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8,335,344 | 10 | 14 | 10. A system for annotating an electronic document comprising: one or more processors configured to: embed annotation information into an electronic annotation object having image data including an annotation; and produce an electronic annotated document using information from the electronic document and the electronic annotation object, wherein said embedded information is used to select corresponding pixel values from one of the electronic annotated object and electronic document to be provided, to the electronic annotated document. | 10. A system for annotating an electronic document comprising: one or more processors configured to: embed annotation information into an electronic annotation object having image data including an annotation; and produce an electronic annotated document using information from the electronic document and the electronic annotation object, wherein said embedded information is used to select corresponding pixel values from one of the electronic annotated object and electronic document to be provided, to the electronic annotated document. 14. The system according to claim 10 , wherein the annotation is one of opaque and transparent annotation. | 0.775424 |
9,368,108 | 7 | 9 | 7. A speech recognition device, comprising: a receiver configured to receive speech; a memory configured to store instruction codes; and a processor, upon executing the instruction codes, configured to: acquire a text file; extract, according to a predetermined rule, a command word from the text file, and obtain a command word list; compare the command word list with a command word library, and confirm whether the command word list comprises a new command word, wherein the new command word is a command word that is comprised in the command word list but not comprised in the command word library; if it is determined that the command word list comprises a new command word, generate a corresponding new pronunciation dictionary according to the new command word and perform training to obtain a new language model, and merge the new language model into a language model library corresponding to the command word library; perform, according to an acoustic model, a phonation dictionary, and the merged language model library, speech recognition on the speech; after completing the speech recognition, determine whether a speech recognition result is a preset flag command word; if it is determined that the speech recognition result is a preset flag command word, acquire a text file corresponding to the preset flag command word; and if it is determined that the speech recognition result is not a preset flag command word, execute an operation. | 7. A speech recognition device, comprising: a receiver configured to receive speech; a memory configured to store instruction codes; and a processor, upon executing the instruction codes, configured to: acquire a text file; extract, according to a predetermined rule, a command word from the text file, and obtain a command word list; compare the command word list with a command word library, and confirm whether the command word list comprises a new command word, wherein the new command word is a command word that is comprised in the command word list but not comprised in the command word library; if it is determined that the command word list comprises a new command word, generate a corresponding new pronunciation dictionary according to the new command word and perform training to obtain a new language model, and merge the new language model into a language model library corresponding to the command word library; perform, according to an acoustic model, a phonation dictionary, and the merged language model library, speech recognition on the speech; after completing the speech recognition, determine whether a speech recognition result is a preset flag command word; if it is determined that the speech recognition result is a preset flag command word, acquire a text file corresponding to the preset flag command word; and if it is determined that the speech recognition result is not a preset flag command word, execute an operation. 9. The device according to claim 7 , wherein the processor is configured to: read content of the text file; perform word segmentation on the content; and select the command word from a word segmentation result according to the predetermined rule, to obtain the command word list. | 0.5 |
7,734,623 | 16 | 22 | 16. The method of claim 9 , further comprising: receiving a search string; identifying a second logical representation corresponding to said search string; locating said second logical representation within a knowledge base; retrieving a second set of possible interpretations from said knowledge base; and augmenting said second search string with one or more search string augmentations corresponding to said second set of possible interpretations. | 16. The method of claim 9 , further comprising: receiving a search string; identifying a second logical representation corresponding to said search string; locating said second logical representation within a knowledge base; retrieving a second set of possible interpretations from said knowledge base; and augmenting said second search string with one or more search string augmentations corresponding to said second set of possible interpretations. 22. The method of claim 16 , further comprising searching a database comprising said first document and utilizing said string augmentations to produce a set of search results identifying said first document. | 0.525229 |
9,740,696 | 1 | 9 | 1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, audio data from a client device; determining, by the one or more computers, specific content from captured media that matches the received audio data, wherein the captured media is captured from one or more media sources at a backend system and includes at least one of audio media or audio-video media, and wherein determining the specific content that matches the received audio data includes identifying an advertisement that is (i) included within the captured media and (ii) included within the media programming associated with the received audio data, wherein the captured media comprises a collection of audio fingerprints stored in an audio fingerprint repository, wherein each audio fingerprint is generated from at least a portion of an audio stream extracted from one or more monitored digital television broadcast channels; obtaining, by the one or more computers, additional information associated with the advertisement included within the media programming associated with the received audio data; generating, by the one or more computers, a search query based at least in part on the obtained additional information associated with the advertisement included within the media programming associated with the received audio data; and returning, by the one or more computers, one or more search results to the client device responsive to the search query. | 1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, audio data from a client device; determining, by the one or more computers, specific content from captured media that matches the received audio data, wherein the captured media is captured from one or more media sources at a backend system and includes at least one of audio media or audio-video media, and wherein determining the specific content that matches the received audio data includes identifying an advertisement that is (i) included within the captured media and (ii) included within the media programming associated with the received audio data, wherein the captured media comprises a collection of audio fingerprints stored in an audio fingerprint repository, wherein each audio fingerprint is generated from at least a portion of an audio stream extracted from one or more monitored digital television broadcast channels; obtaining, by the one or more computers, additional information associated with the advertisement included within the media programming associated with the received audio data; generating, by the one or more computers, a search query based at least in part on the obtained additional information associated with the advertisement included within the media programming associated with the received audio data; and returning, by the one or more computers, one or more search results to the client device responsive to the search query. 9. The method of claim 1 , wherein determining the specific content from the captured media that matches the received audio data comprises determining that at least a portion of the received audio data matches audio data of the advertisement. | 0.80261 |
9,032,289 | 10 | 13 | 10. The method of claim 1 , further comprising: receiving a request, from the particular user, for a ranked list of documents identified as needing comments; and providing the ranked list of documents, identified as needing comments, based on receiving the request. | 10. The method of claim 1 , further comprising: receiving a request, from the particular user, for a ranked list of documents identified as needing comments; and providing the ranked list of documents, identified as needing comments, based on receiving the request. 13. The method of claim 10 , further comprising: ranking documents, to form the ranked list of documents identified as needing comments, based on one or more subjective criteria associated with the particular user, where providing the ranked list of documents includes: providing the ranked list of documents to the particular user with a suggestion, to the particular user, to write a comment about one or more of the documents in the ranked list of documents. | 0.5 |
9,479,385 | 1 | 2 | 1. An apparatus comprising a server having a programmable processor coupled to a memory which can be any type of memory including RAM and a disk drive or disk array, said programmable processor also coupled to a communication interface for coupling to a data path such as the internet, operations of said programmable processor controlled by one or more computer programs, said one or more computer programs structured to control said server to prepare a non relational database file system storing performance metric data encoded in a manner suitable for searching by regular expression by performing the following steps: receiving, via said communications interface, a plurality of time series of performance metric data numerical values, each time series measured from an attribute of an instance of a resource type being monitored, each time series of performance metric data numerical values spanning an entire day and wherein each numerical value in a time series is collected during a timeslot during said day; mapping each and every time series of performance metric data numerical values to a time series of Unicode characters; encoding each Unicode character of each time series of Unicode characters into a digital representation that can be stored in said memory; and storing each digital representation of a Unicode character in a non relational database file system stored in said memory in a manner so as to preserve the temporal relationship between a location in said non relational database file system where each Unicode character is stored and the timeslot during which each said performance metric data numerical value said Unicode character represents was measured; and wherein said one or more computer programs are structured to control said programmable processor to implement a user interface which allows a user to specify a relevant interval and to compose a search query using a query definition language implemented by said one or more computer programs, said query definition language having syntax building blocks which allow said user to use a regular expression to specify filter or matching conditions for each search of said Unicode characters, and to specify an attribute for each search and to specify a resource type for each search, said syntax building blocks allowing a user to specify more than one search in a search query, and wherein said one or more computer programs further structured to control said programmable processor in accordance with said search query to retrieve from said non relational database file Unicode characters representing time series performance metric data numerical values collected during said relevant interval from one or more user specified attributes of one or more user specified resource types and carry out one or more searches using said one or more filter or matching conditions specified in said one or more regular expressions of said one or more searches. | 1. An apparatus comprising a server having a programmable processor coupled to a memory which can be any type of memory including RAM and a disk drive or disk array, said programmable processor also coupled to a communication interface for coupling to a data path such as the internet, operations of said programmable processor controlled by one or more computer programs, said one or more computer programs structured to control said server to prepare a non relational database file system storing performance metric data encoded in a manner suitable for searching by regular expression by performing the following steps: receiving, via said communications interface, a plurality of time series of performance metric data numerical values, each time series measured from an attribute of an instance of a resource type being monitored, each time series of performance metric data numerical values spanning an entire day and wherein each numerical value in a time series is collected during a timeslot during said day; mapping each and every time series of performance metric data numerical values to a time series of Unicode characters; encoding each Unicode character of each time series of Unicode characters into a digital representation that can be stored in said memory; and storing each digital representation of a Unicode character in a non relational database file system stored in said memory in a manner so as to preserve the temporal relationship between a location in said non relational database file system where each Unicode character is stored and the timeslot during which each said performance metric data numerical value said Unicode character represents was measured; and wherein said one or more computer programs are structured to control said programmable processor to implement a user interface which allows a user to specify a relevant interval and to compose a search query using a query definition language implemented by said one or more computer programs, said query definition language having syntax building blocks which allow said user to use a regular expression to specify filter or matching conditions for each search of said Unicode characters, and to specify an attribute for each search and to specify a resource type for each search, said syntax building blocks allowing a user to specify more than one search in a search query, and wherein said one or more computer programs further structured to control said programmable processor in accordance with said search query to retrieve from said non relational database file Unicode characters representing time series performance metric data numerical values collected during said relevant interval from one or more user specified attributes of one or more user specified resource types and carry out one or more searches using said one or more filter or matching conditions specified in said one or more regular expressions of said one or more searches. 2. The apparatus of claim 1 wherein said one or more computer programs are structured to control said programmable processor to carry out said step of storing said digital representations of Unicode characters in a manner so as to preserve metadata of each performance metric data numerical value in the structure itself of said non relational database file system, said metadata including the date and timeslot during which each performance metric data numerical value was measured or gathered, and the identities of the resource instance and attribute of said resource instance from which each performance metric data numerical value was measured or gathered. | 0.5 |
10,108,676 | 33 | 34 | 33. The system of claim 20 , further comprising: identifying one or more objects associated with the online social network, each of the identified object corresponding to at least a portion of the text string; accessing the grammar model, wherein the grammar model is a context-free grammar model comprising a plurality of grammars, each grammar comprising one or more tokens; and identifying one or more grammars, each identified grammar having one or more tokens corresponding to at least one of the identified objects. | 33. The system of claim 20 , further comprising: identifying one or more objects associated with the online social network, each of the identified object corresponding to at least a portion of the text string; accessing the grammar model, wherein the grammar model is a context-free grammar model comprising a plurality of grammars, each grammar comprising one or more tokens; and identifying one or more grammars, each identified grammar having one or more tokens corresponding to at least one of the identified objects. 34. The system of claim 33 , further comprising: determining a grammar score for each identified grammar; and wherein each suggested query in the set corresponds to an identified grammar having a grammar score greater than a grammar-threshold score, the suggested query being based on a string generated by the identified grammar, each suggested query comprising the tokens of the corresponding identified grammar, wherein one or more of the tokens of the suggested query corresponds to at least one of the identified objects. | 0.5 |
8,600,100 | 13 | 15 | 13. The method of claim 1 , wherein the stimulus comprises one or more of questions, statements, or scenarios. | 13. The method of claim 1 , wherein the stimulus comprises one or more of questions, statements, or scenarios. 15. The method of claim 13 , wherein the objective the individual is being assessed for is to determine potential romantic partners. | 0.707965 |
8,694,320 | 4 | 5 | 4. The method of claim 1 , wherein said processing the tag further comprises adding randomness. | 4. The method of claim 1 , wherein said processing the tag further comprises adding randomness. 5. The method of claim 4 , wherein said adding randomness is implemented by changes in the instructions, such that said changes vary at least one of manners or parameters, for generating the audio. | 0.5 |
10,163,440 | 1 | 19 | 1. A method for assisting a user with one or more desired tasks within a domain, the method comprising: receiving, by a computing system comprising one or more computing devices, a verbal language input and at least one of a plurality of different kinds of non-verbal input from the user; determining, by the computing system, from the verbal language input and the at least one of a plurality of different kinds of non-verbal input, an intention of the user with respect to the one or more desired tasks, by an executable generic language understanding module and a run-time specification comprising a model configured to a specific field of use; and performing, by the computing system, a domain-specific task in accordance with the intention of the user, by an executable generic task reasoning module and a run-time specification comprising a task flow configured to the specific field of use. | 1. A method for assisting a user with one or more desired tasks within a domain, the method comprising: receiving, by a computing system comprising one or more computing devices, a verbal language input and at least one of a plurality of different kinds of non-verbal input from the user; determining, by the computing system, from the verbal language input and the at least one of a plurality of different kinds of non-verbal input, an intention of the user with respect to the one or more desired tasks, by an executable generic language understanding module and a run-time specification comprising a model configured to a specific field of use; and performing, by the computing system, a domain-specific task in accordance with the intention of the user, by an executable generic task reasoning module and a run-time specification comprising a task flow configured to the specific field of use. 19. The method of claim 1 , wherein the desired tasks comprise at least one of: content search; content retrieval; and transaction completion. | 0.801676 |
7,493,247 | 5 | 7 | 5. A system according to claim 1 wherein said model checker engine includes means for determining whether a model checker-based trace is a reproduction of said ICUT-based trace. | 5. A system according to claim 1 wherein said model checker engine includes means for determining whether a model checker-based trace is a reproduction of said ICUT-based trace. 7. A system according to claim 5 wherein said model checker engine includes means responsive to said determination, for generating a new assertion, and for applying said new assertion to said Controller, and wherein said Controller includes means responsive to said applied new assertion for generating a new configuration signals and for applying said new configuration signals to said DL region of said ICUT. | 0.579918 |
8,504,908 | 9 | 11 | 9. A computer-implemented method according to claim 1 , wherein the method further comprises providing a user with computer-user interface means for reviewing extracted data concerning instances of entities. | 9. A computer-implemented method according to claim 1 , wherein the method further comprises providing a user with computer-user interface means for reviewing extracted data concerning instances of entities. 11. A computer-implemented method according to claim 9 , wherein the method further comprises providing a user with computer-user interface means operable to receive data concerning instances of entities which have been identified within the digital representation of a document by a curator, but are not specified by the extracted data. | 0.5 |
9,092,463 | 13 | 15 | 13. A system comprising: a network interface configured to receive structured data describing a content item, the structured data including one or more data elements comprising one or more descriptions and values for the one or more data elements, the structured data indicating a category for the content item; a data storage device storing stored data for the category, the stored data identifying one or more domains; a module configured to form a first query based on data elements in the structured data; a module configured to search at least one of the one or more of the domains using the first query to identify resources associated with the one or more domains; a module configured to determine one or more queries based on data reflecting past search queries, where each of the one or more queries resulted in one or more of the resources being returned as part of a search result; a module configured to determine keywords based on the one or more queries; a module configured to transmit or to store the keywords for use in impression allocation decisions; a module configured to determine an allocation score for the content item based at least in part on comparison of the keywords to a term associated with a request for an impression, where the allocation score is used to determine whether the content item will be selected for the impression; a module configured to select the content item for display in response to the request, based on the allocation score; and a network interface configured to transmit data specifying the content item in response to the request. | 13. A system comprising: a network interface configured to receive structured data describing a content item, the structured data including one or more data elements comprising one or more descriptions and values for the one or more data elements, the structured data indicating a category for the content item; a data storage device storing stored data for the category, the stored data identifying one or more domains; a module configured to form a first query based on data elements in the structured data; a module configured to search at least one of the one or more of the domains using the first query to identify resources associated with the one or more domains; a module configured to determine one or more queries based on data reflecting past search queries, where each of the one or more queries resulted in one or more of the resources being returned as part of a search result; a module configured to determine keywords based on the one or more queries; a module configured to transmit or to store the keywords for use in impression allocation decisions; a module configured to determine an allocation score for the content item based at least in part on comparison of the keywords to a term associated with a request for an impression, where the allocation score is used to determine whether the content item will be selected for the impression; a module configured to select the content item for display in response to the request, based on the allocation score; and a network interface configured to transmit data specifying the content item in response to the request. 15. The system of claim 13 , in which the resources are each assigned a score and only resources with scores better than a threshold score are used to determine the one or more queries. | 0.5 |
9,916,305 | 11 | 12 | 11. The system of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the system to: identify a sentence in the source language within the digital communication; and identify a first segment and a second segment within the sentence, wherein the first segment and the second segment each comprise a word or a phrase and the new term comprises the word or the phrase of the first segment. | 11. The system of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the system to: identify a sentence in the source language within the digital communication; and identify a first segment and a second segment within the sentence, wherein the first segment and the second segment each comprise a word or a phrase and the new term comprises the word or the phrase of the first segment. 12. The system of claim 11 , further comprising instructions that, when executed by the at least one processor, cause the system to: identify an additional term based on the second segment; create a third hashkey based on the additional term, the source language, and the target language; and locate a translation of the additional term using the third hashkey. | 0.5 |
9,092,416 | 18 | 21 | 18. The method of claim 1 further comprising receiving a quotation search request that includes a query, and determining whether the quotation matches the query. | 18. The method of claim 1 further comprising receiving a quotation search request that includes a query, and determining whether the quotation matches the query. 21. The method of claim 18 wherein the query specifies a subject by including at least one of: an entity reference, a facet reference, one or more keyterms, and/or any subject. | 0.707641 |
8,386,241 | 8 | 13 | 8. An automated dictionary system, useful in association with a personal appliance including at least one dictionary which contains entries, the automated dictionary system comprising: a retriever configured to retrieve a message containing words, wherein the message is received by the personal appliance; a message parser configured to parse the words of the text message; a dictionary comparator configured to compare the parsed words to the entries of the at least one dictionary, wherein the dictionary comparer is further configured to identify new words of the parsed words which are not found within the at least one dictionary; a statistical analyzer configured to generate statistical information for the parsed words; a phrase group identifier configured to identify phrases from the parsed words by identifying phrase markers, wherein the phrase markers include at least one of italicized word groups, quoted word groups, bolded word groups, capitalized word groups, and word groups containing more than one new word, said phrase group identifier further configured to apply semantic rules to identify phrases from the parsed words by identifying word groups that include joining words and further comprising a linker configured to link the words of the identified phrases; and a word storage moderator configured to store the new words within at least one of the at least one dictionary, wherein the storing the new words enables recall of the new words for generating a candidate word list, and wherein the word storage moderator is further configured to store the linkage of the words of the identified phrases with additional information that allows them to remain linked without storing the entire identified phrases. | 8. An automated dictionary system, useful in association with a personal appliance including at least one dictionary which contains entries, the automated dictionary system comprising: a retriever configured to retrieve a message containing words, wherein the message is received by the personal appliance; a message parser configured to parse the words of the text message; a dictionary comparator configured to compare the parsed words to the entries of the at least one dictionary, wherein the dictionary comparer is further configured to identify new words of the parsed words which are not found within the at least one dictionary; a statistical analyzer configured to generate statistical information for the parsed words; a phrase group identifier configured to identify phrases from the parsed words by identifying phrase markers, wherein the phrase markers include at least one of italicized word groups, quoted word groups, bolded word groups, capitalized word groups, and word groups containing more than one new word, said phrase group identifier further configured to apply semantic rules to identify phrases from the parsed words by identifying word groups that include joining words and further comprising a linker configured to link the words of the identified phrases; and a word storage moderator configured to store the new words within at least one of the at least one dictionary, wherein the storing the new words enables recall of the new words for generating a candidate word list, and wherein the word storage moderator is further configured to store the linkage of the words of the identified phrases with additional information that allows them to remain linked without storing the entire identified phrases. 13. The automated dictionary system of claim 8 , wherein the retriever is configured to initiate retrieval when a user accesses the received message. | 0.908813 |
9,727,663 | 1 | 2 | 1. A method, comprising: receiving a portion of a natural language query of a data store; generating, based at least in part on the portion of the natural language query, a prediction of a plurality of phrases identifying a service component metric of an information technology (IT) system, a service component log of the IT system, or a service component event of the IT system, wherein generating comprises: identifying an outlier indicator for the service component metric, the service component log, or the service component event, wherein the outlier indicator indicates irregular behavior specifically by the service component metric, the service component log, or the service component event that exceeds or falls below a baseline standard; and including the service component metric, the service component log, or the service component event with the outlier indicator in at least one of the plurality of phrases; sorting the predicted plurality of phrases to order the service component metric, the service component log, or the service component event with the outlier indicator earlier in a sort order than other service component metrics, service component logs, or service component events without the outlier indicator; proposing the sorted predicted plurality of phrases for completing the natural language query; and receiving a selection of a proposed predicted phrase of the proposed predicted plurality of phrases. | 1. A method, comprising: receiving a portion of a natural language query of a data store; generating, based at least in part on the portion of the natural language query, a prediction of a plurality of phrases identifying a service component metric of an information technology (IT) system, a service component log of the IT system, or a service component event of the IT system, wherein generating comprises: identifying an outlier indicator for the service component metric, the service component log, or the service component event, wherein the outlier indicator indicates irregular behavior specifically by the service component metric, the service component log, or the service component event that exceeds or falls below a baseline standard; and including the service component metric, the service component log, or the service component event with the outlier indicator in at least one of the plurality of phrases; sorting the predicted plurality of phrases to order the service component metric, the service component log, or the service component event with the outlier indicator earlier in a sort order than other service component metrics, service component logs, or service component events without the outlier indicator; proposing the sorted predicted plurality of phrases for completing the natural language query; and receiving a selection of a proposed predicted phrase of the proposed predicted plurality of phrases. 2. The method of claim 1 , wherein the predicted plurality of phrases include a key attribute indicating keyword followed by a key attribute identifying an instance of a service component metric, a service component log, or a service component event included in the data store. | 0.820596 |
7,774,354 | 4 | 8 | 4. The method of claim 1 further comprising: tracking changes to the data in the database in a modification list, wherein the changes have not been made to the cached data in the particular materialized view, rewriting the new query, and executing the rewritten query such that the relevant changes to the data in the database are included in the result of the new query. | 4. The method of claim 1 further comprising: tracking changes to the data in the database in a modification list, wherein the changes have not been made to the cached data in the particular materialized view, rewriting the new query, and executing the rewritten query such that the relevant changes to the data in the database are included in the result of the new query. 8. The method of claim 4 wherein the number of changes taken into account by the rewritten query is reduced from the total number of changes that have occurred in the database, wherein the reduced number of changes is determined by considering only changes of data that match a predetermined particular property of the new query. | 0.539216 |
9,268,694 | 18 | 19 | 18. The method of claim 11 , further comprising writing an entry to the second cache based on entries in the first cache. | 18. The method of claim 11 , further comprising writing an entry to the second cache based on entries in the first cache. 19. The method of claim 18 , further comprising: locating entries in the first and second logical portions having a common second address domain; and writing the entry to the second cache based on the located entries in the first and second logical portions. | 0.5 |
8,713,054 | 1 | 4 | 1. A computer implemented method to automate an overall document classification mark determination for information of an electronic document in accordance with an information security classification process, said method comprising: a. executing on at least one computer system, b. establishing an electronic document security regimen comprising of at least one criterion of an information security classification process, c. establishing a hierarchal algorithm associated with said at least one criterion of said electronic document security regimen, d. establishing an overall document mark for information of an electronic document from said hierarchal algorithm, where said hierarchal algorithm uses at least one classification mark existing for at least one informational portion of said electronic document, and e. inserting said overall document mark into said electronic document. | 1. A computer implemented method to automate an overall document classification mark determination for information of an electronic document in accordance with an information security classification process, said method comprising: a. executing on at least one computer system, b. establishing an electronic document security regimen comprising of at least one criterion of an information security classification process, c. establishing a hierarchal algorithm associated with said at least one criterion of said electronic document security regimen, d. establishing an overall document mark for information of an electronic document from said hierarchal algorithm, where said hierarchal algorithm uses at least one classification mark existing for at least one informational portion of said electronic document, and e. inserting said overall document mark into said electronic document. 4. The method of claim 1 , further comprising: a. identifying a change to said electronic document, b. re-establishing said overall document mark for said electronic document, and c. re-inserting said overall document mark in said electronic document. | 0.690123 |
10,152,556 | 7 | 11 | 7. A method for updating an ontology in a database, the method comprising: scanning, by a semantic modeling platform, one or more databases to determine when at least one of the one or more databases is ready to update; receiving, by the semantic modeling platform, an indication for updating at least one of the one or more databases to accommodate data, when the determination indicates that the at least one of the one or more databases is ready to update; parsing, by the semantic modeling platform, a first ontology associated with at least one table in the at least one of the one or more databases; creating, by the semantic modeling platform, a second ontology that describes the data to is accommodated; mapping, by the semantic modeling platform, the parsed first ontology on to the created second ontology; analyzing, by the semantic modeling platform, the mapping of the first ontology on to the created second ontology; determining, by the semantic modeling platform, one or more differences between the first and the second ontologies based on the analyzing; recommending, by the semantic modeling platform, one or more changes to the second ontology based on the determined one or more differences between the first and the second ontologies; and updating, by the semantic modeling platform, the created second ontology based on the recommended one or more changes to the second ontology. | 7. A method for updating an ontology in a database, the method comprising: scanning, by a semantic modeling platform, one or more databases to determine when at least one of the one or more databases is ready to update; receiving, by the semantic modeling platform, an indication for updating at least one of the one or more databases to accommodate data, when the determination indicates that the at least one of the one or more databases is ready to update; parsing, by the semantic modeling platform, a first ontology associated with at least one table in the at least one of the one or more databases; creating, by the semantic modeling platform, a second ontology that describes the data to is accommodated; mapping, by the semantic modeling platform, the parsed first ontology on to the created second ontology; analyzing, by the semantic modeling platform, the mapping of the first ontology on to the created second ontology; determining, by the semantic modeling platform, one or more differences between the first and the second ontologies based on the analyzing; recommending, by the semantic modeling platform, one or more changes to the second ontology based on the determined one or more differences between the first and the second ontologies; and updating, by the semantic modeling platform, the created second ontology based on the recommended one or more changes to the second ontology. 11. The method of claim 7 , further comprising: receiving, by the semantic modeling platform, an input indicating one or more web services are updated to accommodate data; parsing, by the semantic modeling platform, a first ontology associated with at least one of the one or more web services; creating, by the semantic modeling platform, a second ontology that describes the data based on the first XSD file; mapping, by the semantic modeling platform, the parsed first ontology on to the created second ontology; determining, by the semantic modeling platform, one or more differences between the first and the second ontologies; updating, by the semantic modeling platform, the created second ontology based on the determined differences between the first and the second ontologies; and exporting, by the semantic modeling platform, the updated ontology to a data modeler that creates and utilizes a second XSD file to modify the one or more web services or create a new web service. | 0.535311 |
9,122,727 | 1 | 4 | 1. A method comprising: identifying a respective ordered list of search result documents for each query in a plurality of queries; identifying: a given query in the plurality of queries; a first and second grouping in the ordered list for the given query; and a first and second grouping in the ordered list for each of the remaining queries in the plurality of queries; determining non-overlap scores between the given query and each of the remaining queries in the plurality of queries, wherein the non-overlap scores measure dissimilarities between the search result documents within the first grouping in the ordered list for the given query and the first grouping in the ordered list for each of the remaining queries in the plurality of queries; selecting one or more candidate queries from the remaining queries in the plurality of queries based on the non-overlap scores; determining overlap scores between the given query and each of the candidate queries, wherein the overlap scores measure similarities between the search result documents within the second grouping in the ordered list for the given query and the second grouping in the ordered list for each of the candidate queries; selecting one or more related queries from the candidate queries based on the overlap scores; and storing data associating the related queries with the given query. | 1. A method comprising: identifying a respective ordered list of search result documents for each query in a plurality of queries; identifying: a given query in the plurality of queries; a first and second grouping in the ordered list for the given query; and a first and second grouping in the ordered list for each of the remaining queries in the plurality of queries; determining non-overlap scores between the given query and each of the remaining queries in the plurality of queries, wherein the non-overlap scores measure dissimilarities between the search result documents within the first grouping in the ordered list for the given query and the first grouping in the ordered list for each of the remaining queries in the plurality of queries; selecting one or more candidate queries from the remaining queries in the plurality of queries based on the non-overlap scores; determining overlap scores between the given query and each of the candidate queries, wherein the overlap scores measure similarities between the search result documents within the second grouping in the ordered list for the given query and the second grouping in the ordered list for each of the candidate queries; selecting one or more related queries from the candidate queries based on the overlap scores; and storing data associating the related queries with the given query. 4. The method of claim 1 , wherein: the non-overlap scores are determined based on both the comparison of the search result documents within the respective first groupings and on similarity scores between the search result documents within the respective first groupings. | 0.624654 |
9,767,357 | 17 | 18 | 17. The non-transitory computer-readable storage medium of claim 16 , wherein the review set is determined based on a sampling rate. | 17. The non-transitory computer-readable storage medium of claim 16 , wherein the review set is determined based on a sampling rate. 18. The non-transitory computer-readable storage medium of claim 17 , wherein the method further comprises receiving a sampling rate selection from a user. | 0.5 |
9,098,635 | 29 | 32 | 29. A computer program product that includes a non-transitory computer readable storage medium, the computer readable medium comprising a plurality of computer instructions which, when executed by a processor, cause the processor to execute performing a process for testing a user interface to a software application, the process comprising: extending a hardware verification language by defining one or more custom libraries such that the extended hardware verification language can be used to interface with the user interface to the software application in addition to hardware designs, wherein the hardware verification language is different from a programming language used to create the user interface to the software application, and is a programming language specifically designed for verification of hardware designs, and wherein the extended hardware verification language is extended by providing an API (applications programming interface) corresponding to the e language; generating a test for the user interface to the software application written in the extended hardware verification language; using the test written in the extended hardware verification language to drive one or more elements of the user interface to the software application; collecting data resulting from driving the user interface to the software application using the test; analyzing the data from driving the user interface to the software application; and displaying analysis results or storing the analysis results in a computer readable medium. | 29. A computer program product that includes a non-transitory computer readable storage medium, the computer readable medium comprising a plurality of computer instructions which, when executed by a processor, cause the processor to execute performing a process for testing a user interface to a software application, the process comprising: extending a hardware verification language by defining one or more custom libraries such that the extended hardware verification language can be used to interface with the user interface to the software application in addition to hardware designs, wherein the hardware verification language is different from a programming language used to create the user interface to the software application, and is a programming language specifically designed for verification of hardware designs, and wherein the extended hardware verification language is extended by providing an API (applications programming interface) corresponding to the e language; generating a test for the user interface to the software application written in the extended hardware verification language; using the test written in the extended hardware verification language to drive one or more elements of the user interface to the software application; collecting data resulting from driving the user interface to the software application using the test; analyzing the data from driving the user interface to the software application; and displaying analysis results or storing the analysis results in a computer readable medium. 32. The computer program product of claim 29 further comprising performing regression testing upon the user interface to the software application. | 0.5 |
5,559,969 | 2 | 3 | 2. An improvement according to claim 1 wherein the first bus operates at a higher frequency than the second bus. | 2. An improvement according to claim 1 wherein the first bus operates at a higher frequency than the second bus. 3. An improvement according to claim 2 wherein the first bus operates at twice the frequency of the second bus. | 0.5 |
4,829,472 | 1 | 8 | 1. In an apparatus having a keyboard for generating keystroke data and keystroke control signals, and a data processor for receiving said keystroke data and keystroke control signals, said keyboard having a keyboard connector with a plurality of contacts, and said data processor having a data processor connector with a plurality of contacts, wherein said keyboard connector and said data processor connector are normally interconnected for conducting keystroke data and control signals between the keyboard and the data processor, an improvement comprising: a spelling check module having first and second connectors interposed between said keyboard connector and said data processor connector, said first connector being connected to said keyboard connector, and said second connector being connected to said data processor connector. | 1. In an apparatus having a keyboard for generating keystroke data and keystroke control signals, and a data processor for receiving said keystroke data and keystroke control signals, said keyboard having a keyboard connector with a plurality of contacts, and said data processor having a data processor connector with a plurality of contacts, wherein said keyboard connector and said data processor connector are normally interconnected for conducting keystroke data and control signals between the keyboard and the data processor, an improvement comprising: a spelling check module having first and second connectors interposed between said keyboard connector and said data processor connector, said first connector being connected to said keyboard connector, and said second connector being connected to said data processor connector. 8. A spelling check module in accordance with claim 1 further comprising: control means connected to said plurality of contacts of said keyboard connector for transferring received signals to said plurality of contacts of said data processor connector; said control means also connected to said plurality of contacts of said data processor connector for transferring received signals to said plurality of contacts of said keyboard connector; said control means further including register means connected to said plurality of conductors of said keyboard connector, wherein said plurality of conductors of said keyboard connector conduct signals representing successive keystroke data in digital form, said register means including means for accumulating successive alphanumeric keystroke data; dictionary means containing a plurality of codes in digital form corresponding to correctly spelled words; said control means further includes means responsive to said register means and said plurality of connecting means for detecting a typed word, and responsive to said dictionary means for comparing said detected typed word to the digitally coded contents of said dictionary means and for providing a first output indication corresponding to whether said dictionary means does not contain a digital code corresponding to said detected typed word; and indicator means responsive to said first output indication from said control means for indicating that said detected typed word is misspelled. | 0.5 |
8,996,528 | 16 | 17 | 16. A method for relational analysis of data, comprising: (a) receiving a data set comprising a plurality of interrelated data objects each having at least one type of data associated with a plurality of latent classes, and having at least one of respective data object attributes, homogeneous relations between the respective data object and data objects having the same type, and heterogeneous relations between the respective data object and data objects having different types; (b) generating latent indicators for the plurality of interrelated data objects, comprising respective latent class membership parameters, based on at least the respective data object attributes, available homogeneous relations between the respective data object and data objects having the same type, and available heterogeneous relations between the respective data object and data objects having different types, wherein the latent indicators have respective latent class membership parameters generated based on a distribution selected from the group consisting of: a multinomial distribution; a Bernoulli distribution; a normal distribution; and an exponential distribution; (c) optimizing a probabilistic function comprising a mixed membership relational clustering model which estimates a joint probability distribution over the generated latent indicators of the data set and observations of the respective data object attributes; (d) clustering the data set with at least one automated processor, using the optimized probabilistic function, based on at least the data object attributes, the homogeneous relations and the heterogeneous relations; and (d) storing information representing the clustering of the plurality of the data set. | 16. A method for relational analysis of data, comprising: (a) receiving a data set comprising a plurality of interrelated data objects each having at least one type of data associated with a plurality of latent classes, and having at least one of respective data object attributes, homogeneous relations between the respective data object and data objects having the same type, and heterogeneous relations between the respective data object and data objects having different types; (b) generating latent indicators for the plurality of interrelated data objects, comprising respective latent class membership parameters, based on at least the respective data object attributes, available homogeneous relations between the respective data object and data objects having the same type, and available heterogeneous relations between the respective data object and data objects having different types, wherein the latent indicators have respective latent class membership parameters generated based on a distribution selected from the group consisting of: a multinomial distribution; a Bernoulli distribution; a normal distribution; and an exponential distribution; (c) optimizing a probabilistic function comprising a mixed membership relational clustering model which estimates a joint probability distribution over the generated latent indicators of the data set and observations of the respective data object attributes; (d) clustering the data set with at least one automated processor, using the optimized probabilistic function, based on at least the data object attributes, the homogeneous relations and the heterogeneous relations; and (d) storing information representing the clustering of the plurality of the data set. 17. The method according to claim 16 , wherein said optimizing comprises initializing the probabilistic function and computing a posterior function:
Pr ({C (j) }|F (j) } j=1 m , {S (j) } j=1 m , {R (ij) } i,j=1 m , {tilde over (Ω)}), wherein: the input data set represented as a set of exponential family distributions {{F (j) } j=1 m , {S (j) } j=1 m , {R (ij) } i,j=1 m }; the initial estimate of a set of matrices is {tilde over (Ω)} the membership matrices are {Λ (j) } j=1 m , the attribute matrices are F (j) , the attribute expectation matrices are {Θ (j) } j=1 m the homogeneous relation matrices are S (j) the homogeneous relation expectation matrices are {Γ (j) } j=1 m , the heterogeneous relation matrices are R (ij) , the heterogeneous relation expectation matrices are {Υ (ij) } i,j=1 m C (j) is a cluster indicator matrix, Λ (j) is computed using Λ hp (1) =Pr(C hp (1) =1|F,S,R,{tilde over (Ω)}), Θ ( j ) is computed using Θ · g = ∑ p = 1 n 1 F · p Pr ( C gp ( 1 ) = 1 ❘ F , S , R , Ω ~ ) ∑ p = 1 n 1 Pr ( C gp ( 1 ) = 1 ❘ F , S , R , Ω ~ ) , Γ ( j ) is computed using Γ gh = ∑ p , q = 1 n 1 S pq Pr ( C gp ( 1 ) = 1 , C hq ( 1 ) = 1 ❘ F , S , R , Ω ~ ) ∑ p , q = 1 n 1 Pr ( C gp ( 1 ) = 1 , C hq ( 1 ) = 1 ❘ F , S , R , Ω ~ ) , Υ ( ij ) is computed using Υ gh = ∑ p = 1 n 1 ∑ q = 1 n 2 R pq Pr ( C gp ( 1 ) = 1 , C hq ( 2 ) = 1 ❘ F , S , R , Ω ~ ) ∑ p = 1 n 1 ∑ q = 1 n 2 Pr ( C gp ( 1 ) = 1 , C hq ( 2 ) = 1 ❘ F , S , R , Ω ~ ) ; and wherein the probabilistic function is maximized by iteratively updating {tilde over (Ω)}=Ω over the range of i and j, until convergence is achieved. | 0.536108 |
8,200,657 | 9 | 11 | 9. A computer readable medium including program instructions implemented by a computer, the program instructions for searching for data in a database, the program instructions implementing steps comprising: receiving a query that is a request for data in the database, wherein the query includes at least one uneven non-Boolean term condition including an OR condition that spans at least two tables of the database, wherein the OR condition includes two predicates; splitting the at least one uneven non-Boolean term condition into a plurality of separate query portions that each provide a Boolean term satisfied by accessing a different particular one of the at least two tables, wherein each predicate is provided to a different one of the separate query portions; executing the separate query portions independently of each other to find at least one data result in each of the at least two tables that satisfies the Boolean term of each separate query portion; identifying at least one bridge table, wherein the at least one bridge table does not satisfy the at least one uneven non-Boolean term condition and has at least one column from each of the at least two tables; and combining the data results from each separate query portion into a final result that satisfies the query, wherein the at least one bridge table is used to join each of the at least two tables to combine the data results. | 9. A computer readable medium including program instructions implemented by a computer, the program instructions for searching for data in a database, the program instructions implementing steps comprising: receiving a query that is a request for data in the database, wherein the query includes at least one uneven non-Boolean term condition including an OR condition that spans at least two tables of the database, wherein the OR condition includes two predicates; splitting the at least one uneven non-Boolean term condition into a plurality of separate query portions that each provide a Boolean term satisfied by accessing a different particular one of the at least two tables, wherein each predicate is provided to a different one of the separate query portions; executing the separate query portions independently of each other to find at least one data result in each of the at least two tables that satisfies the Boolean term of each separate query portion; identifying at least one bridge table, wherein the at least one bridge table does not satisfy the at least one uneven non-Boolean term condition and has at least one column from each of the at least two tables; and combining the data results from each separate query portion into a final result that satisfies the query, wherein the at least one bridge table is used to join each of the at least two tables to combine the data results. 11. The computer readable medium of claim 9 further comprising rewriting the query before splitting the non-Boolean term conditions into separate query portions, such that the number of separate portions needed to be executed is reduced. | 0.668067 |
8,370,352 | 1 | 5 | 1. A system for searching one or more electronic records and displaying relevant data based on the search, the system comprising: a processor; and one or more non-transitory program storage devices readable by the processor, tangibly embodying a searching unit, a visual interface and a statistical analyzer executable by the processor, wherein the searching unit is configured to search for text in the one or more electronic records that are within a context of an entered query string, wherein the context is influenced by text that precedes or follows an instance of the entered query string in the one or more electronic records wherein a context type describes a structure in which the instance of the entered query string may be presented in the one or more electronic records, wherein the context type comprises at least a phrasal context, a bullet context, or a list context, wherein the statistical analyzer is configured to analyze results of the search, provide search statistics, and order the results associated with the entered query string based on the search statistics and the context of the entered query string, and wherein the visual interface is configured to display the search statistics and the results of the search presented in the structure corresponding to the context type. | 1. A system for searching one or more electronic records and displaying relevant data based on the search, the system comprising: a processor; and one or more non-transitory program storage devices readable by the processor, tangibly embodying a searching unit, a visual interface and a statistical analyzer executable by the processor, wherein the searching unit is configured to search for text in the one or more electronic records that are within a context of an entered query string, wherein the context is influenced by text that precedes or follows an instance of the entered query string in the one or more electronic records wherein a context type describes a structure in which the instance of the entered query string may be presented in the one or more electronic records, wherein the context type comprises at least a phrasal context, a bullet context, or a list context, wherein the statistical analyzer is configured to analyze results of the search, provide search statistics, and order the results associated with the entered query string based on the search statistics and the context of the entered query string, and wherein the visual interface is configured to display the search statistics and the results of the search presented in the structure corresponding to the context type. 5. The system of claim 1 , wherein the one or more electronic records comprise one of a medical, financial, or legal record. | 0.798046 |
10,042,927 | 26 | 34 | 26. One or more non-transitory computer readable storage media storing computer-executable instructions for performing a computer process, the computer process comprising: receiving a request by a client device to access a first content that is not available from a first Web domain; identifying at least one interest keyword based on a combination of keywords that yield search results including the first Web domain and a user's clickstream data responsive to the search results; classifying the first content that is not available based on the at least one interest keyword; identifying a second web domain based on historical relevance data and the classification of the first content that is not available, the historical relevance data including one or more previous attempts to access the first Web domain and session data representing activity performed with respect to the first Web domain; and providing the user access to second content similar to the first content from the second Web domain using the identified at least one keyword. | 26. One or more non-transitory computer readable storage media storing computer-executable instructions for performing a computer process, the computer process comprising: receiving a request by a client device to access a first content that is not available from a first Web domain; identifying at least one interest keyword based on a combination of keywords that yield search results including the first Web domain and a user's clickstream data responsive to the search results; classifying the first content that is not available based on the at least one interest keyword; identifying a second web domain based on historical relevance data and the classification of the first content that is not available, the historical relevance data including one or more previous attempts to access the first Web domain and session data representing activity performed with respect to the first Web domain; and providing the user access to second content similar to the first content from the second Web domain using the identified at least one keyword. 34. The one or more computer readable storage media of claim 26 , wherein the second content of the second Web domain is a product offer that is determined to be relevant to the at least one interest keyword. | 0.780591 |
9,189,069 | 1 | 4 | 1. A method comprising: receiving a sensor signal, from at least one sensor of a mobile device, indicating a rapid linear acceleration of the mobile device upon which the mobile device experiences a bulk translation in a substantially linear direction; determining that a flinging gesture has been made with the mobile device, as if a user is throwing the mobile device, by utilizing the sensor signal to distinguish the linear acceleration of the mobile device from a tilting of the mobile device and a shaking of the mobile device; interpreting, using the mobile device, the flinging gesture as a request to dismiss a displayed window on a display of the mobile device; and dismissing the displayed window on the display in response to the request to dismiss. | 1. A method comprising: receiving a sensor signal, from at least one sensor of a mobile device, indicating a rapid linear acceleration of the mobile device upon which the mobile device experiences a bulk translation in a substantially linear direction; determining that a flinging gesture has been made with the mobile device, as if a user is throwing the mobile device, by utilizing the sensor signal to distinguish the linear acceleration of the mobile device from a tilting of the mobile device and a shaking of the mobile device; interpreting, using the mobile device, the flinging gesture as a request to dismiss a displayed window on a display of the mobile device; and dismissing the displayed window on the display in response to the request to dismiss. 4. The method of claim 1 , and further comprising obtaining, using the at least one sensor. a value indicative of movement in the linear direction that the mobile device experiences during the flinging gesture. | 0.5 |
9,063,932 | 8 | 10 | 8. A method of managing electronic documents shared across networked satellite nodes remotely located from one another, the method comprising: storing a first plurality of electronic documents in a common electronic document repository, wherein the first plurality of electronic documents includes electronic documents owned by at least two different owners remotely located from one another; storing ownership information at a master node for the first plurality of electronic documents stored in the common electronic document repository, wherein the ownership information indicates that at least one of the electronic documents of the first plurality of electronic documents is owned by a first owner of the at least two different owners and at least one of the electronic documents of the first plurality of electronic documents is owned by a second owner of the at least two different owners, the second owner different from and remotely located with respect to the first owner; storing ownership information at the master node for a second plurality of electronic documents which are locally stored by at least one satellite node at a respective location remote from the common electronic document repository, wherein the ownership information stored at the master node for the first and the second plurality of electronic documents indicates for each electronic document a logical entity that has authority to authorize changes to the respective electronic document; and providing at least one satellite node with access to at least one electronic document that is stored locally by another satellite node. | 8. A method of managing electronic documents shared across networked satellite nodes remotely located from one another, the method comprising: storing a first plurality of electronic documents in a common electronic document repository, wherein the first plurality of electronic documents includes electronic documents owned by at least two different owners remotely located from one another; storing ownership information at a master node for the first plurality of electronic documents stored in the common electronic document repository, wherein the ownership information indicates that at least one of the electronic documents of the first plurality of electronic documents is owned by a first owner of the at least two different owners and at least one of the electronic documents of the first plurality of electronic documents is owned by a second owner of the at least two different owners, the second owner different from and remotely located with respect to the first owner; storing ownership information at the master node for a second plurality of electronic documents which are locally stored by at least one satellite node at a respective location remote from the common electronic document repository, wherein the ownership information stored at the master node for the first and the second plurality of electronic documents indicates for each electronic document a logical entity that has authority to authorize changes to the respective electronic document; and providing at least one satellite node with access to at least one electronic document that is stored locally by another satellite node. 10. The method of claim 8 wherein storing a first plurality of electronic documents in a common electronic document repository includes replicating at least one change to at least one of the electronic documents from at least one of the networked satellite nodes to the common electronic document repository. | 0.5 |
9,218,107 | 1 | 2 | 1. A method for managing text in cross-platform display, the method comprising: receiving data sent over a communication network from a host device, the data including information regarding a display of the host device; executing instructions stored in memory, wherein execution of instructions by a processor: identifies that a window associated with a display of the host device has been opened, wherein the opening of the window automatically activates a text caret in the opened window, the identification based on the received data, determines that the text caret has been activated, wherein activation of the text caret initiates display of a keyboard in a portion of a display of a client device, and generates instructions for automatic adjustment of the opened window in a remaining portion of the display of the client device, the automatic adjustment based on a location of the active text caret in the opened window, wherein the automatic adjustment comprises zooming in on the text caret that was automatically activated by the opening of the window in the display of the host device; and sending the generated instructions over the communication network to the client device, wherein execution of the instructions by the client device results in the automatic adjustment of the opened window in the client device with respect to the remaining portion of the display of the client device based on the location of the active text caret. | 1. A method for managing text in cross-platform display, the method comprising: receiving data sent over a communication network from a host device, the data including information regarding a display of the host device; executing instructions stored in memory, wherein execution of instructions by a processor: identifies that a window associated with a display of the host device has been opened, wherein the opening of the window automatically activates a text caret in the opened window, the identification based on the received data, determines that the text caret has been activated, wherein activation of the text caret initiates display of a keyboard in a portion of a display of a client device, and generates instructions for automatic adjustment of the opened window in a remaining portion of the display of the client device, the automatic adjustment based on a location of the active text caret in the opened window, wherein the automatic adjustment comprises zooming in on the text caret that was automatically activated by the opening of the window in the display of the host device; and sending the generated instructions over the communication network to the client device, wherein execution of the instructions by the client device results in the automatic adjustment of the opened window in the client device with respect to the remaining portion of the display of the client device based on the location of the active text caret. 2. The method of claim 1 , wherein the determination that the text caret has been activated comprises identifying that the window is an active top-level window. | 0.613527 |
7,519,607 | 1 | 5 | 1. A method for representing similar text documents and similar segments of text documents as standardized text templates and deviations from standardized text templates, the method comprising: partitioning documents into segments; generating standardized text segment templates from segments of documents; determining the deviations of individual text segments from the standardized text segment templates so generated; representing the individual text segments as the combination of standardized text segment templates and deviations from standardized text segment templates; generating standardized text templates representing text documents as sequences of standardized text segment templates; determining the deviations of the individual text documents from the standardized text templates so generated; and representing the individual text documents as a combination of the standardized text templates and the deviations from the standardized text templates. | 1. A method for representing similar text documents and similar segments of text documents as standardized text templates and deviations from standardized text templates, the method comprising: partitioning documents into segments; generating standardized text segment templates from segments of documents; determining the deviations of individual text segments from the standardized text segment templates so generated; representing the individual text segments as the combination of standardized text segment templates and deviations from standardized text segment templates; generating standardized text templates representing text documents as sequences of standardized text segment templates; determining the deviations of the individual text documents from the standardized text templates so generated; and representing the individual text documents as a combination of the standardized text templates and the deviations from the standardized text templates. 5. The method of claim 1 , where the documents are of the file types used in a computer word processor. | 0.85452 |
8,301,995 | 1 | 14 | 1. A method of operating a digital content acquisition device, comprising: a user selects a first annotation stored in the acquisition device that identifies some aspect of at least a first content item to be captured, capture at least the first content item and one or more subsequently captured content items in the acquisition device, associate, within the acquisition device and without user intervention, the first annotation with the first content item, automatically associate, within the acquisition device and without user intervention, the first annotation with any other of the subsequently captured content items until a second annotation stored within the acquisition device that identifies some aspect of at least a second content item to be captured is selected by the user, capture the second content item in the acquisition device, thereafter associate, within the acquisition device and without user intervention, the second annotation with at least the second content item, store data of the captured content items along with the associated first and second annotations and record linking references of the associated annotations into headers of the captured content items; when the acquisition device is turned on, determine whether the acquisition device had been turned off for more than a predetermined time period before the acquisition device being turned on; and if the acquisition device had been turned off for more than the predetermined time period before the acquisition device being turned on, automatically generate an alert of whether to associate a previous annotation with a next content item to be captured, wherein the previous annotation is associated with a last content item captured in the acquisition device before the acquisition device was turned off. | 1. A method of operating a digital content acquisition device, comprising: a user selects a first annotation stored in the acquisition device that identifies some aspect of at least a first content item to be captured, capture at least the first content item and one or more subsequently captured content items in the acquisition device, associate, within the acquisition device and without user intervention, the first annotation with the first content item, automatically associate, within the acquisition device and without user intervention, the first annotation with any other of the subsequently captured content items until a second annotation stored within the acquisition device that identifies some aspect of at least a second content item to be captured is selected by the user, capture the second content item in the acquisition device, thereafter associate, within the acquisition device and without user intervention, the second annotation with at least the second content item, store data of the captured content items along with the associated first and second annotations and record linking references of the associated annotations into headers of the captured content items; when the acquisition device is turned on, determine whether the acquisition device had been turned off for more than a predetermined time period before the acquisition device being turned on; and if the acquisition device had been turned off for more than the predetermined time period before the acquisition device being turned on, automatically generate an alert of whether to associate a previous annotation with a next content item to be captured, wherein the previous annotation is associated with a last content item captured in the acquisition device before the acquisition device was turned off. 14. The method of claim 1 , wherein at least one of the first and second annotations identifies a date at which the respective first or second content items are to be captured. | 0.78 |
9,613,625 | 1 | 3 | 1. A data input device that includes two inputs including a character string input that accepts a character string and a voice input that accepts voice input, a display that displays the character string, and a speech recognition dictionary, the data input device comprising: a dynamic speech recognition dictionary generator which, in operation, extracts phrases of which heads match a head of the character string inputted through the character string input from phrases stored in the speech recognition dictionary, and generates a dynamic speech recognition dictionary that stores difference phrases, the difference phrases each being part of an extracted phrase excluding a common phrase that is common among the extracted phrases; a display controller which, in operation, displays the difference phrases of an input character string candidate, the difference phrases being highlighted on the display and excluding the common phrase; a speech recognizer which, in operation, carries out speech recognition of voice inputted through the voice input by using the dynamic speech recognition dictionary; an input character string confirmer which, in operation, confirms the input character string candidate that includes a difference phrase recognized by the speech recognizer as an input character string; and an input switcher which, in operation, switches between the character string input and the voice input based on a running state of a vehicle, wherein, in a case of receiving a changed state of the vehicle from stopping to starting before a whole character string is finished inputting, the input switcher switches from the character string input to the voice input, the display controller displays the difference phrases of the input character string candidate with the common phrase that has already been confirmed by the character string input, the difference phrases being highlighted on the display, and the input character string confirmer confirms the input character string candidate using the highlighted difference phrase recognized by the speech recognizer as the input character string, and at least one of the dynamic speech recognition dictionary generator, the display controller, the speech recognizer and the input character string confirmer is included in a processor. | 1. A data input device that includes two inputs including a character string input that accepts a character string and a voice input that accepts voice input, a display that displays the character string, and a speech recognition dictionary, the data input device comprising: a dynamic speech recognition dictionary generator which, in operation, extracts phrases of which heads match a head of the character string inputted through the character string input from phrases stored in the speech recognition dictionary, and generates a dynamic speech recognition dictionary that stores difference phrases, the difference phrases each being part of an extracted phrase excluding a common phrase that is common among the extracted phrases; a display controller which, in operation, displays the difference phrases of an input character string candidate, the difference phrases being highlighted on the display and excluding the common phrase; a speech recognizer which, in operation, carries out speech recognition of voice inputted through the voice input by using the dynamic speech recognition dictionary; an input character string confirmer which, in operation, confirms the input character string candidate that includes a difference phrase recognized by the speech recognizer as an input character string; and an input switcher which, in operation, switches between the character string input and the voice input based on a running state of a vehicle, wherein, in a case of receiving a changed state of the vehicle from stopping to starting before a whole character string is finished inputting, the input switcher switches from the character string input to the voice input, the display controller displays the difference phrases of the input character string candidate with the common phrase that has already been confirmed by the character string input, the difference phrases being highlighted on the display, and the input character string confirmer confirms the input character string candidate using the highlighted difference phrase recognized by the speech recognizer as the input character string, and at least one of the dynamic speech recognition dictionary generator, the display controller, the speech recognizer and the input character string confirmer is included in a processor. 3. The data input device according to claim 1 , wherein the dynamic speech recognition dictionary generator generates the dynamic speech recognition dictionary each time a character is inputted through the character string input. | 0.5 |
8,924,335 | 6 | 14 | 6. The method of claim 3 , wherein one or more of said aspects of the user interface pertain to any of priority of fields, color contrast, whitespace, alignment, field and/or element labels, redundancy, tool tips, progress indicators, and display resolution. | 6. The method of claim 3 , wherein one or more of said aspects of the user interface pertain to any of priority of fields, color contrast, whitespace, alignment, field and/or element labels, redundancy, tool tips, progress indicators, and display resolution. 14. The method of claim 6 , wherein the requirement pertains to a quantity of unused area and wherein a said conforming user interface includes a reduced percentage of unused area vis-a-vis the non-conforming user interface which would result from a said rule. | 0.530686 |
7,756,708 | 1 | 8 | 1. A computer-implemented method for generating a speech recognition model, comprising: accessing a baseline speech recognition model installed on a server system; obtaining, at the server system, information from recent text search queries submitted by a plurality of users to a search system, wherein the information (i)specifies a frequency of occurrence for one or more words in the recent search queries and (ii) identifies times when instances of the one or more words were submitted to the search system in recent search queries; and modifying, by the server system, the speech recognition model to revise probabilities of a portion of a sound occurrence based on the information obtained from the recent text search queries, wherein the modification weights influences of instances of the one or more words on the revised probabilities based on times when the one or more words were submitted to the search system in recent search queries. | 1. A computer-implemented method for generating a speech recognition model, comprising: accessing a baseline speech recognition model installed on a server system; obtaining, at the server system, information from recent text search queries submitted by a plurality of users to a search system, wherein the information (i)specifies a frequency of occurrence for one or more words in the recent search queries and (ii) identifies times when instances of the one or more words were submitted to the search system in recent search queries; and modifying, by the server system, the speech recognition model to revise probabilities of a portion of a sound occurrence based on the information obtained from the recent text search queries, wherein the modification weights influences of instances of the one or more words on the revised probabilities based on times when the one or more words were submitted to the search system in recent search queries. 8. The method of claim 1 , wherein the speech recognition model is a rule-based model, a statistical model, or both. | 0.712871 |
7,899,666 | 47 | 49 | 47. The method of claim 28 wherein the program further comprises a linguistic processor that includes a sentence identification stage, a token extraction stage, a morphological and grammatical analysis stage, a sentence analysis stage, and a semantic disambiguation stage. | 47. The method of claim 28 wherein the program further comprises a linguistic processor that includes a sentence identification stage, a token extraction stage, a morphological and grammatical analysis stage, a sentence analysis stage, and a semantic disambiguation stage. 49. The method of claim 47 wherein the a sentence analysis stage uses information in the semantic network and analysis rules to identify structural elements of each sentence, including subject/object/verb, complements, and main and subordinate clauses. | 0.565517 |
9,177,069 | 1 | 18 | 1. A method comprising: determining a target geographic feature that has insufficient targeting information associated therewith, wherein the insufficient targeting information is insufficient to provide targeted content associated with the target geographic feature, the target geographic feature defining a location; determining one or more similar geographic features to the target geographic feature, each similar geographic feature including targeting information and defining a different non-overlapping location from the target geographic location, wherein the one or more similar geographic features are determined based at least in part by identifying a geographic feature having one or more excess queries in common with the target geographic feature, wherein each excess query is a query associated with and exceeds an expected query count for each of the one or more similar geographic features and the target geographic feature; attributing targeting information associated with at least one of the one or more similar geographic features to the target geographic feature; and serving content responsive to queries that relate to the target geographic feature based at least in part on the attributed targeting information; wherein for each of the target geographic feature and the one or more similar geographic features, the expected query count associated with the query is computed as a function of a total number of queries received over a time period for the target geographic feature or the one or more similar geographic features and a query share associated with the query; wherein the query share is computed as a ratio of the number of times that the query was received from user devices in a baseline geographic region relative to a total number of queries that have been received from user devices in the baseline geographic region. | 1. A method comprising: determining a target geographic feature that has insufficient targeting information associated therewith, wherein the insufficient targeting information is insufficient to provide targeted content associated with the target geographic feature, the target geographic feature defining a location; determining one or more similar geographic features to the target geographic feature, each similar geographic feature including targeting information and defining a different non-overlapping location from the target geographic location, wherein the one or more similar geographic features are determined based at least in part by identifying a geographic feature having one or more excess queries in common with the target geographic feature, wherein each excess query is a query associated with and exceeds an expected query count for each of the one or more similar geographic features and the target geographic feature; attributing targeting information associated with at least one of the one or more similar geographic features to the target geographic feature; and serving content responsive to queries that relate to the target geographic feature based at least in part on the attributed targeting information; wherein for each of the target geographic feature and the one or more similar geographic features, the expected query count associated with the query is computed as a function of a total number of queries received over a time period for the target geographic feature or the one or more similar geographic features and a query share associated with the query; wherein the query share is computed as a ratio of the number of times that the query was received from user devices in a baseline geographic region relative to a total number of queries that have been received from user devices in the baseline geographic region. 18. The method of claim 1 further comprising: attributing information associated with one geographic feature with a similar geographic feature; and using the attributed information to target content to the similar geographic feature. | 0.864219 |
8,706,723 | 11 | 12 | 11. The method of claim 10 , further comprising presenting, to the user, at least a portion of the second plurality of suggested matches. | 11. The method of claim 10 , further comprising presenting, to the user, at least a portion of the second plurality of suggested matches. 12. The method of claim 11 , wherein the presenting of at least a portion of the first plurality of suggested matches occurs after the receiving of the first portion and before the receiving of the second portion. | 0.5 |
9,311,505 | 10 | 16 | 10. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, determine an ontology for specifying a hierarchy of one or more abstraction levels for items data used in latent factorization models; generate one or more user models for the items data corresponding to each abstraction level of the ontology; process at least one request for one or more recommendations (a) to determine a requested abstraction level, and (b) to determine a privacy level, a security level, or a combination thereof associated with the at least one request; process the privacy level, the security level, or the combination thereof against one or more privacy policies, one or more security policies, or a combination thereof to determine permission to access the requested abstraction level; generate and/or retrieve the at least one of the one or more user models based, at least in part, on whether the at least one of the one or more user models exists at the requested abstraction level, select at least one of the one or more user models for generating the one or more recommendations for one or more applications, one or more services, or a combination thereof based, at least in part, on the one or more privacy policies, the one or more security policies, or the combination thereof; and wherein the one or more abstraction levels correspond to different levels of the privacy policies and the security policies of the one or more user models. | 10. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, determine an ontology for specifying a hierarchy of one or more abstraction levels for items data used in latent factorization models; generate one or more user models for the items data corresponding to each abstraction level of the ontology; process at least one request for one or more recommendations (a) to determine a requested abstraction level, and (b) to determine a privacy level, a security level, or a combination thereof associated with the at least one request; process the privacy level, the security level, or the combination thereof against one or more privacy policies, one or more security policies, or a combination thereof to determine permission to access the requested abstraction level; generate and/or retrieve the at least one of the one or more user models based, at least in part, on whether the at least one of the one or more user models exists at the requested abstraction level, select at least one of the one or more user models for generating the one or more recommendations for one or more applications, one or more services, or a combination thereof based, at least in part, on the one or more privacy policies, the one or more security policies, or the combination thereof; and wherein the one or more abstraction levels correspond to different levels of the privacy policies and the security policies of the one or more user models. 16. An apparatus of claim 10 , wherein the apparatus is further caused to: generate and/or retrieve one or more item models associated with the one or more abstraction levels; and select at least one of the one or more item models for generating the one or more recommendations based, at least in part, on the one or more privacy policies, the one or more security policies, the selected at least one user model, the requested abstraction level, or a combination thereof. | 0.558989 |
8,185,455 | 1 | 5 | 1. An apparatus comprising: a processor to: receive a user selection of an audit data set including a plurality of exceptions, wherein each exception of the plurality of exceptions represents an instance of misbilling associated with the audit data set, wherein the audit data set is selected from a plurality of billing data sets, each billing data set of the plurality billing data sets including corresponding billing data that has been extracted by the processor from a database; apply a first audit rule to audit the audit data set and produce first audit rule results, wherein the first audit rule results identify a first subset of exceptions of the plurality of exceptions within the audit data set; apply a second audit rule, distinct from the first audit rule, to audit the audit data set and produce second audit rule results, wherein the second audit rule results identify a second subset of exceptions of the plurality of exceptions within the audit data set; present the first subset of exceptions and the second subset of exceptions to a user via a results user interface; and receive a selection of a particular audit rule, wherein the particular audit rule is one of the first audit rule and the second audit rule, and wherein the particular audit rule is selected based on the first audit rule results and the second audit rule results. | 1. An apparatus comprising: a processor to: receive a user selection of an audit data set including a plurality of exceptions, wherein each exception of the plurality of exceptions represents an instance of misbilling associated with the audit data set, wherein the audit data set is selected from a plurality of billing data sets, each billing data set of the plurality billing data sets including corresponding billing data that has been extracted by the processor from a database; apply a first audit rule to audit the audit data set and produce first audit rule results, wherein the first audit rule results identify a first subset of exceptions of the plurality of exceptions within the audit data set; apply a second audit rule, distinct from the first audit rule, to audit the audit data set and produce second audit rule results, wherein the second audit rule results identify a second subset of exceptions of the plurality of exceptions within the audit data set; present the first subset of exceptions and the second subset of exceptions to a user via a results user interface; and receive a selection of a particular audit rule, wherein the particular audit rule is one of the first audit rule and the second audit rule, and wherein the particular audit rule is selected based on the first audit rule results and the second audit rule results. 5. The apparatus of claim 1 , wherein, prior to applying the first audit rule to the audit data set, the processor is to test the first audit rule using a test data file that includes one or more embedded account attributes. | 0.716456 |
9,484,036 | 8 | 9 | 8. A method according to claim 7 further including determining whether the periodicity function exhibits a peak at a point corresponding to a potential speech frame length. | 8. A method according to claim 7 further including determining whether the periodicity function exhibits a peak at a point corresponding to a potential speech frame length. 9. A method according to claim 8 , wherein determining whether the periodicity function exhibits a peak at a point corresponding to a potential speech frame length includes comparing a value of the periodicity function to a threshold value. | 0.5 |
7,900,134 | 10 | 16 | 10. A method of providing a user interface comprising: considering multiple parameters one of which includes an XSL-T file; and based upon the considered parameters, rendering a user interface sufficient to enable a user to interact with a DHTML view that has been rendered from an XML document using a crystal, the crystal containing one or more behaviors and at least one XSL-T file; and receiving, via the user interface, a user interaction with the DHTML view; and mapping, via the one or more behaviors, the user interaction to the XML document. | 10. A method of providing a user interface comprising: considering multiple parameters one of which includes an XSL-T file; and based upon the considered parameters, rendering a user interface sufficient to enable a user to interact with a DHTML view that has been rendered from an XML document using a crystal, the crystal containing one or more behaviors and at least one XSL-T file; and receiving, via the user interface, a user interaction with the DHTML view; and mapping, via the one or more behaviors, the user interaction to the XML document. 16. The method of claim 10 , wherein the considering of the multiple parameters comprises identifying from multiple user interfaces which user interfaces are more suited to have their functionalities provided by an in-document user interface. | 0.5 |
7,509,303 | 17 | 20 | 17. The computer-implemented method of claim 16 , further comprising inputting said mapping information in said medium. | 17. The computer-implemented method of claim 16 , further comprising inputting said mapping information in said medium. 20. The computer-implemented method of claim 17 , wherein said inputting comprises selecting an attribute of data from a data source to be associated with a search attribute. | 0.527174 |
9,633,257 | 2 | 3 | 2. The non-transitory machine-readable storage medium of claim 1 , wherein: the feature is a feature that was previously determined to be a feature capable of distinguishing the document image or a document that comprises the document image, and the feature was previously identified by analysis of a plurality of training documents each having at least one unique feature different from at least one of the other training documents. | 2. The non-transitory machine-readable storage medium of claim 1 , wherein: the feature is a feature that was previously determined to be a feature capable of distinguishing the document image or a document that comprises the document image, and the feature was previously identified by analysis of a plurality of training documents each having at least one unique feature different from at least one of the other training documents. 3. The non-transitory machine-readable storage medium of claim 2 , wherein: the feature is associated with a feature type, identifying the feature in the plurality of training documents further comprises identifying a corresponding feature type for the feature, and a feature type decision tree is generated that comprises the feature type. | 0.5 |
9,965,475 | 1 | 7 | 1. A computer, comprising: a network interface configured to connect the computer to a computer network, the computer network being connected to a shared storage system, the shared storage system comprising a file system configured to store a plurality of electronic documents and to make the plurality of electronic documents available to a plurality of users for modification of structure and content of the electronic documents; and a processing system comprising one or more processing units and storage, the storage comprising computer program code that, when executed by the processing system, configures the processing system to comprise: an application configured to process user input to modify structure and content of an electronic document and associate comments with the content of the electronic document, the application comprising a graphical user interface including a document pane configured to display a first portion of the electronic document as a currently viewed portion of the electronic document, and wherein the graphical user interface is further configured to display comments from the plurality of users in association with the currently viewed portion of the electronic document, wherein comments have at least context data indicating a location within the electronic document and content data; the application configured to, based on at least the currently viewed portion of the electronic document, identify a next comment or previous comment associated with content of the electronic document outside of the currently viewed portion of the electronic document, and to generate and display, with the displayed comments in the graphical user interface, a hint comprising a graphical representation of an indication of at least context data and content data of the identified comment; the application configured to, in response to user input to navigate to displaying a second portion of the electronic document as the currently viewed portion of the electronic document, repeat identifying, based on at least the currently viewed portion of the electronic document, a next or previous comment with respect to the second portion of the electronic document, and generate and display a hint of the identified next or previous comment; and the application configured to, in response to an input associated with a displayed hint related to a comment, navigate to displaying, in the document pane, a third portion of the electronic document associated with the comment related to the displayed hint. | 1. A computer, comprising: a network interface configured to connect the computer to a computer network, the computer network being connected to a shared storage system, the shared storage system comprising a file system configured to store a plurality of electronic documents and to make the plurality of electronic documents available to a plurality of users for modification of structure and content of the electronic documents; and a processing system comprising one or more processing units and storage, the storage comprising computer program code that, when executed by the processing system, configures the processing system to comprise: an application configured to process user input to modify structure and content of an electronic document and associate comments with the content of the electronic document, the application comprising a graphical user interface including a document pane configured to display a first portion of the electronic document as a currently viewed portion of the electronic document, and wherein the graphical user interface is further configured to display comments from the plurality of users in association with the currently viewed portion of the electronic document, wherein comments have at least context data indicating a location within the electronic document and content data; the application configured to, based on at least the currently viewed portion of the electronic document, identify a next comment or previous comment associated with content of the electronic document outside of the currently viewed portion of the electronic document, and to generate and display, with the displayed comments in the graphical user interface, a hint comprising a graphical representation of an indication of at least context data and content data of the identified comment; the application configured to, in response to user input to navigate to displaying a second portion of the electronic document as the currently viewed portion of the electronic document, repeat identifying, based on at least the currently viewed portion of the electronic document, a next or previous comment with respect to the second portion of the electronic document, and generate and display a hint of the identified next or previous comment; and the application configured to, in response to an input associated with a displayed hint related to a comment, navigate to displaying, in the document pane, a third portion of the electronic document associated with the comment related to the displayed hint. 7. The computer of claim 1 wherein comment data further includes metadata for a comment and a displayed hint further includes data indicative of the metadata for the comment. | 0.57767 |
7,574,652 | 12 | 13 | 12. A method according to claim 1 , wherein said transformation is a binary transform involving sequential pairs of data operands. | 12. A method according to claim 1 , wherein said transformation is a binary transform involving sequential pairs of data operands. 13. A method according to claim 12 wherein said binary transforms include mathematical functions selected from the group consisting of addition, subtraction, division and multiplication. | 0.5 |
8,781,235 | 1 | 3 | 1. An object recognition apparatus comprising at least one processor functioning as: an extraction unit configured to extract first dictionary information associated with a first category from among multiple categories included in a dictionary for object recognition and second dictionary information associated with a second category from among multiple categories included in the dictionary or another dictionary; a determination unit configured to calculate a first feature amount and a second feature amount from the first dictionary information and the second dictionary information, respectively, and determine whether or not a similarity between the calculated first feature amount and second feature amount is greater than a predetermined threshold; a comparison unit configured to compare a name of the first category with a name of the second category; a reception unit configured to receive an instruction as to whether or not to integrate the name of the first category and the name of the second category in the case where the determination unit has determined that the similarity is greater than the predetermined threshold and the comparison unit has determined that the name of the first category and the name of the second category do not match; and an integration unit configured, in the case where the reception unit has received an instruction to integrate the names of the categories and a post-integration name, to integrate the name of the first category and the name of the second category with the received post-integration name. | 1. An object recognition apparatus comprising at least one processor functioning as: an extraction unit configured to extract first dictionary information associated with a first category from among multiple categories included in a dictionary for object recognition and second dictionary information associated with a second category from among multiple categories included in the dictionary or another dictionary; a determination unit configured to calculate a first feature amount and a second feature amount from the first dictionary information and the second dictionary information, respectively, and determine whether or not a similarity between the calculated first feature amount and second feature amount is greater than a predetermined threshold; a comparison unit configured to compare a name of the first category with a name of the second category; a reception unit configured to receive an instruction as to whether or not to integrate the name of the first category and the name of the second category in the case where the determination unit has determined that the similarity is greater than the predetermined threshold and the comparison unit has determined that the name of the first category and the name of the second category do not match; and an integration unit configured, in the case where the reception unit has received an instruction to integrate the names of the categories and a post-integration name, to integrate the name of the first category and the name of the second category with the received post-integration name. 3. The object recognition apparatus according to claim 1 , wherein the first feature amount is a first luminance vector calculated from the facial region of an image of a person included in the first dictionary information, the second feature amount is a second luminance vector calculated from the facial region of an image of a person included in the second dictionary information, and the determination unit determines whether or not a correlation value between the first luminance vector and the second luminance vector is greater than the predetermined threshold. | 0.5 |
8,849,650 | 1 | 4 | 1. A system for automatically generating sentences in a computer programming language, comprising: at least one grammar processor for acquiring a grammar as input and creating a grammar hierarchy by converting said grammar into a hierarchical representation, wherein said grammar hierarchy includes a plurality of trees corresponding to a plurality of productions in said grammar; and at least one grammar explorer module for acquiring an exploration specification as input and exploring and traversing said grammar hierarchy based on a plurality of exploration types externally specified in said exploration specification, wherein said grammar explorer module generates a plurality of sentences of a language in accordance with said explored and traversed grammar hierarchy. | 1. A system for automatically generating sentences in a computer programming language, comprising: at least one grammar processor for acquiring a grammar as input and creating a grammar hierarchy by converting said grammar into a hierarchical representation, wherein said grammar hierarchy includes a plurality of trees corresponding to a plurality of productions in said grammar; and at least one grammar explorer module for acquiring an exploration specification as input and exploring and traversing said grammar hierarchy based on a plurality of exploration types externally specified in said exploration specification, wherein said grammar explorer module generates a plurality of sentences of a language in accordance with said explored and traversed grammar hierarchy. 4. The system of claim 1 , wherein said plurality of iterators explores said plurality of nodes of said grammar hierarchy. | 0.659218 |
9,214,043 | 1 | 9 | 1. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following: based on a received free-space user gesture associated with a real-world geographic location where the gesture was performed and a gesture direction representing the direction in which the user gesture was made, automatically provide for the making of an annotation to a map comprising three-dimensional models of geographic elements, the three-dimensional models including surfaces that correspond to real-world surfaces of geographical elements represented in the model, wherein analysis of the map of three-dimensional models using the real-world geographic location and the gesture direction provides for identification of an annotation point comprising a particular surface of the surfaces of the three-dimensional models, the annotation being based on said user gesture and positioned at the annotation point on the particular surface of the three-dimensional model of the map to be rendered onto said surface of the three-dimensional model and wherein if a particular surface cannot be identified, the annotation is positioned at a location in the map corresponding to the real-world geographic location. | 1. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following: based on a received free-space user gesture associated with a real-world geographic location where the gesture was performed and a gesture direction representing the direction in which the user gesture was made, automatically provide for the making of an annotation to a map comprising three-dimensional models of geographic elements, the three-dimensional models including surfaces that correspond to real-world surfaces of geographical elements represented in the model, wherein analysis of the map of three-dimensional models using the real-world geographic location and the gesture direction provides for identification of an annotation point comprising a particular surface of the surfaces of the three-dimensional models, the annotation being based on said user gesture and positioned at the annotation point on the particular surface of the three-dimensional model of the map to be rendered onto said surface of the three-dimensional model and wherein if a particular surface cannot be identified, the annotation is positioned at a location in the map corresponding to the real-world geographic location. 9. An apparatus according to claim 1 , wherein the apparatus provides for the display of a map including a three-dimensional model of the real world geographic area, wherein the annotation is rendered onto the three-dimensional model. | 0.779661 |
9,191,384 | 8 | 13 | 8. A method comprising: receiving a request for a document from a first entity by a cloud service participating in a federated identity platform, the request including an identifier associated with a second entity, the cloud service having a plurality of tenants; comparing the identifier to a set of tenant identifiers each corresponding to one of the plurality of tenants to determine whether the second entity is one of the plurality of tenants; generating a fictitious response in response to the request based on the determination; and sending the generated fictitious response to the first entity, thereby obfuscating whether the second entity is one of the plurality of tenants, wherein the process of generating the fictitious response comprises: generating a certificate; generating a fictitious version of the document; and digitally signing the generated fictitious version of the document using the generated certificate. | 8. A method comprising: receiving a request for a document from a first entity by a cloud service participating in a federated identity platform, the request including an identifier associated with a second entity, the cloud service having a plurality of tenants; comparing the identifier to a set of tenant identifiers each corresponding to one of the plurality of tenants to determine whether the second entity is one of the plurality of tenants; generating a fictitious response in response to the request based on the determination; and sending the generated fictitious response to the first entity, thereby obfuscating whether the second entity is one of the plurality of tenants, wherein the process of generating the fictitious response comprises: generating a certificate; generating a fictitious version of the document; and digitally signing the generated fictitious version of the document using the generated certificate. 13. The method of claim 8 , further comprising extracting the identifier from the received request. | 0.773973 |
9,141,194 | 8 | 9 | 8. The method of claim 7 , wherein detecting the perturbation by the HWM of the determined field magnitude at least as large as the perturbation threshold comprises: making a determination that at least one of the field magnitude samples h j deviates from μ N 1 ,N 2 by an amount at least as large as the perturbation threshold, wherein N 1 ≦j≦N 2 . | 8. The method of claim 7 , wherein detecting the perturbation by the HWM of the determined field magnitude at least as large as the perturbation threshold comprises: making a determination that at least one of the field magnitude samples h j deviates from μ N 1 ,N 2 by an amount at least as large as the perturbation threshold, wherein N 1 ≦j≦N 2 . 9. The method of claim 8 , wherein N≧2, and wherein making the determination that the at least one of the field magnitude samples h j deviates from μ N 1 ,N 2 by an amount at least as large as the perturbation threshold comprises: computing a standard deviation σ N 1 , N 2 = 1 N - 1 ∑ i = N 1 N 2 ( h i - μ N 1 , N 2 ) 2 over W N 1 ,N 2 ; and determining that for the at least one of the field magnitude samples h j , a deviation d j = ( h j - μ N 1 , N 2 ) 2 σ N 1 , N 2 2 is at least as large as a threshold deviation θ, wherein the perturbation threshold is θ×φ N 1 ,N 2 . | 0.5 |
8,402,042 | 1 | 6 | 1. A mining rule database update apparatus using a named entity dictionary and a mining rule combined with an ontology schema, the apparatus comprising: a named entity dictionary and mining rule database storage module for storing the named entity dictionary where a named entity of a terminology combined with the ontology schema and connected to a concept (class) is defined and a mining rule database where the mining rule configured with an RDF triple and a mining pattern combined with the ontology schema and connected to a relationship name is defined; a mining pattern generation module for recognizing a terminology from a text and converting the terminology into the mining pattern; a named entity and mining rule search module for searching for a corresponding named entity and a mining rule from the named entity dictionary and the mining rule database using the recognized terminology and the mining pattern; and a mining rule database update module for estimating a relationship name using a named entity of the recognized terminology and the ontology schema, generating a corresponding mining rule, and then storing the generated mining rule in the mining rule database depending on a user's selection, if a mining rule corresponding to the mining pattern is not searched from the mining rule database and the named entity corresponding to the recognized terminology is searched from the named entity dictionary. | 1. A mining rule database update apparatus using a named entity dictionary and a mining rule combined with an ontology schema, the apparatus comprising: a named entity dictionary and mining rule database storage module for storing the named entity dictionary where a named entity of a terminology combined with the ontology schema and connected to a concept (class) is defined and a mining rule database where the mining rule configured with an RDF triple and a mining pattern combined with the ontology schema and connected to a relationship name is defined; a mining pattern generation module for recognizing a terminology from a text and converting the terminology into the mining pattern; a named entity and mining rule search module for searching for a corresponding named entity and a mining rule from the named entity dictionary and the mining rule database using the recognized terminology and the mining pattern; and a mining rule database update module for estimating a relationship name using a named entity of the recognized terminology and the ontology schema, generating a corresponding mining rule, and then storing the generated mining rule in the mining rule database depending on a user's selection, if a mining rule corresponding to the mining pattern is not searched from the mining rule database and the named entity corresponding to the recognized terminology is searched from the named entity dictionary. 6. The apparatus according to claim 1 , wherein the mining pattern generation module includes: a named entity recognition unit for recognizing the terminology from the text using lexical analysis, syntactic analysis, and semantic analysis in association with the named entity dictionary and expressing the recognized terminology as a named entity corresponding to a terminology stored in the named entity dictionary; and a mining pattern conversion unit for converting the text including the named entity into a mining pattern. | 0.698857 |
8,732,595 | 8 | 13 | 8. A condition editor for creating and deploying conditions for a business process activity monitoring system, the condition editor comprising: at least one processor; a computer having a display; and a user interface generated by the computer, the user interface comprising an operator palette, an editor view, a condition variable view, a binding view, and a message log view, the editor view providing an editing area on the display in which to receive a text-based expression of one or more conditions related to a workflow of an executing business application process, the one or more conditions being associated with respective one or more monitored events in the executing business application process and configured to provide corresponding alerts in the message log view when the respective one or more events are detected, at least one text-based expression including at least one operator and at least one variable, the editing area providing drag-and-drop editing of the text-based expression of the one or more conditions to build complex conditions for monitoring the workflow of the business application process, the user interface displays a pop-up window including a list of all possible values, operators, parenthesis, or operands for insertion at a current cursor position while building the one or more conditions, the at least one variable being defined in the binding view and declared in the condition variable view, one or more conditions depend on existence of at least one corresponding object within the distributed business application and upon deletion of the at least one object, the one or more conditions corresponding to the at least one object are deleted, wherein the user interface highlights the at least one variable as a valid variable if the at least one variable is valid and the user interface highlights the at least one variable as an invalid variable if the at least one variable is invalid, the binding view providing binding of values to the at least one variable, wherein a deletion or a modification of at least one variable is not allowed in the binding view, wherein the user interface having a functionality to provide at least one comment while writing one or more conditions, wherein the at least one comment is visible at a design time and has no impact at a runtime. | 8. A condition editor for creating and deploying conditions for a business process activity monitoring system, the condition editor comprising: at least one processor; a computer having a display; and a user interface generated by the computer, the user interface comprising an operator palette, an editor view, a condition variable view, a binding view, and a message log view, the editor view providing an editing area on the display in which to receive a text-based expression of one or more conditions related to a workflow of an executing business application process, the one or more conditions being associated with respective one or more monitored events in the executing business application process and configured to provide corresponding alerts in the message log view when the respective one or more events are detected, at least one text-based expression including at least one operator and at least one variable, the editing area providing drag-and-drop editing of the text-based expression of the one or more conditions to build complex conditions for monitoring the workflow of the business application process, the user interface displays a pop-up window including a list of all possible values, operators, parenthesis, or operands for insertion at a current cursor position while building the one or more conditions, the at least one variable being defined in the binding view and declared in the condition variable view, one or more conditions depend on existence of at least one corresponding object within the distributed business application and upon deletion of the at least one object, the one or more conditions corresponding to the at least one object are deleted, wherein the user interface highlights the at least one variable as a valid variable if the at least one variable is valid and the user interface highlights the at least one variable as an invalid variable if the at least one variable is invalid, the binding view providing binding of values to the at least one variable, wherein a deletion or a modification of at least one variable is not allowed in the binding view, wherein the user interface having a functionality to provide at least one comment while writing one or more conditions, wherein the at least one comment is visible at a design time and has no impact at a runtime. 13. A condition editor in accordance with claim 8 , further comprising a message log in the user interface to display syntactic and semantic error messages that are generated while a condition is being created in the editing area. | 0.674221 |
9,465,790 | 2 | 3 | 2. The method of claim 1 , further comprising deriving sentiment from the identified subject, verb, and object. | 2. The method of claim 1 , further comprising deriving sentiment from the identified subject, verb, and object. 3. The method of claim 2 , wherein the derived sentiment is determined from a predefined category selected from the group consisting of: positive, neutral, and negative. | 0.5 |
7,805,673 | 1 | 54 | 1. A method comprising: enabling a user to define a redaction of a part of a document in a corpus of documents, the redaction definition including a scope defining a range of documents in the corpus to which the redaction applies, wherein the document is produced as a bitmap image file in which a redacted region appears as a region of black pixel data; creating a temporary image file representing an unredacted version of the document; creating a temporary image file representing a redacted version of the document utilizing custom fonts in rendering which result in foreground and background colors of redaction regions being an inverse of the foreground and the background colors of fonts used for non-redaction regions; performing XOR operations between corresponding sections in the temporary image files of the unredacted and the redacted documents; and creating a mapping between a redacted token and pixel space bounds of the redacted token, thereby creating the region of black pixel data. | 1. A method comprising: enabling a user to define a redaction of a part of a document in a corpus of documents, the redaction definition including a scope defining a range of documents in the corpus to which the redaction applies, wherein the document is produced as a bitmap image file in which a redacted region appears as a region of black pixel data; creating a temporary image file representing an unredacted version of the document; creating a temporary image file representing a redacted version of the document utilizing custom fonts in rendering which result in foreground and background colors of redaction regions being an inverse of the foreground and the background colors of fonts used for non-redaction regions; performing XOR operations between corresponding sections in the temporary image files of the unredacted and the redacted documents; and creating a mapping between a redacted token and pixel space bounds of the redacted token, thereby creating the region of black pixel data. 54. The method of claim 1 , further comprising: creating a mapping between the redacted token and a redaction category; using the created mapping to render a name of the redaction category on the black pixel data region representing the associated redacted token. | 0.595385 |
8,442,964 | 1 | 3 | 1. A method for information processing in a processing system, comprising: receiving a portion of a first complete document in a first language, said portion including some but not all information in said first complete document; searching a database for and retrieving a complete copy of said first complete document in said first language; machine translating said first complete document from said first language to a second language thereby generating a machine-translated document in said second language; and using the machine-translated document in said second language as a basis for searching for a complete original document in said second language, corresponding to said machine-translated document. | 1. A method for information processing in a processing system, comprising: receiving a portion of a first complete document in a first language, said portion including some but not all information in said first complete document; searching a database for and retrieving a complete copy of said first complete document in said first language; machine translating said first complete document from said first language to a second language thereby generating a machine-translated document in said second language; and using the machine-translated document in said second language as a basis for searching for a complete original document in said second language, corresponding to said machine-translated document. 3. The method of claim 1 , further comprising automatic speech recognition (ASR) of said portion of said first complete document and using a product of said ASR to search said database. | 0.631474 |
8,090,708 | 15 | 16 | 15. A system comprising: a processor; and a computer-readable medium comprising instructions to cause the processor to perform operations comprising: updating a computer searchable index of a corpus of resources from time to time to generate an updated index for use by a search engine to provide index search results to search queries, the search results for any search query being based on a most recently updated index; recording in a computer readable memory change data specifying changes made by users affecting resources in the corpus, including recording for each change a respective user making the change, the recorded changes occurring so late as not to be reflected in the most recently updated index; receiving a first search query from a first user and a corresponding first index search result based on the most recently updated index, wherein the first index search result comprises resources indexed in the most-recently updated index that satisfy the query; and searching the change data recorded in the memory to identify any changes to the corpus of resources made by the first user that relate to the first search query and if any such changes are found, generating a revised search result from the changes and the first index search result and providing the revised search result to the first user as a response to the first query, and otherwise providing the first index search result to the first user as a response to the first query. | 15. A system comprising: a processor; and a computer-readable medium comprising instructions to cause the processor to perform operations comprising: updating a computer searchable index of a corpus of resources from time to time to generate an updated index for use by a search engine to provide index search results to search queries, the search results for any search query being based on a most recently updated index; recording in a computer readable memory change data specifying changes made by users affecting resources in the corpus, including recording for each change a respective user making the change, the recorded changes occurring so late as not to be reflected in the most recently updated index; receiving a first search query from a first user and a corresponding first index search result based on the most recently updated index, wherein the first index search result comprises resources indexed in the most-recently updated index that satisfy the query; and searching the change data recorded in the memory to identify any changes to the corpus of resources made by the first user that relate to the first search query and if any such changes are found, generating a revised search result from the changes and the first index search result and providing the revised search result to the first user as a response to the first query, and otherwise providing the first index search result to the first user as a response to the first query. 16. The system of claim 15 , wherein the changes include a modification of a resource associated with the first user, and wherein generating the revised search result comprises: determining that the modification causes the resource to no longer satisfy the first search query; and removing the resource from the first index search result. | 0.518519 |
8,484,578 | 2 | 3 | 2. The method of claim 1 , further comprising: receiving a selection of the out-space actuator from the out-space communication user interface (UI) component; in response to receiving the selection of the out-space actuator from the out-space communication user interface (UI) component, displaying the out-space user interface; and displaying the status of the document in the out-space user interface. | 2. The method of claim 1 , further comprising: receiving a selection of the out-space actuator from the out-space communication user interface (UI) component; in response to receiving the selection of the out-space actuator from the out-space communication user interface (UI) component, displaying the out-space user interface; and displaying the status of the document in the out-space user interface. 3. The method of claim 2 , further comprising: displaying the status of the document in a document status display pane that is displayed in the out-space user interface; and visually highlighting the document status display pane to indicate that the status of the document displayed in the document status display pane is associated with the out-space communication user interface (UI) component temporarily displayed in the in-space user interface for alerting a user of the document about the availability of the status of the document. | 0.5 |
9,245,205 | 14 | 17 | 14. A computer-implemented method for generating a global image representation of a text image, the method comprising: a) extracting a plurality of image patch descriptors representative of a plurality of respective image patches representative of the text image, the plurality of image patches including a background area and a foreground area associated with the text image; b) computing a plurality of aggregated representations of the image patch descriptors, each aggregated representation associated with an image block including two or more image patches; c) determining character annotations associated with each image block by projecting each image block's aggregated representation computer in step b) into an intermediate subspace associated with training text images including one or more annotated character bounding boxes, the intermediate subspace mapping visual features to a semantic space; and d) associating the determined character annotation with each respective image block associated with the text image to generate the global image representation of the text image. | 14. A computer-implemented method for generating a global image representation of a text image, the method comprising: a) extracting a plurality of image patch descriptors representative of a plurality of respective image patches representative of the text image, the plurality of image patches including a background area and a foreground area associated with the text image; b) computing a plurality of aggregated representations of the image patch descriptors, each aggregated representation associated with an image block including two or more image patches; c) determining character annotations associated with each image block by projecting each image block's aggregated representation computer in step b) into an intermediate subspace associated with training text images including one or more annotated character bounding boxes, the intermediate subspace mapping visual features to a semantic space; and d) associating the determined character annotation with each respective image block associated with the text image to generate the global image representation of the text image. 17. The computer-implemented method for generating a global image representation of a text image according to claim 14 , wherein step b) and step c2) encodes the image blocks using FV over SIFT descriptors with a spatial pyramid. | 0.900866 |
7,680,783 | 10 | 19 | 10. A search system comprising a computer-readable storage medium storing instructions to be executed by a processor, the instructions, when executed, implementing: an identification strategy associating a parsing grammar in a data entry field with a search algorithm, the parsing grammar comprising parsing grammar rules which split data into a plurality of token names, each token name identifying data in a section of a grammatical statement; a plurality of expression formats, at least one expression format preceding each of the plurality of token names, each expression format representing a number of alphanumeric characters of the identified data of the token name that the expression format precedes; and a punctuation, the punctuation separating each of the plurality of token names; the search algorithm comprising search rules, a search rule producing a query identifying a field in a database to be searched using the data identified by at least one token name in the parsing grammar; a configuration interface displayed on a computer display, the configuration interface receiving a change to the identification strategy; a configuration engine which updates the identification strategy to reflect the change; an application interface displayed on one of the computer display and a second computer display, the application interface receiving search data in the data entry field; a parsing engine to apply the parsing grammar to split the search data by: checking whether the entered data contains the punctuation; checking whether the entered data before the punctuation contains the number of alphanumeric characters required by the expression format for the token name preceding the punctuation; and checking whether the entered data after the punctuation contains the number of alphanumeric characters required by the expression format for the token name following the punctuation; a query generating engine to apply the search algorithm to produce a search query using at least a portion of the search data corresponding to at least one token name; and a search engine to execute the search query in a database to produce and return a results set. | 10. A search system comprising a computer-readable storage medium storing instructions to be executed by a processor, the instructions, when executed, implementing: an identification strategy associating a parsing grammar in a data entry field with a search algorithm, the parsing grammar comprising parsing grammar rules which split data into a plurality of token names, each token name identifying data in a section of a grammatical statement; a plurality of expression formats, at least one expression format preceding each of the plurality of token names, each expression format representing a number of alphanumeric characters of the identified data of the token name that the expression format precedes; and a punctuation, the punctuation separating each of the plurality of token names; the search algorithm comprising search rules, a search rule producing a query identifying a field in a database to be searched using the data identified by at least one token name in the parsing grammar; a configuration interface displayed on a computer display, the configuration interface receiving a change to the identification strategy; a configuration engine which updates the identification strategy to reflect the change; an application interface displayed on one of the computer display and a second computer display, the application interface receiving search data in the data entry field; a parsing engine to apply the parsing grammar to split the search data by: checking whether the entered data contains the punctuation; checking whether the entered data before the punctuation contains the number of alphanumeric characters required by the expression format for the token name preceding the punctuation; and checking whether the entered data after the punctuation contains the number of alphanumeric characters required by the expression format for the token name following the punctuation; a query generating engine to apply the search algorithm to produce a search query using at least a portion of the search data corresponding to at least one token name; and a search engine to execute the search query in a database to produce and return a results set. 19. The system of claim 10 , wherein the identity strategy further associates a second parsing grammar with a second search algorithm. | 0.699552 |
8,880,430 | 10 | 11 | 10. The method of claim 1 , before applying the first set of rules and the second set of rules, further comprising the computer transforming the on-line bank account data as entered by an account holder into a standardized format by normalizing the on-line account data and deleting punctuation from the on-line account data. | 10. The method of claim 1 , before applying the first set of rules and the second set of rules, further comprising the computer transforming the on-line bank account data as entered by an account holder into a standardized format by normalizing the on-line account data and deleting punctuation from the on-line account data. 11. The method of claim 10 , wherein on-line bank account data as entered by the account holder when the on-line bank account was opened is transformed into the standardized format. | 0.5 |
9,547,628 | 14 | 18 | 14. A non-transitory computer readable medium for storing computer instructions that, when executed by at least one processor cause the at least one processor to perform a method for automatically improving legibility based on preferred font characteristics comprising: determining a plurality of preferences regarding a plurality of font size characteristics of a sample text, wherein the plurality of preferences comprise a preferred height, a preferred weight, and a preferred condensation of the sample text; receiving a request to view an electronic document having text in a given font; adjusting the text of the electronic document to a first zoom level based on the preferred height; adjusting the first zoom level to a second zoom level to adjust the text to the preferred weight; adjusting the second zoom level to a final zoom level to adjust the text to the preferred condensation; and displaying the text of the electronic document in the given font at the final zoom level based on the plurality of preferences. | 14. A non-transitory computer readable medium for storing computer instructions that, when executed by at least one processor cause the at least one processor to perform a method for automatically improving legibility based on preferred font characteristics comprising: determining a plurality of preferences regarding a plurality of font size characteristics of a sample text, wherein the plurality of preferences comprise a preferred height, a preferred weight, and a preferred condensation of the sample text; receiving a request to view an electronic document having text in a given font; adjusting the text of the electronic document to a first zoom level based on the preferred height; adjusting the first zoom level to a second zoom level to adjust the text to the preferred weight; adjusting the second zoom level to a final zoom level to adjust the text to the preferred condensation; and displaying the text of the electronic document in the given font at the final zoom level based on the plurality of preferences. 18. The computer readable medium of claim 14 , wherein adjusting to the first zoom level comprises: determining a primary text in the electronic document; measuring a height of the primary text at 100% zoom level; and adjusting the text in the electronic document to the first zoom level such that the height of the primary text matches the preferred height in the plurality of preferences. | 0.619141 |
9,946,510 | 4 | 5 | 4. The mobile terminal of claim 1 , wherein the controller is further configured to cause the touch screen to output a list of candidate words for replacing a word of the displayed text in response to selection of the word. | 4. The mobile terminal of claim 1 , wherein the controller is further configured to cause the touch screen to output a list of candidate words for replacing a word of the displayed text in response to selection of the word. 5. The mobile terminal of claim 4 , wherein the candidate words are arranged in a specific order according to their degrees of similarity to a signal section of the voice signal corresponding to the word. | 0.5 |
9,727,537 | 8 | 9 | 8. The non-transitory computer-readable medium of claim 6 , wherein: said set of target fonts include a web font associated with a web font pointer provided by a third party; and said mapping is applied when said web font pointer is utilized. | 8. The non-transitory computer-readable medium of claim 6 , wherein: said set of target fonts include a web font associated with a web font pointer provided by a third party; and said mapping is applied when said web font pointer is utilized. 9. The non-transitory computer-readable medium of claim 8 , wherein said web font pointer utilizes an @font-face definition for a cascading style sheet. | 0.5 |
10,096,317 | 2 | 5 | 2. A computer-implemented method, comprising: accessing a literal speech recognition corpus comprising a plurality of expressions, an expression comprising a sequence of word tokens; accessing a concept tagging module for identifying instances of a plurality of concepts within an expression and for replacing expressions with placeholders that indicate classes associated with concepts; generating a parameterized speech recognition corpus by using the concept tagging module to identify, within the expressions of the literal speech recognition corpus, portions of the expressions that are instances of the concepts and to replace the identified portions of the expressions with placeholders; and generating a parameterized statistical model based on the parameterized speech recognition corpus receiving, over a computer network, an utterance of a user, the utterance having been accepted from the user at a client device as spoken input; and generating a text interpretation of the utterance using the parameterized statistical model together with a language sub-model corresponding to one of the plurality of concepts. | 2. A computer-implemented method, comprising: accessing a literal speech recognition corpus comprising a plurality of expressions, an expression comprising a sequence of word tokens; accessing a concept tagging module for identifying instances of a plurality of concepts within an expression and for replacing expressions with placeholders that indicate classes associated with concepts; generating a parameterized speech recognition corpus by using the concept tagging module to identify, within the expressions of the literal speech recognition corpus, portions of the expressions that are instances of the concepts and to replace the identified portions of the expressions with placeholders; and generating a parameterized statistical model based on the parameterized speech recognition corpus receiving, over a computer network, an utterance of a user, the utterance having been accepted from the user at a client device as spoken input; and generating a text interpretation of the utterance using the parameterized statistical model together with a language sub-model corresponding to one of the plurality of concepts. 5. The computer-implemented method of claim 2 , wherein the interpretation comprises a lattice in which nodes of the lattice are literal word tokens and edges between the nodes have weights indicating probabilities that the corresponding literal word tokens occur in sequence. | 0.520833 |
8,701,008 | 25 | 30 | 25. A method performed at a first server comprising a computing device for sharing multimedia content editing techniques by a user, comprising: receiving a project description file, thumbnail graphics, and a location identifier at the first server, wherein the project description file is generated during editing of multimedia content by the user, and wherein the thumbnail graphics represent multimedia editing objects incorporated into the edited multimedia content; retrieving the edited multimedia content from a second server at the first server based on the location identifier; synchronizing, by the first server, the edited multimedia content received from the second server with the thumbnail graphics and multimedia editing objects at the first server according to timing data specifying a duration of each of the multimedia editing objects, the timing data being specified by the project description file, wherein synchronizing the edited multimedia content, thumbnail graphics, and multimedia editing objects is performed by receiving, at the first server, a specified location of a progression bar with respect to a timeline; and displaying, at the first server, the synchronized edited multimedia content, thumbnail graphics, and multimedia editing objects on the timeline, wherein the multimedia editing objects comprise video editing effects previously applied to the multimedia content to generate the edited multimedia content. | 25. A method performed at a first server comprising a computing device for sharing multimedia content editing techniques by a user, comprising: receiving a project description file, thumbnail graphics, and a location identifier at the first server, wherein the project description file is generated during editing of multimedia content by the user, and wherein the thumbnail graphics represent multimedia editing objects incorporated into the edited multimedia content; retrieving the edited multimedia content from a second server at the first server based on the location identifier; synchronizing, by the first server, the edited multimedia content received from the second server with the thumbnail graphics and multimedia editing objects at the first server according to timing data specifying a duration of each of the multimedia editing objects, the timing data being specified by the project description file, wherein synchronizing the edited multimedia content, thumbnail graphics, and multimedia editing objects is performed by receiving, at the first server, a specified location of a progression bar with respect to a timeline; and displaying, at the first server, the synchronized edited multimedia content, thumbnail graphics, and multimedia editing objects on the timeline, wherein the multimedia editing objects comprise video editing effects previously applied to the multimedia content to generate the edited multimedia content. 30. The method of claim 25 , wherein the location identifier is a uniform resource locator (URL) generated by the second server storing the edited multimedia content. | 0.711806 |
9,009,586 | 16 | 19 | 16. An a computer system including a computer processor for authoring, storing and searching a plurality of knowledgebase articles based on at least one electronic document each comprising at least one text snippet, the computer comprising: a knowledgebase for storing the plurality of articles, each article comprising a plurality of data fields; an electronic display; a selecting device comprising a user operable button; an article authoring applet displayed on the monitor, the applet comprising a plurality of panes, one of each of said panes associated with a respective one of the plurality of article data fields, wherein said selection device is used to highlight a text snippet from the at least one electronic document by moving a cursor to a start of said text snippet, engaging and holding a user operable selection means while moving said cursor to an end of said text snippet wherein on release of said user operable selection means said highlighted text snippet is copied to an active pane as a pane content; selecting one of said panes as said active pane; storing said pane content of said plurality of panes as an article in the knowledgebase, wherein for each of said panes, said pane content is stored in the article data field associated with said pane; and a search engine comprising a keyword search input field and a search results display, wherein when a keyword entered via the search input field matches an article in said knowledgebase, at least a title of said article is displayed in said search results display. | 16. An a computer system including a computer processor for authoring, storing and searching a plurality of knowledgebase articles based on at least one electronic document each comprising at least one text snippet, the computer comprising: a knowledgebase for storing the plurality of articles, each article comprising a plurality of data fields; an electronic display; a selecting device comprising a user operable button; an article authoring applet displayed on the monitor, the applet comprising a plurality of panes, one of each of said panes associated with a respective one of the plurality of article data fields, wherein said selection device is used to highlight a text snippet from the at least one electronic document by moving a cursor to a start of said text snippet, engaging and holding a user operable selection means while moving said cursor to an end of said text snippet wherein on release of said user operable selection means said highlighted text snippet is copied to an active pane as a pane content; selecting one of said panes as said active pane; storing said pane content of said plurality of panes as an article in the knowledgebase, wherein for each of said panes, said pane content is stored in the article data field associated with said pane; and a search engine comprising a keyword search input field and a search results display, wherein when a keyword entered via the search input field matches an article in said knowledgebase, at least a title of said article is displayed in said search results display. 19. The computer system of claim 16 , wherein said article authoring applet further comprises a means for manually editing said pane content of said active pane. | 0.681818 |
8,046,320 | 20 | 21 | 20. The method of claim 19 , further comprising: configuring a knowledge agent to receive resource data and configured to provide knowledge data based on the ontology model to generate a situational knowledge of a mission using the resource aspect, the rule aspect, the result aspect and the responsibility aspect; configuring a resource agent to provide the resource data to the knowledge agent; and configuring a domain-independent reasoning agent to process the knowledge data from the knowledge agent to provide C2 data to answer C2 queries. | 20. The method of claim 19 , further comprising: configuring a knowledge agent to receive resource data and configured to provide knowledge data based on the ontology model to generate a situational knowledge of a mission using the resource aspect, the rule aspect, the result aspect and the responsibility aspect; configuring a resource agent to provide the resource data to the knowledge agent; and configuring a domain-independent reasoning agent to process the knowledge data from the knowledge agent to provide C2 data to answer C2 queries. 21. The method of claim 20 , further comprising: populating the ontology model with domain-specific instances; and configuring a domain-dependent reasoning agent associated with the domain to customize the C2 data provided by the domain-independent reasoning agent using the domain-specific instances in the ontology model, wherein the domain is from a group of domains consisting of a military domain, a disaster preparedness domain, a disaster response domain and a corporate business domain. | 0.5 |
7,574,349 | 1 | 14 | 1. A method for processing electronic mail comprising: computing a probability that a text string in an electronic mail message refers to an attachment as a function of a stored probability value for each of a plurality of sequences of words within the text string, the computing of the probability including computing a first probability that the text string refers to an attachment using a first set of stored probability values and, where the first probability exceeds a predetermined value, computing a second probability that the text string does not refer to an attachment using a second set of stored probability values, the probability that a text string in an electronic mail message refers to an attachment being computed as a function of the first and second probabilities; and where the electronic mail message lacks an attachment, prompting a user if the computed probability indicates that the text string refers to an attachment. | 1. A method for processing electronic mail comprising: computing a probability that a text string in an electronic mail message refers to an attachment as a function of a stored probability value for each of a plurality of sequences of words within the text string, the computing of the probability including computing a first probability that the text string refers to an attachment using a first set of stored probability values and, where the first probability exceeds a predetermined value, computing a second probability that the text string does not refer to an attachment using a second set of stored probability values, the probability that a text string in an electronic mail message refers to an attachment being computed as a function of the first and second probabilities; and where the electronic mail message lacks an attachment, prompting a user if the computed probability indicates that the text string refers to an attachment. 14. The method of claim 1 , further comprising adapting at least one stored probability value to the writing patterns of the user. | 0.815341 |
7,953,679 | 1 | 3 | 1. A computer-implemented method for creating a set of indexes for a collection of documents according to document layout, comprising: providing a plurality of documents to computer memory; extracting layout blocks from the provided documents; using a computer processor, clustering the layout blocks into a plurality of layout block clusters; computing a representative block for each of the layout block clusters; generating a document index for each provided document based on the layout blocks of the document and the computed representative blocks; clustering the created document indexes into a plurality of document index clusters; generating a representative cluster index for each of the document index clusters; and outputting the generated document indexes, representative blocks, document index clusters, and representative cluster indexes to memory. | 1. A computer-implemented method for creating a set of indexes for a collection of documents according to document layout, comprising: providing a plurality of documents to computer memory; extracting layout blocks from the provided documents; using a computer processor, clustering the layout blocks into a plurality of layout block clusters; computing a representative block for each of the layout block clusters; generating a document index for each provided document based on the layout blocks of the document and the computed representative blocks; clustering the created document indexes into a plurality of document index clusters; generating a representative cluster index for each of the document index clusters; and outputting the generated document indexes, representative blocks, document index clusters, and representative cluster indexes to memory. 3. The method of claim 1 , wherein at least one of the clustering of the generated document indexes into document index clusters and the clustering of the layout blocks into layout block clusters comprises using one of the following algorithms: a k-means clustering algorithm, and a hierarchical clustering algorithm. | 0.796534 |
7,685,585 | 4 | 5 | 4. The method of claim 3 further comprising: processing said selection of said one or more functions. | 4. The method of claim 3 further comprising: processing said selection of said one or more functions. 5. The method of claim 4 wherein said processing comprises: accessing said library; and calling said sequence of associated implicit control flow functions. | 0.5 |
8,799,197 | 4 | 7 | 4. A data processing apparatus comprising: an input unit configured to receive input data having a natural language format; a rule database configured to store storage data having the natural language format, wherein the storage data is updated based on the input data; a parser configured to infer the input data and the storage data having the natural language format to recognize an input rule included in the input data a storage rule included in the storage data; an algorithm calculator configured to apply a Self Evolutionary Rule-base algorithm to compare the input rule to the storage rule, and to update the storage data stored in the rule database according to the result of the comparison, wherein each of the input rule and the storage rule is composed of an item and a detail, and in response to a result of comparing indicating that at least one item included in the input rule is a new item that is not identical to an item included in the storage rule, the updating of the storage data comprises adding the input rule including the new item to the rule database. | 4. A data processing apparatus comprising: an input unit configured to receive input data having a natural language format; a rule database configured to store storage data having the natural language format, wherein the storage data is updated based on the input data; a parser configured to infer the input data and the storage data having the natural language format to recognize an input rule included in the input data a storage rule included in the storage data; an algorithm calculator configured to apply a Self Evolutionary Rule-base algorithm to compare the input rule to the storage rule, and to update the storage data stored in the rule database according to the result of the comparison, wherein each of the input rule and the storage rule is composed of an item and a detail, and in response to a result of comparing indicating that at least one item included in the input rule is a new item that is not identical to an item included in the storage rule, the updating of the storage data comprises adding the input rule including the new item to the rule database. 7. The data processing apparatus of claim 4 , wherein, in response to the result of the comparison indicates that at least one item included in the input rule is identical to an item included in the storage rule and a detail of the item of the input rule is different from a detail of the item of the storage rule, the algorithm calculator substitutes the detail of the item of the storage rule by the detail of the item of the input rule. | 0.5 |
9,152,709 | 15 | 16 | 15. A computing system comprising: one or more processors; one or more computer-readable media maintaining instructions that, when executed by the one or more processors, cause the one or more processors to perform acts comprising: generating a first topic space based on a plurality of microblog entries, the plurality of microblog entries being unrelated to a network access history of the computing system; receiving a microblog entry from a social stream domain; determining, based on a second topic space associated with the plurality of microblog entries and a media domain, a topic that is associated with the microblog entry; determining, based on the second topic space, one or more videos in the media domain that are associated with the topic; identifying the one or more videos as recommended videos based on the microblog entry; and determining a popularity ranking of the one or more recommended videos based on a first weight associated with a view count of the one or more recommended videos and a second weight associated with a number of tags that the one or more recommended videos have in common with words of the topic. | 15. A computing system comprising: one or more processors; one or more computer-readable media maintaining instructions that, when executed by the one or more processors, cause the one or more processors to perform acts comprising: generating a first topic space based on a plurality of microblog entries, the plurality of microblog entries being unrelated to a network access history of the computing system; receiving a microblog entry from a social stream domain; determining, based on a second topic space associated with the plurality of microblog entries and a media domain, a topic that is associated with the microblog entry; determining, based on the second topic space, one or more videos in the media domain that are associated with the topic; identifying the one or more videos as recommended videos based on the microblog entry; and determining a popularity ranking of the one or more recommended videos based on a first weight associated with a view count of the one or more recommended videos and a second weight associated with a number of tags that the one or more recommended videos have in common with words of the topic. 16. The computing system as recited in claim 15 , the acts further comprising: generating an updated topic space based on a plurality of additional microblog entries that are received via the social stream domain; receiving a second microblog entry from the social stream domain that is associated with the topic; determining, based on the updated topic space, that at least one different video in the media domain is associated with the topic; and identifying the at least one different video as a recommended video based on the second microblog entry. | 0.5 |
10,140,285 | 1 | 4 | 1. A computer-implemented method of generating phrase based categories for interactions recorded at a call center, the method comprising: displaying, using a computer processor, a graphical user interface to a user, the graphical user interface comprising: an input area for the user to input a base category and one or more phrases, for analysis of the base category, and an input area for the user to input a candidate phrase for analysis; obtaining via user input the base category; generating, using the computer processor, a base trend for the base category based on a frequency of appearance of at least one of the one or more phrases in a set of recorded interactions that are specific to the call center, the base trend comprising a series of numbers of interactions per time unit for each of a series of time units, each recorded interaction comprising a text recording of a conversational exchange, wherein at least some of the text recordings are produced via a speech to text process applied to an audio recording; obtaining via user input the candidate phrase; generating, using the computer processor, an accuracy value for the candidate phrase by determining a correlation between: a first candidate trend determined based on the frequency of appearance of the candidate phrase in the set of recorded interactions determined using a first accuracy value; and a second candidate trend determined based on the frequency of appearance of the candidate phrase in the set of recorded interactions determined using a second accuracy value; generating, using the computer processor, a candidate trend for the candidate phrase based on a frequency of appearance of the candidate phrase in the set of recorded interactions determined using the generated accuracy value, each of the candidate trend, the first candidate trend, and the second candidate trend comprising a series of numbers of interactions per time unit for each of a series of time units; calculating, using the computer processor, a correlation level for the candidate trend based on the candidate trend and the base trend, wherein the correlation level quantifies a difference in a behavior of the candidate trend and the base trend; if the correlation level is greater than a threshold level then including, using the computer processor, the candidate phrase in the base category; and displaying to the user the candidate phrase. | 1. A computer-implemented method of generating phrase based categories for interactions recorded at a call center, the method comprising: displaying, using a computer processor, a graphical user interface to a user, the graphical user interface comprising: an input area for the user to input a base category and one or more phrases, for analysis of the base category, and an input area for the user to input a candidate phrase for analysis; obtaining via user input the base category; generating, using the computer processor, a base trend for the base category based on a frequency of appearance of at least one of the one or more phrases in a set of recorded interactions that are specific to the call center, the base trend comprising a series of numbers of interactions per time unit for each of a series of time units, each recorded interaction comprising a text recording of a conversational exchange, wherein at least some of the text recordings are produced via a speech to text process applied to an audio recording; obtaining via user input the candidate phrase; generating, using the computer processor, an accuracy value for the candidate phrase by determining a correlation between: a first candidate trend determined based on the frequency of appearance of the candidate phrase in the set of recorded interactions determined using a first accuracy value; and a second candidate trend determined based on the frequency of appearance of the candidate phrase in the set of recorded interactions determined using a second accuracy value; generating, using the computer processor, a candidate trend for the candidate phrase based on a frequency of appearance of the candidate phrase in the set of recorded interactions determined using the generated accuracy value, each of the candidate trend, the first candidate trend, and the second candidate trend comprising a series of numbers of interactions per time unit for each of a series of time units; calculating, using the computer processor, a correlation level for the candidate trend based on the candidate trend and the base trend, wherein the correlation level quantifies a difference in a behavior of the candidate trend and the base trend; if the correlation level is greater than a threshold level then including, using the computer processor, the candidate phrase in the base category; and displaying to the user the candidate phrase. 4. The method of claim 1 , wherein generating the candidate trend includes ascertaining that the candidate trend is different from a trend of the number of interactions per time period. | 0.77657 |
7,565,281 | 1 | 16 | 1. A computer natural language translation system, comprising: means for inputting source language text; means for outputting target language text; and transfer means for generating said target language text from said source language text using stored translation data generated from examples of source and corresponding target language texts, wherein said stored translation data comprises a plurality of translation units, each unit comprising: respective surface data representative of the order of occurrence of language units of said source and target languages; and respective dependency data related to the semantic relationship between said language units of said source and target languages; the dependency data of language units of said source language being aligned with corresponding dependency data of language units of said target language, and wherein said transfer means comprises: (i) analyzing means for analyzing said source language text using said surface data of said source language; (ii) generating means for generating said target language text using said surface data of said target language; and (iii) transforming means for transforming the analysis of said source text into an analysis for said target language using said dependency data. | 1. A computer natural language translation system, comprising: means for inputting source language text; means for outputting target language text; and transfer means for generating said target language text from said source language text using stored translation data generated from examples of source and corresponding target language texts, wherein said stored translation data comprises a plurality of translation units, each unit comprising: respective surface data representative of the order of occurrence of language units of said source and target languages; and respective dependency data related to the semantic relationship between said language units of said source and target languages; the dependency data of language units of said source language being aligned with corresponding dependency data of language units of said target language, and wherein said transfer means comprises: (i) analyzing means for analyzing said source language text using said surface data of said source language; (ii) generating means for generating said target language text using said surface data of said target language; and (iii) transforming means for transforming the analysis of said source text into an analysis for said target language using said dependency data. 16. A machine readable storage medium containing computer program code which, when executed on a computer, causes said computer to act as the system of claim 1 . | 0.731667 |
9,171,063 | 1 | 5 | 1. A method comprising: by one or more computing devices, accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to an object associated with the online social network, each object being of a particular object type; by one or more computing devices, receiving a search query from the first user; by one or more computing devices, determining one or more search terms based on the received search query, each search term comprising a prefix and a suffix, wherein each prefix corresponds to an edge type and an object type of the social graph, and wherein each suffix corresponds to a particular node of the plurality of nodes; by one or more computing devices, for each of the search terms: generating a first binary number based on the each search term's prefix and suffix; and accessing and retrieving one or more search results of the each search term from one or more data stores by hashing the first binary number, wherein each search result corresponds to a node of the plurality of second nodes; and by one or more computing devices, aggregating search results of the respective search terms. | 1. A method comprising: by one or more computing devices, accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to an object associated with the online social network, each object being of a particular object type; by one or more computing devices, receiving a search query from the first user; by one or more computing devices, determining one or more search terms based on the received search query, each search term comprising a prefix and a suffix, wherein each prefix corresponds to an edge type and an object type of the social graph, and wherein each suffix corresponds to a particular node of the plurality of nodes; by one or more computing devices, for each of the search terms: generating a first binary number based on the each search term's prefix and suffix; and accessing and retrieving one or more search results of the each search term from one or more data stores by hashing the first binary number, wherein each search result corresponds to a node of the plurality of second nodes; and by one or more computing devices, aggregating search results of the respective search terms. 5. The method of claim 1 , wherein a social-networking system comprises the computing devices and the data stores. | 0.877944 |
10,089,985 | 1 | 17 | 1. A method of providing content upon request, the method comprising: receiving, from a first user, a configuration for a guide application, the guide application being configured for use by a second user, the second user being different than the first user; receiving, from the first user, authorization for the guide application to return search results for specific content; storing, in a database, searches and content selections of the specific content; receiving, from the second user, a request to open the guide application on a user device; and via the guide application: receiving a search request for items of content, the second user selecting a first selectable graphical icon among a plurality of first selectable graphical icons, and the second user selecting, based on a selection of the first selectable graphical icon, a second selectable graphical icon among a plurality of second selectable graphical icons, the search request for the items of content being received based on a selection of the second selectable graphical icon; recognizing, by a processor of the user device, a pattern of the content selections stored in the database; modifying, by the processor and based on recognition of the pattern, the search request before a search algorithm searches for the items of content to return in response to the search request; determining, based on the search request modified by the processor and from the specific content authorized by the first user, a plurality of listings for content; and converting text describing the plurality of listings to corresponding speech describing the plurality of listings. | 1. A method of providing content upon request, the method comprising: receiving, from a first user, a configuration for a guide application, the guide application being configured for use by a second user, the second user being different than the first user; receiving, from the first user, authorization for the guide application to return search results for specific content; storing, in a database, searches and content selections of the specific content; receiving, from the second user, a request to open the guide application on a user device; and via the guide application: receiving a search request for items of content, the second user selecting a first selectable graphical icon among a plurality of first selectable graphical icons, and the second user selecting, based on a selection of the first selectable graphical icon, a second selectable graphical icon among a plurality of second selectable graphical icons, the search request for the items of content being received based on a selection of the second selectable graphical icon; recognizing, by a processor of the user device, a pattern of the content selections stored in the database; modifying, by the processor and based on recognition of the pattern, the search request before a search algorithm searches for the items of content to return in response to the search request; determining, based on the search request modified by the processor and from the specific content authorized by the first user, a plurality of listings for content; and converting text describing the plurality of listings to corresponding speech describing the plurality of listings. 17. The method of claim 1 , wherein the guide application used to accept the search request is downloaded to the user device from an online store. | 0.782738 |
5,519,866 | 10 | 11 | 10. An apparatus for use on a computer system with a memory for incrementally linking a user-modified part of a computer program with previously compiled and linked parts of the computer program, the computer program being comprised of source code stored in the memory and the apparatus comprising: (a) means for storing in the memory a user-created model of the computer program the model comprising an ordered collection of components, each of the collection of components having a source code property referencing a portion of the source code in the memory, an object code property specifying a portion of the memory and client information identifying others of the collection of components which must be changed when the each component is changed; (b) first means for compiling and linking the source code portions in each of the collection of components to store executable object code in the memory portions specified by the object code properties of each of the collection of components; (c) means responsive to a user request for modifying a first portion of the source code and for identifying one of the collection of components having a source code property which references the first source code portion; (d) means for accessing the client information of the one component to identify others of the collection of components which must be changed; and (e) second means, responsive to the means for accessing, for concurrently compiling and linking the one component and all of the other components that must be changed to store new executable object code in the memory portions specified by the object code properties of the one component and the other components identified by the accessing means. | 10. An apparatus for use on a computer system with a memory for incrementally linking a user-modified part of a computer program with previously compiled and linked parts of the computer program, the computer program being comprised of source code stored in the memory and the apparatus comprising: (a) means for storing in the memory a user-created model of the computer program the model comprising an ordered collection of components, each of the collection of components having a source code property referencing a portion of the source code in the memory, an object code property specifying a portion of the memory and client information identifying others of the collection of components which must be changed when the each component is changed; (b) first means for compiling and linking the source code portions in each of the collection of components to store executable object code in the memory portions specified by the object code properties of each of the collection of components; (c) means responsive to a user request for modifying a first portion of the source code and for identifying one of the collection of components having a source code property which references the first source code portion; (d) means for accessing the client information of the one component to identify others of the collection of components which must be changed; and (e) second means, responsive to the means for accessing, for concurrently compiling and linking the one component and all of the other components that must be changed to store new executable object code in the memory portions specified by the object code properties of the one component and the other components identified by the accessing means. 11. The apparatus of claim 10 wherein the source code in the modified component comprises an interface portion for communicating with the client components and an implementation portion comprising a remainder of the source code in the modified component which does not communicate with the client components and wherein the modified component includes an interface attribute, describing the interface portion, and an implementation attribute, describing the implementation portion, and wherein the user request receiving and processing means includes: means responsive to a modification of the implementation portion for updating the implementation attribute; means responsive to a modification of the interface portion for updating the interface attribute; and wherein the second compiling and linking means is responsive to the interface attribute and to the implementation attribute for concurrently compiling and incrementally linking only the modified component when only the implementation portion is modified and for concurrently compiling and incrementally linking the modified component and the client components when the interface portion is modified. | 0.5 |
7,831,534 | 2 | 8 | 2. A computer-implemented method for building a polyhierarchical classification of objects, comprising: a) identifying a plurality of criteria for specializing the objects based on their properties, wherein each criterion of the plurality of criteria is defined by a set of mutually exclusive attributes, wherein each attribute describes one or more properties of the objects; b) recurrently defining a root category for each criterion in terms of an attributive expression representing a logical composition of one or more attributes of criteria whose root categories have been previously defined in the recurrent sequence, or the empty attributive expression; wherein no one criterion participates in the definition of its own root category, and each attributive expression encodes a sequence of specializations by criteria so that the root category of each following criterion includes the category represented by the sequence of all previous specializations; c) storing in a computer-readable medium the plurality of criteria and their root categories in the form of attributive expressions; and d) using the stored plurality of criteria for polyhierachically structuring, updating and accessing information associated with the objects. | 2. A computer-implemented method for building a polyhierarchical classification of objects, comprising: a) identifying a plurality of criteria for specializing the objects based on their properties, wherein each criterion of the plurality of criteria is defined by a set of mutually exclusive attributes, wherein each attribute describes one or more properties of the objects; b) recurrently defining a root category for each criterion in terms of an attributive expression representing a logical composition of one or more attributes of criteria whose root categories have been previously defined in the recurrent sequence, or the empty attributive expression; wherein no one criterion participates in the definition of its own root category, and each attributive expression encodes a sequence of specializations by criteria so that the root category of each following criterion includes the category represented by the sequence of all previous specializations; c) storing in a computer-readable medium the plurality of criteria and their root categories in the form of attributive expressions; and d) using the stored plurality of criteria for polyhierachically structuring, updating and accessing information associated with the objects. 8. The method of claim 2 , further comprising permanently storing the classification as a template classification such that it can be associated with a particular set of objects. | 0.911178 |
5,546,575 | 55 | 60 | 55. A database system, which comprises: a computer system, comprising a random access memory, a mass storage memory, an input device, an output device, a processor and a bus for coupling the random access memory, the mass storage memory, the input device, the output device and the processor; an operating system, executable by the processor, for controlling the functions of the computer system; a database structure, comprising a database image residing in the mass storage memory and a translation table and a record information table residing in the random access memory, the database image comprising a plurality of partitions, the partitions comprising a plurality of subpartitions, the subpartitions comprising a plurality of compacted records, the compacted records comprising a plurality of fields, the fields comprising a plurality of compacted data values, the record information table equating the partitions and subpartitions to a plurality of record type designations, such that a particular one of the partitions comprises a subset of the compacted records all having an identical length and a particular one of the subpartitions comprises a subset of the compacted records all having a particular one of the record type designations, the particular record type designation specifying a plurality of pack methods dependent on the fields; an access subsystem, executable by the processor, for performing a user request entered on the input device, which comprises reading a subset of the compacted records from the database image, reading the compacted data values from these compacted records, translating the compacted data values into the uncompacted data values and outputting the uncompacted data values to the output device. | 55. A database system, which comprises: a computer system, comprising a random access memory, a mass storage memory, an input device, an output device, a processor and a bus for coupling the random access memory, the mass storage memory, the input device, the output device and the processor; an operating system, executable by the processor, for controlling the functions of the computer system; a database structure, comprising a database image residing in the mass storage memory and a translation table and a record information table residing in the random access memory, the database image comprising a plurality of partitions, the partitions comprising a plurality of subpartitions, the subpartitions comprising a plurality of compacted records, the compacted records comprising a plurality of fields, the fields comprising a plurality of compacted data values, the record information table equating the partitions and subpartitions to a plurality of record type designations, such that a particular one of the partitions comprises a subset of the compacted records all having an identical length and a particular one of the subpartitions comprises a subset of the compacted records all having a particular one of the record type designations, the particular record type designation specifying a plurality of pack methods dependent on the fields; an access subsystem, executable by the processor, for performing a user request entered on the input device, which comprises reading a subset of the compacted records from the database image, reading the compacted data values from these compacted records, translating the compacted data values into the uncompacted data values and outputting the uncompacted data values to the output device. 60. A database system according to claim 55, further comprising: a database management system; and an uncompacted database accessible by the database management system, such that deletes, inserts and updates are performed both by the access subsystem on the database image and by the database management system on the uncompacted database, a subset of database access requests are processed only by the access subsystem on the database image and database access requests which are not in the subset are processed only by the database management system on the uncompacted database. | 0.555896 |
9,472,113 | 6 | 8 | 6. The computer-implemented method of claim 1 , wherein the user perceptible cue is at least one of a visual cue or a tactile cue. | 6. The computer-implemented method of claim 1 , wherein the user perceptible cue is at least one of a visual cue or a tactile cue. 8. The computer implemented method of claim 6 , wherein the user perceptible cue is a tactile cue comprising at least one of electrical pulses or thermopneumatic actuators. | 0.522222 |
8,875,249 | 15 | 16 | 15. A non-transitory computer-readable storage medium storing instructions, the instructions which when executed by one or more processors cause the one or more processors to minimize storage time for security credentials for a secure crawl, the instructions comprising: instructions for initiating, at a computer system, a crawl of a secure source; instructions for examining, in response to initiating the crawl of the secure source, a setting for the secure source, the setting selected by an administrator or user specifying whether security credentials including a temporary password for the secure source are to be stored temporarily; instructions for determining, in response to examining the setting, that security credentials for the secure source are required to be stored temporarily, and prompting, at the computer system, for security credentials including the temporary password at a time of the crawl, wherein the security credentials including the temporary password are associated with said administrator or user; instructions for writing, at the computer system, the security credentials including the temporary password to temporary storage; instructions for crawling a plurality of documents obtained from the secure source using the security credentials including the temporary password, and indexing at the computer system the plurality of documents; if the crawl is interrupted before completion, instructions for deleting, at the computer system, the security credentials including the temporary password after the interruption; and if the crawl is completed, instructions for deleting, at the computer system, the security credentials including the temporary password from temporary storage when no longer needed for the crawling. | 15. A non-transitory computer-readable storage medium storing instructions, the instructions which when executed by one or more processors cause the one or more processors to minimize storage time for security credentials for a secure crawl, the instructions comprising: instructions for initiating, at a computer system, a crawl of a secure source; instructions for examining, in response to initiating the crawl of the secure source, a setting for the secure source, the setting selected by an administrator or user specifying whether security credentials including a temporary password for the secure source are to be stored temporarily; instructions for determining, in response to examining the setting, that security credentials for the secure source are required to be stored temporarily, and prompting, at the computer system, for security credentials including the temporary password at a time of the crawl, wherein the security credentials including the temporary password are associated with said administrator or user; instructions for writing, at the computer system, the security credentials including the temporary password to temporary storage; instructions for crawling a plurality of documents obtained from the secure source using the security credentials including the temporary password, and indexing at the computer system the plurality of documents; if the crawl is interrupted before completion, instructions for deleting, at the computer system, the security credentials including the temporary password after the interruption; and if the crawl is completed, instructions for deleting, at the computer system, the security credentials including the temporary password from temporary storage when no longer needed for the crawling. 16. The non-transitory computer-readable storage medium according to claim 15 , wherein: instructions for deleting the security credentials including the temporary password includes instructions for performing a callback at the end of the crawling. | 0.605096 |
8,903,829 | 11 | 14 | 11. A system for indexing a structured document, the system comprising: a processor-based database management system, which when executed on a computer system will cause the processor to: store a structured document in its native format; provide a multi-path index definition associated with a data model corresponding to a structured document, the multi-path index definition including a first sub-path definition that covers a first plurality of descendant elements of a root element of the data model and a second sub-path definition that covers a second plurality of descendant elements of the root element of the data model, the multi-path index definition further including at least two index properties from a set of index properties that specifies a type of search to be performed for the content of each of the descendant elements covered by the sub-path definitions, the set of index properties including at least a full-text search, a value comparison, an element type definition, an enumerate repeating elements, and a start end marker; receive a first path expression representing a first descendant element of one of the first plurality of descendant elements or the second plurality of descendant elements from a first structured document received by the database management system; determine that the first descendant element is covered by one of the first sub-path definition based on the first path expression or the second sub-path definition based on the first path expression; index the first descendant element according to the at least two index properties to generate a path-value pair comprising the first path expression and a value associated with the first descendant element; and store the path-value pair and a reference to the first structured document in a record in an inverted multi-path index associated with the multi-path index definition. | 11. A system for indexing a structured document, the system comprising: a processor-based database management system, which when executed on a computer system will cause the processor to: store a structured document in its native format; provide a multi-path index definition associated with a data model corresponding to a structured document, the multi-path index definition including a first sub-path definition that covers a first plurality of descendant elements of a root element of the data model and a second sub-path definition that covers a second plurality of descendant elements of the root element of the data model, the multi-path index definition further including at least two index properties from a set of index properties that specifies a type of search to be performed for the content of each of the descendant elements covered by the sub-path definitions, the set of index properties including at least a full-text search, a value comparison, an element type definition, an enumerate repeating elements, and a start end marker; receive a first path expression representing a first descendant element of one of the first plurality of descendant elements or the second plurality of descendant elements from a first structured document received by the database management system; determine that the first descendant element is covered by one of the first sub-path definition based on the first path expression or the second sub-path definition based on the first path expression; index the first descendant element according to the at least two index properties to generate a path-value pair comprising the first path expression and a value associated with the first descendant element; and store the path-value pair and a reference to the first structured document in a record in an inverted multi-path index associated with the multi-path index definition. 14. The system of claim 11 wherein the first plurality of descendant elements is automatically indexed according to a first index property of the first sub-path definition and the second plurality of descendant elements is automatically indexed according to a second index property of the second sub-path definition. | 0.707948 |
8,447,702 | 5 | 7 | 5. The system of claim 1 , wherein said domain name appraisal module is further configured to calculate said popularity value for said domain name by: i) receiving, from one or more search engines, one or more search result metrics measured by said one or more search engines; ii) generating a search engine metrics value comprising said one or more search result metrics; iii) receiving, from one or more search engine optimization monitoring services or software, one or more search tracking metrics tracking, at regular intervals, an estimated number of searches of a plurality of words via said one or more search engine optimization monitoring services or software; and iv) generating a search tracking metrics value comprising said one or more search tracking metrics. | 5. The system of claim 1 , wherein said domain name appraisal module is further configured to calculate said popularity value for said domain name by: i) receiving, from one or more search engines, one or more search result metrics measured by said one or more search engines; ii) generating a search engine metrics value comprising said one or more search result metrics; iii) receiving, from one or more search engine optimization monitoring services or software, one or more search tracking metrics tracking, at regular intervals, an estimated number of searches of a plurality of words via said one or more search engine optimization monitoring services or software; and iv) generating a search tracking metrics value comprising said one or more search tracking metrics. 7. The system of claim 5 , wherein said domain name appraisal module is further configured to: i) write said search engine metrics value to a search engine metrics data field in a record for said domain name stored in a database communicatively coupled to said network; ii) write said search tracking metrics value to a search tracking metrics data field in said record; and iii) write said popularity value to a popularity data field in said record. | 0.778543 |
8,612,293 | 1 | 13 | 1. An advertising targeting system configured to generate a set of targeting keywords that target a specific offer to a desired audience, the system comprising: a targeting server system comprising a network interface and a database; wherein the targeting server system is configured to: obtain a set of offer keywords comprising the attributes of at least one specific offer within an advertising campaign obtain a set of member profile data from at least one server that forms part of an online social network using the network interface, where a member profile in the obtained member profile data describes activities performed on the online social network associated with the member profiles; determine member profile affinity metadata for a subset of the set of member profile data, where the member profile affinity metadata describes the affinity of a member profile with respect to a set of specific keywords; generate a member affinity database stored using the database and containing the member profiles and the determined member profile affinity metadata; and identify targeting keywords within the specific keywords based on the offer keywords and the member affinity database by: clustering the member profiles within the member affinity database based on the member profile affinity metadata and the offer keywords; selecting at least one member profile cluster based on the affinity of the member profiles within the member profile cluster to at least one of the offer keywords; identifying at least one additional keyword within the specific keywords based on the affinity of the member profiles within the selected at least one member profile cluster to the at least one additional keyword; and determining a set of targeting keywords based on the offer keywords and the additional keywords. | 1. An advertising targeting system configured to generate a set of targeting keywords that target a specific offer to a desired audience, the system comprising: a targeting server system comprising a network interface and a database; wherein the targeting server system is configured to: obtain a set of offer keywords comprising the attributes of at least one specific offer within an advertising campaign obtain a set of member profile data from at least one server that forms part of an online social network using the network interface, where a member profile in the obtained member profile data describes activities performed on the online social network associated with the member profiles; determine member profile affinity metadata for a subset of the set of member profile data, where the member profile affinity metadata describes the affinity of a member profile with respect to a set of specific keywords; generate a member affinity database stored using the database and containing the member profiles and the determined member profile affinity metadata; and identify targeting keywords within the specific keywords based on the offer keywords and the member affinity database by: clustering the member profiles within the member affinity database based on the member profile affinity metadata and the offer keywords; selecting at least one member profile cluster based on the affinity of the member profiles within the member profile cluster to at least one of the offer keywords; identifying at least one additional keyword within the specific keywords based on the affinity of the member profiles within the selected at least one member profile cluster to the at least one additional keyword; and determining a set of targeting keywords based on the offer keywords and the additional keywords. 13. The advertising targeting system of claim 1 , wherein the targeting server system is further configured to select a set of targeting keywords using set completion. | 0.769972 |
7,827,032 | 1 | 2 | 1. A method for adapting a model for a speech recognition system using an adaptation process, the method comprising: with an apparatus using at least one hardware-implemented processor, determining an error rate, corresponding to either recognition of instances of a word or recognition of instances of various words among a set of words; and adjusting an adaptation process for the model for the word or various models for the various words, based on the error rate. | 1. A method for adapting a model for a speech recognition system using an adaptation process, the method comprising: with an apparatus using at least one hardware-implemented processor, determining an error rate, corresponding to either recognition of instances of a word or recognition of instances of various words among a set of words; and adjusting an adaptation process for the model for the word or various models for the various words, based on the error rate. 2. The method of claim 1 , wherein the error rate is based on actual errors determined from comparing a transcript of words input to the system with corresponding hypotheses generated by the system. | 0.633333 |
8,082,220 | 1 | 4 | 1. A computer-readable storage medium comprising a set of instructions that when executed by a processor in a computing apparatus cause the processor to: construct in a computing system for each of a plurality of independent sub-problems an abstract graph corresponding thereto, wherein the plurality of independent sub-problems represent a main problem, wherein each abstract graph comprises an ordered set of nodes, wherein a first node of a first abstract graph of the abstract graphs is associated with a second node of a second abstract graph of the abstract graphs; at the first node, determine if available data can be used to solve the first abstract graph to resolve the sub-problem corresponding thereto; and if the available data cannot be used to resolve the sub-problem corresponding to the first abstract graph, switch to the second node for resolving the sub-problem corresponding to the second abstract graph. | 1. A computer-readable storage medium comprising a set of instructions that when executed by a processor in a computing apparatus cause the processor to: construct in a computing system for each of a plurality of independent sub-problems an abstract graph corresponding thereto, wherein the plurality of independent sub-problems represent a main problem, wherein each abstract graph comprises an ordered set of nodes, wherein a first node of a first abstract graph of the abstract graphs is associated with a second node of a second abstract graph of the abstract graphs; at the first node, determine if available data can be used to solve the first abstract graph to resolve the sub-problem corresponding thereto; and if the available data cannot be used to resolve the sub-problem corresponding to the first abstract graph, switch to the second node for resolving the sub-problem corresponding to the second abstract graph. 4. The computer-readable storage medium of claim 1 , wherein the association is made according to association rules. | 0.725118 |
8,402,371 | 1 | 15 | 1. A method for embedding covert data in a text document, the method comprising: providing the document with multiple characters that include a first character that occurs in first and second occurrences; analyzing a frequency of the multiple characters; selecting the first character from the multiple characters in response to the first character occurring most frequently in the multiple characters; selecting the first occurrence of the first character as a reference character and the second occurrence of the first character as a rotatable character; altering a rotational orientation of the rotatable character to produce an altered character with a predetermined rotation with respect to the reference character, wherein the rotation represents the embedded covert data; and formatting the document to produce a formatted document based on the altered character. | 1. A method for embedding covert data in a text document, the method comprising: providing the document with multiple characters that include a first character that occurs in first and second occurrences; analyzing a frequency of the multiple characters; selecting the first character from the multiple characters in response to the first character occurring most frequently in the multiple characters; selecting the first occurrence of the first character as a reference character and the second occurrence of the first character as a rotatable character; altering a rotational orientation of the rotatable character to produce an altered character with a predetermined rotation with respect to the reference character, wherein the rotation represents the embedded covert data; and formatting the document to produce a formatted document based on the altered character. 15. A method as claimed in claim 1 , wherein the rotation of the altered character represents a binary sequence. | 0.932854 |
7,818,713 | 22 | 23 | 22. The process according to claim 21 , wherein said receiving step further comprises the steps of: defining said domain context that said solution is to be used in, said domain context defined including one or more sub-domains; assigning a valid range of specification values for each of said defined set of specifications inputted for said domain context defined that said solution is to be used in; defining said attributes based on said domain context defined for said solution; and storing said domain context defined, said valid range of specification values assigned and said attributes defined in said repository. | 22. The process according to claim 21 , wherein said receiving step further comprises the steps of: defining said domain context that said solution is to be used in, said domain context defined including one or more sub-domains; assigning a valid range of specification values for each of said defined set of specifications inputted for said domain context defined that said solution is to be used in; defining said attributes based on said domain context defined for said solution; and storing said domain context defined, said valid range of specification values assigned and said attributes defined in said repository. 23. The process according to claim 22 , wherein said determining step further comprises the steps of: mapping said one or more specifications to said each attribute of said defined set of attributes inputted to form relationship mappings; and storing said relationship mappings formed in said repository. | 0.5 |
9,361,586 | 1 | 4 | 1. A method to facilitate pattern recognition comprising: processing a set of vectors into feature vectors; wherein the processing comprises employing machine learning component adjusted parameters; wherein the machine learning component adjusted parameters are adjusted based at least in part on at least partially conflicting learning objectives including an input fidelity objective and an invariance objective, and are further adjusted at least in part by adding one or more scaled derivatives of the input fidelity objective approximately concurrently with one or more scaled derivatives of the invariance objective to one or more of the machine learning component adjusted parameters. | 1. A method to facilitate pattern recognition comprising: processing a set of vectors into feature vectors; wherein the processing comprises employing machine learning component adjusted parameters; wherein the machine learning component adjusted parameters are adjusted based at least in part on at least partially conflicting learning objectives including an input fidelity objective and an invariance objective, and are further adjusted at least in part by adding one or more scaled derivatives of the input fidelity objective approximately concurrently with one or more scaled derivatives of the invariance objective to one or more of the machine learning component adjusted parameters. 4. The method of claim 1 wherein the input fidelity objective comprises a likelihood objective. | 0.6875 |
9,946,510 | 6 | 7 | 6. The mobile terminal of claim 1 , wherein the controller is further configured to cause the touch screen to display a second pop-up window including a text pasting mode for converting the received voice signal to the text to be displayed and an audio data pasting mode for causing displaying of a playback icon for playing the received voice signal such that one of the text pasting mode and the audio data pasting mode is selected via the second pop-up window. | 6. The mobile terminal of claim 1 , wherein the controller is further configured to cause the touch screen to display a second pop-up window including a text pasting mode for converting the received voice signal to the text to be displayed and an audio data pasting mode for causing displaying of a playback icon for playing the received voice signal such that one of the text pasting mode and the audio data pasting mode is selected via the second pop-up window. 7. The mobile terminal of claim 6 , wherein the controller is further configured to convert the received voice signal to the text in response to selection of the text pasting mode from the second pop-up window such that the converted text is displayed at the specific position of the execution screen. | 0.5 |
6,088,699 | 12 | 13 | 12. The medium of claim 11, where the data object types further include textual data objects. | 12. The medium of claim 11, where the data object types further include textual data objects. 13. The medium of claim 12, where each dictionary includes multiple sub-dictionaries each sub-dictionary exclusively containing dictionary index codes of a single type of data object. | 0.740057 |
9,240,178 | 18 | 19 | 18. The computing device of claim 12 , wherein the second TTS output comprises references to units stored in a unit database associated with the second voice corpus. | 18. The computing device of claim 12 , wherein the second TTS output comprises references to units stored in a unit database associated with the second voice corpus. 19. The computing device of claim 18 , wherein: determining the third TTS output comprises synthesizing speech using at least a portion of the references; and the third TTS output comprises the synthesized speech. | 0.5 |
7,805,710 | 21 | 22 | 21. The method of claim 20 , further comprising: identifying one or more dynamic target code portions amongst a plurality of portions of the target code produced by the first translator instance, wherein the dynamic target code portions are derived from dynamically generated portions of the subject code; and discarding the dynamic target code portions. | 21. The method of claim 20 , further comprising: identifying one or more dynamic target code portions amongst a plurality of portions of the target code produced by the first translator instance, wherein the dynamic target code portions are derived from dynamically generated portions of the subject code; and discarding the dynamic target code portions. 22. The method of claim 21 , further comprising selectively identifying, caching, identifying and discarding upon completing execution of the first translator instance. | 0.5 |
8,645,288 | 16 | 17 | 16. The computing device according to claim 15 , wherein: the items are web pages; and the learning component is further executed to generate the model based at least in part on features extracted from the training set of web pages, the features comprising at least one of: ranking features, uniform resource locator (URL) features, click features, graph propagation features, or document features. | 16. The computing device according to claim 15 , wherein: the items are web pages; and the learning component is further executed to generate the model based at least in part on features extracted from the training set of web pages, the features comprising at least one of: ranking features, uniform resource locator (URL) features, click features, graph propagation features, or document features. 17. The computing device according to claim 16 , further comprising a page selection component executed on the processor to apply the model to selecting the subset of web pages for indexing from a plurality of crawled web pages, the page selection component applying the model based at least in part on a graph representing the link relationships between the crawled web pages. | 0.5 |
8,091,067 | 39 | 40 | 39. A system for hosting a programming environment and processing user input comprising: an interaction environment executing in a virtual machine on a server; an information retrieval component provided by the interaction environment and in communication with a search index and a collection of information; and a user interface module provided by the interaction environment and in communication with the information retrieval component, the user interface module comprising: a transceiver receiving, during a first session between a user and an interaction environment, via one of a plurality of media gateways, a definition of an expression type, the definition specifying an expression format and a response type, and receiving, during a second session between a second user and the interaction environment, an expression having a semantic structure; a semantic evaluator identifying an expression format of the received expression as the expression format specified by the definition of the expression type, responsive to an evaluation of the semantic structure of the received expression; and a response generating component providing a response to the expression based on the identified expression format and responsive to an execution of a computer program associated with the response type specified by the definition of the expression type. | 39. A system for hosting a programming environment and processing user input comprising: an interaction environment executing in a virtual machine on a server; an information retrieval component provided by the interaction environment and in communication with a search index and a collection of information; and a user interface module provided by the interaction environment and in communication with the information retrieval component, the user interface module comprising: a transceiver receiving, during a first session between a user and an interaction environment, via one of a plurality of media gateways, a definition of an expression type, the definition specifying an expression format and a response type, and receiving, during a second session between a second user and the interaction environment, an expression having a semantic structure; a semantic evaluator identifying an expression format of the received expression as the expression format specified by the definition of the expression type, responsive to an evaluation of the semantic structure of the received expression; and a response generating component providing a response to the expression based on the identified expression format and responsive to an execution of a computer program associated with the response type specified by the definition of the expression type. 40. The system of claim 39 , wherein the interaction environment further comprises a collaborative web site. | 0.856383 |
8,397,157 | 1 | 8 | 1. A method comprising: accessing, in at least one of a memory device and a data storage device, a first data object and a second data object of a data structure, the data structure representing a page description language document that includes page description language document content and non-page description language document content included or referenced in data objects of the page description language document, the second data object being associated with the first data object; selecting, based on first content included in the first data object, a grammar rule included in a grammar, the grammar rule including a grammar rule item, the grammar being a descriptive specification composed of grammar rules used to computationally determine content types to facilitate selection of grammar rules suitable to translate electronic content to a desired form utilizing grammar rule items; based on second content included in the second data object, selecting the grammar rule item included in the grammar rule, the second content being non-page description language document content; based on the second content and the grammar rule item, executing instructions on a computer processor to generate a portion of a markup language document representation of the page description language document; and wherein the non-page description language document content is at least one of digital video, frames or sets of frames of digital video, digital audio, an animation, an image, and a media stream. | 1. A method comprising: accessing, in at least one of a memory device and a data storage device, a first data object and a second data object of a data structure, the data structure representing a page description language document that includes page description language document content and non-page description language document content included or referenced in data objects of the page description language document, the second data object being associated with the first data object; selecting, based on first content included in the first data object, a grammar rule included in a grammar, the grammar rule including a grammar rule item, the grammar being a descriptive specification composed of grammar rules used to computationally determine content types to facilitate selection of grammar rules suitable to translate electronic content to a desired form utilizing grammar rule items; based on second content included in the second data object, selecting the grammar rule item included in the grammar rule, the second content being non-page description language document content; based on the second content and the grammar rule item, executing instructions on a computer processor to generate a portion of a markup language document representation of the page description language document; and wherein the non-page description language document content is at least one of digital video, frames or sets of frames of digital video, digital audio, an animation, an image, and a media stream. 8. The method of claim 1 , wherein the first content included in the first data object includes a type of the second data object, the type matching a type of the grammar rule. | 0.68638 |
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