for use with a pattern search engine said method comprising: using said pattern search engine comprising a programmable state machine comprising a balanced routing table search (BaRT)-based finite state machine (BFSM), said BFSM being implemented in hardware, or a combination of hardware and software; an initial rule bank, a default rule bank and a transition rule bank, each said rule having a test portion to determine if there is a match to a current rule, and a result portion which defines the next state targeted by said rule; storing default rules and dual hash rules that apply to a pattern context search in a default; rule bank that is indexed independently; storing transition rules that apply to said pattern context search in a transition rule bank; utilizing a rule entry in said default rule bank as an extension of a transition rule hash, said rule entry comprising a dual hash rule applicable to said pattern context search; and utilizing said dual hash rule when the default rule lookup is not required for a state; said transition rules having a higher priority than the rules on said default side, which is used for said dual hash; and when there is no match on either one of said default rules or said transition rules, said search engine reverts to said initial state; said dual hash being used (1) for any state for which input values covered by said transition rules are a super-set of said input values covered by said default rules; (2) wherein previous coverage can also be enforced by adding the missing uncovered input values of one or more default rules to a given state; and (3) wherein dual hash can always be used for anchored matching after a first character. 27. The method according to claim 23 , wherein said dual hash rules enable a significant reduction in the number of rules required to represent a state as dual hash rules are used for rules that cover a plurality of characters. | 0.779848 |
1. A method for rules-based knowledge-driven search filters, the method performed by a data processing system and comprising: receiving metadata for a plurality of searchable objects, by the data processing system, the metadata including at least one of an object type definition and object properties; defining search filter rules based on user properties and data conditions, by the data processing system; performing a search according to a rule-based configuration, by the data processing system, the rule-based configuration including filters for object properties and filter ordering rules, the filter ordering rules specifying the order in which the filters are applied; and displaying search results according to the rule-based configuration, by the data processing system. | 1. A method for rules-based knowledge-driven search filters, the method performed by a data processing system and comprising: receiving metadata for a plurality of searchable objects, by the data processing system, the metadata including at least one of an object type definition and object properties; defining search filter rules based on user properties and data conditions, by the data processing system; performing a search according to a rule-based configuration, by the data processing system, the rule-based configuration including filters for object properties and filter ordering rules, the filter ordering rules specifying the order in which the filters are applied; and displaying search results according to the rule-based configuration, by the data processing system. 8. The method of claim 1 , wherein the data processing system maintains a plurality of configuration definitions each corresponding to a respective specific search engine based on the search filter rules and the rule-based configuration. | 0.5 |
1. Network apparatus configured to provide information to at least one client apparatus in communication therewith, the network apparatus comprising: a wireless interface; and a network interface in data communication with the wireless interface; wherein said network apparatus is configured to: receive via the wireless interface a digitized representation of a speech input, the digitized representation generated by a speech recognition apparatus of the at least one client apparatus, the input relating to an organization or entity which a user of the at least one client apparatus wishes to locate; forward the digitized representation via the network interface to a server disposed remotely from the client apparatus, for identification by the server of a location associated with the organization or entity, and retrieval of data associated with the location; receive the data, the data relating to a graphical or visual representation of the location, the graphical or visual representation of the location being useful to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity; and forward the received data to the at least one client apparatus via the wireless interface for display on a display device of the client apparatus. | 1. Network apparatus configured to provide information to at least one client apparatus in communication therewith, the network apparatus comprising: a wireless interface; and a network interface in data communication with the wireless interface; wherein said network apparatus is configured to: receive via the wireless interface a digitized representation of a speech input, the digitized representation generated by a speech recognition apparatus of the at least one client apparatus, the input relating to an organization or entity which a user of the at least one client apparatus wishes to locate; forward the digitized representation via the network interface to a server disposed remotely from the client apparatus, for identification by the server of a location associated with the organization or entity, and retrieval of data associated with the location; receive the data, the data relating to a graphical or visual representation of the location, the graphical or visual representation of the location being useful to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity; and forward the received data to the at least one client apparatus via the wireless interface for display on a display device of the client apparatus. 22. The apparatus of claim 1 , wherein the wherein the received data relating to a graphical or visual representation of the location is configured to be displayed on a rotating basis with other content for display on the client apparatus, the rotation occurring without user intervention. | 0.69716 |
2. The method of claim 1 , wherein said received portable certificate of status is generated by an entity that is independent of the forum server. | 2. The method of claim 1 , wherein said received portable certificate of status is generated by an entity that is independent of the forum server. 3. The method of claim 2 , wherein the portable certificate of status is encrypted with a private key of the independent entity, the independent entity providing a matching public key to authenticate the portable certificate of status. | 0.948606 |
5. The method of claim 4 , wherein each rule includes a condition portion and an executable portion, wherein the condition portion describes a condition that defines whether the rule is applicable, and wherein the executable portion describes at least one action to be performed if the rule is applicable. | 5. The method of claim 4 , wherein each rule includes a condition portion and an executable portion, wherein the condition portion describes a condition that defines whether the rule is applicable, and wherein the executable portion describes at least one action to be performed if the rule is applicable. 6. The method of claim 5 , wherein the condition portion expresses the condition using at least one Boolean operator. | 0.788889 |
10. The apparatus according to claim 9 , wherein the detecting unit detects constant noise that lasts for at least a predetermined first period of time as the noise. | 10. The apparatus according to claim 9 , wherein the detecting unit detects constant noise that lasts for at least a predetermined first period of time as the noise. 11. The apparatus according to claim 10 , wherein the detecting unit detects, as the noise, the constant noise and sudden noise that occurs within a predetermined second period of time that is shorter than the first period of time. | 0.930533 |
8. A computer-readable medium having stored thereon computer-executable instructions for performing a method of analyzing a plurality of search sessions to identify intent-based clusters therein, each session comprising at least one received query from a user and a corresponding set of returned search results, each set of search results including or referring to at least one piece of content, each cluster representing a group of similar search sessions that are perceived as representing a common intent of a plurality of different users and that can be mapped to a common set of search results, the method comprising: identifying for each search session each received query thereof, the corresponding set of search results, and whether any particular piece of content of the search results was acceptable to the user as responsive to the corresponding search session; and grouping search sessions into clusters based on the commonality of judgments of a plurality of different users about a search result that is common to the user's respective search sessions, wherein each of said clusters includes search queries and search results, such grouping comprising: constructing a table with a plurality of entries therein, each entry representing a unique pair of sessions such that each session is paired with every other session a single time in the table; judging, for each entry of the table, a strength of commonality of the pair of sessions thereof; reordering the entries in the table according to decreasing strength; and reviewing each entry in the table as reordered to decide based on the judged strength thereof whether to assign each session thereof to an intent-based cluster. | 8. A computer-readable medium having stored thereon computer-executable instructions for performing a method of analyzing a plurality of search sessions to identify intent-based clusters therein, each session comprising at least one received query from a user and a corresponding set of returned search results, each set of search results including or referring to at least one piece of content, each cluster representing a group of similar search sessions that are perceived as representing a common intent of a plurality of different users and that can be mapped to a common set of search results, the method comprising: identifying for each search session each received query thereof, the corresponding set of search results, and whether any particular piece of content of the search results was acceptable to the user as responsive to the corresponding search session; and grouping search sessions into clusters based on the commonality of judgments of a plurality of different users about a search result that is common to the user's respective search sessions, wherein each of said clusters includes search queries and search results, such grouping comprising: constructing a table with a plurality of entries therein, each entry representing a unique pair of sessions such that each session is paired with every other session a single time in the table; judging, for each entry of the table, a strength of commonality of the pair of sessions thereof; reordering the entries in the table according to decreasing strength; and reviewing each entry in the table as reordered to decide based on the judged strength thereof whether to assign each session thereof to an intent-based cluster. 14. The medium of claim 8 wherein the method further comprises mapping each cluster to a common set of search results that is believed to satisfy the common purpose of such cluster so that all queries with the same common purpose map correctly based on such cluster. | 0.602658 |
1. A method for improving the operation of a computer system, the method comprising: creating a data record having data that can be accessed by credentialed users of a multi-tenant computing system; establishing restricted access for the created record and storing the restricted-access record in a tenant data store in the multi-tenant computing system such that a first subset of the credentialed users of the multi-tenant computing system may access the restricted-access record; accessing the restricted-access record stored in the tenant data store using access credentials of a user in the first subset of users; generating a note associated with the record, the note having restricted access that is different from the restricted access of the record that corresponds to a second subset of the credentialed users of the multi-tenant computing system; accessing the restricted-access record using access credentials of a user in the second subset; and displaying the record on the display with the note displayed over the record if the access credentials allow for access to both the restricted-access record and the note. | 1. A method for improving the operation of a computer system, the method comprising: creating a data record having data that can be accessed by credentialed users of a multi-tenant computing system; establishing restricted access for the created record and storing the restricted-access record in a tenant data store in the multi-tenant computing system such that a first subset of the credentialed users of the multi-tenant computing system may access the restricted-access record; accessing the restricted-access record stored in the tenant data store using access credentials of a user in the first subset of users; generating a note associated with the record, the note having restricted access that is different from the restricted access of the record that corresponds to a second subset of the credentialed users of the multi-tenant computing system; accessing the restricted-access record using access credentials of a user in the second subset; and displaying the record on the display with the note displayed over the record if the access credentials allow for access to both the restricted-access record and the note. 8. The method of claim 1 , wherein the display of the note comprises text data entered at the time of the creation of the note. | 0.728114 |
18. A system for ranking candidate documents in response to a search query, comprising: at least one processor; a memory, operatively connected to the at least one processor and containing instructions that, when executed by the at least one processor, perform a method comprising: creating an index of a plurality of documents in a corpus; calculating a junk score for at least a first document in the corpus, wherein calculating the junk score comprises: using a first candidate histogram for the first document in the corpus, wherein the first candidate histogram is specific to the first document; and using a junk profile, wherein the junk profile comprises: a first reference histogram for a first known junk document, wherein the first reference histogram is specific to the first known junk document and is based on a first junk variable; and comparing the first candidate histogram to the first reference histogram; receiving a search query; identifying, based on the search query and the index, candidate documents from the plurality of documents in the corpus, wherein the candidate documents include at least the first document; ranking the candidate documents based at least in part on the junk score for the first document; wherein creating the index comprises separately delineating document data from the plurality of documents if the document data matches the junk profile. | 18. A system for ranking candidate documents in response to a search query, comprising: at least one processor; a memory, operatively connected to the at least one processor and containing instructions that, when executed by the at least one processor, perform a method comprising: creating an index of a plurality of documents in a corpus; calculating a junk score for at least a first document in the corpus, wherein calculating the junk score comprises: using a first candidate histogram for the first document in the corpus, wherein the first candidate histogram is specific to the first document; and using a junk profile, wherein the junk profile comprises: a first reference histogram for a first known junk document, wherein the first reference histogram is specific to the first known junk document and is based on a first junk variable; and comparing the first candidate histogram to the first reference histogram; receiving a search query; identifying, based on the search query and the index, candidate documents from the plurality of documents in the corpus, wherein the candidate documents include at least the first document; ranking the candidate documents based at least in part on the junk score for the first document; wherein creating the index comprises separately delineating document data from the plurality of documents if the document data matches the junk profile. 19. The system of claim 18 , wherein the method further comprises: creating, for at least the first document, a candidate histogram for at least a first junk variable; wherein calculating the junk score comprises comparing the candidate histogram to the first reference histogram to determine a first similarity metric; wherein the junk profile comprises a dictionary of automatically generated data; wherein calculating the junk score further comprises comparing document data from the plurality of documents in the corpus to the dictionary of automatically generated data; and wherein creating the index comprises delineating in the index document data that matches the automatically generated data. | 0.5 |
9. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: creating two indexes in a client device, the two indexes including a prefix index that indexes documents stored on the client device according to partial words that are parts of words in titles of the documents, and further including a content index that indexes the documents stored on the client device according to full words found in textual content of the documents; receiving a desktop search request including a given search term; querying the prefix index to identify two or more first documents stored on the client device, where each first document has a title that includes a word that matches the given search term or that has a prefix that matches the given search term; querying the content index to identify two or more second documents stored on the client device, where each second document has textual content that includes a full word that matches the given search term; ranking the first documents and separately ranking the second documents to identify highest ranking first documents and highest ranking second documents stored on the client device; and determining a relevance score for each of the highest ranking first documents and the highest ranking second documents; determining a first combined relevance score of the highest ranking first documents and a second combined relevance score of the highest ranking second documents; displaying data identifying the highest ranking first documents above data identifying the highest ranking second documents in a results window on the display device when the combined relevance score of the first documents exceeds the combined relevance score of the second documents; and displaying data identifying the highest ranking second documents above data identifying the highest ranking first documents in the results window on the display device when the combined relevance score of the first documents exceeds the combined relevance score of the second documents. | 9. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: creating two indexes in a client device, the two indexes including a prefix index that indexes documents stored on the client device according to partial words that are parts of words in titles of the documents, and further including a content index that indexes the documents stored on the client device according to full words found in textual content of the documents; receiving a desktop search request including a given search term; querying the prefix index to identify two or more first documents stored on the client device, where each first document has a title that includes a word that matches the given search term or that has a prefix that matches the given search term; querying the content index to identify two or more second documents stored on the client device, where each second document has textual content that includes a full word that matches the given search term; ranking the first documents and separately ranking the second documents to identify highest ranking first documents and highest ranking second documents stored on the client device; and determining a relevance score for each of the highest ranking first documents and the highest ranking second documents; determining a first combined relevance score of the highest ranking first documents and a second combined relevance score of the highest ranking second documents; displaying data identifying the highest ranking first documents above data identifying the highest ranking second documents in a results window on the display device when the combined relevance score of the first documents exceeds the combined relevance score of the second documents; and displaying data identifying the highest ranking second documents above data identifying the highest ranking first documents in the results window on the display device when the combined relevance score of the first documents exceeds the combined relevance score of the second documents. 12. The computer storage medium of claim 9 , wherein the operations further comprise: determining a combined total quantity of the first documents and the second documents; and displaying a link to a separate web page that identifies all the first documents and the second documents, the link indicating the combined total quantity of the first documents and the second documents. | 0.603791 |
65. The method of claim 64 , wherein when the second information associated with first information exists, performing the further step of displaying the second information. | 65. The method of claim 64 , wherein when the second information associated with first information exists, performing the further step of displaying the second information. 66. The method of claim 65 , wherein the first information comprises a name. | 0.898712 |
10. An information processing method comprising: collecting texts stored in a storage unit in response to a general word extracting request signal input by a user or when a predetermined time is reached, and extracting a plurality of words from said collected texts; calculating a score for each of said plurality of words based on an appearance frequency for a first predetermined period and an appearance frequency for every second predetermined period shorter than said first predetermined period; creating a general word list which includes said plurality of words and said scores; collecting texts including a keyword from texts stored in said storage unit in response to said keyword entered for a search; extracting nouns from collected first texts, determining a noun which partially matches said keyword as a first word; extracting second texts including said first word from among said first texts; extracting a word which belongs to at least one word from among a noun, verb, and adjective from said second texts; counting a number of times said word extracted from said second texts is used; determining words extracted from said second texts, as second words which are pertinent word to said first word, if the words are ranked at a predetermined position or higher with respect to the number of times the words are used; and lowering the rank of a second word which matches any one from among said plurality of words in said general word list, and outputting said second words together with said first word. | 10. An information processing method comprising: collecting texts stored in a storage unit in response to a general word extracting request signal input by a user or when a predetermined time is reached, and extracting a plurality of words from said collected texts; calculating a score for each of said plurality of words based on an appearance frequency for a first predetermined period and an appearance frequency for every second predetermined period shorter than said first predetermined period; creating a general word list which includes said plurality of words and said scores; collecting texts including a keyword from texts stored in said storage unit in response to said keyword entered for a search; extracting nouns from collected first texts, determining a noun which partially matches said keyword as a first word; extracting second texts including said first word from among said first texts; extracting a word which belongs to at least one word from among a noun, verb, and adjective from said second texts; counting a number of times said word extracted from said second texts is used; determining words extracted from said second texts, as second words which are pertinent word to said first word, if the words are ranked at a predetermined position or higher with respect to the number of times the words are used; and lowering the rank of a second word which matches any one from among said plurality of words in said general word list, and outputting said second words together with said first word. 12. The information processing method according to claim 10 , wherein said every second predetermined period is daily, weekly, or monthly. | 0.883708 |
4. The method of claim 1 , further comprising associating a second sub context, of the basic context, with a second portion of the speech based document, the second sub context comprising a third lexicon and a third language model, and recognizing speech corresponding to the second portion using the second sub context. | 4. The method of claim 1 , further comprising associating a second sub context, of the basic context, with a second portion of the speech based document, the second sub context comprising a third lexicon and a third language model, and recognizing speech corresponding to the second portion using the second sub context. 5. The method of claim 4 , wherein the second sub context further comprises a third grammar. | 0.823784 |
17. One or more non-transitory computer-readable storage media encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving a plurality of documents of text, wherein each document is associated with one or more category labels and includes one or more sequences of one or more words; determining a plurality of topics from the plurality of documents, wherein each topic represents a subdivision of a respective category label; performing a plurality of sampling iterations to generate a category-topic model that represents co-occurrence relationships between sequences and topics and co-occurrence relationships between topics and categories, wherein performing each of the plurality of sampling iterations comprises, for each sequence in each of the plurality of documents: sampling a category label for the sequence from the category labels associated with the document that includes the sequence; sampling a topic for the sequence; and updating current values of representations of the co-occurrence relationships based on the category label and the topic sampled for the sequence. | 17. One or more non-transitory computer-readable storage media encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving a plurality of documents of text, wherein each document is associated with one or more category labels and includes one or more sequences of one or more words; determining a plurality of topics from the plurality of documents, wherein each topic represents a subdivision of a respective category label; performing a plurality of sampling iterations to generate a category-topic model that represents co-occurrence relationships between sequences and topics and co-occurrence relationships between topics and categories, wherein performing each of the plurality of sampling iterations comprises, for each sequence in each of the plurality of documents: sampling a category label for the sequence from the category labels associated with the document that includes the sequence; sampling a topic for the sequence; and updating current values of representations of the co-occurrence relationships based on the category label and the topic sampled for the sequence. 18. The computer-readable storage media of claim 17 , where sampling the category label and the topic comprises sampling the category label and the topic from a distribution that satisfies: P ( u d , i = c , z d , i = k | w d , i = v , w d , - i , z d , - i , u d , - i , y d , α , β ) = C v , k W T + β ∑ v ′ = 1 V C v , k WT + V β C k , c TC + α ∑ k ′ = 1 K C k , c TC + K α ; where u d,i is a category label; c is a particular category;z d,i is a topic; k is a particular topic; w d,i is a sequence of one or more words; v is a particular sequence of one or more words; C v,k WT is a number of times that topic k is assigned to sequence v , not including a current instance of sampling i; C k,c TC is a number of times that topic k is assigned to category c, not including the current instance of sampling i; α is a constant; β is a constant; and d is a document. | 0.5 |
1. A method comprising: associating speakers with respective segments of an audio speech file to yield associated speaker segments; generating, via a processor using automatic speech recognition of audio in the audio speech file, expertise vectors for one or more of the speakers, the expertise vectors comprising scores based on: (i) number of times the speakers have spoken about a topic in the audio speech file by searching the associated speaker segments for a term associated with the topic, and (ii) at least one of word classes, usages, styles, or behaviors of the speakers; and ranking the speakers as experts based on the expertise vectors; presenting, by the processor, the ranking of the speakers as experts based on the expertise vectors; tagging the associated speaker segments having the term with keyword tags; and matching a respective segment from the associated speaker segments with a speaker, the respective segment having a keyword tag. | 1. A method comprising: associating speakers with respective segments of an audio speech file to yield associated speaker segments; generating, via a processor using automatic speech recognition of audio in the audio speech file, expertise vectors for one or more of the speakers, the expertise vectors comprising scores based on: (i) number of times the speakers have spoken about a topic in the audio speech file by searching the associated speaker segments for a term associated with the topic, and (ii) at least one of word classes, usages, styles, or behaviors of the speakers; and ranking the speakers as experts based on the expertise vectors; presenting, by the processor, the ranking of the speakers as experts based on the expertise vectors; tagging the associated speaker segments having the term with keyword tags; and matching a respective segment from the associated speaker segments with a speaker, the respective segment having a keyword tag. 6. The method of claim 1 , wherein the number of times the speakers have spoken about the topic in the audio speech file are within a predetermined time period. | 0.634709 |
18. The device as set forth in claim 17 , wherein the instructions, when executed by the processor, further cause the processor to: receive a first level information associated with a parent reusable template and a second level information associated with a child reusable template; define a third and fourth reusable templates using the received first level information and the second level information. | 18. The device as set forth in claim 17 , wherein the instructions, when executed by the processor, further cause the processor to: receive a first level information associated with a parent reusable template and a second level information associated with a child reusable template; define a third and fourth reusable templates using the received first level information and the second level information. 21. The device as set forth in claim 18 , wherein the instructions, when executed by the processor, cause the at least one processor to: receive a selection of a reusable template of the one or more reusable templates; and create, using the selected reusable template, one or more first data models for managing data associated with corresponding one or more first tangible objects. | 0.882803 |
1. A method implemented on a computer comprising a processor, and for determining relevance between a text content and an object or a topic, the method comprising: receiving a text content comprising one or more words or phrases or sentences as terms, and tokenizing the text content into one or more tokens, each being an instance of a term in the text content; identifying a grammatical attribute, or a semantic attribute, or an external term frequency associated with the one or more tokens or terms in the text content, wherein the grammatical attribute includes at least a subject, a predicate or part of a predicate, a modifier in a phrase, a head of a phrase, a sub-phrase of a phrase, an object, a noun, a verb, an adjective, or an adverb, wherein the semantic attribute includes at least semantic roles and attribute values, wherein the external term frequency is obtained from text contents other than the received text content; determining an importance measure for each token or term based on the grammatical attribute, or the semantic attribute, or the external term frequency; receiving one or more datasets, wherein each dataset is associated with a name or description representing an object, wherein the object comprises a physical or conceptual object, a topic, or a pre-defined attribute, and wherein each dataset comprises one or more words or phrases as names of properties associated with the corresponding object, wherein the names of properties represent other objects or concepts or topics or attributes-related to the object, wherein the names of properties collectively represent a type of definition or representation of the object; matching at least two tokens or terms in the text content with at least two property names in each of the one or more datasets; for each of the one or more datasets, producing a score based at least on the importance measure of the token or term that matches a property name in the dataset, when the importance measure is in the form of a term importance score that is calculated based on the external frequency, or based on the grammatical attribute, or based on the semantic attribute or attribute value, and when the score based on the importance measure is in the form of a relevance score, the relevance score is produced as a function of the term importance score; and marking or selecting one or more of the names or descriptions representing the one or more objects as being relevant to the text content if the corresponding score is above a predefined threshold. | 1. A method implemented on a computer comprising a processor, and for determining relevance between a text content and an object or a topic, the method comprising: receiving a text content comprising one or more words or phrases or sentences as terms, and tokenizing the text content into one or more tokens, each being an instance of a term in the text content; identifying a grammatical attribute, or a semantic attribute, or an external term frequency associated with the one or more tokens or terms in the text content, wherein the grammatical attribute includes at least a subject, a predicate or part of a predicate, a modifier in a phrase, a head of a phrase, a sub-phrase of a phrase, an object, a noun, a verb, an adjective, or an adverb, wherein the semantic attribute includes at least semantic roles and attribute values, wherein the external term frequency is obtained from text contents other than the received text content; determining an importance measure for each token or term based on the grammatical attribute, or the semantic attribute, or the external term frequency; receiving one or more datasets, wherein each dataset is associated with a name or description representing an object, wherein the object comprises a physical or conceptual object, a topic, or a pre-defined attribute, and wherein each dataset comprises one or more words or phrases as names of properties associated with the corresponding object, wherein the names of properties represent other objects or concepts or topics or attributes-related to the object, wherein the names of properties collectively represent a type of definition or representation of the object; matching at least two tokens or terms in the text content with at least two property names in each of the one or more datasets; for each of the one or more datasets, producing a score based at least on the importance measure of the token or term that matches a property name in the dataset, when the importance measure is in the form of a term importance score that is calculated based on the external frequency, or based on the grammatical attribute, or based on the semantic attribute or attribute value, and when the score based on the importance measure is in the form of a relevance score, the relevance score is produced as a function of the term importance score; and marking or selecting one or more of the names or descriptions representing the one or more objects as being relevant to the text content if the corresponding score is above a predefined threshold. 4. The method of claim 1 , wherein a property name in each of the datasets has a corresponding numerical value representing the association strength between the property name and the object, wherein the score is produced further based on the association strength value associated with the matched property name. | 0.884956 |
6. The method of claim 1 further comprising: ingesting, into the first corpus, a first set of one or more passages from a first source selected from the first set of sources; and identifying a second set of one or more passages from a second source selected from the second set of sources, wherein the identification is based on the second set of passages being an update to the first set of passages and the second source being the same as the first source. | 6. The method of claim 1 further comprising: ingesting, into the first corpus, a first set of one or more passages from a first source selected from the first set of sources; and identifying a second set of one or more passages from a second source selected from the second set of sources, wherein the identification is based on the second set of passages being an update to the first set of passages and the second source being the same as the first source. 7. The method of claim 6 wherein the first and second sources are selected from the group consisting of a newspaper, a magazine, a journal, and a periodical. | 0.924145 |
2. The computer-implemented method of claim 1 wherein determining whether the first parser is able to parse the nested document comprises determining whether the first field comprising the nested document is of a data type that is associated with the first content type and different than the second content type. | 2. The computer-implemented method of claim 1 wherein determining whether the first parser is able to parse the nested document comprises determining whether the first field comprising the nested document is of a data type that is associated with the first content type and different than the second content type. 6. The computer-implemented method of claim 2 wherein if the data type of the first field comprising the nested document is not associated with the first content type, the computer-implemented method further comprises: determining, based on data types of fields that are in the nested document, whether there are other methods of parsing the nested document; selecting a parser for each identified method of parsing the nested document; and parsing the nested document using each of the selected parsers. | 0.854397 |
8. A system for locally presenting to a human user an alphanumeric message comprising a sequence of words received over a telephone line as a series of tone signals entered through the keypad of a remote tone-generating telephone dialing device, said system including: one or more databases of words, said words being arranged in records and each record including a numeric record number; means for converting received tone signals into electrical signals, each electrical signal representing the activation of either a numeric key or a control character key on the keypad, each numeric key signal representing a single alphabetic character or number; means for assembling the electrical signals into a series of input units, each input unit consisting of one or more numeric key signals followed by a control key signal and representing one word in the sequence of words; means for addressing said one or more databases using the input units serially as addresses to locate records having numeric record numbers matching the input units; means for locally outputting the message by serially presenting words stored in any such records in a sequence and in a form perceptible to the human user of the system, said last-named means identifying and presenting multiple words having the same numeric record number to permit the human user to select the most appropriate of the multiple words from the sequential context in which it appears. | 8. A system for locally presenting to a human user an alphanumeric message comprising a sequence of words received over a telephone line as a series of tone signals entered through the keypad of a remote tone-generating telephone dialing device, said system including: one or more databases of words, said words being arranged in records and each record including a numeric record number; means for converting received tone signals into electrical signals, each electrical signal representing the activation of either a numeric key or a control character key on the keypad, each numeric key signal representing a single alphabetic character or number; means for assembling the electrical signals into a series of input units, each input unit consisting of one or more numeric key signals followed by a control key signal and representing one word in the sequence of words; means for addressing said one or more databases using the input units serially as addresses to locate records having numeric record numbers matching the input units; means for locally outputting the message by serially presenting words stored in any such records in a sequence and in a form perceptible to the human user of the system, said last-named means identifying and presenting multiple words having the same numeric record number to permit the human user to select the most appropriate of the multiple words from the sequential context in which it appears. 9. The system as defined in claim 8 further including means responsive to a predetermined sequence of control key signals for sending an input unit to the presenting means in the form of a sequence of one or more numbers without addressing a database. | 0.5 |
1. A system, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: receiving a code segment in a first computer language; decomposing the code segment into constituent code elements; determining metaphoric elements corresponding to the constituent code elements; determining metaphor data representing a metaphor, in a second computer language, corresponding to the code segment based on the metaphoric elements; determining other metaphor data, in the second computer language, representing another metaphor for another code segment, received in a third computer language different from the first or second computer language, based on other metaphoric elements corresponding to other constituent code elements associated with the other code segment, wherein the other metaphor is determined to be the same as the metaphor as a result of the metaphoric elements and the other metaphoric elements being the same; and facilitating access to the metaphor data and the other metaphor data. | 1. A system, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: receiving a code segment in a first computer language; decomposing the code segment into constituent code elements; determining metaphoric elements corresponding to the constituent code elements; determining metaphor data representing a metaphor, in a second computer language, corresponding to the code segment based on the metaphoric elements; determining other metaphor data, in the second computer language, representing another metaphor for another code segment, received in a third computer language different from the first or second computer language, based on other metaphoric elements corresponding to other constituent code elements associated with the other code segment, wherein the other metaphor is determined to be the same as the metaphor as a result of the metaphoric elements and the other metaphoric elements being the same; and facilitating access to the metaphor data and the other metaphor data. 2. The system of claim 1 , wherein the first computer language is different from the second computer language. | 0.580075 |
4. An electronic apparatus-comprising: a display device; an input unit; a dictionary storage which stores dictionary information that causes an entry word in a first language to correspond to explanatory information in a second language which is a language different from the first language; a reading-kanji correspondence storage which stores reading-kanji correspondence information that causes a kanji character in the second language to correspond to a reading in the second language; a kanji correspondence storage which stores kanji correspondence information that causes a kanji character in the first language to correspond to a kanji character in the second language; a second-language reading input section which takes in a reading in the second language via the input unit; a first language kanji display section which reads a kanji character in the second language corresponding to the reading in the second language input by the second language reading input section from the reading-kanji correspondence information stored in the reading-kanji correspondence storage, then reads a kanji character in the first language corresponding to the kanji character in the second language from the kanji correspondence information stored in the kanji correspondence storage, and performs display control of the read kanji character on the display device; and a dictionary information display section which reads explanatory information that uses a character string including the kanji character in the first language subjected to display control at the first-language kanji display section as an entry word from dictionary information stored in the dictionary storage and performs display control of the explanatory information on the display device; a multiple kanji correspondence storage which stores multiple kanji correspondence information that causes a plurality of kanji characters in the first language to correspond to a plurality of kanji characters in the second language, wherein the first-language kanji display section reads a kanji character in the second language corresponding to the reading in the second language input by the second-language reading input section from the reading-kanji correspondence information stored in the reading kanji correspondence storage and determines whether the read kanji character in the second language is in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage, reads the plurality of kanji characters in the first language corresponding to the plurality of kanji characters in the second language from the multiple kanji correspondence information stored in the multiple kanji correspondence storage and performs display control of the read kanji characters on the display device if it has been determined that the kanji character in the second language read from the reading-kanji correspondence information is in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage, and reads a kanji character in the first language corresponding to the kanji character in the second language from the kanji correspondence information stored in the kanji correspondence storage and performs display control of the read kanji character on the display device, if it has been determined that the kanji character in the second language read from the reading-kanji correspondence information is not in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage. | 4. An electronic apparatus-comprising: a display device; an input unit; a dictionary storage which stores dictionary information that causes an entry word in a first language to correspond to explanatory information in a second language which is a language different from the first language; a reading-kanji correspondence storage which stores reading-kanji correspondence information that causes a kanji character in the second language to correspond to a reading in the second language; a kanji correspondence storage which stores kanji correspondence information that causes a kanji character in the first language to correspond to a kanji character in the second language; a second-language reading input section which takes in a reading in the second language via the input unit; a first language kanji display section which reads a kanji character in the second language corresponding to the reading in the second language input by the second language reading input section from the reading-kanji correspondence information stored in the reading-kanji correspondence storage, then reads a kanji character in the first language corresponding to the kanji character in the second language from the kanji correspondence information stored in the kanji correspondence storage, and performs display control of the read kanji character on the display device; and a dictionary information display section which reads explanatory information that uses a character string including the kanji character in the first language subjected to display control at the first-language kanji display section as an entry word from dictionary information stored in the dictionary storage and performs display control of the explanatory information on the display device; a multiple kanji correspondence storage which stores multiple kanji correspondence information that causes a plurality of kanji characters in the first language to correspond to a plurality of kanji characters in the second language, wherein the first-language kanji display section reads a kanji character in the second language corresponding to the reading in the second language input by the second-language reading input section from the reading-kanji correspondence information stored in the reading kanji correspondence storage and determines whether the read kanji character in the second language is in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage, reads the plurality of kanji characters in the first language corresponding to the plurality of kanji characters in the second language from the multiple kanji correspondence information stored in the multiple kanji correspondence storage and performs display control of the read kanji characters on the display device if it has been determined that the kanji character in the second language read from the reading-kanji correspondence information is in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage, and reads a kanji character in the first language corresponding to the kanji character in the second language from the kanji correspondence information stored in the kanji correspondence storage and performs display control of the read kanji character on the display device, if it has been determined that the kanji character in the second language read from the reading-kanji correspondence information is not in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage. 6. The electronic apparatus according to claim 4 , wherein each of the first language and the second language is any one of Japanese, Korean, and Chinese. | 0.5 |
17. A system, comprising: at least one computer interoperably coupled with a memory storage and configured to: receive a plurality of core data foundations representing database resources and comprising database tables and operations; define a derived data foundation comprising a first plurality of links to the plurality of core data foundations and representing a hierarchical inheritance relationship of the plurality of core data foundations; receive a plurality of core business layers representing business concepts and comprising data objects associated to the database tables and the operations; define a derived business layer comprising a second plurality of links to the plurality of core business layers; generate a universe by compiling the derived business layer on top of the derived data foundation, wherein the universe exposes only data objects that are permitted to be published and that are associated with the derived business layer or inherited by the derived business layer from the derived data foundation; and process the universe using a computer-executable model checking tool for evaluating an integrity of the universe by determining whether one or more links of the first plurality of links or the second plurality of links is broken, such that determining that the one or more links are broken triggers a notification configured to enable a repair of the one or more links. | 17. A system, comprising: at least one computer interoperably coupled with a memory storage and configured to: receive a plurality of core data foundations representing database resources and comprising database tables and operations; define a derived data foundation comprising a first plurality of links to the plurality of core data foundations and representing a hierarchical inheritance relationship of the plurality of core data foundations; receive a plurality of core business layers representing business concepts and comprising data objects associated to the database tables and the operations; define a derived business layer comprising a second plurality of links to the plurality of core business layers; generate a universe by compiling the derived business layer on top of the derived data foundation, wherein the universe exposes only data objects that are permitted to be published and that are associated with the derived business layer or inherited by the derived business layer from the derived data foundation; and process the universe using a computer-executable model checking tool for evaluating an integrity of the universe by determining whether one or more links of the first plurality of links or the second plurality of links is broken, such that determining that the one or more links are broken triggers a notification configured to enable a repair of the one or more links. 18. The system of claim 17 , wherein each core data foundation of the plurality of core data foundations can be defined on different data sources. | 0.596571 |
7. The mobile terminal of claim 1 , wherein the translation window is movable based on a touch input to the display unit, and wherein when the translation window reaches a border region of the display unit while being moved based on the touch input, the controller to translate the entire screen information displayed on the display unit and to display, at the translation window, the translation-source information into which the entire screen information is translated. | 7. The mobile terminal of claim 1 , wherein the translation window is movable based on a touch input to the display unit, and wherein when the translation window reaches a border region of the display unit while being moved based on the touch input, the controller to translate the entire screen information displayed on the display unit and to display, at the translation window, the translation-source information into which the entire screen information is translated. 8. The mobile terminal of claim 7 , wherein when the translation window reaches the border region of the display unit, the controller to change a size of the translation window such that the size of the translation window corresponds to a size of an output region of the display unit and to output the translation-target information into which the entire screen information that is output to the display unit is translated, on the translation window whose size is changed. | 0.753106 |
1. A system for performing a task for or providing a service to a source, the system comprising: a first device having a first sensor for receiving recognition information from the source and transmitting the received recognition information to a second device; the first and second devices for independently processing at least different portions of the recognition information, wherein the first and second devices use a common recognition model or use a different recognition model to process the recognition information, and the first and second devices independently assigning a respective first and second recognition score to the source, wherein the second device is communicatively linked to the first device, a dynamic paring code derived from each of the independently assigned recognition scores; one or both of the first and second devices authenticating the source responsive to the first and second recognition scores by collaboratively determining whether the source is authenticated based on the dynamic paring code; and responsive to the source having been authenticated, the first or second device for performing the task or for providing the service to the source. | 1. A system for performing a task for or providing a service to a source, the system comprising: a first device having a first sensor for receiving recognition information from the source and transmitting the received recognition information to a second device; the first and second devices for independently processing at least different portions of the recognition information, wherein the first and second devices use a common recognition model or use a different recognition model to process the recognition information, and the first and second devices independently assigning a respective first and second recognition score to the source, wherein the second device is communicatively linked to the first device, a dynamic paring code derived from each of the independently assigned recognition scores; one or both of the first and second devices authenticating the source responsive to the first and second recognition scores by collaboratively determining whether the source is authenticated based on the dynamic paring code; and responsive to the source having been authenticated, the first or second device for performing the task or for providing the service to the source. 7. The system of claim 1 the first and second devices for analyzing the recognition information according to operating capabilities of each one of the first and second devices, the operating capabilities comprising, power, bandwidth, proximity, processing power, range, availability, memory capacity, available power, first sensor type, and first sensor quality. | 0.532429 |
6. The apparatus of claim 1 , wherein the memory includes computer program code configured to, working with the processor, cause the apparatus to perform at least the following: determine a transportation mode, wherein determining the location candidate is based, at least in part, on the transportation mode. | 6. The apparatus of claim 1 , wherein the memory includes computer program code configured to, working with the processor, cause the apparatus to perform at least the following: determine a transportation mode, wherein determining the location candidate is based, at least in part, on the transportation mode. 7. The apparatus of claim 6 , wherein determining the location candidate comprises: determining a navigational attribute type based, at least in part, on correlation between the navigational attribute type and the transportation mode; identifying a navigational attribute of the navigational attribute type; and determining the location candidate indicative of the navigational attribute. | 0.752935 |
11. A computer-based method for generating a medical imaging study report comprising the steps of: storing a medical imaging report generation database in a computer readable medium, the medical imaging report generation database containing at least one of the following: (a) phrases associated with a plurality of image study types interpreted in a medical imaging study and inclusion and exclusion rules, and/or (b) report templates consisting of aggregations of such phrases, and/or (c) data regarding prior patterns of usage of such phrases in previous instances of use of the system, and/or (d) a database of full report texts which can be drawn upon to identify additional phrase suggestions; executing computer code using a computer processor linked to the computer readable medium; generating, by executing the computer code using the computer processor, a medical imaging study report on display on a computer display device, using the stored report generation database, wherein the medical imaging study report contains an architecture accommodating one or more text fields; presenting a plurality of study types for display to the user via a user-output device by executing the computer code using the computer processor; upon the user selecting a study type via a user-input device, providing to the user via the user-output device by executing the computer code using the computer processor, a report template having a plurality of phrases based on the selected study type; presenting one or more phrases related to the template phrases via the user-output device; upon the user selecting one or more related phrases, applying by executing the computer code using the computer processor, one or more inclusion rules based on patterns of usage to the template phrases and the selected related phrases; upon the user selecting one or more related phrases, applying to the template phrases and the selected related phrases by executing the computer code using the computer processor one or more exclusion rules based on patterns of usage to the phrases, thereby identifying one or more phrases to be excluded from the medical imaging report; generating a medical imaging report containing the selected phrases in the text fields and the study type via a report output device; and updating the database by saving back into the database at least a portion of, or all of, the text in the generated report, and inclusion and exclusion selection decisions made by the user. | 11. A computer-based method for generating a medical imaging study report comprising the steps of: storing a medical imaging report generation database in a computer readable medium, the medical imaging report generation database containing at least one of the following: (a) phrases associated with a plurality of image study types interpreted in a medical imaging study and inclusion and exclusion rules, and/or (b) report templates consisting of aggregations of such phrases, and/or (c) data regarding prior patterns of usage of such phrases in previous instances of use of the system, and/or (d) a database of full report texts which can be drawn upon to identify additional phrase suggestions; executing computer code using a computer processor linked to the computer readable medium; generating, by executing the computer code using the computer processor, a medical imaging study report on display on a computer display device, using the stored report generation database, wherein the medical imaging study report contains an architecture accommodating one or more text fields; presenting a plurality of study types for display to the user via a user-output device by executing the computer code using the computer processor; upon the user selecting a study type via a user-input device, providing to the user via the user-output device by executing the computer code using the computer processor, a report template having a plurality of phrases based on the selected study type; presenting one or more phrases related to the template phrases via the user-output device; upon the user selecting one or more related phrases, applying by executing the computer code using the computer processor, one or more inclusion rules based on patterns of usage to the template phrases and the selected related phrases; upon the user selecting one or more related phrases, applying to the template phrases and the selected related phrases by executing the computer code using the computer processor one or more exclusion rules based on patterns of usage to the phrases, thereby identifying one or more phrases to be excluded from the medical imaging report; generating a medical imaging report containing the selected phrases in the text fields and the study type via a report output device; and updating the database by saving back into the database at least a portion of, or all of, the text in the generated report, and inclusion and exclusion selection decisions made by the user. 15. The method of claim 11 further comprising: presenting phrases based on their frequency of use in like reports, and identifying new phrases based on use in prior reports. | 0.59279 |
15. A system, comprising: a processor; and a memory coupled to the processor and storing computer-readable instructions which, when executed by the processor, cause performance of a method comprising: converting a medical document, having textual content and rich formatting, into a first XHTML document that retains the textual content and the rich formatting of the medical document, the first XHTML document including a first text string in rich formatting; generating from the first XHTML document a plain text document that retains the textual content and not the rich formatting of the first XHTML document, wherein generating the plain text document comprises extracting text nodes from the first XHTML document and forming the plain text document from the extracted text nodes, the plain text document including the first text string in plain text without rich formatting; generating one or more annotations of the plain text document by applying a natural language understanding (NLU) engine implemented on a processor to the plain text document, the one or more annotations including a first annotation linked to the first text string in the plain text document without rich formatting; and displaying an annotated XHTML document created by applying the one or more annotations of the plain text document to a tokenized XHTML document including the textual content and the rich formatting of the medical document, the tokenized XHTML document including the first text string in rich formatting, wherein displaying the annotated XHTML document comprises displaying the first annotation linked to the first text string in rich formatting in the tokenized XHTML document. | 15. A system, comprising: a processor; and a memory coupled to the processor and storing computer-readable instructions which, when executed by the processor, cause performance of a method comprising: converting a medical document, having textual content and rich formatting, into a first XHTML document that retains the textual content and the rich formatting of the medical document, the first XHTML document including a first text string in rich formatting; generating from the first XHTML document a plain text document that retains the textual content and not the rich formatting of the first XHTML document, wherein generating the plain text document comprises extracting text nodes from the first XHTML document and forming the plain text document from the extracted text nodes, the plain text document including the first text string in plain text without rich formatting; generating one or more annotations of the plain text document by applying a natural language understanding (NLU) engine implemented on a processor to the plain text document, the one or more annotations including a first annotation linked to the first text string in the plain text document without rich formatting; and displaying an annotated XHTML document created by applying the one or more annotations of the plain text document to a tokenized XHTML document including the textual content and the rich formatting of the medical document, the tokenized XHTML document including the first text string in rich formatting, wherein displaying the annotated XHTML document comprises displaying the first annotation linked to the first text string in rich formatting in the tokenized XHTML document. 19. The system of claim 15 , wherein the one or more annotations comprise a medical code. | 0.585933 |
7. A method of processing content in a plurality of languages, the method comprising: establish a bind relationship between content in an embedded database, wherein the embedded database stores and retrieves content in a plurality languages, the content configuring user interface elements of an application program executing on the client computer, the user interface elements each associated with an identifier for associating the content, wherein first content is the content in a first language and second content is the content in a second language translated from the first language, at a client computer and a content database on a server computer, the bind relationship allowing the server computer to notify the client computer of any occurrences of changes to the content; generating, by the application program at the client computer, a request to the server computer for first content which is in a first language, if the first content is not stored in an embedded database of the client computer; and automatically receiving from the server computer updated first content in the first language, if there is a change in second content which is content in a second language translated from the first language; storing the first content in the embedded database at the client computer; retrieving the first content from the embedded database at the client computer; displaying the first content on a window of the application program at the client computer; and overlaying the displayed first content with the updated first content. | 7. A method of processing content in a plurality of languages, the method comprising: establish a bind relationship between content in an embedded database, wherein the embedded database stores and retrieves content in a plurality languages, the content configuring user interface elements of an application program executing on the client computer, the user interface elements each associated with an identifier for associating the content, wherein first content is the content in a first language and second content is the content in a second language translated from the first language, at a client computer and a content database on a server computer, the bind relationship allowing the server computer to notify the client computer of any occurrences of changes to the content; generating, by the application program at the client computer, a request to the server computer for first content which is in a first language, if the first content is not stored in an embedded database of the client computer; and automatically receiving from the server computer updated first content in the first language, if there is a change in second content which is content in a second language translated from the first language; storing the first content in the embedded database at the client computer; retrieving the first content from the embedded database at the client computer; displaying the first content on a window of the application program at the client computer; and overlaying the displayed first content with the updated first content. 10. The method of claim 7 further comprising: automatically generate a request to the server computer for second content, if the second content is not stored in the embedded database. | 0.606497 |
1. A system comprising: a transfer determining module configured to determine that a computing device, that was presenting an item, has been transferred from a first user to a second user, the transfer determining module including at least: a visual cue detecting module configured to determine that the computing device has been transferred from the first user to the second user when the visual cue detecting module at least detects presence or absence of one or more visual cues in proximate vicinity of the computing device that when detected as occurring at least suggested transfer of the computing device between the first and second users, the visual cue detecting module including at least: a gesture detecting module configured to detect the presence or absence of the one or more visual cues in the proximate vicinity of the computing device when the gesture detecting module at least detects visually one or more gestures exhibited by the first user that when detected as occurring at least suggested transfer of the computing device from the first user to the second user at least in part by the first user moving the computing device at least in part with the one or more gestures; and a highlighted portion presenting module configured to present, via the computing device, one or more highlighted portions of the item, the highlighted portion presenting module being responsive at least in part to the transfer determining module configured to determine that a computing device, that was presenting an item, has been transferred from a first user to a second user, the highlighted portion presenting module being configured to present the one or more highlighted portions of the item responsive at least in part to the transfer determining module and to a highlighting selection detecting module, the highlighting selection detection module configured to detect, prior to the transfer of the computing device from the first user to the second user, that the first user has at least one of marked or tagged at least one or more parts of the one or more portions to select the one or more portions for highlighting. | 1. A system comprising: a transfer determining module configured to determine that a computing device, that was presenting an item, has been transferred from a first user to a second user, the transfer determining module including at least: a visual cue detecting module configured to determine that the computing device has been transferred from the first user to the second user when the visual cue detecting module at least detects presence or absence of one or more visual cues in proximate vicinity of the computing device that when detected as occurring at least suggested transfer of the computing device between the first and second users, the visual cue detecting module including at least: a gesture detecting module configured to detect the presence or absence of the one or more visual cues in the proximate vicinity of the computing device when the gesture detecting module at least detects visually one or more gestures exhibited by the first user that when detected as occurring at least suggested transfer of the computing device from the first user to the second user at least in part by the first user moving the computing device at least in part with the one or more gestures; and a highlighted portion presenting module configured to present, via the computing device, one or more highlighted portions of the item, the highlighted portion presenting module being responsive at least in part to the transfer determining module configured to determine that a computing device, that was presenting an item, has been transferred from a first user to a second user, the highlighted portion presenting module being configured to present the one or more highlighted portions of the item responsive at least in part to the transfer determining module and to a highlighting selection detecting module, the highlighting selection detection module configured to detect, prior to the transfer of the computing device from the first user to the second user, that the first user has at least one of marked or tagged at least one or more parts of the one or more portions to select the one or more portions for highlighting. 49. The system of claim 1 , wherein said highlighted portion presenting module configured to present, via the computing device, one or more highlighted portions of the item, the highlighted portion presenting module being responsive at least in part to the transfer determining module configured to determine that a computing device, that was presenting an item, has been transferred from a first user to a second user, the highlighted portion presenting module being configured to present the one or more highlighted portions of the item responsive at least in part to the transfer determining module and to a highlighting selection detecting module, the highlighting selection detection module configured to detect, prior to the transfer of the computing device from the first user to the second user, that the first user has at least one of marked or tagged at least one or more parts of the one or more portions to select the one or more portions for highlighting comprises: a highlighting selection detection module configured to detect, prior to the transfer of the computing device from the first user to the second user, that the first user has at least one of marked or tagged at least one or more parts of the one or more portions with at least one of a touchscreen or a mouse by at least one of writing a symbol on the at least one or more parts, writing a symbol near the at least one or more parts, or drawing a circle around the at least one or more parts. | 0.529395 |
1. A computer-implemented method of presenting additional content for a term presented by a first mobile communication device, the computer-implemented method comprising: receiving, by the first mobile communication device, a first utterance; transmitting, by the first mobile communication device, a first identifier of the first mobile communication device and the first utterance to a server; receiving, by the first mobile communication device from the server, text representing a transcription of the first utterance; receiving, by the first mobile communication device from the server, an indicator that first additional content is available for a term identified within the text by the indicator, wherein the term is associated at the server with the first identifier of the first mobile communication device and a second identifier of a second mobile communication device, and wherein the first additional content for the term is associated with the first identifier and the second identifier; presenting, on the first mobile communication device, the text with an emphasis on the term identified by the indicator; after presenting the text on the first mobile communication device, receiving, by the first mobile communication device, a second utterance that includes the term; transmitting, by the first mobile communication device, the first identifier and the second utterance to the server; receiving, by the first mobile communication device from the server, in response to transmitting the second utterance and the first identifier, the first additional content; presenting, on the first mobile communication device the first additional content for the term; transmitting, by the first mobile communication device, the second identifier to the server, the server configured to send the text as well as the indicator that first additional content is available for the term to the second mobile communication device using the second identifier of the second mobile communication device; and receiving, by the first mobile communication device from the server, a message including a transcribed third utterance received by the second communication device in response to the text. | 1. A computer-implemented method of presenting additional content for a term presented by a first mobile communication device, the computer-implemented method comprising: receiving, by the first mobile communication device, a first utterance; transmitting, by the first mobile communication device, a first identifier of the first mobile communication device and the first utterance to a server; receiving, by the first mobile communication device from the server, text representing a transcription of the first utterance; receiving, by the first mobile communication device from the server, an indicator that first additional content is available for a term identified within the text by the indicator, wherein the term is associated at the server with the first identifier of the first mobile communication device and a second identifier of a second mobile communication device, and wherein the first additional content for the term is associated with the first identifier and the second identifier; presenting, on the first mobile communication device, the text with an emphasis on the term identified by the indicator; after presenting the text on the first mobile communication device, receiving, by the first mobile communication device, a second utterance that includes the term; transmitting, by the first mobile communication device, the first identifier and the second utterance to the server; receiving, by the first mobile communication device from the server, in response to transmitting the second utterance and the first identifier, the first additional content; presenting, on the first mobile communication device the first additional content for the term; transmitting, by the first mobile communication device, the second identifier to the server, the server configured to send the text as well as the indicator that first additional content is available for the term to the second mobile communication device using the second identifier of the second mobile communication device; and receiving, by the first mobile communication device from the server, a message including a transcribed third utterance received by the second communication device in response to the text. 18. The method of claim 1 , wherein multiple alternative first additional content exists for the term and are available for presentation by the first mobile communication device, and wherein the method further comprises selecting and presenting at least one alternative first additional content of the multiple alternative first additional content. | 0.551494 |
9. A vision system configured to automatically propagate a set of landmark points from a small set of images to a large set of images for a predetermined object class in response to an algorithmic software, wherein the vision system is configured to automatically estimate landmark point locations for the large set of images using manually labeled landmark locations for the small set of images in response to the algorithmic software, and wherein the vision system is configured to iteratively partition a primary patch region into localized smaller child patch regions, such that initial landmark locations are based on the primary patch region and further such that refined landmark estimations result in accurate landmark labeling based on the resultant local patch appearance in response to the algorithmic software. | 9. A vision system configured to automatically propagate a set of landmark points from a small set of images to a large set of images for a predetermined object class in response to an algorithmic software, wherein the vision system is configured to automatically estimate landmark point locations for the large set of images using manually labeled landmark locations for the small set of images in response to the algorithmic software, and wherein the vision system is configured to iteratively partition a primary patch region into localized smaller child patch regions, such that initial landmark locations are based on the primary patch region and further such that refined landmark estimations result in accurate landmark labeling based on the resultant local patch appearance in response to the algorithmic software. 10. The vision system according to claim 9 , wherein the large set of images is an integer number of images less than about 5,000. | 0.576453 |
3. The method of claim 1 , comprising: determining a loudness of the audio data associated with the particular, predefined hotword; and in response to determining that the utterance likely includes the particular, predefined hotword, transmitting, to the server, the loudness of the audio data associated with the particular, predefined hotword. | 3. The method of claim 1 , comprising: determining a loudness of the audio data associated with the particular, predefined hotword; and in response to determining that the utterance likely includes the particular, predefined hotword, transmitting, to the server, the loudness of the audio data associated with the particular, predefined hotword. 4. The method of claim 3 , wherein determining a loudness of the audio data associated with the particular, predefined hotword comprises: determining a power of the audio data associated with the particular, predefined hotword; and determining a power of audio data that is not associated with the particular, predefined hotword and that the first computing device received before the audio data associated with the particular, predefined hotword, wherein the loudness of the audio data associated with the particular, predefined hotword is based on the power of the audio data associated with the particular, predefined hotword and the power of the audio data that is not associated with the particular, predefined hotword and that the first computing device received before the audio data associated with the particular, predefined hotword. | 0.804136 |
1. A method comprising: receiving, by one or more processors, a first input indicating user activity that comprises a first edit to a document at a first position in the document in a document editing application executing on a computing device, wherein the document editing application is navigable among different partial views of the document, and the document editing application displays a frame element that indicates a position of a presently displayed partial view of the document with reference to an entirety of the document; and displaying, by the one or more processors, in response to the first input indicating the user activity that comprises the first edit to the document, a first marker, in or proximate to the frame element, indicating where the first position of user activity is located with reference to the entirety of the document, wherein the first marker is separate from the first edit to the document; receiving, by the one or more processors, a second input indicating user activity that comprises a second edit to the document at a second position in the document in the document editing application; displaying, in response to the second input indicating the user activity that comprises the second edit to the document, a second marker, in or proximate to the frame element, indicating where the second position of user activity is located with reference to the entirety of the document, wherein the second marker is separate from the second edit to the document and is visually distinct from the first marker, wherein the first marker and the second marker are different numbers, and wherein the numbers for the markers are modified as additional markers are added, such that a first number always represents a position of a most recent user activity, and a second number always represents a position of a second most recent user activity. | 1. A method comprising: receiving, by one or more processors, a first input indicating user activity that comprises a first edit to a document at a first position in the document in a document editing application executing on a computing device, wherein the document editing application is navigable among different partial views of the document, and the document editing application displays a frame element that indicates a position of a presently displayed partial view of the document with reference to an entirety of the document; and displaying, by the one or more processors, in response to the first input indicating the user activity that comprises the first edit to the document, a first marker, in or proximate to the frame element, indicating where the first position of user activity is located with reference to the entirety of the document, wherein the first marker is separate from the first edit to the document; receiving, by the one or more processors, a second input indicating user activity that comprises a second edit to the document at a second position in the document in the document editing application; displaying, in response to the second input indicating the user activity that comprises the second edit to the document, a second marker, in or proximate to the frame element, indicating where the second position of user activity is located with reference to the entirety of the document, wherein the second marker is separate from the second edit to the document and is visually distinct from the first marker, wherein the first marker and the second marker are different numbers, and wherein the numbers for the markers are modified as additional markers are added, such that a first number always represents a position of a most recent user activity, and a second number always represents a position of a second most recent user activity. 13. The method of claim 1 , wherein the first marker comprises a change in a color or a shade in or proximate to the frame element at a frame element position that corresponds to the first position, the method further comprising: receiving additional inputs indicating user activity at the first position of user activity in the document in the document editing application; and displaying, in response to the additional inputs indicating user activity at the first position of user activity, cumulative changes in the color or the shade in or proximate to the frame element at the frame element position that corresponds to the first position. | 0.7492 |
19. A computer-based system for processing one or more citations for inclusion in an electronic document, the system comprising: a processor; a memory communicatively coupled with the processor; computer executable code stored in the memory, the computer executable code comprising: a document rendering application; a citation editing code set comprising: citation interface code set when executed by the processor adapted to present a citation interface and receive a user input representing a set of citation terms related to a citation for inclusion in the electronic document; citation identifying code set adapted to identify a set of at least one citation record from at least one citation library based at least in part on the received set of citation terms; citation selection code set adapted to present a representation of one or more of the identified set of at least one citation record and to receive an electronic signal representing a user selection of a citation from the presented one or more of the set of at least one citation record; and citation insertion code set adapted to insert into the electronic document citation data from the corresponding citation record associated with the selected citation. | 19. A computer-based system for processing one or more citations for inclusion in an electronic document, the system comprising: a processor; a memory communicatively coupled with the processor; computer executable code stored in the memory, the computer executable code comprising: a document rendering application; a citation editing code set comprising: citation interface code set when executed by the processor adapted to present a citation interface and receive a user input representing a set of citation terms related to a citation for inclusion in the electronic document; citation identifying code set adapted to identify a set of at least one citation record from at least one citation library based at least in part on the received set of citation terms; citation selection code set adapted to present a representation of one or more of the identified set of at least one citation record and to receive an electronic signal representing a user selection of a citation from the presented one or more of the set of at least one citation record; and citation insertion code set adapted to insert into the electronic document citation data from the corresponding citation record associated with the selected citation. 32. The system of claim 19 further comprising a bibliography code set adapted to generate a bibliography comprising the citation data from the corresponding citation record associated with the selected citation. | 0.570955 |
7. A method comprising: intercepting a flow; classifying the flow according to transmission protocol; extracting one or more objects from the classified flow using a protocol handler corresponding with the transmission protocol, wherein the objects are respective pluralities of packets that are captured and broken down by a capture system and then reassembled; classifying the one or more objects based on content type by statistically analyzing the object, wherein tokens found in the object have an associated weight and the weights of the tokens are used to determine the content type of the object, and wherein a confidence level is assigned for classifying the content type of the object; and inserting the content type into a content field of a tag that indexes the object in a storage location and contains a plurality of fields to describe the object, wherein a capture system that receives the captured object, which is part of a document, is configured to allow the document to be forwarded from the capture system to its intended destination at a network node unless a capture rule prohibits forwarding the document based on the document including one or more objects; and further classifying the object as an encrypted document based on a statistical characteristic of the object if the object is determined to be binary in nature, wherein statistically analyzing the object comprises determining a byte distribution. | 7. A method comprising: intercepting a flow; classifying the flow according to transmission protocol; extracting one or more objects from the classified flow using a protocol handler corresponding with the transmission protocol, wherein the objects are respective pluralities of packets that are captured and broken down by a capture system and then reassembled; classifying the one or more objects based on content type by statistically analyzing the object, wherein tokens found in the object have an associated weight and the weights of the tokens are used to determine the content type of the object, and wherein a confidence level is assigned for classifying the content type of the object; and inserting the content type into a content field of a tag that indexes the object in a storage location and contains a plurality of fields to describe the object, wherein a capture system that receives the captured object, which is part of a document, is configured to allow the document to be forwarded from the capture system to its intended destination at a network node unless a capture rule prohibits forwarding the document based on the document including one or more objects; and further classifying the object as an encrypted document based on a statistical characteristic of the object if the object is determined to be binary in nature, wherein statistically analyzing the object comprises determining a byte distribution. 8. The method of claim 7 , wherein classifying the flow according to protocol comprises not recognizing a transmission protocol carrying the flow and classifying the flow as unknown; and wherein extracting one or more object comprises using a default protocol handler to extract the one or more objects from the unknown flow. | 0.649171 |
1. A computer-implemented method comprising: obtaining, by a computer system, information that identifies interactions among users of a social network; generating, by the computer system, a graph that is based at least in part on the obtained information and comprises i) nodes that represent the users of the social network and ii) edges that connect the nodes and that represent relationships between the users; assigning, to at least a portion of the nodes in the graph and for one or more labels, initial label values that indicate levels of interest of users associated with the portion of the nodes in content associated with the one or more labels; determining, for the nodes in the graph, label values for the one or more labels based on iterative propagation of the initial label values among the nodes using the edges of the graph, wherein iterative propagation comprises, for a particular node from the nodes in the graph, determining particular label values for the particular node at each of a plurality of iterations by combining, at each of the plurality of iterations, neighboring label values for neighboring nodes that are connected to the particular node by a portion of the edges of the graph; and identifying, by the computer system for a particular label from the one or more labels, one or more users to provide with particular content that is associated with the particular label, wherein the one or more users are identified based on the determined label values for the particular label. | 1. A computer-implemented method comprising: obtaining, by a computer system, information that identifies interactions among users of a social network; generating, by the computer system, a graph that is based at least in part on the obtained information and comprises i) nodes that represent the users of the social network and ii) edges that connect the nodes and that represent relationships between the users; assigning, to at least a portion of the nodes in the graph and for one or more labels, initial label values that indicate levels of interest of users associated with the portion of the nodes in content associated with the one or more labels; determining, for the nodes in the graph, label values for the one or more labels based on iterative propagation of the initial label values among the nodes using the edges of the graph, wherein iterative propagation comprises, for a particular node from the nodes in the graph, determining particular label values for the particular node at each of a plurality of iterations by combining, at each of the plurality of iterations, neighboring label values for neighboring nodes that are connected to the particular node by a portion of the edges of the graph; and identifying, by the computer system for a particular label from the one or more labels, one or more users to provide with particular content that is associated with the particular label, wherein the one or more users are identified based on the determined label values for the particular label. 12. The computer-implemented method of claim 1 , wherein the particular content comprises an advertisement and the determined label values for the particular label indicate levels of interests of the users in the advertisement. | 0.607984 |
1. A computer-aided learning method for assessing a student's understanding in a subject, the method, using test results from the latest test and the prior-to-the-latest test results taken by the student, comprising the steps of: accessing the student's prior-to-the-latest test results and the latest test results; and analyzing, by a first computing device that can access a network, the student's prior-to-the-latest and the latest test results to generate a recommendation, which provides an assessment on the student's understanding in the subject; wherein the recommendation can be transmitted to a second computing device through the network to be used by the second computing device. | 1. A computer-aided learning method for assessing a student's understanding in a subject, the method, using test results from the latest test and the prior-to-the-latest test results taken by the student, comprising the steps of: accessing the student's prior-to-the-latest test results and the latest test results; and analyzing, by a first computing device that can access a network, the student's prior-to-the-latest and the latest test results to generate a recommendation, which provides an assessment on the student's understanding in the subject; wherein the recommendation can be transmitted to a second computing device through the network to be used by the second computing device. 4. A computer-aided learning method as recited in claim 1 wherein: the subject is divided into line-items with at least one line-item being more difficult than another line-item; and the latest test includes questions for different line-items; and the method further comprising the steps of generating an overall score for each group of questions having the same line-item for generating the recommendation. | 0.5 |
29. A computer-implemented method comprising: storing one or more graphical documents; storing content rating information associated with the one or more stored graphical documents; comparing graphical content of a graphical document under evaluation with graphical content of the one or more stored graphical documents to identify a matching graphical document by a processor; and granting a distribution approval to the graphical document under evaluation based on the match and content rating information associated with the matching graphical document by the processor. | 29. A computer-implemented method comprising: storing one or more graphical documents; storing content rating information associated with the one or more stored graphical documents; comparing graphical content of a graphical document under evaluation with graphical content of the one or more stored graphical documents to identify a matching graphical document by a processor; and granting a distribution approval to the graphical document under evaluation based on the match and content rating information associated with the matching graphical document by the processor. 39. The method of claim 29 , further comprising comparing at least one of an image, animation, and sound of the graphical document under evaluation with at least one corresponding image, animation, and sound of the one or more stored graphical documents. | 0.757143 |
1. A method of providing contextual information to a user, comprising: receiving context data describing the user's current context; identifying a plurality of information items corresponding to the user's current context; applying a personalized user behavior model for the user to determine, for each of the plurality of information items, a likelihood that the information item will be of value to the user, the user behavior model including a routine model describing correlations between contexts, the routine model comprising a plurality of transition rules; selecting an information item from among the plurality of information items based on the corresponding likelihood; providing the selected information item for presentation to the user; receiving feedback indicating the user found value in presentation of the selected information item; identifying a contributing transition rule from among the plurality of transition rules based on the contributing transition rule having contributed to selection of the selected information item, the contributing transition rule comprising a source context and a destination context; and storing an indication that the user found value in presentation of the selected information item in conjunction with the contributing transition rule such that information items associated with the destination context are in future determined to have a higher likelihood when the user is associated with the source context. | 1. A method of providing contextual information to a user, comprising: receiving context data describing the user's current context; identifying a plurality of information items corresponding to the user's current context; applying a personalized user behavior model for the user to determine, for each of the plurality of information items, a likelihood that the information item will be of value to the user, the user behavior model including a routine model describing correlations between contexts, the routine model comprising a plurality of transition rules; selecting an information item from among the plurality of information items based on the corresponding likelihood; providing the selected information item for presentation to the user; receiving feedback indicating the user found value in presentation of the selected information item; identifying a contributing transition rule from among the plurality of transition rules based on the contributing transition rule having contributed to selection of the selected information item, the contributing transition rule comprising a source context and a destination context; and storing an indication that the user found value in presentation of the selected information item in conjunction with the contributing transition rule such that information items associated with the destination context are in future determined to have a higher likelihood when the user is associated with the source context. 6. The method of claim 1 , wherein the routine model describes correlations between contexts and comprises a transition rule including a source context and a destination context, the likelihood of a given information item being of value being based on both the source context corresponding to the user's current context and the destination context corresponding to the given information item. | 0.741447 |
12. The method of claim 11 , wherein the step of parsing each of said logical components to identify first level concepts within individual concept zones further comprises: searching the financially related document to identify dominant concept keywords to establish the individual concept zones. | 12. The method of claim 11 , wherein the step of parsing each of said logical components to identify first level concepts within individual concept zones further comprises: searching the financially related document to identify dominant concept keywords to establish the individual concept zones. 13. The method of claim 12 , wherein the step of searching the financially related document to identify dominant concept keywords to establish the individual concept zones further comprises: counting the frequency of keywords and their proximity relative to one another relative to the structural zones components and logical components within the document. | 0.93492 |
3. The method according to claim 1 , wherein the reading each fragment cutting time point from the record file of the fragment cutting time point, performing time mapping on the fragment cutting time point, and storing, in an array, a new fragment cutting time point that is obtained after the mapping specifically comprises: performing mapping on multiple times of fragment cutting of each audio fragment, and mapping a fragment cutting time point to a corresponding audio fragment; reading a fragment cutting start time point and a fragment cutting end time point from the record file of the fragment cutting time point; when a cutting segment indicates first cutting of the audio fragment, saving a fragment cutting start time point and a fragment cutting end time point of the cutting segment in the array; and when the cutting segment indicates cutting other than the first cutting of the audio fragment, comparing the fragment cutting start time point and the fragment cutting end time point of the cutting segment with a previously saved cutting time period, and then performing the mapping; and after each audio fragment is mapped, mapping a fragment cutting time period of each audio fragment to the audio file, and storing, in the array, the new fragment cutting time point that is obtained after the mapping. | 3. The method according to claim 1 , wherein the reading each fragment cutting time point from the record file of the fragment cutting time point, performing time mapping on the fragment cutting time point, and storing, in an array, a new fragment cutting time point that is obtained after the mapping specifically comprises: performing mapping on multiple times of fragment cutting of each audio fragment, and mapping a fragment cutting time point to a corresponding audio fragment; reading a fragment cutting start time point and a fragment cutting end time point from the record file of the fragment cutting time point; when a cutting segment indicates first cutting of the audio fragment, saving a fragment cutting start time point and a fragment cutting end time point of the cutting segment in the array; and when the cutting segment indicates cutting other than the first cutting of the audio fragment, comparing the fragment cutting start time point and the fragment cutting end time point of the cutting segment with a previously saved cutting time period, and then performing the mapping; and after each audio fragment is mapped, mapping a fragment cutting time period of each audio fragment to the audio file, and storing, in the array, the new fragment cutting time point that is obtained after the mapping. 4. The method according to claim 3 , wherein the comparing the fragment cutting start time point and the fragment cutting end time point of the cutting segment with a previously saved cutting time period specifically comprises: when the fragment cutting start time point a.start and the fragment cutting end time point a.stop of the cutting segment are both less than a fragment cutting start time point b.start of a saved cutting segment, saving the cutting segment a before the cutting segment b; when the b.start is in the middle of the start time point a.start and the end time point a.stop of the cutting segment a, that is, the a and the b overlap, combining the cutting segment a and the cutting segment b into a new cutting segment, and continuing to perform comparison mapping on the new cutting segment and a next saved cutting segment; and when the start time point a.start and the end time point a.stop of the cutting segment a are both greater than the b.start, transforming the time points of the cutting segment a, and continuing to perform comparison mapping on the transformed cutting segment and a next saved cutting segment. | 0.547972 |
1. A method for optimizing pattern query searches on a graph database, the method being implemented by a computer including at least one processor and comprising: reading a first pattern query for a pattern search; identifying, using a pattern query optimizer executed by the at least one processor, a complex configuration in the first pattern query, the complex configuration including at least one branch or cycle; and generating, using the pattern query optimizer, two or more subpattern queries by decomposing each branch and cycle of the complex configuration into equivalent straight line nodes joined by edges to be converted to search expressions, wherein the generating includes: forming subgraphs by removing nodes that are adjacent to more than two other nodes in the first pattern query; separating the subgraphs into connected components; searching for and locating nodes in any of the connected components that are connected to less than two other nodes in a same connected component; adding nodes in the first pattern query that are adjacent to the located nodes into the connected components along with connecting edges; and when a cycle is found, splitting the cycle into two or more separate paths. | 1. A method for optimizing pattern query searches on a graph database, the method being implemented by a computer including at least one processor and comprising: reading a first pattern query for a pattern search; identifying, using a pattern query optimizer executed by the at least one processor, a complex configuration in the first pattern query, the complex configuration including at least one branch or cycle; and generating, using the pattern query optimizer, two or more subpattern queries by decomposing each branch and cycle of the complex configuration into equivalent straight line nodes joined by edges to be converted to search expressions, wherein the generating includes: forming subgraphs by removing nodes that are adjacent to more than two other nodes in the first pattern query; separating the subgraphs into connected components; searching for and locating nodes in any of the connected components that are connected to less than two other nodes in a same connected component; adding nodes in the first pattern query that are adjacent to the located nodes into the connected components along with connecting edges; and when a cycle is found, splitting the cycle into two or more separate paths. 3. The method of claim 1 , wherein at least one search expression comprises a search query language (SQL) expression. | 0.605263 |
1. A method, comprising: identifying a first network comprising one or more indexed classes of artificial neurons; and determining one or more tags for the one or more indexed classes of artificial neurons regardless of their indexing, wherein determining the one or more tags for the one or more indexed classes of artificial neurons comprises: augmenting the first network with a second network comprising one or more artificial neurons, wherein each neuron in the second network corresponds to a tag; connecting each of the one or more indexed classes of artificial neurons to all the neurons in the second network with one or more plastic connections; and providing supervisory bias signals to the one or more indexed classes of artificial neurons via the plastic connections, such that the supervisory signal imposes a desired mapping between classes and output layer neurons. | 1. A method, comprising: identifying a first network comprising one or more indexed classes of artificial neurons; and determining one or more tags for the one or more indexed classes of artificial neurons regardless of their indexing, wherein determining the one or more tags for the one or more indexed classes of artificial neurons comprises: augmenting the first network with a second network comprising one or more artificial neurons, wherein each neuron in the second network corresponds to a tag; connecting each of the one or more indexed classes of artificial neurons to all the neurons in the second network with one or more plastic connections; and providing supervisory bias signals to the one or more indexed classes of artificial neurons via the plastic connections, such that the supervisory signal imposes a desired mapping between classes and output layer neurons. 4. The method of claim 1 , wherein each of the indexed classes of artificial neurons correspond to one or more tags. | 0.633673 |
13. The method according to claim 12 wherein the step of modifying the relational schema comprises: removing symbols from the changed program code file from the relational schema if the change is one of “remove” and “update”; and incorporating symbols from the changed program code file in the relational schema if the change if one of “add” and “update”. | 13. The method according to claim 12 wherein the step of modifying the relational schema comprises: removing symbols from the changed program code file from the relational schema if the change is one of “remove” and “update”; and incorporating symbols from the changed program code file in the relational schema if the change if one of “add” and “update”. 16. The method according to claim 13 wherein the step of removing symbols comprises: removing public symbols with an associated file corresponding to the changed program code file from the public symbols table; and removing referenced symbols with an associated file corresponding to the changed program code file from the referenced symbols table. | 0.879975 |
1. A paper-sheet recognition apparatus that recognizes a paper sheet, the paper-sheet recognition apparatus comprising: a paper-sheet information acquisition unit that acquires paper-sheet information including an image data of the paper sheet; a candidate narrowing-down unit that narrows down a number of type candidates of the paper sheet to a small number of types based on the image data included in the paper-sheet information; a type determining unit that determines one type from the type candidates narrowed down by the candidate narrowing-down unit based on the image data included in the paper-sheet information; an authenticity recognition unit that recognizes authenticity of the paper sheet as to each of the type candidates narrowed down by the candidate narrowing-down unit; an execution instructing unit that issues an instruction such that the type determining unit and the authenticity recognition unit are operated concurrently; and a final judgment unit that performs a final judgment on the paper sheet by combining the type determined by the type determining unit and an authenticity recognition result corresponding to the type from among authenticity recognition results of the candidate types recognized by the authenticity recognition unit. | 1. A paper-sheet recognition apparatus that recognizes a paper sheet, the paper-sheet recognition apparatus comprising: a paper-sheet information acquisition unit that acquires paper-sheet information including an image data of the paper sheet; a candidate narrowing-down unit that narrows down a number of type candidates of the paper sheet to a small number of types based on the image data included in the paper-sheet information; a type determining unit that determines one type from the type candidates narrowed down by the candidate narrowing-down unit based on the image data included in the paper-sheet information; an authenticity recognition unit that recognizes authenticity of the paper sheet as to each of the type candidates narrowed down by the candidate narrowing-down unit; an execution instructing unit that issues an instruction such that the type determining unit and the authenticity recognition unit are operated concurrently; and a final judgment unit that performs a final judgment on the paper sheet by combining the type determined by the type determining unit and an authenticity recognition result corresponding to the type from among authenticity recognition results of the candidate types recognized by the authenticity recognition unit. 4. The paper-sheet recognition apparatus according to claim 1 , wherein the candidate narrowing-down unit narrows down the number of the type candidates based on a shape of the paper sheet. | 0.796574 |
13. A computer-implemented method comprising: receiving text comprising a first text portion and a second text portion; performing text-to-speech (TTS) processing on the first text portion to determine a first TTS result; performing first TTS processing on the second text portion to determine a second TTS result; determining first output data corresponding to the first TTS result and second TTS result; receiving input data corresponding to a correction to a portion of the first output data, the portion of the first output data corresponding to the first text portion; processing the input data to determine an audio characteristic corresponding to the correction; performing second TTS processing, using the audio characteristic, on the first text portion to determine a third TTS result representing the first text portion and comprising a joining speech unit selected based at least in part on the second TTS results; and determining second output data corresponding to the third TTS result and the second TTS result. | 13. A computer-implemented method comprising: receiving text comprising a first text portion and a second text portion; performing text-to-speech (TTS) processing on the first text portion to determine a first TTS result; performing first TTS processing on the second text portion to determine a second TTS result; determining first output data corresponding to the first TTS result and second TTS result; receiving input data corresponding to a correction to a portion of the first output data, the portion of the first output data corresponding to the first text portion; processing the input data to determine an audio characteristic corresponding to the correction; performing second TTS processing, using the audio characteristic, on the first text portion to determine a third TTS result representing the first text portion and comprising a joining speech unit selected based at least in part on the second TTS results; and determining second output data corresponding to the third TTS result and the second TTS result. 18. The computer-implemented method of claim 13 , further comprising determining that the audio characteristic corresponds to a revised audio characteristic of the first TTS result. | 0.620192 |
1. A method of utilizing delta coding in an acceleration proxy server, the method comprising: storing, at a proxy server, a fingerprint index for a plurality of data pages, wherein a page indexed in the fingerprint index is associated with a first plurality of fingerprints, wherein each data page of the plurality of data pages is assigned a same page size, wherein each fingerprint of the fingerprint index uniquely identifies a string of data within one of the plurality of data pages, and wherein each fingerprint of the fingerprint index comprises a checksum for a separate string of data within one of the plurality of data pages; receiving, at the proxy server, a data request, wherein the request includes a second plurality of fingerprints; searching the fingerprint index for the second plurality of fingerprints; matching a subset of the first plurality of fingerprints with a subset of the second plurality of fingerprints; and identifying the page indexed in the fingerprint index for response to the data request based on the matching the subset of the first plurality of fingerprints with the subset of the second plurality of fingerprints. | 1. A method of utilizing delta coding in an acceleration proxy server, the method comprising: storing, at a proxy server, a fingerprint index for a plurality of data pages, wherein a page indexed in the fingerprint index is associated with a first plurality of fingerprints, wherein each data page of the plurality of data pages is assigned a same page size, wherein each fingerprint of the fingerprint index uniquely identifies a string of data within one of the plurality of data pages, and wherein each fingerprint of the fingerprint index comprises a checksum for a separate string of data within one of the plurality of data pages; receiving, at the proxy server, a data request, wherein the request includes a second plurality of fingerprints; searching the fingerprint index for the second plurality of fingerprints; matching a subset of the first plurality of fingerprints with a subset of the second plurality of fingerprints; and identifying the page indexed in the fingerprint index for response to the data request based on the matching the subset of the first plurality of fingerprints with the subset of the second plurality of fingerprints. 2. The method of claim 1 further comprising: encoding the response to the data request using the page indexed in the fingerprint index when a number of matching fingerprints from the subset of the first plurality of fingerprints and the subset of the second plurality of fingerprints exceeds a threshold match value. | 0.5 |
1. A system for generating student group assignments based on student attributes and student-variable-related criteria and conducting group learning over a network based on the student group assignments, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, program the one or more physical processors to obtain student information about students registered to take a course, wherein, for each student, the student information comprises attributes of the student that correspond to variables of the student; obtain group criteria information associated with the course, wherein the group criteria information comprises first criteria indicating that the students are to be grouped in a manner that they achieve a target level of diversity with respect to a first variable and second criteria indicating that the students are to be grouped in a manner that they achieve a level of similarity with respect to a second variable; assign, based on the attributes, the first criteria, and the second criteria, a first set of the students to a first student group, wherein the first set of the students in the first student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; assign, based on the attributes, the first criteria, and the second criteria, a second set of the students to a second student group, wherein the second set of the students in the second student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; generate an instructor user interface display; provide, through the instructor user interface display, a first display option associated with the first student group, the first display option, when selected, specifies that a first message interface should be displayed on the instructor user interface display, wherein the first message interface display includes one or more first messages exchanged via a first communication channel accessible by the first student group; provide, through the instructor user interface display, a second display option associated with the second student group, the second display option, when selected, specifies that a second message interface should be displayed on the instructor user interface display instead of the first message interface, wherein the second message interface display includes one or more second messages exchanged via a second communication channel accessible by the second student group; receive a selection of the first display option, and cause the first message interface to be displayed on the instructor user interface display in response to the selection of the first display option; and receive a selection of the second display option, and cause the second message interface to be displayed on the instructor user interface display instead of the first message interface display in response to the selection of the second display option. | 1. A system for generating student group assignments based on student attributes and student-variable-related criteria and conducting group learning over a network based on the student group assignments, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, program the one or more physical processors to obtain student information about students registered to take a course, wherein, for each student, the student information comprises attributes of the student that correspond to variables of the student; obtain group criteria information associated with the course, wherein the group criteria information comprises first criteria indicating that the students are to be grouped in a manner that they achieve a target level of diversity with respect to a first variable and second criteria indicating that the students are to be grouped in a manner that they achieve a level of similarity with respect to a second variable; assign, based on the attributes, the first criteria, and the second criteria, a first set of the students to a first student group, wherein the first set of the students in the first student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; assign, based on the attributes, the first criteria, and the second criteria, a second set of the students to a second student group, wherein the second set of the students in the second student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; generate an instructor user interface display; provide, through the instructor user interface display, a first display option associated with the first student group, the first display option, when selected, specifies that a first message interface should be displayed on the instructor user interface display, wherein the first message interface display includes one or more first messages exchanged via a first communication channel accessible by the first student group; provide, through the instructor user interface display, a second display option associated with the second student group, the second display option, when selected, specifies that a second message interface should be displayed on the instructor user interface display instead of the first message interface, wherein the second message interface display includes one or more second messages exchanged via a second communication channel accessible by the second student group; receive a selection of the first display option, and cause the first message interface to be displayed on the instructor user interface display in response to the selection of the first display option; and receive a selection of the second display option, and cause the second message interface to be displayed on the instructor user interface display instead of the first message interface display in response to the selection of the second display option. 8. The system of claim 1 , wherein the one or more physical processors are further programmed to: determine that a composition of the students registered to take the course does not satisfy a preferred composition of students for the course; and provide, to one or more students not currently registered to take the course, one or more suggestions to register for the course based on Rail the determination that the composition of students registered to take the course does not satisfy the preferred composition and that the addition of the one or more students creates a composition that satisfies the preferred composition. | 0.552573 |
11. The system of claim 10 , wherein the object information includes a GUI object type and GUI object content. | 11. The system of claim 10 , wherein the object information includes a GUI object type and GUI object content. 13. The system of claim 11 , wherein converting the object information in the first language to object information in the second language comprises: finding, in a translation table, an entry including the GUI object content in the object information in the first language, the translation table storing all texts that can become the GUI object content in the first language and their translations in the second language in association with each other as entries; extracting, from the found entry, a translation in the second language of the GUI object content; and replacing the GUI object content in the object information in the first language with the translation, so that the object information in the first language is converted to the object information in the second language. | 0.798874 |
6. The method of claim 1 , further including parsing the product records to identify word matches in each of the product records and the document. | 6. The method of claim 1 , further including parsing the product records to identify word matches in each of the product records and the document. 8. The method of claim 6 , wherein said parsing step includes obtaining information indicating formatting characteristics of said words of the document including at least one of bolding, italicizing, underlining, capitalization, font type and font size. | 0.882769 |
13. The non-transitory computer-readable medium of claim 12 , wherein said step of generating an abstract interpretation further comprises the steps of: providing a type qualifier for each variable associated with at least one function within said software application; and providing a precondition for each of said at least one function within said software application. | 13. The non-transitory computer-readable medium of claim 12 , wherein said step of generating an abstract interpretation further comprises the steps of: providing a type qualifier for each variable associated with at least one function within said software application; and providing a precondition for each of said at least one function within said software application. 14. The non-transitory computer-readable medium of claim 13 , wherein said step of verifying said correctness of safety states further comprises the step of: evaluating said type qualifiers and said preconditions to identify vulnerabilities in said software application. | 0.803759 |
7. The method of claim 5 , wherein applying the second relevance filter comprises: determining that a subset of the plurality of authoring accounts are verified accounts; and increasing the relevance scores of the verified accounts. | 7. The method of claim 5 , wherein applying the second relevance filter comprises: determining that a subset of the plurality of authoring accounts are verified accounts; and increasing the relevance scores of the verified accounts. 8. The method of claim 7 , further comprising: receiving, from a client computing device, a request for the relevant conversation, wherein providing the relevant conversation is in response to the request; and applying a third relevance filter by: identifying a requesting account of the request, and identifying a predefined graph relationship between the requesting account and an authoring account of the plurality of authoring accounts; and increasing the relevance score of the authoring account based on the predefined graph relationship. | 0.841385 |
19. The system of claim 15 , the one or more hardware processors further configured to include a query log cleaning and normalization module to clean the query log and to normalize the query log. | 19. The system of claim 15 , the one or more hardware processors further configured to include a query log cleaning and normalization module to clean the query log and to normalize the query log. 20. The system of claim 19 wherein the cleaning comprises noise removal and the normalizing comprises dividing the transition scores by the number of users that practice the transition. | 0.925103 |
7. A system comprising: one or more servers configured to perform operations comprising: generating a first vector for one or more first n-grams of a first query and calculating a respective first semantic weight for each of the first n-grams based at least in part on an entropy of the particular first n-gram in which the entropy is estimated from a set of search queries; generating a second vector for one or more second n-grams of a second query and calculating a respective second semantic weight for each of the second n-grams; calculating a similarity measurement between the first query and the second query based on respective similarities of semantically weighted first n-grams to the second vector, and based on respective similarities of the semantically weighted second n-grams to the first vector; and wherein generating and calculating are performed by one or more computers. | 7. A system comprising: one or more servers configured to perform operations comprising: generating a first vector for one or more first n-grams of a first query and calculating a respective first semantic weight for each of the first n-grams based at least in part on an entropy of the particular first n-gram in which the entropy is estimated from a set of search queries; generating a second vector for one or more second n-grams of a second query and calculating a respective second semantic weight for each of the second n-grams; calculating a similarity measurement between the first query and the second query based on respective similarities of semantically weighted first n-grams to the second vector, and based on respective similarities of the semantically weighted second n-grams to the first vector; and wherein generating and calculating are performed by one or more computers. 9. The system of claim 7 , in which calculating the first semantic weight for the first n-gram is based on a combination of an inverse document frequency (IDF) of the first n-gram and an entropy of the first n-gram. | 0.522706 |
1. A method for positioning one or more documents in a visual file space associated with a personal corpus, said method comprising the steps of: storing each of said documents with an indication of term weight for terms appearing in said corresponding document, wherein said term weight is obtained by dividing a fractional frequency of said term in said document by a fractional frequency of said term in said reference corpus, wherein said fractional frequency of said term in said document is the number of occurrences of the term in the document divided by the total number of terms in the document and wherein said fractional frequency of said term in said reference corpus is the number of occurrences of the term in the reference corpus divided by the total number of words in the reference corpus; and performing a singular value decomposition based on said term weights to position a given document in said visual file space based on a relative frequency distribution of terms of said document compared to the occurrence of such terms in a reference corpus. | 1. A method for positioning one or more documents in a visual file space associated with a personal corpus, said method comprising the steps of: storing each of said documents with an indication of term weight for terms appearing in said corresponding document, wherein said term weight is obtained by dividing a fractional frequency of said term in said document by a fractional frequency of said term in said reference corpus, wherein said fractional frequency of said term in said document is the number of occurrences of the term in the document divided by the total number of terms in the document and wherein said fractional frequency of said term in said reference corpus is the number of occurrences of the term in the reference corpus divided by the total number of words in the reference corpus; and performing a singular value decomposition based on said term weights to position a given document in said visual file space based on a relative frequency distribution of terms of said document compared to the occurrence of such terms in a reference corpus. 7. The method of claim 1 , further comprising the step of providing an indication of documents having the highest correlation to one or more user-specified keywords. | 0.819172 |
17. A computer system comprising: a) a client computer interconnected to a computer network comprising a target server computer associated therewith, and b) a computer input device coupled to said client computer, adapted to read a machine readable symbol from a data carrier and transmit to said client computer an input data string; wherein said client computer comprises processing means for transposing said input data string to a plurality of constituent fields, said fields comprising at least a file location pointer; means for utilizing said file location pointer to request the computer file designated thereby; comprising means for passing said file location pointer to an application program on said client computer suitable for processing the corresponding computer file; means for the application program to retrieve the computer file from the specified file location; means for assembling a computer file transfer request word comprising said file location pointer, and means for transmitting said computer file transfer request word to said target server computer via said network; wherein said target server computer comprises: means for receiving said computer file transfer request word; and means for transmitting a computer file to said client computer in response to said computer file transfer request word; wherein said input data string fields also comprise a source identifier data string, said source identifier data string comprising data correlated to an expected user of said data carrier. | 17. A computer system comprising: a) a client computer interconnected to a computer network comprising a target server computer associated therewith, and b) a computer input device coupled to said client computer, adapted to read a machine readable symbol from a data carrier and transmit to said client computer an input data string; wherein said client computer comprises processing means for transposing said input data string to a plurality of constituent fields, said fields comprising at least a file location pointer; means for utilizing said file location pointer to request the computer file designated thereby; comprising means for passing said file location pointer to an application program on said client computer suitable for processing the corresponding computer file; means for the application program to retrieve the computer file from the specified file location; means for assembling a computer file transfer request word comprising said file location pointer, and means for transmitting said computer file transfer request word to said target server computer via said network; wherein said target server computer comprises: means for receiving said computer file transfer request word; and means for transmitting a computer file to said client computer in response to said computer file transfer request word; wherein said input data string fields also comprise a source identifier data string, said source identifier data string comprising data correlated to an expected user of said data carrier. 18. The computer system of claim 17 wherein said computer network is an Internet, and wherein said computer file transfer request word is directed towards a target server computer in communication with the Internet. | 0.5 |
12. The device of claim 11 , wherein the base scores of the respective tables and the base scores of the fields of the respective tables are determined according to a user-specified rule and a correlation relation among the respective tables in the database, the correlation relation referring to a correlation relation formed by correlating two tables via a foreign key, or a correlation relation formed by two tables which appear in a same historical SQL statement executed on the database and are correlated via at least one field. | 12. The device of claim 11 , wherein the base scores of the respective tables and the base scores of the fields of the respective tables are determined according to a user-specified rule and a correlation relation among the respective tables in the database, the correlation relation referring to a correlation relation formed by correlating two tables via a foreign key, or a correlation relation formed by two tables which appear in a same historical SQL statement executed on the database and are correlated via at least one field. 13. The device of claim 12 , wherein a table or a field included in the user-specified rule, and a table in the database, which has the correlation relation with the table, and a field thereof have a first base score, and a remaining table in the database and a field thereof have a second base score which is smaller than the first base score. | 0.831075 |
1. A content addressable memory (CAM) device, comprising: a CAM array including a plurality of rows, each row including a plurality of CAM cells coupled to a match line; a data encoder circuit having an input to receive a first data word and configured to encode the first data word using an encoding scheme to generate an encoded data word that comprises a balanced data word having an equal number of logic high bits and logic low bits; and a read/write circuit coupled to the data encoder circuit and the CAM array and configured to store the encoded balanced data word into a selected row of CAM cells, wherein each row includes a number T of quaternary CAM cells, T being an integer greater than 2, wherein the encoded data word includes 2T data bits, and wherein a number S of possible states represented by the balanced data word is expressed as S=(2T)!/(T!) 2 . | 1. A content addressable memory (CAM) device, comprising: a CAM array including a plurality of rows, each row including a plurality of CAM cells coupled to a match line; a data encoder circuit having an input to receive a first data word and configured to encode the first data word using an encoding scheme to generate an encoded data word that comprises a balanced data word having an equal number of logic high bits and logic low bits; and a read/write circuit coupled to the data encoder circuit and the CAM array and configured to store the encoded balanced data word into a selected row of CAM cells, wherein each row includes a number T of quaternary CAM cells, T being an integer greater than 2, wherein the encoded data word includes 2T data bits, and wherein a number S of possible states represented by the balanced data word is expressed as S=(2T)!/(T!) 2 . 2. The CAM device of claim 1 , wherein each quaternary CAM cell stores two of the data bits. | 0.614162 |
6. A system comprising: a physical computer system comprising one or more computer processors, the physical computer system programmed to: receive a search query from a user computing device; classify the search query, based at least in part on query parameters associated with the search query; identify one or more specialized data stores available to answer the search query, based at least in part on the search query classification and whether the one or more the specialized data stores are able to accurately answer queries classified under the search query classification; determine whether at least one of the specialized data stores should be used to answer the search query, wherein the determination is based at least in part on performance data associated with respective specialized data stores, wherein the performance data reflects at least (1) an average response time associated with respective specialized data stores in answering search queries and (2) recency of data stored by respective specialized data stores; if least one of the identified specialized data stores should be used to answer the search query, retrieve the search results for the search query using a selected one of the identified specialized data stores, wherein the selected specialized data store has a lowest average response time and/or more recently stored data; or if none of the identified specialized data stores should be used to answer the search query, retrieve the search results for the search query using a general search engine; and transmit the retrieved search results to the user computing device. | 6. A system comprising: a physical computer system comprising one or more computer processors, the physical computer system programmed to: receive a search query from a user computing device; classify the search query, based at least in part on query parameters associated with the search query; identify one or more specialized data stores available to answer the search query, based at least in part on the search query classification and whether the one or more the specialized data stores are able to accurately answer queries classified under the search query classification; determine whether at least one of the specialized data stores should be used to answer the search query, wherein the determination is based at least in part on performance data associated with respective specialized data stores, wherein the performance data reflects at least (1) an average response time associated with respective specialized data stores in answering search queries and (2) recency of data stored by respective specialized data stores; if least one of the identified specialized data stores should be used to answer the search query, retrieve the search results for the search query using a selected one of the identified specialized data stores, wherein the selected specialized data store has a lowest average response time and/or more recently stored data; or if none of the identified specialized data stores should be used to answer the search query, retrieve the search results for the search query using a general search engine; and transmit the retrieved search results to the user computing device. 10. The system of claim 6 , wherein the physical computer system is further programmed to: identify one or more data stores to answer the search query; retrieve the search results from the one or more data stores; retrieve performance data from the one or more data stores; evaluate the performance data retrieved from the one or more data stores; and categorize one or more of the data stores as specialized data stores, based at least in part on the performance evaluation. | 0.615401 |
13. An electronic system for generating a work of communication, the system comprising: a user input system having user input controls adapted to receive instructions from an author including a designation of a set of content data files and a selection an output form for the work of communication; and, a processor adapted to receive the designated content data files and to determine context indicators from the context data files based upon a contextual framework of rules for identifying context indicators in the content data files, said processor further adapted to determine inference queries based upon the context indicators and a knowledge base for a person associated with the work of communication; to obtain context data files from a source of content data files using the inference queries; and, to prioritize obtained context data files based upon the significance of the context data file relative to the associated person said processor further being adapted to provide context data files that have an assigned priority that is greater than a threshold priority for integration into the work of communication; wherein said context data files comprise content data files other than the designated set of content data files. | 13. An electronic system for generating a work of communication, the system comprising: a user input system having user input controls adapted to receive instructions from an author including a designation of a set of content data files and a selection an output form for the work of communication; and, a processor adapted to receive the designated content data files and to determine context indicators from the context data files based upon a contextual framework of rules for identifying context indicators in the content data files, said processor further adapted to determine inference queries based upon the context indicators and a knowledge base for a person associated with the work of communication; to obtain context data files from a source of content data files using the inference queries; and, to prioritize obtained context data files based upon the significance of the context data file relative to the associated person said processor further being adapted to provide context data files that have an assigned priority that is greater than a threshold priority for integration into the work of communication; wherein said context data files comprise content data files other than the designated set of content data files. 17. The system of claim 13 , further comprising a display system for presenting a work product or portion thereof at a remote location. | 0.641224 |
1. A method of predicting a result of genetic mutation, comprising: determining differences between (i) values of a first plurality of features, of amino acids encoded by a variant of a wild-type polynucleotide sequence, and (ii) values of a second plurality of features, of amino acids encoded by the wild-type polynucleotide sequence; wherein the features of the first plurality are the same as the features of the second plurality; and by a processor and based on the differences, determining a predicted phenotype severity of the variant. | 1. A method of predicting a result of genetic mutation, comprising: determining differences between (i) values of a first plurality of features, of amino acids encoded by a variant of a wild-type polynucleotide sequence, and (ii) values of a second plurality of features, of amino acids encoded by the wild-type polynucleotide sequence; wherein the features of the first plurality are the same as the features of the second plurality; and by a processor and based on the differences, determining a predicted phenotype severity of the variant. 4. The method of claim 1 , wherein at least one of the first plurality of features is selected from the group consisting of alpha NH chemical shifts, normalized frequency of C terminal helix, normalized frequency of chain reversal R, normalized positional frequency at helix termini N2, partition coefficient Garel, relative preference value at C2, relative preference value at N1, weights for beta sheet at the window position of 0, amino acid distribution, average relative fractional occurrence in A0(i), average relative probability of inner beta sheet, composition, effective partition energy, free energy in alpha helical region, frequency of the third residue in turn, helix formation parameters (delta delta G), hydrophobicity, membrane buried preference parameters, normalized frequency of beta structure, normalized frequency of coil, normalized positional frequency at helix termini Cc, STERIMOL maximum width of the side chain, and Zimm Bragg parameter sigma. | 0.514 |
18. The system of claim 15 , wherein the operations associated with the cluster module further comprising labelling the plurality of prototypes as a type character or ligature based on optical character recognition (OCR) data associated with the scanned document. | 18. The system of claim 15 , wherein the operations associated with the cluster module further comprising labelling the plurality of prototypes as a type character or ligature based on optical character recognition (OCR) data associated with the scanned document. 19. The system of claim 18 , wherein the operations associated with the prototype module further comprising comparing the plurality of prototypes to the two or more touching characters of the ligature to identify two or more matched prototypes, the operation of comparing further comprising: identifying two or more type characters corresponding to the two or more touching characters of the ligature; and matching the two or more identified type characters to corresponding labelled prototypes to identify the two or more matched prototypes. | 0.819527 |
1. A method of acquiring tags using web search, the method comprising: receiving a search query in a search engine; processing the search query by the search engine to return and a plurality of candidate resources as a list corresponding to the search query; generating a graphical tag cloud for each of the plurality of candidate resources returned by the search engine, wherein each of the graphical tag clouds is displayed in association with a respective candidate resource; sorting the list of candidate resources; receiving a selection of a candidate resource from the list of candidate resources; extracting at least one tag from the search query; tagging the candidate resource with an extracted tag from the search query; and incrementing a hit count for only the candidate resource selected from the list of candidate resources and a hit count for at least one tag associated with the candidate resource matching the extracted tags; wherein a frequency of occurrence for each extracted tag with respect to the candidate resource selected from the list of candidate resources is maintained by increasing a corresponding counter by one. | 1. A method of acquiring tags using web search, the method comprising: receiving a search query in a search engine; processing the search query by the search engine to return and a plurality of candidate resources as a list corresponding to the search query; generating a graphical tag cloud for each of the plurality of candidate resources returned by the search engine, wherein each of the graphical tag clouds is displayed in association with a respective candidate resource; sorting the list of candidate resources; receiving a selection of a candidate resource from the list of candidate resources; extracting at least one tag from the search query; tagging the candidate resource with an extracted tag from the search query; and incrementing a hit count for only the candidate resource selected from the list of candidate resources and a hit count for at least one tag associated with the candidate resource matching the extracted tags; wherein a frequency of occurrence for each extracted tag with respect to the candidate resource selected from the list of candidate resources is maintained by increasing a corresponding counter by one. 8. The method of claim 1 , wherein the tagged candidate resource is one of a picture or an article, or any other digital document that can be accessed on the internet. | 0.666667 |
1. An apparatus, comprising: a processor; and a non-transitory computer-readable storage medium having instructions stored thereupon which are executable by the processor and which, when executed, cause the apparatus to: receive a request at a first network service to internationalize and localize program source code, responsive to the request, cause a second network service to perform static analysis on the program source code to identify one or more hard coded strings contained in the program source code, extract, by way of the first network service, the one or more hard coded strings from the program source code, cause a third network service to generate one or more translated text strings by translating the one or more hard coded strings from a first human readable language to at least one second human readable language, generate, by way of the first network service, internationalized and localized program source code by replacing the one or more hard coded strings with method calls for obtaining the one or more translated text strings, return, by way of the first network service, the internationalized and localized program source code in a reply to the request; and cause a fourth network service to compile the internationalized and localized program source code to create an executable internationalized and localized program, and to deploy the executable internationalized and localized program to at least one computing resource operating in a service provider network, wherein the request comprises the program source code, data identifying the first human readable language and the at least one second human readable language, data indicating whether statistical machine translation or human translation is to be utilized to generate the translated text strings, and data indicating whether the executable internationalized and localized program is to be deployed even if internationalization or localization issues exist in the program source code. | 1. An apparatus, comprising: a processor; and a non-transitory computer-readable storage medium having instructions stored thereupon which are executable by the processor and which, when executed, cause the apparatus to: receive a request at a first network service to internationalize and localize program source code, responsive to the request, cause a second network service to perform static analysis on the program source code to identify one or more hard coded strings contained in the program source code, extract, by way of the first network service, the one or more hard coded strings from the program source code, cause a third network service to generate one or more translated text strings by translating the one or more hard coded strings from a first human readable language to at least one second human readable language, generate, by way of the first network service, internationalized and localized program source code by replacing the one or more hard coded strings with method calls for obtaining the one or more translated text strings, return, by way of the first network service, the internationalized and localized program source code in a reply to the request; and cause a fourth network service to compile the internationalized and localized program source code to create an executable internationalized and localized program, and to deploy the executable internationalized and localized program to at least one computing resource operating in a service provider network, wherein the request comprises the program source code, data identifying the first human readable language and the at least one second human readable language, data indicating whether statistical machine translation or human translation is to be utilized to generate the translated text strings, and data indicating whether the executable internationalized and localized program is to be deployed even if internationalization or localization issues exist in the program source code. 3. The apparatus of claim 1 , wherein the third network service is configured to generate the one or more translated text strings utilizing statistical machine translation. | 0.66479 |
1. A method for enabling collaborative development of a database application, the method comprising: receiving a database, generated by a first user in a first database language, via a first database management system (DBMS); designating a set of tables from the database as a set of static data tables; committing the database and the set of static data tables to a repository; deploying, from the repository, the database in a second DBMS; receiving a change to the database, by a second user in a second database language, via at least one of: the first DBMS, and the second DBMS, wherein the change is represented as metadata that is general to both the first DBMS and the second DBMS; and synchronizing the change to the database within the repository based on the metadata. | 1. A method for enabling collaborative development of a database application, the method comprising: receiving a database, generated by a first user in a first database language, via a first database management system (DBMS); designating a set of tables from the database as a set of static data tables; committing the database and the set of static data tables to a repository; deploying, from the repository, the database in a second DBMS; receiving a change to the database, by a second user in a second database language, via at least one of: the first DBMS, and the second DBMS, wherein the change is represented as metadata that is general to both the first DBMS and the second DBMS; and synchronizing the change to the database within the repository based on the metadata. 6. The method according to claim 1 , wherein the first DBMS has a first DBMS type and the second DBMS has a second DBMS type different than the first DBMS type. | 0.86379 |
17. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: performing automatic speech recognition using a bootstrap model on utterance data not having a corresponding manual transcription, to produce automatically transcribed utterances, wherein the bootstrap model is based on text data mined from a website relevant to a specific domain; selecting a predetermined number of utterances not having a corresponding manual transcription based on a geometrically computed n-tuple confidence score; and generating a language model based on the automatically transcribed utterances, the predetermined number of utterances, and transcriptions of the predetermined number of utterances. | 17. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: performing automatic speech recognition using a bootstrap model on utterance data not having a corresponding manual transcription, to produce automatically transcribed utterances, wherein the bootstrap model is based on text data mined from a website relevant to a specific domain; selecting a predetermined number of utterances not having a corresponding manual transcription based on a geometrically computed n-tuple confidence score; and generating a language model based on the automatically transcribed utterances, the predetermined number of utterances, and transcriptions of the predetermined number of utterances. 18. The computer-readable storage device of claim 17 , wherein the transcriptions of the predetermined number of utterances are made by a human being. | 0.625114 |
7. The computer-implemented method of claim 6 , wherein the method further comprises receiving, from the business, a selection of the option to publish the selected at least one search keyword on the online information resource. | 7. The computer-implemented method of claim 6 , wherein the method further comprises receiving, from the business, a selection of the option to publish the selected at least one search keyword on the online information resource. 8. The computer-implemented method of claim 7 , wherein the selected at least one search keyword is published to the online information resource according to the selection, by the business, of the option to publish the selected at least one search keyword. | 0.929434 |
8. The method of claim 1 , wherein the step of adjusting the ultimate set of tuning parameters of the closed-loop process based upon the degree of oscillation of the oscillatory behavior response and the leading cause of the oscillatory behavior response, further comprises calculating a new set of tuning parameters. | 8. The method of claim 1 , wherein the step of adjusting the ultimate set of tuning parameters of the closed-loop process based upon the degree of oscillation of the oscillatory behavior response and the leading cause of the oscillatory behavior response, further comprises calculating a new set of tuning parameters. 9. The method of claim 8 , further comprising calculating a tuning parameter that determines the aggressiveness of the adjustment. | 0.908822 |
1. A computer-implemented method, comprising: outputting, at a computing device including one or more processors, a media stream that includes at least one of audio data and video data, the media stream being fully defined between a start time and an end time; during the outputting of the media stream: (i) receiving, at the computing device, a user input (a) identifying a temporal point within the media stream and (b) indicating a request for translating a portion of the media stream from a source language to a target language, (ii) in response to receiving the user input, determining, at the computing device, a text by performing one of (a) speech recognition on a sub-period of the audio data as specified by the identified temporal point within the media stream and (b) optical character recognition on an image from the video data as specified by the identified temporal point, and (iii) transmitting, from the computing device, the text to a translation server via a network; receiving, at the computing device, a translated text from the translation server via the network, the translated text having been translated from the source language to the target language by the translation server; and in response to completion of the media stream, displaying, at a display of the computing device, the translated text at the end time of the media stream. | 1. A computer-implemented method, comprising: outputting, at a computing device including one or more processors, a media stream that includes at least one of audio data and video data, the media stream being fully defined between a start time and an end time; during the outputting of the media stream: (i) receiving, at the computing device, a user input (a) identifying a temporal point within the media stream and (b) indicating a request for translating a portion of the media stream from a source language to a target language, (ii) in response to receiving the user input, determining, at the computing device, a text by performing one of (a) speech recognition on a sub-period of the audio data as specified by the identified temporal point within the media stream and (b) optical character recognition on an image from the video data as specified by the identified temporal point, and (iii) transmitting, from the computing device, the text to a translation server via a network; receiving, at the computing device, a translated text from the translation server via the network, the translated text having been translated from the source language to the target language by the translation server; and in response to completion of the media stream, displaying, at a display of the computing device, the translated text at the end time of the media stream. 4. The computer-implemented method of claim 1 , wherein the user input identifies a sub-portion of the image, and wherein the optical character recognition is performed on the sub-portion of the image to obtain the text. | 0.666975 |
8. The method of claim 7 , wherein the method of determining the importance measure comprises: assigning a weighting co-efficient to the term based on the grammatical attribute associated with the term; and producing the importance measure based at least on the weighting co-efficient. | 8. The method of claim 7 , wherein the method of determining the importance measure comprises: assigning a weighting co-efficient to the term based on the grammatical attribute associated with the term; and producing the importance measure based at least on the weighting co-efficient. 9. The method of claim 8 , wherein the method of determining the importance measure further comprises: incrementing a cumulative value for the term based on the number of occurrences of the term in the first chronological segment and the weighting co-efficient for each corresponding occurrence of the term, wherein the importance measure is produced further based on the cumulative value. | 0.879841 |
6. A computer program product, comprising: a non-transitory computer-readable storage medium; and computer-readable code for mapping objects of a user scenario with objects of a user interface embodied on the non-transitory computer-readable storage medium, wherein the computer-readable code, when executed by a processor of a data processing system, causes the processor to: register a user scenario with a user interface automation framework, the user scenario including a first object that is also included in a first user interface, wherein the first object has an associated semantically annotated first field and the user scenario includes a list of actions for objects of the first user interface; generate a second user interface from the first user interface by modifying the first object to create a second object, wherein the second object has an associated semantically annotated second field, wherein the second user interface comprises a plurality of objects; perform semantic relationship matching using a plurality of semantic relationship rules, the semantic relationship matching further comprising the computer-readable code causing the processor to: identify a recorded semantic relationship that is associated with the first field, wherein the recorded semantic relationship defines a relationship between at least the first field and a first other field of the first object; identify a semantic relationship from among one or more semantic relationships in the second user interface that matches the recorded semantic relationship, wherein the matching semantic relationship defines a relationship between at least the second field and a second other field of the first object; and identify, based on the matching semantic relationship, a matching object of the plurality of objects of the second user interface that is most similar to the first object, wherein the matching object is the second object; and in response to the semantic relationship matching resulting in the recognition of the second object, map the first object to the second object based on the first and second fields. | 6. A computer program product, comprising: a non-transitory computer-readable storage medium; and computer-readable code for mapping objects of a user scenario with objects of a user interface embodied on the non-transitory computer-readable storage medium, wherein the computer-readable code, when executed by a processor of a data processing system, causes the processor to: register a user scenario with a user interface automation framework, the user scenario including a first object that is also included in a first user interface, wherein the first object has an associated semantically annotated first field and the user scenario includes a list of actions for objects of the first user interface; generate a second user interface from the first user interface by modifying the first object to create a second object, wherein the second object has an associated semantically annotated second field, wherein the second user interface comprises a plurality of objects; perform semantic relationship matching using a plurality of semantic relationship rules, the semantic relationship matching further comprising the computer-readable code causing the processor to: identify a recorded semantic relationship that is associated with the first field, wherein the recorded semantic relationship defines a relationship between at least the first field and a first other field of the first object; identify a semantic relationship from among one or more semantic relationships in the second user interface that matches the recorded semantic relationship, wherein the matching semantic relationship defines a relationship between at least the second field and a second other field of the first object; and identify, based on the matching semantic relationship, a matching object of the plurality of objects of the second user interface that is most similar to the first object, wherein the matching object is the second object; and in response to the semantic relationship matching resulting in the recognition of the second object, map the first object to the second object based on the first and second fields. 7. The computer program product of claim 6 , wherein the code, when executed by the processor of the data processing system, further causes the processor to: calculate an affinity between ontological concepts expressed in the first and second fields; and map the first object to the second object based on the calculated affinity. | 0.745985 |
1. A method of communicating information between parties comprising: automatically creating a content-dependent just-in-time application file for an electronic authored work based on the content assembled together in the authored work created by an author, wherein the file includes code for: information contained in the authored work, wherein at least a portion of the information may be stored remotely from a networked device processing the just-in-time application for presenting the authored work, creating or invoking at least one first application for presenting the content of the authored work on a networked device, disseminating the file through a computer network; and forwarding the disseminated file to a distribution channel for presenting the authored work to a recipient on a networked device, wherein upon receiving the file on the networked device, the just-in-time application file is processed creating and/or invoking the at least one first application for presenting the authored work based on the content of the authored work. | 1. A method of communicating information between parties comprising: automatically creating a content-dependent just-in-time application file for an electronic authored work based on the content assembled together in the authored work created by an author, wherein the file includes code for: information contained in the authored work, wherein at least a portion of the information may be stored remotely from a networked device processing the just-in-time application for presenting the authored work, creating or invoking at least one first application for presenting the content of the authored work on a networked device, disseminating the file through a computer network; and forwarding the disseminated file to a distribution channel for presenting the authored work to a recipient on a networked device, wherein upon receiving the file on the networked device, the just-in-time application file is processed creating and/or invoking the at least one first application for presenting the authored work based on the content of the authored work. 4. The method according to claim 1 , wherein prior to automatically creating the just-in-time application, the method further includes receiving information of the authored work from the author for automatically creating the content based just-in-time application. | 0.587456 |
1. A system for enabling a user to locate information of interest in different human languages, comprising: one or more databases containing terms in a first human language, wherein the terms are organized into a hierarchical structure; a first computer executing search interface software recorded on a computer-readable medium and associated with a collection of information in a second human language, wherein the search interface software when executed causes the first computer to receive search queries in the second human language and to communicate search results from the collection of information in the second human language; and a second computer executing user interface software recorded on a computer-readable medium, wherein the user interface software when executed causes the second computer to communicate with the one or more databases, the search interface software, and a user, and to: access the terms in the first human language from the one or more databases; communicate with the user to allow the user to navigate through the terms in accordance with the hierarchical structure; receive an indication that the user has selected one or more of the terms in the first human language; generate a draft search query in the second human language based on a translation of the selected one or more terms; display the draft search query in the second human language to the user; receive a revised search query in the second human language from the user; communicate the revised search query in the second human language to the first computer executing the search interface software; receive from the first computer search results in the second human language; and communicate the search results in the second human language to the user, wherein the one or more databases, the first computer, and the second computer are in communication with a computer network. | 1. A system for enabling a user to locate information of interest in different human languages, comprising: one or more databases containing terms in a first human language, wherein the terms are organized into a hierarchical structure; a first computer executing search interface software recorded on a computer-readable medium and associated with a collection of information in a second human language, wherein the search interface software when executed causes the first computer to receive search queries in the second human language and to communicate search results from the collection of information in the second human language; and a second computer executing user interface software recorded on a computer-readable medium, wherein the user interface software when executed causes the second computer to communicate with the one or more databases, the search interface software, and a user, and to: access the terms in the first human language from the one or more databases; communicate with the user to allow the user to navigate through the terms in accordance with the hierarchical structure; receive an indication that the user has selected one or more of the terms in the first human language; generate a draft search query in the second human language based on a translation of the selected one or more terms; display the draft search query in the second human language to the user; receive a revised search query in the second human language from the user; communicate the revised search query in the second human language to the first computer executing the search interface software; receive from the first computer search results in the second human language; and communicate the search results in the second human language to the user, wherein the one or more databases, the first computer, and the second computer are in communication with a computer network. 10. The system of claim 1 , wherein the one or more databases comprise a geographical terms database. | 0.621048 |
1. A system of ranking entities using reputation or influence scores, comprising: one or more processors that determines reputation scores for one or more subjects based on connections, the reputation scores indicating reputations of the subjects; one or more processors that use a plurality of citations, each citation representing an online posting of an expression of opinion by a subject on an object, wherein the subject is representative of a user; one or more processors that select a subset of citations for each object from the citations citing each object, the content of the citations in the selected subset matching one or more of search terms for a search query; one or more processors that assign citation scores to a subset of a plurality of objects, the citation scores indicating relevance of the objects cited by citations and are determined based at least in part on matching one or more search terms with the content of the citations of the objects by the one or more subjects, the selection scores for an object being determined for each search query based on a subset of subjects citing the object; one or more processors that combine the citation scores for the objects and the reputation scores for the subjects citing the objects to calculate selection scores for the objects determined based on matching of the one or more search terms with the content of the citations, the selection scores for an object determined for each search query based on a subset of subjects citing the object, with the subjects in the subset being the subjects of previously selected subsets of citations to each object, a different selection score computed for the same object when a different search query is provided; and one or more processors that select and rank the objects based on the selection scores of the objects, a different ranking computed for a same set or overlapping sets of objects when the search query is different. | 1. A system of ranking entities using reputation or influence scores, comprising: one or more processors that determines reputation scores for one or more subjects based on connections, the reputation scores indicating reputations of the subjects; one or more processors that use a plurality of citations, each citation representing an online posting of an expression of opinion by a subject on an object, wherein the subject is representative of a user; one or more processors that select a subset of citations for each object from the citations citing each object, the content of the citations in the selected subset matching one or more of search terms for a search query; one or more processors that assign citation scores to a subset of a plurality of objects, the citation scores indicating relevance of the objects cited by citations and are determined based at least in part on matching one or more search terms with the content of the citations of the objects by the one or more subjects, the selection scores for an object being determined for each search query based on a subset of subjects citing the object; one or more processors that combine the citation scores for the objects and the reputation scores for the subjects citing the objects to calculate selection scores for the objects determined based on matching of the one or more search terms with the content of the citations, the selection scores for an object determined for each search query based on a subset of subjects citing the object, with the subjects in the subset being the subjects of previously selected subsets of citations to each object, a different selection score computed for the same object when a different search query is provided; and one or more processors that select and rank the objects based on the selection scores of the objects, a different ranking computed for a same set or overlapping sets of objects when the search query is different. 8. The system recited in claim 1 , further comprising: one or more processors that receive search terms, wherein the search terms are provided in a search query; and one or more processors that display a subset of top ranked objects based on the selection scores, wherein the top ranked objects based on the selection scores provide a subjective based search result. | 0.5 |
11. The method according to claim 1 , further comprising constructing the face from the image vector including the plurality of parameters that define the face, said parameters permitting constructing the face from a weighted sum of modes representing reconstructions of the face or a part of the face. | 11. The method according to claim 1 , further comprising constructing the face from the image vector including the plurality of parameters that define the face, said parameters permitting constructing the face from a weighted sum of modes representing reconstructions of the face or a part of the face. 12. The method according to claim 11 , wherein the weighted sum of modes includes modes to represent a shape of the face and an appearance of the face. | 0.935587 |
9. A method of quantizing a vector representative of a portion of a speech or audio signal in an encoder, comprising: (a) determining legal candidate codevectors among a set of candidate codevectors based upon one or more illegal space definitions, the candidate codevectors including line spectral frequencies (LSFs), wherein the one or more illegal space definitions define invalid spacing characteristics of LSFs; (b) deriving a separate error term corresponding to each legal candidate codevector, each error term being a function of the vector and the corresponding legal candidate codevector; (c) determining a best legal candidate codevector among the legal candidate codevectors based on the error terms, whereby the best legal candidate codevector corresponds to a quantization of the vector; and (d) transmitting to a decoder a signal representative of the portion of the speech or audio signal based on the best legal candidate codevector. | 9. A method of quantizing a vector representative of a portion of a speech or audio signal in an encoder, comprising: (a) determining legal candidate codevectors among a set of candidate codevectors based upon one or more illegal space definitions, the candidate codevectors including line spectral frequencies (LSFs), wherein the one or more illegal space definitions define invalid spacing characteristics of LSFs; (b) deriving a separate error term corresponding to each legal candidate codevector, each error term being a function of the vector and the corresponding legal candidate codevector; (c) determining a best legal candidate codevector among the legal candidate codevectors based on the error terms, whereby the best legal candidate codevector corresponds to a quantization of the vector; and (d) transmitting to a decoder a signal representative of the portion of the speech or audio signal based on the best legal candidate codevector. 14. The method of claim 9 , wherein each candidate codevector is a composite codevector including a first component vector and a second component vector. | 0.741214 |
6. The method of claim 1 , further comprising searching the data structure by means of the dictionary which includes tokens by: comparing at least one of said tokens with one of a prefix and a suffix of an entry of said tree. | 6. The method of claim 1 , further comprising searching the data structure by means of the dictionary which includes tokens by: comparing at least one of said tokens with one of a prefix and a suffix of an entry of said tree. 8. The method of claim 6 , further comprising the step: determining if an entry of said tree is one of a prefix and a suffix of a token. | 0.914199 |
9. A method for rewriting a query during a database query processing operation, comprising the steps of: processing the query having one or more one or more target attributes in accordance with at least a portion of a data set producing query results comprising the one or more target attributes and one or more auxiliary attributes, wherein the one or more auxiliary attributes are not included in the query; comparing the query results to at least the portion of the data set to determine a relative selectivity for the one or more auxiliary attributes; and appending the query with at least one new predicate corresponding to at least one of the one or more auxiliary attributes having a high relative selectivity to form a rewritten query; wherein the step of appending the query with at least one new predicate comprises: selecting at least one of the one or more auxiliary attributes based at least in part on a ranking of the determined relative selectivity for the one or more auxiliary attributes; and appending the query with at least one new predicate corresponding to the selected at least one of the one or more auxiliary attributes to form the rewritten query. | 9. A method for rewriting a query during a database query processing operation, comprising the steps of: processing the query having one or more one or more target attributes in accordance with at least a portion of a data set producing query results comprising the one or more target attributes and one or more auxiliary attributes, wherein the one or more auxiliary attributes are not included in the query; comparing the query results to at least the portion of the data set to determine a relative selectivity for the one or more auxiliary attributes; and appending the query with at least one new predicate corresponding to at least one of the one or more auxiliary attributes having a high relative selectivity to form a rewritten query; wherein the step of appending the query with at least one new predicate comprises: selecting at least one of the one or more auxiliary attributes based at least in part on a ranking of the determined relative selectivity for the one or more auxiliary attributes; and appending the query with at least one new predicate corresponding to the selected at least one of the one or more auxiliary attributes to form the rewritten query. 16. The method of claim 9 , further comprising the step of performing a query processing operation on the data set with a rewritten query. | 0.63994 |
1. A method for a system implemented in a network and configured for providing data objects and search services to at least one individual, the method comprising: recording onto a computer readable storage medium, by the system within the network, artifacts representing accessing of chosen destinations throughout the network by different individuals having respective personal identities, each access of one of the chosen destinations by one of the individuals using any one of a plurality of available user devices being recorded within the network by the system as a corresponding artifact identifying the corresponding personal identity and the corresponding chosen destination, the chosen destinations reachable via the network, the network having multiple information sources, each information source providing at least one of the chosen destinations, the chosen destinations accessed by the individuals via the network from among the information sources including data objects and address identifiers for reaching identified individuals having respective personal identities; and updating a connection context, identifying relationships between the chosen destinations, as the respective artifacts are recorded, the updating including: (1) establishing a relationship between a corresponding first and second of the chosen destinations, accessed from among the information sources, based on determining a correlation between a first and a second of the artifacts, the first artifact recorded in response to a first of the individuals accessing the first of the chosen destinations using a first of the available user devices, the second artifact recorded in response to the first of the individuals accessing the second of the chosen destinations using a second of the available user devices that is different from the first of the available user devices, and (2) updating the relationship between the first and second chosen destinations based on subsequent artifacts, associated with the first and second chosen destinations, indicating selection by the individuals subsequent to the establishment of the corresponding relationship, the updating including increasing a strength of the relationship based on an aggregation of the artifacts and the subsequent artifacts from the individuals, the aggregation identifying an increase in the correlation associated with the first and second chosen destinations. | 1. A method for a system implemented in a network and configured for providing data objects and search services to at least one individual, the method comprising: recording onto a computer readable storage medium, by the system within the network, artifacts representing accessing of chosen destinations throughout the network by different individuals having respective personal identities, each access of one of the chosen destinations by one of the individuals using any one of a plurality of available user devices being recorded within the network by the system as a corresponding artifact identifying the corresponding personal identity and the corresponding chosen destination, the chosen destinations reachable via the network, the network having multiple information sources, each information source providing at least one of the chosen destinations, the chosen destinations accessed by the individuals via the network from among the information sources including data objects and address identifiers for reaching identified individuals having respective personal identities; and updating a connection context, identifying relationships between the chosen destinations, as the respective artifacts are recorded, the updating including: (1) establishing a relationship between a corresponding first and second of the chosen destinations, accessed from among the information sources, based on determining a correlation between a first and a second of the artifacts, the first artifact recorded in response to a first of the individuals accessing the first of the chosen destinations using a first of the available user devices, the second artifact recorded in response to the first of the individuals accessing the second of the chosen destinations using a second of the available user devices that is different from the first of the available user devices, and (2) updating the relationship between the first and second chosen destinations based on subsequent artifacts, associated with the first and second chosen destinations, indicating selection by the individuals subsequent to the establishment of the corresponding relationship, the updating including increasing a strength of the relationship based on an aggregation of the artifacts and the subsequent artifacts from the individuals, the aggregation identifying an increase in the correlation associated with the first and second chosen destinations. 6. The method of claim 1 , wherein the chosen destinations include at least one of a Voice over IP call destination, an e-mail message destination, a paging message destination, or an instant message destination. | 0.621975 |
1. A network storage system comprising: data storage that stores file data and metadata associated with the file data, the file data and metadata received from at least first and second computers each running a different operating system, with each different operating system defining a different file system, wherein each of the different file systems for the first and second computers stores file data and metadata associated with the file data in corresponding first and second different formats; one or more application program interfaces (APIs) in communication with the data storage that define operations for reading and writing the file data and metadata in the first and second different formats; and a metadata handler having a library of functions that handle at least the metadata in the first and second formats, the library of functions comprising a metadata object extraction function that accesses a metadata object having populated information corresponding to all metadata fields used by the first and second formats, the populated information being in a third format different from the first and second formats, extracts the populated information from the metadata object, and cooperates with at least one of the one or more APIs to generate at least a portion of the metadata in at least one of the first and second formats from the extracted populated information. | 1. A network storage system comprising: data storage that stores file data and metadata associated with the file data, the file data and metadata received from at least first and second computers each running a different operating system, with each different operating system defining a different file system, wherein each of the different file systems for the first and second computers stores file data and metadata associated with the file data in corresponding first and second different formats; one or more application program interfaces (APIs) in communication with the data storage that define operations for reading and writing the file data and metadata in the first and second different formats; and a metadata handler having a library of functions that handle at least the metadata in the first and second formats, the library of functions comprising a metadata object extraction function that accesses a metadata object having populated information corresponding to all metadata fields used by the first and second formats, the populated information being in a third format different from the first and second formats, extracts the populated information from the metadata object, and cooperates with at least one of the one or more APIs to generate at least a portion of the metadata in at least one of the first and second formats from the extracted populated information. 2. The system of claim 1 , wherein the first file system is different than the second file system. | 0.5163 |
47. The computer program of claim 20 , wherein selecting the matched data cluster from among one or more existing data clusters includes selecting the matched data cluster from among multiple candidate data clusters for which the selected data record satisfies a cluster membership criterion. | 47. The computer program of claim 20 , wherein selecting the matched data cluster from among one or more existing data clusters includes selecting the matched data cluster from among multiple candidate data clusters for which the selected data record satisfies a cluster membership criterion. 48. The computer program of claim 47 , further including instructions for causing a computing system to store information identifying one or more candidate data clusters that were not selected as the matched data cluster for the selected data record. | 0.928983 |
8. A computer-implemented method for separating speech of individual speakers in audio segments representing speech of a plurality of speakers, the method comprising: obtaining a plurality of audio segments, wherein each audio segment of the plurality of audio segments includes a representation of speech generated by a speaker of the plurality of speakers; computing a speaker model for each audio segment of the plurality of audio segments; computing a plurality of scores, wherein each score of the plurality of scores corresponds to a pair of speaker models, the plurality of scores comprising a first score and a second score, wherein: the first score is computed using a first speaker model corresponding to a first audio segment and a second speaker model corresponding to a second audio segment, and the second score is computed using a third speaker model corresponding to a third audio segment and a fourth speaker model corresponding to a fourth audio segment; generating a graph, wherein each audio segment of the plurality of audio segments corresponds to a node in the graph; determining to include an edge between a first node of the graph and a second node of the graph using the first score, wherein the first node corresponds to the first audio segment and the second node corresponds to the second audio segment; determining to not include an edge between a third node of the graph and a fourth node of the graph using the second score, wherein the third node corresponds to the third audio segment and the fourth node corresponds to the fourth audio segment; determining that the first node corresponds to a first community of nodes using edges connected to the first node, wherein the first community of nodes corresponds to a first speaker of the plurality of speakers; and determining that the second node corresponds to a second community of nodes using edges connected to the second node, wherein the second community of nodes corresponds to a second speaker of the plurality of speakers. | 8. A computer-implemented method for separating speech of individual speakers in audio segments representing speech of a plurality of speakers, the method comprising: obtaining a plurality of audio segments, wherein each audio segment of the plurality of audio segments includes a representation of speech generated by a speaker of the plurality of speakers; computing a speaker model for each audio segment of the plurality of audio segments; computing a plurality of scores, wherein each score of the plurality of scores corresponds to a pair of speaker models, the plurality of scores comprising a first score and a second score, wherein: the first score is computed using a first speaker model corresponding to a first audio segment and a second speaker model corresponding to a second audio segment, and the second score is computed using a third speaker model corresponding to a third audio segment and a fourth speaker model corresponding to a fourth audio segment; generating a graph, wherein each audio segment of the plurality of audio segments corresponds to a node in the graph; determining to include an edge between a first node of the graph and a second node of the graph using the first score, wherein the first node corresponds to the first audio segment and the second node corresponds to the second audio segment; determining to not include an edge between a third node of the graph and a fourth node of the graph using the second score, wherein the third node corresponds to the third audio segment and the fourth node corresponds to the fourth audio segment; determining that the first node corresponds to a first community of nodes using edges connected to the first node, wherein the first community of nodes corresponds to a first speaker of the plurality of speakers; and determining that the second node corresponds to a second community of nodes using edges connected to the second node, wherein the second community of nodes corresponds to a second speaker of the plurality of speakers. 14. The method of claim 8 , further comprising determining that the first node corresponds to the first community of nodes by using a graph modularity metric. | 0.560559 |
1. A setting apparatus comprising a caption setting unit for setting a timing of displaying text of speech in synchronization with reproduction of said speech, the text of said speech being predetermined, said caption setting unit comprising: a scenario data obtaining unit for obtaining scenario data representing content of said speech; a speech recognition unit for dividing textual data resulting from recognition of said speech being reproduced to generate a plurality of pieces of recognition data; a character string detection unit for detecting in said scenario data a character string that matches each of said plurality of pieces of recognition data; a character detection unit for detecting a character string that matches the recognition data from said scenario data by detecting a character contained in the recognition data for each recognition data with which said character string detection unit has detected no matching characters string; a display setting unit for setting the display timing of displaying each of the character strings contained in said scenario data to the timing at which speech recognized as a piece of recognition data that matches said character string is reproduce; and a reliability calculating unit for calculating a reliability factor that represents a likelihood that each of the plurality of pieces of recognition data matches one character string, wherein said display setting unit generates a setting that, if the calculated reliability factor associated with a first character string to be displayed in two successive character strings among the plurality of character strings in the scenario data is higher than the calculated reliability factor associated with a second character string to be displayed in the two successive character strings, causes a concatenated character string comprising said first character string with said second character string appended to said first character string to be displayed at a time point at which said first character string should be displayed. | 1. A setting apparatus comprising a caption setting unit for setting a timing of displaying text of speech in synchronization with reproduction of said speech, the text of said speech being predetermined, said caption setting unit comprising: a scenario data obtaining unit for obtaining scenario data representing content of said speech; a speech recognition unit for dividing textual data resulting from recognition of said speech being reproduced to generate a plurality of pieces of recognition data; a character string detection unit for detecting in said scenario data a character string that matches each of said plurality of pieces of recognition data; a character detection unit for detecting a character string that matches the recognition data from said scenario data by detecting a character contained in the recognition data for each recognition data with which said character string detection unit has detected no matching characters string; a display setting unit for setting the display timing of displaying each of the character strings contained in said scenario data to the timing at which speech recognized as a piece of recognition data that matches said character string is reproduce; and a reliability calculating unit for calculating a reliability factor that represents a likelihood that each of the plurality of pieces of recognition data matches one character string, wherein said display setting unit generates a setting that, if the calculated reliability factor associated with a first character string to be displayed in two successive character strings among the plurality of character strings in the scenario data is higher than the calculated reliability factor associated with a second character string to be displayed in the two successive character strings, causes a concatenated character string comprising said first character string with said second character string appended to said first character string to be displayed at a time point at which said first character string should be displayed. 8. The setting apparatus according to claim 1 , further comprising a phoneme detection unit for detecting in a phonetic representation of said scenario data a phoneme that matches a phoneme contained in a character in said recognition data for which no matching character has been detected by said character detection unit, wherein said character detection unit detects in said scenario data, as a character that matches a character in said recognition data for which a matching phoneme has been detected by said phoneme detection unit, a character containing said phoneme; and said reliability calculating unit produces a lower reliability for a piece of recognition data containing a character for which a matching phoneme has been detected by said phoneme detection unit than the reliability of a piece of recognition data containing a character for which no matching phoneme has been detected by said phoneme detection unit but for which a matching character has been detected by said character detection unit. | 0.5 |
1. A method of training an alert message response system, comprising: controlling, by a user, an alert response message application running on a first wireless communication device to enter into a training mode of operation during which it automatically initiates a routine that operates to play a training message which instructs the same user to enter a code in response to the training message into a second wireless communication device, and transmitting the code to the first wireless communication device from the second wireless communication device; wherein the second wireless communication device is in communication with the first wireless communication device over a short range wireless communication link; detecting, by the alert response message application running on the first wireless communication device, receipt of the response code and playing a training alert message on the first wireless communication device, the training alert message having content that is different than content in the training message; and responding, by the user of the second wireless communication device to the played training alert message, with an utterance that is received by the second wireless communication device and transmitted to the alert message response application running on the first wireless communication device over the short-range communication link, and storing the user utterance as an alert message training response in association with the response code. | 1. A method of training an alert message response system, comprising: controlling, by a user, an alert response message application running on a first wireless communication device to enter into a training mode of operation during which it automatically initiates a routine that operates to play a training message which instructs the same user to enter a code in response to the training message into a second wireless communication device, and transmitting the code to the first wireless communication device from the second wireless communication device; wherein the second wireless communication device is in communication with the first wireless communication device over a short range wireless communication link; detecting, by the alert response message application running on the first wireless communication device, receipt of the response code and playing a training alert message on the first wireless communication device, the training alert message having content that is different than content in the training message; and responding, by the user of the second wireless communication device to the played training alert message, with an utterance that is received by the second wireless communication device and transmitted to the alert message response application running on the first wireless communication device over the short-range communication link, and storing the user utterance as an alert message training response in association with the response code. 3. The method of claim 1 , wherein the second wireless communication device is only capable of establishing a short range wireless link. | 0.671034 |
14. A computer-implemented method, comprising evaluating, at a first computer system, an information source according to information retrieved by the first computer system from a search over social network defined by relationships between members of the social network, and filtering messages associated with said information source according to an evaluation of relationships of the members. | 14. A computer-implemented method, comprising evaluating, at a first computer system, an information source according to information retrieved by the first computer system from a search over social network defined by relationships between members of the social network, and filtering messages associated with said information source according to an evaluation of relationships of the members. 19. The method of claim 14 , wherein evaluating said information source includes evaluating connection strength between an individual identified as the information source and an intended recipient of a message. | 0.712082 |
14. The framework of claim 7 , wherein the business object operations are described in Remote Function Call transport protocol. | 14. The framework of claim 7 , wherein the business object operations are described in Remote Function Call transport protocol. 15. The framework of claim 14 , wherein the script contains parameters and values. | 0.971618 |
1. A controller-executed method for operating a query profiling system comprising: profiling database queries in a workload comprising: receiving a query set and a data definition language (DDL) model; extracting metadata of the DDL model; converting data definition elements of the metadata into a catalog of database objects; parsing queries corresponding to a workload to create a set of instances of query representations; binding table and column references in a query to a real table, view, or column object contained in the catalog; analyzing the queries for relevant attributes comprising complexity and number of predicates; and storing the attributes in a repository. | 1. A controller-executed method for operating a query profiling system comprising: profiling database queries in a workload comprising: receiving a query set and a data definition language (DDL) model; extracting metadata of the DDL model; converting data definition elements of the metadata into a catalog of database objects; parsing queries corresponding to a workload to create a set of instances of query representations; binding table and column references in a query to a real table, view, or column object contained in the catalog; analyzing the queries for relevant attributes comprising complexity and number of predicates; and storing the attributes in a repository. 7. The method according to claim 1 further comprising: extracting attributes for SELECT statements comprising columns contained in a list of columns contained in a select list, tables contained in a from list, restriction predicates, join predicates, group by columns, order by columns, and subqueries; and extracting attributes for DELETE, INSERT, and UPDATE statements comprising restriction predicates and subqueries. | 0.770697 |
16. The information handling system of claim 12 , wherein the set of instructions are executable to sort vectors V′k+1, . . . , V′k+b from the first concept vector set to identify one or more additional disruptive concepts based on a computed cosine distance from high to low to a normalized sum of vectors (VL 1 + . . . +VLh) from the second concept vector set. | 16. The information handling system of claim 12 , wherein the set of instructions are executable to sort vectors V′k+1, . . . , V′k+b from the first concept vector set to identify one or more additional disruptive concepts based on a computed cosine distance from high to low to a normalized sum of vectors (VL 1 + . . . +VLh) from the second concept vector set. 17. The information handling system of claim 16 , wherein the set of instructions are executable to generate a list of R 1 new concepts corresponding to R 1 sorted vectors V′k+1, . . . , V′k+b. | 0.900797 |
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