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9,916,379 | 11 | 15 | 11. The computer-readable storage medium of claim 10 , wherein said instructions further comprise instructions that when executed by the processor, cause the processor to: identify a first set of fields in the unstructured data to obtain field identification data from the unstructured data source, the unstructured data including text records, each of the fields in the first set of fields corresponding to a portion of text extracted from a portion of at least one of the text records; wherein generating the second query in the second query language associated with the unstructured data store includes generating the second query by using the identified first set of fields. | 11. The computer-readable storage medium of claim 10 , wherein said instructions further comprise instructions that when executed by the processor, cause the processor to: identify a first set of fields in the unstructured data to obtain field identification data from the unstructured data source, the unstructured data including text records, each of the fields in the first set of fields corresponding to a portion of text extracted from a portion of at least one of the text records; wherein generating the second query in the second query language associated with the unstructured data store includes generating the second query by using the identified first set of fields. 15. The computer-readable storage medium of claim 11 , wherein the first set of fields is identified by automatically identifying fields in the unstructured data as a function of formatting of the unstructured data. | 0.91899 |
8,570,614 | 15 | 17 | 15. The mail processing system of claim 12 , wherein scanning the document includes producing a current image of a background of the view through the aperture before or after the document is transported past the aperture, and wherein the current image of the background is part of the document image. | 15. The mail processing system of claim 12 , wherein scanning the document includes producing a current image of a background of the view through the aperture before or after the document is transported past the aperture, and wherein the current image of the background is part of the document image. 17. The mail processing system of claim 15 , wherein analyzing the document includes producing a current waveform corresponding to the current image of the background, comparing a reference waveform to the current waveform to determine, based on the comparison, that there is the dark obstruction in the document image or that there is the bright obstruction in the document image. | 0.797125 |
9,330,139 | 11 | 14 | 11. A communication device, including: a memory; at least one communications subsystem; and at least one processor configured to enable: receiving a first input comprising a first search keyword and at least one explicitly specified parameter value for use in a query to be transmitted to a first online service; in response to receiving a search command, generating a first query comprising the first search keyword and the at least one explicitly specified parameter value; transmitting the first query to the first online service; and storing the at least one explicitly specified parameter value in association with the first search keyword at the communication device; receiving a second input comprising a second search keyword for use in a query to be transmitted to the first online service or to another online service; and in response to receiving a further search command, generating a second query comprising the second search keyword; in response to determining that the second search keyword matches the first search keyword and that the second input does not include any explicitly specified parameter values, using one or more of the at least one explicitly specified parameter values associated with the first search keyword to modify the second query; and transmitting the modified second query to the first or other online service. | 11. A communication device, including: a memory; at least one communications subsystem; and at least one processor configured to enable: receiving a first input comprising a first search keyword and at least one explicitly specified parameter value for use in a query to be transmitted to a first online service; in response to receiving a search command, generating a first query comprising the first search keyword and the at least one explicitly specified parameter value; transmitting the first query to the first online service; and storing the at least one explicitly specified parameter value in association with the first search keyword at the communication device; receiving a second input comprising a second search keyword for use in a query to be transmitted to the first online service or to another online service; and in response to receiving a further search command, generating a second query comprising the second search keyword; in response to determining that the second search keyword matches the first search keyword and that the second input does not include any explicitly specified parameter values, using one or more of the at least one explicitly specified parameter values associated with the first search keyword to modify the second query; and transmitting the modified second query to the first or other online service. 14. The communication device of claim 11 , wherein the second search keyword is for use in a query to be transmitted to a second online service different from the first online service, and retrieving one or more of the at least one explicitly specified parameter value comprises retrieving those explicitly specified parameter values stored in association with the first search keyword that are acceptable to the second online service. | 0.790462 |
9,268,843 | 13 | 17 | 13. Non-transitory computer-readable media having computer-readable instructions recorded thereon, which when executed by a processor cause the processor to implement a method for generating a targeted list of entities interested in content of interest, the method comprising: receiving, by a computing device, a set of nouns characterizing content of interest, wherein at least one of the nouns characterizes the subject matter of the content of interest; querying a database with a query based on the set of nouns, the database being stored on computer readable media and having stored therein profiles including taxonomic nouns based on user access to content, the profiles being created by: a) assigning a set of taxonomic nouns based upon author-generated classification information of content accessed by a user; b) assigning a set of taxonomic nouns based upon user-generated tag characterization of a content accessed by a user; c) assigning a set of taxonomic nouns based on a search term that resulted in a user accessing content; d) assigning a set of taxonomic nouns based upon attributes related to the manner in which a user accessed content; and e) assigning a set of taxonomic nouns based upon a predetermined pattern rule applied to content accessed by a user; identifying, by a computing device, one or more matching profiles stored in the database that satisfy the query, at least one of the one or more matching profiles including one or more taxonomic nouns that match at least one of the nouns in the set of nouns characterizing the content of interest, and at least one of the one or more taxonomic nouns being based on a user-generated tag, generated by a user, that characterizes at least a portion of an item of content, the item of content having been accessed by the user that generated the user-generated tag; and creating a list of users associated with the matching profiles, the list including at least one user associated with a user profile that includes at least one of the one or more taxonomic nouns that is based on the user-generated tag characterizing the at least one item of content. | 13. Non-transitory computer-readable media having computer-readable instructions recorded thereon, which when executed by a processor cause the processor to implement a method for generating a targeted list of entities interested in content of interest, the method comprising: receiving, by a computing device, a set of nouns characterizing content of interest, wherein at least one of the nouns characterizes the subject matter of the content of interest; querying a database with a query based on the set of nouns, the database being stored on computer readable media and having stored therein profiles including taxonomic nouns based on user access to content, the profiles being created by: a) assigning a set of taxonomic nouns based upon author-generated classification information of content accessed by a user; b) assigning a set of taxonomic nouns based upon user-generated tag characterization of a content accessed by a user; c) assigning a set of taxonomic nouns based on a search term that resulted in a user accessing content; d) assigning a set of taxonomic nouns based upon attributes related to the manner in which a user accessed content; and e) assigning a set of taxonomic nouns based upon a predetermined pattern rule applied to content accessed by a user; identifying, by a computing device, one or more matching profiles stored in the database that satisfy the query, at least one of the one or more matching profiles including one or more taxonomic nouns that match at least one of the nouns in the set of nouns characterizing the content of interest, and at least one of the one or more taxonomic nouns being based on a user-generated tag, generated by a user, that characterizes at least a portion of an item of content, the item of content having been accessed by the user that generated the user-generated tag; and creating a list of users associated with the matching profiles, the list including at least one user associated with a user profile that includes at least one of the one or more taxonomic nouns that is based on the user-generated tag characterizing the at least one item of content. 17. The non-transitory computer-readable media of claim 13 , wherein the method further comprises sending an offer related to the content to be promoted to persons associated with profiles in the list of profiles. | 0.818878 |
8,086,557 | 1 | 15 | 1. A computer implemented method for providing a factuality assessment of a retrieved information source's statement comprising: with a processor: receiving a user's query which identifies an information source whose statements are to be retrieved; retrieving documents which refer to the information source; mapping statements in the retrieved documents to their authors; identifying as information source statements, the mapped statements that are mapped to an author which is compatible with the information source; for at least one of the information source's statements, assessing a factuality of the information source's statement according to the information source. | 1. A computer implemented method for providing a factuality assessment of a retrieved information source's statement comprising: with a processor: receiving a user's query which identifies an information source whose statements are to be retrieved; retrieving documents which refer to the information source; mapping statements in the retrieved documents to their authors; identifying as information source statements, the mapped statements that are mapped to an author which is compatible with the information source; for at least one of the information source's statements, assessing a factuality of the information source's statement according to the information source. 15. A computer program product comprising a non-transitory recording medium which encodes instructions which, when executed by a computer, perform the method of claim 1 . | 0.819533 |
7,646,868 | 10 | 16 | 10. An article comprising: a machine accessible medium containing instructions, which when executed, result in encrypting a clear text message into an obscured, encrypted message using a key phrase by partitioning the key phrase and the clear text message into separate words; determining an index value for each word of the key phrase, concatenating the index values together to form a key string, and partitioning the key string into sections of a first predetermined length; determining an index value for each word of the clear text message, concatenating the index values together to form a message string, and partitioning the message string into sections of a second predetermined length; for each key section and message section pair, concatenating the key section to the message section to form a cipher text section, and adding the cipher text section to a cipher text string; and for each section of the cipher text string, locating a row of a word matrix indexed by the cipher text section, randomly selecting a template from a template file, the template including a plurality of tags, obtaining one or more words from the word matrix row according to columns selected by the tags, and replacing the cipher text section with the obtained words according to the randomly selected template to form the obscured, encrypted message. | 10. An article comprising: a machine accessible medium containing instructions, which when executed, result in encrypting a clear text message into an obscured, encrypted message using a key phrase by partitioning the key phrase and the clear text message into separate words; determining an index value for each word of the key phrase, concatenating the index values together to form a key string, and partitioning the key string into sections of a first predetermined length; determining an index value for each word of the clear text message, concatenating the index values together to form a message string, and partitioning the message string into sections of a second predetermined length; for each key section and message section pair, concatenating the key section to the message section to form a cipher text section, and adding the cipher text section to a cipher text string; and for each section of the cipher text string, locating a row of a word matrix indexed by the cipher text section, randomly selecting a template from a template file, the template including a plurality of tags, obtaining one or more words from the word matrix row according to columns selected by the tags, and replacing the cipher text section with the obtained words according to the randomly selected template to form the obscured, encrypted message. 16. The article of claim 10 , wherein the first predetermined length is three characters, and the second predetermined length is two characters. | 0.844828 |
7,991,720 | 13 | 19 | 13. A non-transitory machine readable medium containing executable computer program instructions which when executed by a data processing system cause said system to perform a method to organize information in the data processing system, the method comprising: determining a mathematical representation of a document, wherein the document is an electronic mail received through an electronic mail system, wherein said document is not part of a collection of documents; comparing said mathematical representation of said document to a collective mathematical representation of the collection of documents; and categorizing said document as being associated with said collection based on said comparing, wherein the content of said document is not known to a user of said data processing system upon said categorizing. | 13. A non-transitory machine readable medium containing executable computer program instructions which when executed by a data processing system cause said system to perform a method to organize information in the data processing system, the method comprising: determining a mathematical representation of a document, wherein the document is an electronic mail received through an electronic mail system, wherein said document is not part of a collection of documents; comparing said mathematical representation of said document to a collective mathematical representation of the collection of documents; and categorizing said document as being associated with said collection based on said comparing, wherein the content of said document is not known to a user of said data processing system upon said categorizing. 19. A medium as in claim 13 , wherein said determining comprises: determining statistical data for non-stop words in said document; wherein said mathematical representation of a document is determined based on said statistical data. | 0.536 |
8,082,242 | 11 | 12 | 11. A device comprising: a memory to store instructions; and a processor to execute the instructions to: receive, independent of any search query and from a first user, a selection of one or more documents, where the one or more documents are used to form a plurality of custom content groups, index the one or more documents to form a custom search index for each of the plurality of custom content groups, where each custom search index is different from a web search index and any other custom search index associated with the plurality of content groups, receive, from a second, different user, a selection of one or more of the plurality of custom content groups, receive, from a client device associated with the second user, a search query, perform, based on the search query, a search of the web search index to identify web search results, perform, based on the search query, a search of one or more of the custom search indexes associated with the selected one or more custom content groups to identify custom search results, generate a search result document that includes the web search results, the custom search results, and a plurality of advertisements presented within at least a first area and a second area of the search result document, where the first area is distinct from the second area within the search result document, where the web search results and one or more of the custom search results are included within the first area, and where the advertisements and another one or more of the custom search results are included within the second area, and provide, to the client device, the search result document. | 11. A device comprising: a memory to store instructions; and a processor to execute the instructions to: receive, independent of any search query and from a first user, a selection of one or more documents, where the one or more documents are used to form a plurality of custom content groups, index the one or more documents to form a custom search index for each of the plurality of custom content groups, where each custom search index is different from a web search index and any other custom search index associated with the plurality of content groups, receive, from a second, different user, a selection of one or more of the plurality of custom content groups, receive, from a client device associated with the second user, a search query, perform, based on the search query, a search of the web search index to identify web search results, perform, based on the search query, a search of one or more of the custom search indexes associated with the selected one or more custom content groups to identify custom search results, generate a search result document that includes the web search results, the custom search results, and a plurality of advertisements presented within at least a first area and a second area of the search result document, where the first area is distinct from the second area within the search result document, where the web search results and one or more of the custom search results are included within the first area, and where the advertisements and another one or more of the custom search results are included within the second area, and provide, to the client device, the search result document. 12. The device of claim 11 , where the processor, when receiving the selection of the one or more custom content groups, is further to: determine at least one of the plurality of custom content groups that the second user is permitted to access, and automatically select the at least one custom content group that the second user is permitted to access. | 0.827637 |
8,392,190 | 27 | 30 | 27. A non-transitory computer-readable memory comprising computer-readable instructions, which when executed cause a processor to perform steps comprising: performing speech recognition on digitized speech using a non-native acoustic model trained with non-native speech to generate word hypotheses for the digitized speech; performing time alignment between the digitized speech and the word hypotheses utilizing a reference acoustic model trained with native-quality speech; calculating statistics regarding individual words and phonemes of the word hypotheses based on said alignment; calculating a plurality of features for use in assessing pronunciation of the speech based on the statistics; calculating an assessment score based on one or more of the calculated features; and storing the assessment score in a computer-readable memory. | 27. A non-transitory computer-readable memory comprising computer-readable instructions, which when executed cause a processor to perform steps comprising: performing speech recognition on digitized speech using a non-native acoustic model trained with non-native speech to generate word hypotheses for the digitized speech; performing time alignment between the digitized speech and the word hypotheses utilizing a reference acoustic model trained with native-quality speech; calculating statistics regarding individual words and phonemes of the word hypotheses based on said alignment; calculating a plurality of features for use in assessing pronunciation of the speech based on the statistics; calculating an assessment score based on one or more of the calculated features; and storing the assessment score in a computer-readable memory. 30. The non-transitory computer-readable memory of claim 27 , wherein the instructions cause the processor to perform steps comprising: excluding words not reliably recognized in generating the word hypotheses from contributing to the assessment score. | 0.941313 |
9,507,945 | 1 | 17 | 1. A cloud based architecture for automated vulnerability identification demonstration comprising: distributed cloud processing circuitry including a plurality of processors configured to execute instructions for: receiving a program and employing a disassembler to disassemble the program; generating a function call tree for the program based on disassembly of the program; receiving an indication of a post condition for which analysis of the program is desired; transforming program statements into logical equations; simplifying the logical equations; propagating each path of the function call tree, based on post conditions, backwards via Dijkstra's weakest preconditions variant; analyzing aliases and processing loops to generate a precondition, wherein analyzing aliases is performed using an “if-then-else” expression through a satisfiability modulo theories (STM) solver and processing loops comprises unrolling each of the loops of each path; using an automated solver to determine whether the precondition is realizable and, if so, providing program inputs required to realize the precondition; identifying code vulnerabilities of the program based on the provided program inputs, wherein the code vulnerabilities would allow an attacker to introduce and execute code on a computer executing the program; and generating analysis results including at least the identified code vulnerabilities, the analysis results being providable to a user, in an interactive tool, using a user interface. | 1. A cloud based architecture for automated vulnerability identification demonstration comprising: distributed cloud processing circuitry including a plurality of processors configured to execute instructions for: receiving a program and employing a disassembler to disassemble the program; generating a function call tree for the program based on disassembly of the program; receiving an indication of a post condition for which analysis of the program is desired; transforming program statements into logical equations; simplifying the logical equations; propagating each path of the function call tree, based on post conditions, backwards via Dijkstra's weakest preconditions variant; analyzing aliases and processing loops to generate a precondition, wherein analyzing aliases is performed using an “if-then-else” expression through a satisfiability modulo theories (STM) solver and processing loops comprises unrolling each of the loops of each path; using an automated solver to determine whether the precondition is realizable and, if so, providing program inputs required to realize the precondition; identifying code vulnerabilities of the program based on the provided program inputs, wherein the code vulnerabilities would allow an attacker to introduce and execute code on a computer executing the program; and generating analysis results including at least the identified code vulnerabilities, the analysis results being providable to a user, in an interactive tool, using a user interface. 17. The cloud based architecture of claim 1 , wherein receiving the indication of the post condition comprises receiving a user input defining the post condition. | 0.849722 |
7,965,293 | 33 | 34 | 33. A digital image processing device comprising a circuit for: executing a pre-scan of a document, on which document the user has marked a plurality of document blocks, and creating pre-scan image data from which pre-scan image data the plurality of document blocks that is marked by the user are detected; extracting the plurality of document blocks that are digital image data representing a portion of the scanned document, the plurality of document blocks includes document image data and background image data, the document image data representing some of the document images on the scanned document, wherein all the document image data in the extracted plurality of document blocks represents fewer document images than are present in the scanned document; generating character code data from character image data within the plurality of document blocks; reconstructing the plurality of document blocks into a single document block in a specific shape based on the plurality of extracted document blocks; and laying out the character code data within the reconstructed document block to create a layout image. | 33. A digital image processing device comprising a circuit for: executing a pre-scan of a document, on which document the user has marked a plurality of document blocks, and creating pre-scan image data from which pre-scan image data the plurality of document blocks that is marked by the user are detected; extracting the plurality of document blocks that are digital image data representing a portion of the scanned document, the plurality of document blocks includes document image data and background image data, the document image data representing some of the document images on the scanned document, wherein all the document image data in the extracted plurality of document blocks represents fewer document images than are present in the scanned document; generating character code data from character image data within the plurality of document blocks; reconstructing the plurality of document blocks into a single document block in a specific shape based on the plurality of extracted document blocks; and laying out the character code data within the reconstructed document block to create a layout image. 34. A digital image processing device as claimed in claim 33 , wherein the character code includes at least font size. | 0.897213 |
7,913,163 | 10 | 11 | 10. The method of claim 1 , wherein the tree of nodes includes a plurality of chunks corresponding to multiple semantically distinct regions in the pseudo-rendered document. | 10. The method of claim 1 , wherein the tree of nodes includes a plurality of chunks corresponding to multiple semantically distinct regions in the pseudo-rendered document. 11. The method of claim 10 , including assigning links in a first semantically distinct region a different weight than links in a second semantically distinct region in the document and performing a computation using said assigned weights. | 0.952333 |
8,200,649 | 13 | 14 | 13. A method performed by an image search engine to perform an image search, the method comprising the steps of: receiving an original search string from a server input; determining whether a thesaurus-based approach or a dictionary-based approach is selected; in response to determining that a thesaurus-based approach is selected: sending various queries out through an output of the image search engine to receive additional user input from a server input, the additional user input allowing the image search engine to select augmenting information from a hierarchical database within storage associated with the image search engine where that augmenting information can be used to augment the original search string into an augmented search string; performing a search of image databases using the augmented search string to generate a list of image search results from the image databases that correlate favorably with the augmented search string; and providing image search result information to an output of the server; in response to determining that that a dictionary-based approach is selected, parsing at least one dictionary word from the original search string; using the at least one dictionary word to access a dictionary database that finds related words for the at least one dictionary word, and using the related words to generate an augmented search string; performing a search of image databases using the augmented search string to generate a list of image search results from the image databases that correlate favorably with the augmented search string; and providing image search result information to an output of the server. | 13. A method performed by an image search engine to perform an image search, the method comprising the steps of: receiving an original search string from a server input; determining whether a thesaurus-based approach or a dictionary-based approach is selected; in response to determining that a thesaurus-based approach is selected: sending various queries out through an output of the image search engine to receive additional user input from a server input, the additional user input allowing the image search engine to select augmenting information from a hierarchical database within storage associated with the image search engine where that augmenting information can be used to augment the original search string into an augmented search string; performing a search of image databases using the augmented search string to generate a list of image search results from the image databases that correlate favorably with the augmented search string; and providing image search result information to an output of the server; in response to determining that that a dictionary-based approach is selected, parsing at least one dictionary word from the original search string; using the at least one dictionary word to access a dictionary database that finds related words for the at least one dictionary word, and using the related words to generate an augmented search string; performing a search of image databases using the augmented search string to generate a list of image search results from the image databases that correlate favorably with the augmented search string; and providing image search result information to an output of the server. 14. The method of claim 13 wherein the image search engine also uses the additional user input to set at least one logical construct of the augmented search string to optimize search results for a user. | 0.713068 |
9,053,703 | 1 | 2 | 1. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, cause the one or more processors to perform operations, the operations comprising: receiving, at a computer system, a request to generate or modify a target acoustic model for a target language; accessing, by the computer system, a source acoustic model for a source language, wherein the source acoustic model includes information that maps acoustic features of the source language to phonemes in a transformed feature space; aligning, using the source acoustic model in the transformed feature space, untransformed voice data in the target language with phonemes in a corresponding textual transcript to obtain aligned voice data, wherein the untransformed voice data is in an untransformed feature space; transforming the aligned voice data according to a particular transform operation using the source acoustic model to obtain transformed voice data; adapting the source acoustic model to the target language, using the untransformed voice data in the target language, to obtain an adapted acoustic model; and training, by the computer system, a target acoustic model for the target language using the transformed voice data and the adapted acoustic model; and providing the target acoustic model in association with the target language. | 1. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, cause the one or more processors to perform operations, the operations comprising: receiving, at a computer system, a request to generate or modify a target acoustic model for a target language; accessing, by the computer system, a source acoustic model for a source language, wherein the source acoustic model includes information that maps acoustic features of the source language to phonemes in a transformed feature space; aligning, using the source acoustic model in the transformed feature space, untransformed voice data in the target language with phonemes in a corresponding textual transcript to obtain aligned voice data, wherein the untransformed voice data is in an untransformed feature space; transforming the aligned voice data according to a particular transform operation using the source acoustic model to obtain transformed voice data; adapting the source acoustic model to the target language, using the untransformed voice data in the target language, to obtain an adapted acoustic model; and training, by the computer system, a target acoustic model for the target language using the transformed voice data and the adapted acoustic model; and providing the target acoustic model in association with the target language. 2. The system of claim 1 , wherein the transformed feature space of the source acoustic model comprises a Constrained Maximum Likelihood Linear Regression (CMLLR) feature space that is generated from a CMLLR transform operation. | 0.711392 |
9,996,675 | 16 | 17 | 16. The at least one non-transitory computer-readable medium of claim 15 , wherein assigning the first word-class information comprises: searching for words of the medical report in a word dictionary memory having word-class information assigned to word information. | 16. The at least one non-transitory computer-readable medium of claim 15 , wherein assigning the first word-class information comprises: searching for words of the medical report in a word dictionary memory having word-class information assigned to word information. 17. The at least one non-transitory computer-readable medium of claim 16 , wherein assigning the first word-class information comprises finding the first word or word sequence in the word dictionary memory, and reading the assigned word-class information for the first word or word sequence from the word dictionary memory. | 0.860294 |
9,286,291 | 1 | 2 | 1. A computer usable program product comprising a computer usable storage device including computer usable code for disambiguation of dependent referring expression in natural language processing, the computer usable code comprising: computer usable code for selecting a portion of a document in a set of documents, the portion including a set of dependent referring expression instances; computer usable code for filtering the portion to identify an instance from a set of dependent referring expression instances by using a linguistic characteristic of the instance, the instance of dependent referring expression referring to a full expression, the full expression occurring in another document in the set of documents; computer usable code for locating the full expression in one member document in the set of documents by locating where the dependent referring expression is defined to be a stand-in for the full expression; and computer usable code for resolving, using a processor and a memory, the instance using the full expression such that information about the full expression is available at a location of the instance, wherein the computer usable code for resolving comprises: computer usable code for modifying the instance by adding data at a location of the instance, such that the data makes the information about the full expression accessible from the location of the instance; computer usable code for modifying the document to produce a second document, wherein the second document includes a mapping between the instance and the full expression in a metadata section of the second document, the metadata section being distinct from a location of the instance; and computer usable code for linking the instance to the mapping using a link, wherein the link is usable to make the information about the full expression accessible from the location of the instance. | 1. A computer usable program product comprising a computer usable storage device including computer usable code for disambiguation of dependent referring expression in natural language processing, the computer usable code comprising: computer usable code for selecting a portion of a document in a set of documents, the portion including a set of dependent referring expression instances; computer usable code for filtering the portion to identify an instance from a set of dependent referring expression instances by using a linguistic characteristic of the instance, the instance of dependent referring expression referring to a full expression, the full expression occurring in another document in the set of documents; computer usable code for locating the full expression in one member document in the set of documents by locating where the dependent referring expression is defined to be a stand-in for the full expression; and computer usable code for resolving, using a processor and a memory, the instance using the full expression such that information about the full expression is available at a location of the instance, wherein the computer usable code for resolving comprises: computer usable code for modifying the instance by adding data at a location of the instance, such that the data makes the information about the full expression accessible from the location of the instance; computer usable code for modifying the document to produce a second document, wherein the second document includes a mapping between the instance and the full expression in a metadata section of the second document, the metadata section being distinct from a location of the instance; and computer usable code for linking the instance to the mapping using a link, wherein the link is usable to make the information about the full expression accessible from the location of the instance. 2. The computer usable program product of claim 1 , further comprising: computer usable code for outputting a second set of documents corresponding to the set of documents, wherein a document in the second set of document corresponds to the document in the set of documents, and wherein the document in the second set of documents includes a modified form of the instance responsive to the resolving. | 0.501247 |
8,972,261 | 10 | 13 | 10. A computer-implemented method for voice transcription error reduction, comprising the steps of: obtaining speech utterances from a voice stream and assigning each speech utterance with a transcribed value and a confidence score; identifying as questionable utterances, those utterances with transcription values associated with lower confidence scores; selecting one of the questionable utterances and generating a pool of related utterances comprising the selected questionable utterance and a predetermined number of questionable utterances, wherein the predetermined number of questionable utterances are assigned transcribed values similar to the transcribed value of the selected questionable utterance and are from other voice streams; receiving a common transcribed value for a portion of the questionable utterances in the pool of related utterances; and generating using those transcribed values with high confidence scores and using the common transcribed value, a transcribed message, wherein the steps are performed by a suitably-programmed computer. | 10. A computer-implemented method for voice transcription error reduction, comprising the steps of: obtaining speech utterances from a voice stream and assigning each speech utterance with a transcribed value and a confidence score; identifying as questionable utterances, those utterances with transcription values associated with lower confidence scores; selecting one of the questionable utterances and generating a pool of related utterances comprising the selected questionable utterance and a predetermined number of questionable utterances, wherein the predetermined number of questionable utterances are assigned transcribed values similar to the transcribed value of the selected questionable utterance and are from other voice streams; receiving a common transcribed value for a portion of the questionable utterances in the pool of related utterances; and generating using those transcribed values with high confidence scores and using the common transcribed value, a transcribed message, wherein the steps are performed by a suitably-programmed computer. 13. A method according to claim 10 , further comprising: assigning a predetermined time period for generating the pool of related utterances. | 0.91637 |
10,146,773 | 1 | 6 | 1. A method using one or more computer processors, comprising: providing, using the one or more computer processors, a first message in a first language to a first transformation module in a sequence of computer-implemented transformation modules, each transformation module comprising executable instructions configured to be executed by the one or more computer processors for performing message transformation operations, wherein each subsequent transformation module in the sequence accepts, as input, an output of a preceding transformation module in the sequence and provides, as output, a respective transformed message, wherein at least one transformation module in the sequence identifies at least a portion of the output of the at least one transformation module as not to be transformed by subsequent transformation modules in the sequence, and wherein the output of a final transformation module in the sequence comprises a transformed message in the first language; and querying, using the one or more computer processors, a computer data store for a translation of the transformed message in a second language. | 1. A method using one or more computer processors, comprising: providing, using the one or more computer processors, a first message in a first language to a first transformation module in a sequence of computer-implemented transformation modules, each transformation module comprising executable instructions configured to be executed by the one or more computer processors for performing message transformation operations, wherein each subsequent transformation module in the sequence accepts, as input, an output of a preceding transformation module in the sequence and provides, as output, a respective transformed message, wherein at least one transformation module in the sequence identifies at least a portion of the output of the at least one transformation module as not to be transformed by subsequent transformation modules in the sequence, and wherein the output of a final transformation module in the sequence comprises a transformed message in the first language; and querying, using the one or more computer processors, a computer data store for a translation of the transformed message in a second language. 6. The method of claim 1 , wherein one or more transformation modules (i) identify an abbreviation in the first message and (ii) replace the abbreviation with a word or a phrase corresponding to the abbreviation. | 0.615942 |
9,734,351 | 17 | 24 | 17. A system for performing computerized employment authorization queries with a federal governmental entity, the system comprising: an electronic form having at least one variable to be entered by a user, the electronic form configured to verify valid entry of the at least one variable by the user; a first database for storing of a record for the person, the first database configured to store the at least one variable in the record for the person; and a processor configured to: transmit the at least one variable to a remote federal government system containing employment eligibility information, receive an indication, from the remote federal government system, that the person corresponding to the at least one variable is legally eligible for employment, the indication being based on: the at least one variable determined to be valid by the remote federal government system, and the at least one variable subsequently being determined to indicate that the person is authorized by the remote federal government system for employment, provide a first authorization interface for receiving the person's electronic signature, the first authorization interface comprising: a first user interface element for obtaining the person's electronic signature; and a second user interface element for enabling the person to withdraw a certified electronic signature previously entered by the person; provide a second authorization interface for receiving a preparer's electronic signature, the second authorization interface comprising: a first preparer interface element for obtaining the preparer's electronic signature via username and password; a second preparer interface element for obtaining an electronic instant signature from the preparer; and a third preparer interface element for calling an account management interface having a first account management interface element for creating an electronic signature account, and a second account management interface element for managing the electronic signature account; provide a third authorization interface for receiving an employer's electronic signature, the third authorization interface comprising: a first employer interface element for obtaining the employer's electronic signature via username and password; a second employer interface element for obtaining an instant signature from the employer; and a third employer interface element for calling the account management interface; and determine an expiration date for legal eligibility for employment of the person. | 17. A system for performing computerized employment authorization queries with a federal governmental entity, the system comprising: an electronic form having at least one variable to be entered by a user, the electronic form configured to verify valid entry of the at least one variable by the user; a first database for storing of a record for the person, the first database configured to store the at least one variable in the record for the person; and a processor configured to: transmit the at least one variable to a remote federal government system containing employment eligibility information, receive an indication, from the remote federal government system, that the person corresponding to the at least one variable is legally eligible for employment, the indication being based on: the at least one variable determined to be valid by the remote federal government system, and the at least one variable subsequently being determined to indicate that the person is authorized by the remote federal government system for employment, provide a first authorization interface for receiving the person's electronic signature, the first authorization interface comprising: a first user interface element for obtaining the person's electronic signature; and a second user interface element for enabling the person to withdraw a certified electronic signature previously entered by the person; provide a second authorization interface for receiving a preparer's electronic signature, the second authorization interface comprising: a first preparer interface element for obtaining the preparer's electronic signature via username and password; a second preparer interface element for obtaining an electronic instant signature from the preparer; and a third preparer interface element for calling an account management interface having a first account management interface element for creating an electronic signature account, and a second account management interface element for managing the electronic signature account; provide a third authorization interface for receiving an employer's electronic signature, the third authorization interface comprising: a first employer interface element for obtaining the employer's electronic signature via username and password; a second employer interface element for obtaining an instant signature from the employer; and a third employer interface element for calling the account management interface; and determine an expiration date for legal eligibility for employment of the person. 24. The system of claim 17 wherein the expiration date for legal eligibility for employment of the person is based on at least some information stored in the record of the first database. | 0.856815 |
8,798,139 | 2 | 3 | 2. The method of claim 1 , further comprising: requesting the first context model and the second context model from a context model table; updating, by the first encoder, the first context model based at least in part on the first bin; updating, by the second encoder, the second context model based at least in part on the second bin; and transmitting the updated first context model and updated second context model to the context model table for storage. | 2. The method of claim 1 , further comprising: requesting the first context model and the second context model from a context model table; updating, by the first encoder, the first context model based at least in part on the first bin; updating, by the second encoder, the second context model based at least in part on the second bin; and transmitting the updated first context model and updated second context model to the context model table for storage. 3. The method of claim 2 , wherein the context model table comprises one or more context models stored at one or more context model table addresses, and wherein at least two context models are stored at one context model table address. | 0.927737 |
6,092,034 | 26 | 27 | 26. The method of claim 19, further comprising the step of pre-processing the series of source words before generating the at least one fertility hypotheses and the sense hypothesis. | 26. The method of claim 19, further comprising the step of pre-processing the series of source words before generating the at least one fertility hypotheses and the sense hypothesis. 27. The method of claim 26, wherein said pre-processing step further comprises at least one of tokenizing, applying part of speech tags, determining morphological root words, and correcting errors in diacritical marks. | 0.96 |
7,606,425 | 1 | 4 | 1. A method of learning events contained within a video image sequence, the method comprising: providing a computing system that is configured to receive the image sequence, the computing system programmed to: provide a behavioral analysis engine that is configured to learn new events contained within the image sequence; initiate a training phase mode within the behavioral analysis engine and obtain a feature vector including one or more parameters relating to an object disposed within the image sequence; identify one or more clusters for at least some of the one or more parameters, at least some of the one or more clusters corresponding to possible event candidates; display an identifier for at least some of the possible event candidates on a display; and allow a user to select one or more of the possible event candidates, and to include the selected one or more of the possible event candidates into an event library. | 1. A method of learning events contained within a video image sequence, the method comprising: providing a computing system that is configured to receive the image sequence, the computing system programmed to: provide a behavioral analysis engine that is configured to learn new events contained within the image sequence; initiate a training phase mode within the behavioral analysis engine and obtain a feature vector including one or more parameters relating to an object disposed within the image sequence; identify one or more clusters for at least some of the one or more parameters, at least some of the one or more clusters corresponding to possible event candidates; display an identifier for at least some of the possible event candidates on a display; and allow a user to select one or more of the possible event candidates, and to include the selected one or more of the possible event candidates into an event library. 4. The method of claim 1 , wherein the feature vector is a multi-dimensional vector. | 0.835938 |
7,603,355 | 16 | 18 | 16. A computer-implemented method for controlling access to a portion of a document, the document comprising a plurality of portions, the method performed by at least one processor, the method comprising: receiving a request to access the document portion, the document portion containing a part of the document that matches a search query; identifying a variable accessibility rule associated with the requested document portion; evaluating the rule based on data describing past accesses of other ones of the plurality of document portions; determining whether to provide access to the requested document portion responsive to the evaluation of the rule; and responding to the request based on the determination. | 16. A computer-implemented method for controlling access to a portion of a document, the document comprising a plurality of portions, the method performed by at least one processor, the method comprising: receiving a request to access the document portion, the document portion containing a part of the document that matches a search query; identifying a variable accessibility rule associated with the requested document portion; evaluating the rule based on data describing past accesses of other ones of the plurality of document portions; determining whether to provide access to the requested document portion responsive to the evaluation of the rule; and responding to the request based on the determination. 18. The method of claim 16 , wherein responding to the request based on the determination comprises responsive to determining not to provide access to the requested document portion, not presenting the part of the document that matches the search query. | 0.680556 |
8,565,419 | 1 | 3 | 1. A physical keyboard comprising: a first user interface comprising a first array of keys arranged in rows and columns; and a second user interface comprising a second array of keys arranged in rows and columns; the second array of keys partially overlapping the first array of keys so that a subset of the first array of keys also comprises a subset of the second array of keys; and wherein the first array of keys comprises a text input keypad, and wherein the text input keypad includes a spacebar that is not a common key but is adjacent a row of keys of the second array of keys and extends across multiple columns of the second array of keys, and wherein the spacebar extends across all columns of a bottom row of the second array of keys. | 1. A physical keyboard comprising: a first user interface comprising a first array of keys arranged in rows and columns; and a second user interface comprising a second array of keys arranged in rows and columns; the second array of keys partially overlapping the first array of keys so that a subset of the first array of keys also comprises a subset of the second array of keys; and wherein the first array of keys comprises a text input keypad, and wherein the text input keypad includes a spacebar that is not a common key but is adjacent a row of keys of the second array of keys and extends across multiple columns of the second array of keys, and wherein the spacebar extends across all columns of a bottom row of the second array of keys. 3. The physical keyboard of claim 1 , wherein the keys in at least one row of the second array of keys are offset above the first array of keys. | 0.754266 |
9,298,441 | 6 | 8 | 6. The method of claim 1 further comprising: extracting the first metadata and the second metadata on a static or dynamic basis. | 6. The method of claim 1 further comprising: extracting the first metadata and the second metadata on a static or dynamic basis. 8. The method of claim 6 further comprising: responsive to extracting the first metadata and the second metadata on a dynamic basis, extracting the first metadata and the second metadata from the at least one database in real time. | 0.920014 |
9,940,933 | 7 | 8 | 7. The method of claim 6 , wherein the calculating of the degree of suitability for each of the sampled candidate words further comprises calculating the degree of suitability for each of the sampled candidate words based on respective results of both the acoustic model and the context based linguistic model by setting a first weighted value to be applied to results of the acoustic model and a second weighted value to be applied to results of the contextual linguistic model. | 7. The method of claim 6 , wherein the calculating of the degree of suitability for each of the sampled candidate words further comprises calculating the degree of suitability for each of the sampled candidate words based on respective results of both the acoustic model and the context based linguistic model by setting a first weighted value to be applied to results of the acoustic model and a second weighted value to be applied to results of the contextual linguistic model. 8. The method of claim 7 , wherein the setting of the first weighted value and the second weighted value comprises dynamically, based on a probability distribution of results of the acoustic model associated with the sentence, controlling the first weighted value and the second weighted value. | 0.894016 |
8,639,693 | 8 | 11 | 8. A system comprising: a memory configured to store a plurality of place listings; and a processor configured to execute a plurality of modules, wherein the modules comprise: a collection assembly and mapping module configured to: generate a plurality of collections of the place listings, wherein the place listings in each collection includes a common trait, the common trait being based on a user's interaction with the place listings, identify each place listing the user has interacted with as a seed listing, and identify a plurality of candidate listings, wherein at least one of the candidate listings and at least one of the seed listings are of a particular collection; a collection identification and comparison module configured to determine the collections which include as members at least one of the candidate listings and at least one of the seed listings; a weight value calculation module configured to calculate a weight value for each seed listing and each candidate listing in each collection, wherein the weight value indicates a strength of association between either the seed listing and the corresponding collection or the candidate listing and the corresponding collection; a recommendation score calculation module configured to: calculate a recommendation score for each candidate listing, wherein the recommendation score is calculated based on the weight values of the seed listings and the weight values of the candidate listings, the recommendation score indicating a likelihood the user would be interested in the candidate listing, determine at least one of the recommendation scores exceed a threshold, and provide the candidate listings corresponding to the at least one of the recommendation scores that exceeds the threshold for display on a computing device. | 8. A system comprising: a memory configured to store a plurality of place listings; and a processor configured to execute a plurality of modules, wherein the modules comprise: a collection assembly and mapping module configured to: generate a plurality of collections of the place listings, wherein the place listings in each collection includes a common trait, the common trait being based on a user's interaction with the place listings, identify each place listing the user has interacted with as a seed listing, and identify a plurality of candidate listings, wherein at least one of the candidate listings and at least one of the seed listings are of a particular collection; a collection identification and comparison module configured to determine the collections which include as members at least one of the candidate listings and at least one of the seed listings; a weight value calculation module configured to calculate a weight value for each seed listing and each candidate listing in each collection, wherein the weight value indicates a strength of association between either the seed listing and the corresponding collection or the candidate listing and the corresponding collection; a recommendation score calculation module configured to: calculate a recommendation score for each candidate listing, wherein the recommendation score is calculated based on the weight values of the seed listings and the weight values of the candidate listings, the recommendation score indicating a likelihood the user would be interested in the candidate listing, determine at least one of the recommendation scores exceed a threshold, and provide the candidate listings corresponding to the at least one of the recommendation scores that exceeds the threshold for display on a computing device. 11. The system of claim 8 , wherein the user's interaction of the place listings comprises providing a rating for at least one of the place listings. | 0.725092 |
9,740,735 | 1 | 4 | 1. A computer system, comprising: a distributed computer cluster; one or more processors; and one or more computer readable storage media having stored thereon computer-executable instructions that are executable by the one or more processors to cause the computer system to generate parallel-processing queries, the computer-executable instructions including instructions that are executable to cause the computer system to perform at least the following: create a structured query according to a structured query language, the structured query being created for execution in parallel across the distributed computer cluster; and; receive programming language syntax that comprises a functions; insert the received programming language syntax into the structured query of the structured query language such that a resulting query includes a structured query language statement in combination with programming language code that specifies both an aggregation and an operation; insert a keyword into the resulting query that defines an object type in the programming language code; compile the programming language code, wherein compiling the programming language code is performed based on the object type defined by the inserted keyword; and execute the resulting query, including both the structured query language and the programming language code, in a distributed manner on the distributed computer cluster. | 1. A computer system, comprising: a distributed computer cluster; one or more processors; and one or more computer readable storage media having stored thereon computer-executable instructions that are executable by the one or more processors to cause the computer system to generate parallel-processing queries, the computer-executable instructions including instructions that are executable to cause the computer system to perform at least the following: create a structured query according to a structured query language, the structured query being created for execution in parallel across the distributed computer cluster; and; receive programming language syntax that comprises a functions; insert the received programming language syntax into the structured query of the structured query language such that a resulting query includes a structured query language statement in combination with programming language code that specifies both an aggregation and an operation; insert a keyword into the resulting query that defines an object type in the programming language code; compile the programming language code, wherein compiling the programming language code is performed based on the object type defined by the inserted keyword; and execute the resulting query, including both the structured query language and the programming language code, in a distributed manner on the distributed computer cluster. 4. The system of claim 1 , wherein the syntax is employed with an operator. | 0.744898 |
8,484,148 | 11 | 12 | 11. A computer-implemented method of predicting whether character strings refer to a same subject matter, the method comprising: referencing in a database a first character string and a second character string that are included in a set of text documents; utilizing a processor to apply a prediction algorithm to each of the first character string and the second character string, the prediction algorithm being usable to quantify a likelihood that the first character string and the second character string refer to the same subject matter, (1) wherein the prediction algorithm is learned by a support vector machine based on an inner product that is determined using a mapping of a training set of data, and (2) wherein the mapping is based on a first kernel function comprising a mathematical combination of a first IDF of a character string included in the first character string, a second IDF of a character string included in the second character string, and a value quantifying a measure of similarity; and based on a prediction value, which is generated by applying the prediction algorithm to each of the first string of characters and the second string of characters, associating in the database the first character string with the second character string. | 11. A computer-implemented method of predicting whether character strings refer to a same subject matter, the method comprising: referencing in a database a first character string and a second character string that are included in a set of text documents; utilizing a processor to apply a prediction algorithm to each of the first character string and the second character string, the prediction algorithm being usable to quantify a likelihood that the first character string and the second character string refer to the same subject matter, (1) wherein the prediction algorithm is learned by a support vector machine based on an inner product that is determined using a mapping of a training set of data, and (2) wherein the mapping is based on a first kernel function comprising a mathematical combination of a first IDF of a character string included in the first character string, a second IDF of a character string included in the second character string, and a value quantifying a measure of similarity; and based on a prediction value, which is generated by applying the prediction algorithm to each of the first string of characters and the second string of characters, associating in the database the first character string with the second character string. 12. The computer-implemented method of claim 11 , wherein the support vector machine uses the inner product to generate a set of real parameters and a set of corresponding support vectors. | 0.864943 |
7,657,515 | 1 | 43 | 1. A computer-implemented document search method comprising, by execution of program instructions by a computer system that comprises one or more computing devices: in response to receiving a query including first and second lists of query terms, logically combining terms from the first and second lists to form document search sub-queries, each sub-query comprising at least one term from the first list and at least one term from the second list; searching a data store by executing the sub-queries such that at least two of the document search sub-queries are executed in parallel, to identify responsive documents; obtaining results from executing the document search sub-queries, the results including location information identifying the location of any of the terms from the first and second lists in the responsive documents; combining the results from all sub-queries to form a single query result that includes the location information; and returning the query result. | 1. A computer-implemented document search method comprising, by execution of program instructions by a computer system that comprises one or more computing devices: in response to receiving a query including first and second lists of query terms, logically combining terms from the first and second lists to form document search sub-queries, each sub-query comprising at least one term from the first list and at least one term from the second list; searching a data store by executing the sub-queries such that at least two of the document search sub-queries are executed in parallel, to identify responsive documents; obtaining results from executing the document search sub-queries, the results including location information identifying the location of any of the terms from the first and second lists in the responsive documents; combining the results from all sub-queries to form a single query result that includes the location information; and returning the query result. 43. The method of claim 1 , wherein said sub-queries are formed in response to a determination that the size of the first or second lists exceeds a threshold. | 0.844794 |
9,037,566 | 15 | 16 | 15. A non-transitory computer-readable medium having instructions executable by a computer to cause the computer to carry out a process, the process comprising: annotating a supplemental content item to derive an annotated supplemental content item, wherein the supplemental content item is derived from an original content item, and wherein the annotated supplemental content item includes at least one annotation and a subset of content from the supplemental content item and a plurality of annotations and the reference references a sequentially first annotation in the annotated supplemental content item; designating a unique identifier for the annotated supplemental content item; generating a reference to the annotated supplemental content item, the reference including the unique identifier for the annotated supplemental content item; inserting the reference into a primary document to link the primary document to the annotated supplemental content item, wherein the reference is a link and wherein the unique identifier is a globally unique identifier or a hash of a filename; and assembling the primary document, the supplemental content item and the annotated supplemental content item into a structured electronic document by converting a format of the primary document to another format and locking the structured electronic document to prevent further editing. | 15. A non-transitory computer-readable medium having instructions executable by a computer to cause the computer to carry out a process, the process comprising: annotating a supplemental content item to derive an annotated supplemental content item, wherein the supplemental content item is derived from an original content item, and wherein the annotated supplemental content item includes at least one annotation and a subset of content from the supplemental content item and a plurality of annotations and the reference references a sequentially first annotation in the annotated supplemental content item; designating a unique identifier for the annotated supplemental content item; generating a reference to the annotated supplemental content item, the reference including the unique identifier for the annotated supplemental content item; inserting the reference into a primary document to link the primary document to the annotated supplemental content item, wherein the reference is a link and wherein the unique identifier is a globally unique identifier or a hash of a filename; and assembling the primary document, the supplemental content item and the annotated supplemental content item into a structured electronic document by converting a format of the primary document to another format and locking the structured electronic document to prevent further editing. 16. The computer-readable medium as recited in claim 15 , wherein the process further comprises presenting a user interface including a content item insertion control, which enables the user to insert the supplemental content item into the structured electronic document. | 0.708602 |
7,529,685 | 9 | 10 | 9. The method of claim 1 , further comprising the step of selecting an initial descriptive taxonomy from a plurality of prestored initial descriptive taxonomies prior to the step of querying the computer database utilizing the initial descriptive taxonomy. | 9. The method of claim 1 , further comprising the step of selecting an initial descriptive taxonomy from a plurality of prestored initial descriptive taxonomies prior to the step of querying the computer database utilizing the initial descriptive taxonomy. 10. The method of claim 9 , wherein storing the at least one inclusion rule and the at least one exclusion rule further comprises the step of combining the at least one initial inclusion rule with at least one existing inclusion rule from the selected initial descriptive taxonomy. | 0.956231 |
4,520,501 | 41 | 45 | 41. The apparatus of claim 39, wherein the presenting means comprises means for presenting the patterns as illuminated areas on a display. | 41. The apparatus of claim 39, wherein the presenting means comprises means for presenting the patterns as illuminated areas on a display. 45. The apparatus of claim 41, wherein the display comprises means for producing electrical signals representative of the patterns displayed thereon for driving another presenting means. | 0.888756 |
8,200,676 | 1 | 4 | 1. A computer-implemented method comprising: using a geoparser engine to identify one or more potential geographic references within a document, and to generate respective geotags associated with the identified geographic references; determining to display on a visual display device a visual representation of the geotags along with the associated geographic references; providing a user interface that facilitates one or more of a change of at least one of the displayed geotags, and a specification of one or more additional geographic references within the document and of additional respective geotags associated with the additional geographic references; and determining to send the one or more of the change(s) to the displayed geotags, and the specification of additional geographic references and additional respective geotags to the geoparser engine for one or more of display on the visual display device within the visual representation and future use by the geoparser engine; wherein each of the geotags includes a relevance, parameter for assessing a pertinence of the geotag with respect to the document, or a confidence parameter for assessing a relevance of the geotag with respect to the associated geographic reference, or a combination thereof. | 1. A computer-implemented method comprising: using a geoparser engine to identify one or more potential geographic references within a document, and to generate respective geotags associated with the identified geographic references; determining to display on a visual display device a visual representation of the geotags along with the associated geographic references; providing a user interface that facilitates one or more of a change of at least one of the displayed geotags, and a specification of one or more additional geographic references within the document and of additional respective geotags associated with the additional geographic references; and determining to send the one or more of the change(s) to the displayed geotags, and the specification of additional geographic references and additional respective geotags to the geoparser engine for one or more of display on the visual display device within the visual representation and future use by the geoparser engine; wherein each of the geotags includes a relevance, parameter for assessing a pertinence of the geotag with respect to the document, or a confidence parameter for assessing a relevance of the geotag with respect to the associated geographic reference, or a combination thereof. 4. The method of claim 1 , wherein an enabled change includes the confidence parameter of a selectable one of the displayed geotags. | 0.875 |
8,341,178 | 20 | 27 | 20. A computer-readable storage medium storing instructions, wherein the instructions include instructions which, when executed by one or more processors, cause the one or more processors to perform steps of: selecting, from a workload set, a set of targeted database query language statements for performance analysis, wherein the workload set comprises database query language statements; executing, on a first database system, the set of targeted database query language statements; wherein executing the set of targeted database query language statements on the first database system comprises gathering a first set of performance data about the execution of each database query language statement of said targeted database query language statements on the first database system; executing, on a second database system, the set of targeted database query language statements, wherein the database of the second database system is a modified version of the database of the first database system; wherein executing the set of targeted database query language statements on the second database system comprises gathering a second set of performance data about the execution of said each database query language statement of said targeted database query language statements on the second database system; wherein each of the first set of performance data and second set of performance data comprises statistics based on at least one of the following: (a) CPU time consumed to execute said each database query language statement of said set of targeted database query language statements, (b) buffer reads incurred to execute said each database query language statement of said set of targeted database query language statements, and (c) disk reads incurred to execute said each database query language statement of said set of targeted database query language statements; comparing the first set of performance data with the second set of performance data; and generating information that indicates a result of the comparison, wherein the information that indicates a result of the comparison includes a difference in a total performance metric for executing the set of targeted database query language statements between the first database system and the second database system; and wherein the information that indicates a result of the comparison includes, for each database query language statement in the set of targeted database query language statements, a difference in a performance metric for executing said each database query language statement between the first database system and the second database system. | 20. A computer-readable storage medium storing instructions, wherein the instructions include instructions which, when executed by one or more processors, cause the one or more processors to perform steps of: selecting, from a workload set, a set of targeted database query language statements for performance analysis, wherein the workload set comprises database query language statements; executing, on a first database system, the set of targeted database query language statements; wherein executing the set of targeted database query language statements on the first database system comprises gathering a first set of performance data about the execution of each database query language statement of said targeted database query language statements on the first database system; executing, on a second database system, the set of targeted database query language statements, wherein the database of the second database system is a modified version of the database of the first database system; wherein executing the set of targeted database query language statements on the second database system comprises gathering a second set of performance data about the execution of said each database query language statement of said targeted database query language statements on the second database system; wherein each of the first set of performance data and second set of performance data comprises statistics based on at least one of the following: (a) CPU time consumed to execute said each database query language statement of said set of targeted database query language statements, (b) buffer reads incurred to execute said each database query language statement of said set of targeted database query language statements, and (c) disk reads incurred to execute said each database query language statement of said set of targeted database query language statements; comparing the first set of performance data with the second set of performance data; and generating information that indicates a result of the comparison, wherein the information that indicates a result of the comparison includes a difference in a total performance metric for executing the set of targeted database query language statements between the first database system and the second database system; and wherein the information that indicates a result of the comparison includes, for each database query language statement in the set of targeted database query language statements, a difference in a performance metric for executing said each database query language statement between the first database system and the second database system. 27. The computer-readable storage medium of claim 20 , wherein the first set of performance data includes, for each database query language statement in the set of targeted database query language statements, a total execution time. | 0.768463 |
9,373,031 | 1 | 3 | 1. A method comprising: receiving, by a processor, a first template document, wherein the first template document comprises a first plurality of text objects; and receiving by the processor, a reference document, wherein the reference document comprises second a plurality of text objects, wherein at least one of the first template document and the reference document are misaligned or upside down during the following steps: identifying by the processor, the first plurality of text objects in the first template document; identifying by the processor, the second plurality of text objects in the reference document; identifying by the processor, a plurality of common identical text objects between the first template document and the reference document; identifying by the processor, locations of the plurality of common identical text objects in the first template document; identifying by the processor, two or more distances between the locations of the plurality of common identical text objects in the first template document; identifying by the processor, locations of the plurality of common identical text objects in the reference document; identifying by the processor, two or more distances between the locations of the plurality of common identical text objects in the reference document; determining, by the processor, that the two or more distances between the plurality of common identical text objects in the first template document are within a given percentage of variance as the two or more distances between the plurality of common identical text objects in the reference document; and in response to determining that the two or more distances between the plurality of common identical text objects in the first template document are within the given percentage of variance as the two or more distances between the plurality of common identical text objects in the reference document, grouping the first template document and the reference document as common documents, wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the first template document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the first template document and wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the reference document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the reference document. | 1. A method comprising: receiving, by a processor, a first template document, wherein the first template document comprises a first plurality of text objects; and receiving by the processor, a reference document, wherein the reference document comprises second a plurality of text objects, wherein at least one of the first template document and the reference document are misaligned or upside down during the following steps: identifying by the processor, the first plurality of text objects in the first template document; identifying by the processor, the second plurality of text objects in the reference document; identifying by the processor, a plurality of common identical text objects between the first template document and the reference document; identifying by the processor, locations of the plurality of common identical text objects in the first template document; identifying by the processor, two or more distances between the locations of the plurality of common identical text objects in the first template document; identifying by the processor, locations of the plurality of common identical text objects in the reference document; identifying by the processor, two or more distances between the locations of the plurality of common identical text objects in the reference document; determining, by the processor, that the two or more distances between the plurality of common identical text objects in the first template document are within a given percentage of variance as the two or more distances between the plurality of common identical text objects in the reference document; and in response to determining that the two or more distances between the plurality of common identical text objects in the first template document are within the given percentage of variance as the two or more distances between the plurality of common identical text objects in the reference document, grouping the first template document and the reference document as common documents, wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the first template document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the first template document and wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the reference document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the reference document. 3. The method of claim 1 , wherein determining that the plurality of distances are within the given percentage of variance is based on a relative distance using a number of Dots Per Inch (DPI) between the plurality of common identical text objects in the first template document and the plurality of common identical text objects in the reference document. | 0.897347 |
8,489,601 | 13 | 14 | 13. The method of claim 6 , wherein the step of extracting combinations of information from the reconstructed service repair verbatims includes extracting combination of at least two terms from the identified part words, the symptom words, and the repair action words of each service verbatim. | 13. The method of claim 6 , wherein the step of extracting combinations of information from the reconstructed service repair verbatims includes extracting combination of at least two terms from the identified part words, the symptom words, and the repair action words of each service verbatim. 14. The method of claim 13 , wherein the extracted combinations of information are extracted as paired combinations. | 0.98244 |
7,903,878 | 1 | 13 | 1. A handheld apparatus for capturing text found on an object, the handheld apparatus comprising: a. a framing component configured to aid in positioning the object; b. a light source configured to provide lighting on the object; c. a focusing component configured to generate an image; d. an image capture component configured to generate an image of the object; e. an image composition component configured to process the image to create a composition page scan; f. an image conditioning component configured to create a conditioned image; g. an OCR component configured to convert the conditioned image to a digital text, wherein the digital text is stored in a data structure; h. a material context component configured to organize the data structure to retain the layout of the text on the object; i. a storage component configured to store the data structure as a stored digital text; j. a librarian component configured to manage access to the stored digital text from the storage component; k. a data port for data transfer; l. a handheld housing containing the framing component, the light source, the image capture component, the image composition component, the image conditioning component, the OCR component, the data port, and the material context component, m. wherein the handheld apparatus is configured to be mounted to and removed from a standalone system including an automatic page turner and a docking mechanism configured to receive the handheld apparatus. | 1. A handheld apparatus for capturing text found on an object, the handheld apparatus comprising: a. a framing component configured to aid in positioning the object; b. a light source configured to provide lighting on the object; c. a focusing component configured to generate an image; d. an image capture component configured to generate an image of the object; e. an image composition component configured to process the image to create a composition page scan; f. an image conditioning component configured to create a conditioned image; g. an OCR component configured to convert the conditioned image to a digital text, wherein the digital text is stored in a data structure; h. a material context component configured to organize the data structure to retain the layout of the text on the object; i. a storage component configured to store the data structure as a stored digital text; j. a librarian component configured to manage access to the stored digital text from the storage component; k. a data port for data transfer; l. a handheld housing containing the framing component, the light source, the image capture component, the image composition component, the image conditioning component, the OCR component, the data port, and the material context component, m. wherein the handheld apparatus is configured to be mounted to and removed from a standalone system including an automatic page turner and a docking mechanism configured to receive the handheld apparatus. 13. The handheld apparatus of claim 1 , wherein the handheld apparatus is configured to present the digital text when not mounted to the docking mechanism. | 0.688755 |
10,083,210 | 10 | 12 | 10. A system for processing a data stream of events, the system comprising: a memory storing a plurality of instructions; and a processor coupled to the memory, the processor configured to execute the plurality of instructions to: determine that multiple portions of a continuous event processing (CEP) query can be executed concurrently relative to an event in an event stream, the instructions to determine that multiple portions of the CEP query can be executed concurrently relative to an event in an event stream comprising instructions to: split the CEP query into a plurality of separate operators; determine a separate constraint for each operator within the plurality of separate operators; and determine, based at least in part on the separate constraint for each operator within the plurality of separate operators, whether at least a part of the CEP query can be executed in a concurrent manner; execute the multiple portions of the CEP query concurrently against a first event received via the event stream in response to determining that at least part of the CEP query can be executed in a concurrent manner; and merge, into a single shared operator, (a) a first operator that is used by a first CEP query that processes at least the first event in the event stream, and (b) a second operator that is used by a second CEP query that also processes at least the first event in the event stream, in response to determining that the first operator and the second operator both perform a particular type of operation. | 10. A system for processing a data stream of events, the system comprising: a memory storing a plurality of instructions; and a processor coupled to the memory, the processor configured to execute the plurality of instructions to: determine that multiple portions of a continuous event processing (CEP) query can be executed concurrently relative to an event in an event stream, the instructions to determine that multiple portions of the CEP query can be executed concurrently relative to an event in an event stream comprising instructions to: split the CEP query into a plurality of separate operators; determine a separate constraint for each operator within the plurality of separate operators; and determine, based at least in part on the separate constraint for each operator within the plurality of separate operators, whether at least a part of the CEP query can be executed in a concurrent manner; execute the multiple portions of the CEP query concurrently against a first event received via the event stream in response to determining that at least part of the CEP query can be executed in a concurrent manner; and merge, into a single shared operator, (a) a first operator that is used by a first CEP query that processes at least the first event in the event stream, and (b) a second operator that is used by a second CEP query that also processes at least the first event in the event stream, in response to determining that the first operator and the second operator both perform a particular type of operation. 12. The system of claim 10 , wherein the processor is configured to determine the separate constraint for each operator within the plurality of separate operators at least in part by determining the separate constraint for the operator based at least in part on one or more constraints of one or more other operators from which the operator receives input. | 0.823413 |
8,234,561 | 29 | 36 | 29. A software product tangibly stored on a machine-readable medium, the software product comprising instructions operable to cause a programmable processor to perform operations comprising: observing values entered in form field objects; determining a semantic similarity between a current form field object and a form field for which values have been observed; generating likelihood assessments for possible values for the current form field object based on the observed values for the form field and the determined semantic similarity, the likelihood assessments indicating relative probability of the possible values being entered in the current form field object; and providing the generated likelihood assessments and the possible values for use in predicting a value for the current form field object. | 29. A software product tangibly stored on a machine-readable medium, the software product comprising instructions operable to cause a programmable processor to perform operations comprising: observing values entered in form field objects; determining a semantic similarity between a current form field object and a form field for which values have been observed; generating likelihood assessments for possible values for the current form field object based on the observed values for the form field and the determined semantic similarity, the likelihood assessments indicating relative probability of the possible values being entered in the current form field object; and providing the generated likelihood assessments and the possible values for use in predicting a value for the current form field object. 36. The software product of claim 29 , wherein generating a likelihood assessment for a possible value comprises generating a likelihood assessment that is proportional to the semantic similarity and to a frequency of use of the possible value in the form field; and wherein determining a semantic similarity comprises: comparing the current form field object and the form field with a semantic category, and comparing the observed values with each other. | 0.732038 |
8,775,165 | 2 | 3 | 2. The method of claim 1 , wherein the user annotation comprises a text string. | 2. The method of claim 1 , wherein the user annotation comprises a text string. 3. The method of claim 2 , wherein the user annotation can be inputted via an input field displayed proximate to the candidate word in an electronic display. | 0.937099 |
9,928,834 | 8 | 12 | 8. An electronic device comprising a processor and a storage medium in which computer program instructions are stored, wherein the computer program instructions, when executed by the processor, cause the electronic device to: obtain voice information; obtain at least one voice feature in the voice information by identifying the voice information; generate a voice operation instruction based on the voice information; determine a presentation outcome of multimedia data based on the at least one voice feature and the voice operation instruction, wherein the presentation outcome matches the voice feature; and present the multimedia data based on the presentation outcome, wherein: obtaining the at least one voice feature in the voice information by identifying the voice information includes determining, based on the voice information, an age feature of a first user inputting the voice information, determining the presentation outcome of the multimedia data based on the at least one voice feature and the voice operation instruction includes: outputting voice reply information based on the voice operation instruction, and setting a voice speed for the voice reply information to be a first voice speed, and the first voice speed corresponds to the age feature. | 8. An electronic device comprising a processor and a storage medium in which computer program instructions are stored, wherein the computer program instructions, when executed by the processor, cause the electronic device to: obtain voice information; obtain at least one voice feature in the voice information by identifying the voice information; generate a voice operation instruction based on the voice information; determine a presentation outcome of multimedia data based on the at least one voice feature and the voice operation instruction, wherein the presentation outcome matches the voice feature; and present the multimedia data based on the presentation outcome, wherein: obtaining the at least one voice feature in the voice information by identifying the voice information includes determining, based on the voice information, an age feature of a first user inputting the voice information, determining the presentation outcome of the multimedia data based on the at least one voice feature and the voice operation instruction includes: outputting voice reply information based on the voice operation instruction, and setting a voice speed for the voice reply information to be a first voice speed, and the first voice speed corresponds to the age feature. 12. The electronic device according to claim 8 , wherein: obtaining the at least one voice feature in the voice information by identifying the voice information includes determining, based on the voice information, a gender feature of the first user inputting the voice information, determining the presentation outcome of the multimedia data based on the at least one voice feature and the voice operation instruction includes setting a first output user corresponding to the voice reply information to be a preset output user, and the preset output user corresponds to the gender feature. | 0.506689 |
8,874,504 | 3 | 6 | 3. The method of claim 1 , wherein the identified electronic document and the identified position are identified without determining a standard-character-set representation of the selected document portion. | 3. The method of claim 1 , wherein the identified electronic document and the identified position are identified without determining a standard-character-set representation of the selected document portion. 6. The method of claim 3 , wherein the selected document portion is contained by a plurality of electronic documents of the corpus, the method further comprising: identifying a user who provided the user input; retrieving context information for the identified user; and identifying a document among the plurality of electronic documents most likely to correspond to the rendered document based upon contents of the retrieved context information. | 0.900313 |
8,885,923 | 7 | 8 | 7. A feature point selecting method, comprising: executing a recognition task using an importance of each of a plurality of feature point candidates on a three-dimensional shape model for a plurality of evaluation images which are generated from the three-dimensional shape model and which are used to evaluate a recognition error in the recognition task; evaluating a recognition error related to all evaluation images from a difference between a recognition result of the recognition task and correct data of the recognition task for each evaluation image; determining the importance of each feature point candidate by setting a cost function which is a function for the importance of each feature point candidate and which is represented as a function obtained by adding a restriction condition that an importance of an unimportant feature point candidate becomes close to zero, to the recognition error related to the all evaluation images, and calculating the importance of each feature point candidate which minimizes a value of the cost function; until the value of the cost function which is set based on the importance of each determined feature point candidate converges, repeatedly executing the recognition task, evaluating the recognition error related to the all evaluation images and determining the importance of the feature point candidates; and selecting a feature point which needs to be used in the recognition task from the feature point candidates on the three-dimensional shape model based on the importance of each feature point candidate such that the feature point is selected to match a recognition algorithm in the recognition task. | 7. A feature point selecting method, comprising: executing a recognition task using an importance of each of a plurality of feature point candidates on a three-dimensional shape model for a plurality of evaluation images which are generated from the three-dimensional shape model and which are used to evaluate a recognition error in the recognition task; evaluating a recognition error related to all evaluation images from a difference between a recognition result of the recognition task and correct data of the recognition task for each evaluation image; determining the importance of each feature point candidate by setting a cost function which is a function for the importance of each feature point candidate and which is represented as a function obtained by adding a restriction condition that an importance of an unimportant feature point candidate becomes close to zero, to the recognition error related to the all evaluation images, and calculating the importance of each feature point candidate which minimizes a value of the cost function; until the value of the cost function which is set based on the importance of each determined feature point candidate converges, repeatedly executing the recognition task, evaluating the recognition error related to the all evaluation images and determining the importance of the feature point candidates; and selecting a feature point which needs to be used in the recognition task from the feature point candidates on the three-dimensional shape model based on the importance of each feature point candidate such that the feature point is selected to match a recognition algorithm in the recognition task. 8. The feature point selecting method according to claim 7 , wherein a feature point candidate comprising an importance equal to or less than a threshold determined in advance is excluded from a processing target of the recognition task. | 0.926987 |
7,689,927 | 49 | 50 | 49. A computer-readable medium according to claim 45 , wherein the first system includes at least one scroll bar. | 49. A computer-readable medium according to claim 45 , wherein the first system includes at least one scroll bar. 50. A computer-readable medium according to claim 49 , wherein the scroll bar is limited based on information contained in the viewable document section. | 0.967097 |
8,200,495 | 15 | 28 | 15. An apparatus for recognizing speech and implementing a speech recognition function, the apparatus comprising: circuitry for initiating a speech dialog with at least one point in the dialog where there is a grammar of possible responses and a set of at least one expected response and wherein the set is a subset of the grammar and the set includes the most likely response or responses expected to be uttered by a user at the at least one point in the speech dialog, the set of at least one expected response for the at least one point being known in the speech recognition system before receiving input speech from the user; circuitry operable for receiving input speech from the user for progressing through the speech dialog; circuitry configured for generating acoustic features of the input speech received from a user; processing circuitry including a match/search algorithm having acoustic models, the acoustic models including acoustic models that are associated with the set of at least one expected response; the processing circuitry operable for comparing the generated input speech acoustic features to acoustic models associated with words in the grammar to generate a hypothesis and further operable for comparing the hypothesis with at least one expected response in the set to determine if the hypothesis matches the at least one expected response in the set; the processing circuitry further operable, if the hypothesis matches the at least one expected response in the set to adapt at least one acoustic model corresponding to the matched expected response using the acoustic features of the input speech to use the at least one adapted model with future input speech in the speech recognition system, otherwise, not adapting the at least one acoustic model corresponding to the expected response. | 15. An apparatus for recognizing speech and implementing a speech recognition function, the apparatus comprising: circuitry for initiating a speech dialog with at least one point in the dialog where there is a grammar of possible responses and a set of at least one expected response and wherein the set is a subset of the grammar and the set includes the most likely response or responses expected to be uttered by a user at the at least one point in the speech dialog, the set of at least one expected response for the at least one point being known in the speech recognition system before receiving input speech from the user; circuitry operable for receiving input speech from the user for progressing through the speech dialog; circuitry configured for generating acoustic features of the input speech received from a user; processing circuitry including a match/search algorithm having acoustic models, the acoustic models including acoustic models that are associated with the set of at least one expected response; the processing circuitry operable for comparing the generated input speech acoustic features to acoustic models associated with words in the grammar to generate a hypothesis and further operable for comparing the hypothesis with at least one expected response in the set to determine if the hypothesis matches the at least one expected response in the set; the processing circuitry further operable, if the hypothesis matches the at least one expected response in the set to adapt at least one acoustic model corresponding to the matched expected response using the acoustic features of the input speech to use the at least one adapted model with future input speech in the speech recognition system, otherwise, not adapting the at least one acoustic model corresponding to the expected response. 28. The apparatus of claim 15 wherein the models are adapted for an individual user by performing adaptation using speech data only from that user. | 0.679039 |
7,664,734 | 32 | 33 | 32. The system of claim 30 , wherein at least a first event of the plurality of events comprises one or more words and the user-context attributes module for identifying the plurality of user-context attributes is adapted to extract a term from the one or more words. | 32. The system of claim 30 , wherein at least a first event of the plurality of events comprises one or more words and the user-context attributes module for identifying the plurality of user-context attributes is adapted to extract a term from the one or more words. 33. The system of claim 32 , wherein the user-context attributes module for identifying the plurality of user-context attributes is adapted to generate a term measure based on at least a first frequency that the extracted term occurs in at least one of the one or more words and an index of content. | 0.884645 |
9,515,979 | 8 | 14 | 8. A method for personalized network dialogs comprising: providing a graphical user interface to allow a first user to specify to a dialog system a second user to participate in an automated dialog, specific response option, and a maximum time period for responding; accessing a data store to determine an address for the second user; executing a first instruction associated with the dialog at the dialog system to send a first communication to the second user from a server via a first communications channel, the first communication containing the specific response option; determining at the dialog system if a first event has occurred in conjunction with the second user, wherein the first event comprises a response by the second user according to the specific response option within the maximum time period for responding; assigning a value to a variable associated with the first event based on the determination; branching the dialog based on the value of the variable associated with the first event, wherein: in a first branch, executing at the dialog system a second instruction associated with the dialog to send a second communication to the second user using a second communications channel; in a second branch, executing at the dialog system a third instruction associated with the dialog. | 8. A method for personalized network dialogs comprising: providing a graphical user interface to allow a first user to specify to a dialog system a second user to participate in an automated dialog, specific response option, and a maximum time period for responding; accessing a data store to determine an address for the second user; executing a first instruction associated with the dialog at the dialog system to send a first communication to the second user from a server via a first communications channel, the first communication containing the specific response option; determining at the dialog system if a first event has occurred in conjunction with the second user, wherein the first event comprises a response by the second user according to the specific response option within the maximum time period for responding; assigning a value to a variable associated with the first event based on the determination; branching the dialog based on the value of the variable associated with the first event, wherein: in a first branch, executing at the dialog system a second instruction associated with the dialog to send a second communication to the second user using a second communications channel; in a second branch, executing at the dialog system a third instruction associated with the dialog. 14. The method of claim 8 , wherein the user interface presents a set of function shapes corresponding to functions of the dialog and allows the first user to interconnect the function shapes to define a flow of the dialog. | 0.766247 |
8,417,528 | 3 | 5 | 3. The speech recognition system according to claim 1 , wherein the one or more processors are further configured to extract from the sound block a phoneme graph, the phoneme graph assigning a phoneme to each edge, and wherein the phonetic transcription of the words in the word graph is based on the phoneme graph. | 3. The speech recognition system according to claim 1 , wherein the one or more processors are further configured to extract from the sound block a phoneme graph, the phoneme graph assigning a phoneme to each edge, and wherein the phonetic transcription of the words in the word graph is based on the phoneme graph. 5. The speech recognition system according to claim 3 , wherein the one or more processors are further configured to convert the phoneme graph to a word-phoneme graph, the word-phoneme graph assigning a word and associated phonetic transcription to each edge. | 0.825941 |
7,991,806 | 1 | 2 | 1. A computer implemented method comprising: storing, at a network entity, a first taxonomy associated with at least one content publisher, for classifying content for use in delivering advertisements from said network entity, said first taxonomy comprising a plurality of nodes arranged in at least one hierarchical structure, said plurality of nodes corresponding to a plurality of categories associated with said content; storing, at said network entity, a second taxonomy associated with at least one advertiser entity, for classifying advertisements delivered from said network entity, said second taxonomy comprising a plurality of nodes arranged in at least one hierarchical structure, said plurality of nodes corresponding to a plurality of categories associated with said advertisements; associating, using a computer, each of the categories of the nodes of the second taxonomy with a plurality of advertisement themes; generating mapping information, in a computer, by correlating a node of said second taxonomy to a plurality of nodes of said first taxonomy, wherein a second category corresponding to said node of said second taxonomy is related to a plurality of first categories corresponding to said nodes of said first taxonomy based on a logical association between advertisement themes of said second category and said first categories. | 1. A computer implemented method comprising: storing, at a network entity, a first taxonomy associated with at least one content publisher, for classifying content for use in delivering advertisements from said network entity, said first taxonomy comprising a plurality of nodes arranged in at least one hierarchical structure, said plurality of nodes corresponding to a plurality of categories associated with said content; storing, at said network entity, a second taxonomy associated with at least one advertiser entity, for classifying advertisements delivered from said network entity, said second taxonomy comprising a plurality of nodes arranged in at least one hierarchical structure, said plurality of nodes corresponding to a plurality of categories associated with said advertisements; associating, using a computer, each of the categories of the nodes of the second taxonomy with a plurality of advertisement themes; generating mapping information, in a computer, by correlating a node of said second taxonomy to a plurality of nodes of said first taxonomy, wherein a second category corresponding to said node of said second taxonomy is related to a plurality of first categories corresponding to said nodes of said first taxonomy based on a logical association between advertisement themes of said second category and said first categories. 2. The method according to claim 1 , further comprising: parsing, in a computer, said second taxonomy to retrieve said advertisements and categories associated with data stored at corresponding nodes of said second taxonomy. | 0.78828 |
8,041,669 | 14 | 16 | 14. A tangible computer readable storage medium including executable program instructions which, when executed by a computer processor, cause the computer to implement a system comprising: a text mining tool to process text in an electronic document to identify a topical expression and a polar expression in the electronic document; a text classifier to determine a topic of the topical expression and a polarity of the polar expression, to identify a relevance of the polar expression to the topical expression; and a user interface to display the topical expression with the polar expression to a user. | 14. A tangible computer readable storage medium including executable program instructions which, when executed by a computer processor, cause the computer to implement a system comprising: a text mining tool to process text in an electronic document to identify a topical expression and a polar expression in the electronic document; a text classifier to determine a topic of the topical expression and a polarity of the polar expression, to identify a relevance of the polar expression to the topical expression; and a user interface to display the topical expression with the polar expression to a user. 16. The computer readable storage medium of claim 14 , wherein the user interface is to display an aggregated plurality of topical expression and corresponding polar expressions identified from a plurality of electronic documents. | 0.786642 |
9,021,398 | 9 | 10 | 9. The method of claim 1 , further comprising: mapping at least one accessibility control to at least one associated radial context based menu control. | 9. The method of claim 1 , further comprising: mapping at least one accessibility control to at least one associated radial context based menu control. 10. The method of claim 9 , further comprising: exposing the at least one accessibility control to a text-to-speech accessibility system for identification of the at least one associated radial context based menu control. | 0.94342 |
7,684,991 | 11 | 17 | 11. An apparatus for searching audio files in a portable audio player in combination with an automobile audio system, comprising: means for reading meta-tag data associated with each audio file and producing voice data files for information retrieved from the meta-tag data; means for creating a play list that lists the voice data files produced based on the meta-tag data in an predetermined order where each of the voice data files and audio files is accompanied by address data; means for storing the play list and the audio files in the portable audio player; means for connecting the portable audio player with the automobile audio system for sending the voice data files in the play list and the audio files to the automobile audio system and receiving command signals from the automobile audio system; means for generating speech sounds that successively and automatically read aloud the data in the voice data files in the play list by the automobile audio system in a predetermined order and speed; means for accepting user's commands made in response to the speech sounds where the user's commands are transmitted through the automobile audio system to the portable audio player; and means for searching an audio file in the portable audio player based on the user's commands; wherein the speech sounds generated from the automobile audio system include a series of information on audio files so that a particular audio file is specified when both the information on the particular audio file is announced by the speech sounds and the user's commands are issued. | 11. An apparatus for searching audio files in a portable audio player in combination with an automobile audio system, comprising: means for reading meta-tag data associated with each audio file and producing voice data files for information retrieved from the meta-tag data; means for creating a play list that lists the voice data files produced based on the meta-tag data in an predetermined order where each of the voice data files and audio files is accompanied by address data; means for storing the play list and the audio files in the portable audio player; means for connecting the portable audio player with the automobile audio system for sending the voice data files in the play list and the audio files to the automobile audio system and receiving command signals from the automobile audio system; means for generating speech sounds that successively and automatically read aloud the data in the voice data files in the play list by the automobile audio system in a predetermined order and speed; means for accepting user's commands made in response to the speech sounds where the user's commands are transmitted through the automobile audio system to the portable audio player; and means for searching an audio file in the portable audio player based on the user's commands; wherein the speech sounds generated from the automobile audio system include a series of information on audio files so that a particular audio file is specified when both the information on the particular audio file is announced by the speech sounds and the user's commands are issued. 17. An apparatus for searching an audio file as defined in claim 11 , wherein said means for creating the play list that lists the voice data files includes means for creating two or more layers of files containing the voice data files which are linked to one another in a hierarchical structure, and wherein one of the layers of voice data files lists alphabetical characters each indicating the first character of voice data files in the next layer of voice data file, and wherein the alphabetical characters are read aloud through the automobile audio system to prompt user's command. | 0.503384 |
8,825,853 | 1 | 14 | 1. A computer-implemented method for providing automatic, personalized information services to a user u, the method comprising: a) transparently monitoring user interactions with data while the user is engaged in normal use of a computer; b) updating user-specific data files, wherein the user-specific data files comprise the monitored user interactions with the data and a set of documents associated with the user; c) estimating parameters of a learning machine, wherein the parameters define a User Model specific to the user and wherein the parameters are estimated in part from the user-specific data files; d) analyzing a document d to identify properties of the document, the properties including (a) words of the document and (b) at least one additional property, the words of the document having (i) a first word frequency within the document and (ii) a second word frequency within other documents; e) estimating a probability P(u|d) that an unseen document d is of interest to the user u, wherein the probability P(u|d) is estimated by applying the identified properties of the document to the learning machine having the parameters defined by the User Model; and f) using the estimated probability to provide automatic, personalized information services to the user. | 1. A computer-implemented method for providing automatic, personalized information services to a user u, the method comprising: a) transparently monitoring user interactions with data while the user is engaged in normal use of a computer; b) updating user-specific data files, wherein the user-specific data files comprise the monitored user interactions with the data and a set of documents associated with the user; c) estimating parameters of a learning machine, wherein the parameters define a User Model specific to the user and wherein the parameters are estimated in part from the user-specific data files; d) analyzing a document d to identify properties of the document, the properties including (a) words of the document and (b) at least one additional property, the words of the document having (i) a first word frequency within the document and (ii) a second word frequency within other documents; e) estimating a probability P(u|d) that an unseen document d is of interest to the user u, wherein the probability P(u|d) is estimated by applying the identified properties of the document to the learning machine having the parameters defined by the User Model; and f) using the estimated probability to provide automatic, personalized information services to the user. 14. The method of claim 1 further comprising initializing the User Model using information selected from the group consisting of a set of documents provided by the user, a web browser history file associated with the user, a web browser bookmarks file associated with the user, ratings by the user of a set of documents, and previous product purchases made by the user. | 0.879333 |
9,135,228 | 13 | 20 | 13. A computer-implemented method of displaying evolution of an electronic document, comprising: presenting a Document Object Model (“DOM”) within a web-browsing application; presenting an electronic document within the DOM; transmitting an Asynchronous JavaScript and XML (“AJAX”) request to a remote device; receiving from the remote device revision history of the electronic document, wherein the revision history is received via AJAX; choosing a first and a second reference points from the revision history; determining revision points between the first and the second reference points; traversing the determined revision points and generating a plurality of graphical representations of the electronic document at each of the revision points wherein each of the graphical representations includes a graphical combination of the electronic document at the first reference point, displayed a first transparency factor, combined with a graphical representation of the electronic document at the second reference point, displayed at a second transparency factor; constructing a presentation sequence comprised of the plurality of graphical representations; and displaying the presentation sequence as animation-sequence-playback, wherein the animation-sequence-playback terminates upon displaying the electronic document at the second reference point. | 13. A computer-implemented method of displaying evolution of an electronic document, comprising: presenting a Document Object Model (“DOM”) within a web-browsing application; presenting an electronic document within the DOM; transmitting an Asynchronous JavaScript and XML (“AJAX”) request to a remote device; receiving from the remote device revision history of the electronic document, wherein the revision history is received via AJAX; choosing a first and a second reference points from the revision history; determining revision points between the first and the second reference points; traversing the determined revision points and generating a plurality of graphical representations of the electronic document at each of the revision points wherein each of the graphical representations includes a graphical combination of the electronic document at the first reference point, displayed a first transparency factor, combined with a graphical representation of the electronic document at the second reference point, displayed at a second transparency factor; constructing a presentation sequence comprised of the plurality of graphical representations; and displaying the presentation sequence as animation-sequence-playback, wherein the animation-sequence-playback terminates upon displaying the electronic document at the second reference point. 20. The method of claim 13 , wherein the step of displaying the presentation sequence further includes: initiating a system timer; and, displaying the traversed revisions of the electronic document at intervals corresponding with timed intervals of the system timer. | 0.852058 |
7,599,957 | 2 | 11 | 2. The system of claim 1 , wherein the at least two metadata database adaptors include a regular metadata database adaptor and a master metadata database adaptor, wherein the regular metadata database adaptor contains a collection template manager module that manages collection, creation, modification, and deletion in its respective metadata database, and posts collection registration to the master metadata database adaptor. | 2. The system of claim 1 , wherein the at least two metadata database adaptors include a regular metadata database adaptor and a master metadata database adaptor, wherein the regular metadata database adaptor contains a collection template manager module that manages collection, creation, modification, and deletion in its respective metadata database, and posts collection registration to the master metadata database adaptor. 11. The system of claim 2 , wherein at least one of the adaptors includes one or more directory services, including at least one of an adaptor directory, a collection template directory, a schema directory, or a query template directory. | 0.956225 |
8,161,131 | 1 | 10 | 1. A method for delivering dynamic media content to collaborators, the method comprising: providing collaborative event media content, wherein the collaborative event media content further comprises a grammar and a structured document, wherein the grammar is a data structure associating key phrases with presentation actions that facilitates a collaborator navigating the structured document of the collaborative event media content using speech commands; providing data identifying a client's location; storing, in the context server in a data structure comprising a dynamic client context for the client, the data identifying the client's location; detecting an event in dependence upon the dynamic client context, said event being characterized by an event type; identifying one or more collaborators in dependence upon the dynamic client context and the event, the one or more collaborators each being characterized by a collaborator classification; selecting from the structured document a classified structural element in dependence upon the event type and the collaborator classification for each of the one or more collaborators; and transmitting the selected structural element to the one or more collaborators. | 1. A method for delivering dynamic media content to collaborators, the method comprising: providing collaborative event media content, wherein the collaborative event media content further comprises a grammar and a structured document, wherein the grammar is a data structure associating key phrases with presentation actions that facilitates a collaborator navigating the structured document of the collaborative event media content using speech commands; providing data identifying a client's location; storing, in the context server in a data structure comprising a dynamic client context for the client, the data identifying the client's location; detecting an event in dependence upon the dynamic client context, said event being characterized by an event type; identifying one or more collaborators in dependence upon the dynamic client context and the event, the one or more collaborators each being characterized by a collaborator classification; selecting from the structured document a classified structural element in dependence upon the event type and the collaborator classification for each of the one or more collaborators; and transmitting the selected structural element to the one or more collaborators. 10. The method of claim 1 wherein said dynamic client context comprises at least two data elements, and said event is defined as a predefined change in each of said at least two data elements. | 0.910112 |
9,967,228 | 11 | 15 | 11. An electronic device comprising: a sensor for generating time-variant data indicative of an environmental condition; a processor; and a memory comprising instructions for causing the processor to encode the time-variant data indicative of the environmental condition using a message format, the message format comprising: one or more resources fields that each identifies a resource to be imported into the time-variant data; one or more records that represent data samples comprising the time-variant data being exchanged in the message; a descriptor field corresponding to at least one respective record of the one or more records and containing metadata describing the time-variant data contained within the at least one record; and a description field having a human-readable string to describe from where the time-variant data samples are derived. | 11. An electronic device comprising: a sensor for generating time-variant data indicative of an environmental condition; a processor; and a memory comprising instructions for causing the processor to encode the time-variant data indicative of the environmental condition using a message format, the message format comprising: one or more resources fields that each identifies a resource to be imported into the time-variant data; one or more records that represent data samples comprising the time-variant data being exchanged in the message; a descriptor field corresponding to at least one respective record of the one or more records and containing metadata describing the time-variant data contained within the at least one record; and a description field having a human-readable string to describe from where the time-variant data samples are derived. 15. The electronic device of claim 11 , wherein the descriptor field comprises a type element that is a caller-assigned 16-bit or 32-bit unsigned fixed-point value that represents a type of data present in the stream, wherein the type element applies to field elements found in the descriptor field unless explicitly overridden by another type element contained in a respective field element of the descriptor. | 0.774229 |
8,442,839 | 1 | 9 | 1. An improved decision-making process, comprising the steps of: providing a collaborative, team-oriented computer architecture wherein human and software agents interact through a shared mental model including an experience knowledge base; receiving information regarding a current situation to be analyzed; consulting the experience knowledge base to qualify the received information based upon any similarities to the current situation; presenting the qualified information to a user through one of the agents; interacting with the user to receive assistance in the form of assumptions or expectancies about the situation; providing the refined information and assumptions or expectancies to other agents; utilizing cues in the experience knowledge base to contact one or more external information sources to gather missing, relevant information, if any, in support of the assumptions or expectancies; using the missing, relevant information in conjunction with other collected information to determine whether a decision about the situation is evolving in an anticipated direction; and, if so: informing the user and updating the experience knowledge base to enhance the quality or timeliness of future decisions regarding similar situations. | 1. An improved decision-making process, comprising the steps of: providing a collaborative, team-oriented computer architecture wherein human and software agents interact through a shared mental model including an experience knowledge base; receiving information regarding a current situation to be analyzed; consulting the experience knowledge base to qualify the received information based upon any similarities to the current situation; presenting the qualified information to a user through one of the agents; interacting with the user to receive assistance in the form of assumptions or expectancies about the situation; providing the refined information and assumptions or expectancies to other agents; utilizing cues in the experience knowledge base to contact one or more external information sources to gather missing, relevant information, if any, in support of the assumptions or expectancies; using the missing, relevant information in conjunction with other collected information to determine whether a decision about the situation is evolving in an anticipated direction; and, if so: informing the user and updating the experience knowledge base to enhance the quality or timeliness of future decisions regarding similar situations. 9. The decision-making process of claim 1 , including agents operative to: a) select a plan of action regarding the situation by determining whether preconditions of the selected plan are satisfied with respect to the experience knowledge base, and b) evaluate the plan of action by asserting effects of the plan into the experience knowledge base and check whether relevant goals become true. | 0.501269 |
8,103,962 | 14 | 17 | 14. The method of claim 1 , wherein extracting is performed in a user interactive mode where a user provides user input facilitating extraction during the extraction. | 14. The method of claim 1 , wherein extracting is performed in a user interactive mode where a user provides user input facilitating extraction during the extraction. 17. The method of claim 14 , wherein the user input facilitating extraction during the extraction is provided as a result of a prompt to the user when an error is detected. | 0.93239 |
8,959,568 | 10 | 12 | 10. A method for enabling a security product endpoint to share security-related data with other security product endpoints within an enterprise security environment, the method comprising the steps of: configuring the security product endpoints in the enterprise security environment to share security assessments over a common communication channel; generating a security assessment to describe an event, in which the generating is based on rules which take into account any combination of a. locally-available information about the event or objects being monitored by the security product endpoint, b. currently active security assessments received by the security product endpoint, and c. local actions taken by the security product endpoint in the past, in which sets of locally-available information for the security product endpoints are mutually exclusive, the security assessment being arranged to provide contextual meaning to the event and being defined with a time interval over which the security assessment is valid, the time interval being based on information available when the security assessment is generated; receiving a current security assessment over the common communication channel in accordance with a subscription to a subset of available security assessments generated by other security product endpoints in the enterprise security environment; generating an updated security assessment for transmission over the common communications channel in response to the received current security assessment, the generating being performed using valid security assessments while disregarding invalid security assessments for which the time interval has elapsed; and taking a response in accordance with a response policy on a per security assessment basis. | 10. A method for enabling a security product endpoint to share security-related data with other security product endpoints within an enterprise security environment, the method comprising the steps of: configuring the security product endpoints in the enterprise security environment to share security assessments over a common communication channel; generating a security assessment to describe an event, in which the generating is based on rules which take into account any combination of a. locally-available information about the event or objects being monitored by the security product endpoint, b. currently active security assessments received by the security product endpoint, and c. local actions taken by the security product endpoint in the past, in which sets of locally-available information for the security product endpoints are mutually exclusive, the security assessment being arranged to provide contextual meaning to the event and being defined with a time interval over which the security assessment is valid, the time interval being based on information available when the security assessment is generated; receiving a current security assessment over the common communication channel in accordance with a subscription to a subset of available security assessments generated by other security product endpoints in the enterprise security environment; generating an updated security assessment for transmission over the common communications channel in response to the received current security assessment, the generating being performed using valid security assessments while disregarding invalid security assessments for which the time interval has elapsed; and taking a response in accordance with a response policy on a per security assessment basis. 12. The method of claim 10 in which the security context comprises one or more previously received security assessments from the subset so long as the previous security assessments are valid. | 0.751302 |
8,938,408 | 1 | 9 | 1. A method for performing search, the method comprising: receiving, by a hardware processor, at least a portion of browsing log of a user, the browsing log comprising at least a plurality of web pages viewed by the user; extracting one or more web page features from the browsing log, wherein the features include at least web address features of the web pages viewed by the user; generating, by the hardware processor, one or more web page classifiers based on the extracted features of the browsing log, wherein different classifiers are related to different search goals of the user, and wherein generating the one or more classifiers includes performing a pairwise classification of at least web address features of the browsing log; segmenting, by the hardware processor, the browsing log using the one or more classifiers into a plurality of separate logical browsing sessions related to different search goals of the user, wherein segmenting the browsing log includes analyzing at least one or more pairs of web pages viewed by the user and determining a probability of whether each of the web address features in each pair relate to a same or different search goal of the user; and performing, by the hardware processor, an Internet search based at least in part on a search query of the user and information about one of the logical browsing sessions. | 1. A method for performing search, the method comprising: receiving, by a hardware processor, at least a portion of browsing log of a user, the browsing log comprising at least a plurality of web pages viewed by the user; extracting one or more web page features from the browsing log, wherein the features include at least web address features of the web pages viewed by the user; generating, by the hardware processor, one or more web page classifiers based on the extracted features of the browsing log, wherein different classifiers are related to different search goals of the user, and wherein generating the one or more classifiers includes performing a pairwise classification of at least web address features of the browsing log; segmenting, by the hardware processor, the browsing log using the one or more classifiers into a plurality of separate logical browsing sessions related to different search goals of the user, wherein segmenting the browsing log includes analyzing at least one or more pairs of web pages viewed by the user and determining a probability of whether each of the web address features in each pair relate to a same or different search goal of the user; and performing, by the hardware processor, an Internet search based at least in part on a search query of the user and information about one of the logical browsing sessions. 9. The method of claim 1 , wherein the features comprises one or more of: a time difference between each of the web pages visited by the user, a length of a longest common substring (LCS) of a URL, a ratio of the LCS to a first one of a plurality of URLs, a ratio of the LCS to a second one of the plurality of URLs, a number of web pages visited by the user between each web page in a pair of web pages, a trigram match of URLs, a context of a ratio of the LCS to a length of one of the plurality of URLs, a context of a ratio of the LCS to a length of a second one of the plurality of URLs, a URL host, and a context of the LCS. | 0.522003 |
9,996,670 | 17 | 28 | 17. A computer-implemented method of analyzing a clinical decision support (CDS) document and improving content analyzer system accuracy, the method comprising: improving content analyzer system accuracy in identifying CDS document deficiencies and consistencies with respect to reference content, the reference content comprising clinical guidelines, by repeatedly training a machine learning module, hosted by a content analyzer system, based on new incoming data, wherein the machine learning module is configured to automatically determine which content features are to be used to determine whether content is to be designated as relevant and matching to the reference content and which content is to be designated as non-relevant and to construct or modify an electronic model accordingly, wherein the features comprise one or more of text length, presence of a medication term, medical intervention language, use of a negation, or context, wherein improving content analyzer system accuracy by training the machine learning module comprises repeatedly: collecting positive and negative cases from CDS documents, training the electronic model using the collected positive and negative cases from CDS documents, taking as input a text segment extracted from a CDS document and returning a likelihood that the text segment matches a reference checklist item, and wherein the new incoming data indicates whether the likelihood that the text segment matches a reference checklist item is correct or incorrect; receiving at a computer system, including hardware and comprising an analytics engine, a clinical decision support document and/or a data extract from a medical service provider system; accessing over a network from a remote system, by the computer system, reference content, the reference content comprising clinical guidelines, corresponding at least in part to the clinical decision support document and/or the data extract from the medical service provider system; using, by the computer system, the electronic model to identify and extract medical intervention content from the clinical decision support document and/or the data extract from the medical service provider system; using feedback with respect to the identification of the medical intervention content to refine the electronic model; segmenting, by the computer system, at least a portion of the extracted medical intervention content into a first plurality of segments including at least a first segment, comprising a first set of text, and a second segment comprising a second set of text, wherein a given segment in the first plurality of segments is evaluated to identify a core concept, wherein identifying the core concept further comprises determining whether a given segment includes a plurality of medical interventions, and determining which of the plurality of medical interventions are part of the core concept and which of the plurality of medical interventions are not part of the core concept, and if the core concept of the given segment comprises at least one a medical intervention, determining whether a negation is associated with the medical intervention; determining, by the trained machine learning engine, if the first segment corresponds to at least a first item included in the reference content, the first item comprising a third set of text different than the first and second sets of text; at least partly in response to determining that the first segment, comprising the first set of text, corresponds to the first item included in the reference content, the first item comprising the third set of text, causing a report to be generated to include a visual indication that the first segment corresponds to the first item included in the reference content; determining, by the trained machine learning engine, if a second item included in the reference content corresponds to at least one of the first plurality of segments; at least partly in response to determining that the second item included in the reference content does not correspond to at least one of the first plurality of segments, causing the report to include a visual indication that the first plurality of segments fails to include at least one segment that corresponds to the second item included in the reference content; and at least partly in response to determining that the second item included in the reference content does correspond to at least one of the first plurality of segments, causing the report to include a visual indication that the first plurality of segments includes at least one segment that corresponds to the second item included in the reference content. | 17. A computer-implemented method of analyzing a clinical decision support (CDS) document and improving content analyzer system accuracy, the method comprising: improving content analyzer system accuracy in identifying CDS document deficiencies and consistencies with respect to reference content, the reference content comprising clinical guidelines, by repeatedly training a machine learning module, hosted by a content analyzer system, based on new incoming data, wherein the machine learning module is configured to automatically determine which content features are to be used to determine whether content is to be designated as relevant and matching to the reference content and which content is to be designated as non-relevant and to construct or modify an electronic model accordingly, wherein the features comprise one or more of text length, presence of a medication term, medical intervention language, use of a negation, or context, wherein improving content analyzer system accuracy by training the machine learning module comprises repeatedly: collecting positive and negative cases from CDS documents, training the electronic model using the collected positive and negative cases from CDS documents, taking as input a text segment extracted from a CDS document and returning a likelihood that the text segment matches a reference checklist item, and wherein the new incoming data indicates whether the likelihood that the text segment matches a reference checklist item is correct or incorrect; receiving at a computer system, including hardware and comprising an analytics engine, a clinical decision support document and/or a data extract from a medical service provider system; accessing over a network from a remote system, by the computer system, reference content, the reference content comprising clinical guidelines, corresponding at least in part to the clinical decision support document and/or the data extract from the medical service provider system; using, by the computer system, the electronic model to identify and extract medical intervention content from the clinical decision support document and/or the data extract from the medical service provider system; using feedback with respect to the identification of the medical intervention content to refine the electronic model; segmenting, by the computer system, at least a portion of the extracted medical intervention content into a first plurality of segments including at least a first segment, comprising a first set of text, and a second segment comprising a second set of text, wherein a given segment in the first plurality of segments is evaluated to identify a core concept, wherein identifying the core concept further comprises determining whether a given segment includes a plurality of medical interventions, and determining which of the plurality of medical interventions are part of the core concept and which of the plurality of medical interventions are not part of the core concept, and if the core concept of the given segment comprises at least one a medical intervention, determining whether a negation is associated with the medical intervention; determining, by the trained machine learning engine, if the first segment corresponds to at least a first item included in the reference content, the first item comprising a third set of text different than the first and second sets of text; at least partly in response to determining that the first segment, comprising the first set of text, corresponds to the first item included in the reference content, the first item comprising the third set of text, causing a report to be generated to include a visual indication that the first segment corresponds to the first item included in the reference content; determining, by the trained machine learning engine, if a second item included in the reference content corresponds to at least one of the first plurality of segments; at least partly in response to determining that the second item included in the reference content does not correspond to at least one of the first plurality of segments, causing the report to include a visual indication that the first plurality of segments fails to include at least one segment that corresponds to the second item included in the reference content; and at least partly in response to determining that the second item included in the reference content does correspond to at least one of the first plurality of segments, causing the report to include a visual indication that the first plurality of segments includes at least one segment that corresponds to the second item included in the reference content. 28. The method as defined in claim 17 , wherein the identification and extraction of medical intervention content from the clinical decision support document further comprises identifying content related to a vital signs measurement. | 0.741111 |
8,233,679 | 1 | 9 | 1. A method for determining similar faces within images based on a perception of facial similarity, the method comprising: assessing, by at least one processor, training data representing perceptions of one or more training users regarding a similarity of a first set of two different training faces relative to a similarity of a second set of two different training faces; determining, based on the accessed training data, similarity information that indicates human perception of facial similarity; receiving a query image that includes a query face; determining, by at least one processor, one or more search result images that include at least one face that is similar to the query face based on the similarity information that indicates human perception of facial similarity; and providing the search result images to a user. | 1. A method for determining similar faces within images based on a perception of facial similarity, the method comprising: assessing, by at least one processor, training data representing perceptions of one or more training users regarding a similarity of a first set of two different training faces relative to a similarity of a second set of two different training faces; determining, based on the accessed training data, similarity information that indicates human perception of facial similarity; receiving a query image that includes a query face; determining, by at least one processor, one or more search result images that include at least one face that is similar to the query face based on the similarity information that indicates human perception of facial similarity; and providing the search result images to a user. 9. The method of claim 1 , further comprising providing the search result images to the user in a dating application. | 0.939189 |
9,484,020 | 8 | 12 | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: annotating data by inserting, via a discriminative classification approach independent of using n-grams, boundary tags at boundaries in a speech utterance text based on weighted examples, wherein higher weights indicate more difficult examples, to yield annotated data; and iteratively repeating the annotating of the data, where each successive iteration has a longer turn than an immediately preceding iteration and each successive iteration is used to retrain a model associated with the discriminative classification approach. | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: annotating data by inserting, via a discriminative classification approach independent of using n-grams, boundary tags at boundaries in a speech utterance text based on weighted examples, wherein higher weights indicate more difficult examples, to yield annotated data; and iteratively repeating the annotating of the data, where each successive iteration has a longer turn than an immediately preceding iteration and each successive iteration is used to retrain a model associated with the discriminative classification approach. 12. The system of claim 8 , the computer-readable storage medium having additional instructions stored which result in operations comprising inserting conjunction tags within the unedited text which identify, without relying on punctuation cues, coordinating conjunctions selected from a list. | 0.505068 |
9,760,547 | 11 | 12 | 11. The method of claim 1 , comprising: receiving, by the server, the search query including an author identifier; identifying, by the server, the one or more edited content items associated with the author identifier; and transmitting, by the server, to the first client device, an identification of the one or more edited content items associated with the author identifier. | 11. The method of claim 1 , comprising: receiving, by the server, the search query including an author identifier; identifying, by the server, the one or more edited content items associated with the author identifier; and transmitting, by the server, to the first client device, an identification of the one or more edited content items associated with the author identifier. 12. The method of claim 11 , further comprising: monitoring, by the server, for creation of a new content item in the content editing environment by a third user identifier associated with the author identifier; and transmitting, by the server, to the first client device, an identification of the new content item associated with the author identifier. | 0.959685 |
8,843,493 | 13 | 18 | 13. A system for comparing documents, comprising: a processor; a text analyzer executing on the processor and configured to: extract a plurality of extracted elements from a first formatted document, wherein each of the plurality of extracted elements corresponds to a text element of the first formatted document, wherein the plurality of extracted elements comprises at least one selected from a group consisting of a plurality of words and a plurality of word lengths; a fingerprint extractor executing on the processor and configured to: extract a first plurality of text fingerprints from a sequence of the plurality of extracted elements to form a first text feature of the first formatted document, wherein the first plurality of text fingerprints comprises at least one selected from a group consisting of a plurality of word n-grams and a plurality of word length n-grams, wherein the first text feature comprises at least one selected from a group consisting of a first text content feature based on the plurality of word n-grams and a first text geometric feature based on the plurality of word length n-grams; a comparison module executing on the processor and configured to: compare the first text feature and a second text feature of a second formatted document to generate a comparison result, wherein the second text feature comprises at least one selected from a group consisting of a second text content feature and a second text geometric feature, wherein the comparison result comprises at least one selected from a group consisting of a text content match rate between the first and second text content features and a text geometric match rate between the first and second text geometric features; and determine, in response to the comparison result meeting a pre-determined criterion, that each of the first formatted document and the second formatted document contains a common text content, wherein the comparison result meeting the pre-determined criterion is based on at least one selected from a group consisting of the text content match rate and the text geometric match rate exceeding a pre-determined threshold; and a repository couple to the processor and configured to store the first formatted document, the plurality of extracted elements, first text feature, and second text feature. | 13. A system for comparing documents, comprising: a processor; a text analyzer executing on the processor and configured to: extract a plurality of extracted elements from a first formatted document, wherein each of the plurality of extracted elements corresponds to a text element of the first formatted document, wherein the plurality of extracted elements comprises at least one selected from a group consisting of a plurality of words and a plurality of word lengths; a fingerprint extractor executing on the processor and configured to: extract a first plurality of text fingerprints from a sequence of the plurality of extracted elements to form a first text feature of the first formatted document, wherein the first plurality of text fingerprints comprises at least one selected from a group consisting of a plurality of word n-grams and a plurality of word length n-grams, wherein the first text feature comprises at least one selected from a group consisting of a first text content feature based on the plurality of word n-grams and a first text geometric feature based on the plurality of word length n-grams; a comparison module executing on the processor and configured to: compare the first text feature and a second text feature of a second formatted document to generate a comparison result, wherein the second text feature comprises at least one selected from a group consisting of a second text content feature and a second text geometric feature, wherein the comparison result comprises at least one selected from a group consisting of a text content match rate between the first and second text content features and a text geometric match rate between the first and second text geometric features; and determine, in response to the comparison result meeting a pre-determined criterion, that each of the first formatted document and the second formatted document contains a common text content, wherein the comparison result meeting the pre-determined criterion is based on at least one selected from a group consisting of the text content match rate and the text geometric match rate exceeding a pre-determined threshold; and a repository couple to the processor and configured to store the first formatted document, the plurality of extracted elements, first text feature, and second text feature. 18. The system of claim 13 , wherein the first formatted document and the second formatted documents contain the same text content. | 0.876648 |
9,060,029 | 10 | 14 | 10. A computer software product, including a non-transitory computer-readable storage medium in which computer program instructions are stored, which instructions, when executed by a computer, cause the computer to perform the steps of: identifying properties of a target individual, wherein a correlation processor extracts user identifiers from retrieved data items, and correlates the user identifiers from different web sites; building an initial social circle of the target individual by crawling a plurality of web sites from different social media providers to identify direct and indirect associations between users of the social media providers and the target individual, wherein the target individual has no direct connection with at least one of the social media providers; deriving references to the target individual from the direct and indirect associations; and compiling a dossier on the target individual from the references to the target individual. | 10. A computer software product, including a non-transitory computer-readable storage medium in which computer program instructions are stored, which instructions, when executed by a computer, cause the computer to perform the steps of: identifying properties of a target individual, wherein a correlation processor extracts user identifiers from retrieved data items, and correlates the user identifiers from different web sites; building an initial social circle of the target individual by crawling a plurality of web sites from different social media providers to identify direct and indirect associations between users of the social media providers and the target individual, wherein the target individual has no direct connection with at least one of the social media providers; deriving references to the target individual from the direct and indirect associations; and compiling a dossier on the target individual from the references to the target individual. 14. The computer software product according to claim 10 , wherein compiling a dossier comprises weighting the references to the target individual for correlation thereof. | 0.829317 |
7,788,293 | 13 | 15 | 13. A method for generating structured data, comprising: using a computer to perform steps comprising: receiving an electronic document containing unstructured data describing facts about business hours of an enterprise; extracting the unstructured data describing facts about the business hours of the enterprise from the electronic document; and receiving the extracted unstructured data and creating structured representations of the facts about the business hours of the enterprise described by the unstructured data, wherein the receiving extracted unstructured data and creating comprises: receiving a string describing facts about the business hours of the enterprise extracted from the electronic document; parsing the string to classify symbols within the string, the parsing classifying symbols within the string as representing days of the week and classifying symbols within the string as representing times of the enterprise's business hours; collapsing the symbols representing days of the week in the string to form a collapsed string, the collapsed string having a symbol representing a sequence of days and the symbols representing times of the enterprise's business hours, wherein the symbol representing the sequence of days is described in the structured representation by a vector having bits indicating days of the week on which the enterprise is open; and interpreting the symbols within the collapsed string to determine business hours for the enterprise on the days in the sequence; wherein the structured representations of the facts about the business hours of the enterprise comprise a vector describing the symbol representing the sequence of days using bits indicating days of the week on which the enterprise is open. | 13. A method for generating structured data, comprising: using a computer to perform steps comprising: receiving an electronic document containing unstructured data describing facts about business hours of an enterprise; extracting the unstructured data describing facts about the business hours of the enterprise from the electronic document; and receiving the extracted unstructured data and creating structured representations of the facts about the business hours of the enterprise described by the unstructured data, wherein the receiving extracted unstructured data and creating comprises: receiving a string describing facts about the business hours of the enterprise extracted from the electronic document; parsing the string to classify symbols within the string, the parsing classifying symbols within the string as representing days of the week and classifying symbols within the string as representing times of the enterprise's business hours; collapsing the symbols representing days of the week in the string to form a collapsed string, the collapsed string having a symbol representing a sequence of days and the symbols representing times of the enterprise's business hours, wherein the symbol representing the sequence of days is described in the structured representation by a vector having bits indicating days of the week on which the enterprise is open; and interpreting the symbols within the collapsed string to determine business hours for the enterprise on the days in the sequence; wherein the structured representations of the facts about the business hours of the enterprise comprise a vector describing the symbol representing the sequence of days using bits indicating days of the week on which the enterprise is open. 15. The method of claim 13 , wherein the value normalization module is further for: identifying, within the string, a description of the enterprise's business hours missing a bounding value; and inserting a symbol representing a time of the enterprise's business hours into the string as the bounding value. | 0.692385 |
9,280,535 | 22 | 23 | 22. The computer-readable storage media of claim 21 , wherein the inverted index is based on one or more materialized views of the database. | 22. The computer-readable storage media of claim 21 , wherein the inverted index is based on one or more materialized views of the database. 23. The computer-readable storage media of claim 22 , the method further comprising presenting query suggestions in the user interface. | 0.969304 |
7,529,674 | 15 | 19 | 15. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, causes the one or more computers to perform operations comprising: accessing a request to provide speech animation content to a user using a graphically represented, animated talking agent, the request comprising: emotion, expression, look direction, and voice parameters for the animated talking agent; speech elements including textual content data to be spoken by the animated talking agent, at least a portion of the textual content data being dynamically derived from an item selected by the user in a current application session; a speech attribute defining whether the speech elements are to be sequentially or randomly provided; and context information identifying a characteristic of the user, the characteristic being used to customize the generated speech animation; identifying raw data to be used to generate speech animation content based on the request; generating the speech animation content adapted for the user, using the identified raw data; and providing the generated speech animation content for display to the user. | 15. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, causes the one or more computers to perform operations comprising: accessing a request to provide speech animation content to a user using a graphically represented, animated talking agent, the request comprising: emotion, expression, look direction, and voice parameters for the animated talking agent; speech elements including textual content data to be spoken by the animated talking agent, at least a portion of the textual content data being dynamically derived from an item selected by the user in a current application session; a speech attribute defining whether the speech elements are to be sequentially or randomly provided; and context information identifying a characteristic of the user, the characteristic being used to customize the generated speech animation; identifying raw data to be used to generate speech animation content based on the request; generating the speech animation content adapted for the user, using the identified raw data; and providing the generated speech animation content for display to the user. 19. The system of claim 15 , wherein the context information includes information about how long an application session has been active. | 0.791411 |
4,881,197 | 75 | 76 | 75. Apparatus according to claim 64, further including means for controlling the CRT display to display in a distinct manner the document portions which are in the process of being defined. | 75. Apparatus according to claim 64, further including means for controlling the CRT display to display in a distinct manner the document portions which are in the process of being defined. 76. Apparatus according to claim 75, further including means for responding to a range start or range end command for displaying the document from the range start point through the end of the document or from the range end to the beginning of the document in a differentiating manner. | 0.950263 |
8,302,011 | 28 | 29 | 28. The system of claim 25 , wherein the markup document corresponds to a weblog page: wherein the first portion of content includes information relating to a previous version of the weblog page content that had been previously displayed to the user; wherein the second portion of content includes information relating to a current version of the weblog page content; wherein the third portion of content includes information relating to new or modified weblog page content that was not previously displayed to the user. | 28. The system of claim 25 , wherein the markup document corresponds to a weblog page: wherein the first portion of content includes information relating to a previous version of the weblog page content that had been previously displayed to the user; wherein the second portion of content includes information relating to a current version of the weblog page content; wherein the third portion of content includes information relating to new or modified weblog page content that was not previously displayed to the user. 29. The system of claim 28 , being further configured or designed to initially display the third portion of content to the user in response to the action. | 0.969768 |
8,843,474 | 14 | 16 | 14. A computer accessible memory medium storing program instructions for executing an extended markup language (XML) database query, wherein the program instructions are executable by a processor to: compile the XML database query to provide at least two alternative execution plans, wherein the at least two alternate execution plans provide a same response to the XML database query; select one of the at least two alternative execution plans at runtime; and execute the selected execution plan; wherein said selecting comprises dynamically selecting one of the at least two alternative plans, wherein the selection is performed based on intermediate results, which are at least partly reused for evaluating the result of the execution of the XML database query according to at least one of the at least two alternative execution plans. | 14. A computer accessible memory medium storing program instructions for executing an extended markup language (XML) database query, wherein the program instructions are executable by a processor to: compile the XML database query to provide at least two alternative execution plans, wherein the at least two alternate execution plans provide a same response to the XML database query; select one of the at least two alternative execution plans at runtime; and execute the selected execution plan; wherein said selecting comprises dynamically selecting one of the at least two alternative plans, wherein the selection is performed based on intermediate results, which are at least partly reused for evaluating the result of the execution of the XML database query according to at least one of the at least two alternative execution plans. 16. The memory medium of claim 14 , wherein the at least two execution plans differ by the use of at least one XML database index. | 0.844125 |
8,611,507 | 15 | 16 | 15. A computer-readable storage medium that is not a transient signal, the computer-readable storage medium comprising executable instructions, which when executed by a processor, cause the processor to effectuate operations comprising: receiving a telephonic communication comprising speech; transcribing the telephonic communication to generate a transcript; detecting an instruction generated by a telephone within the telephonic communication; determining that the telephone is associated with an authorized user; and responsive to detecting the instruction and determining that the telephone is associated with the authorized user, supplementing the transcript with additional information. | 15. A computer-readable storage medium that is not a transient signal, the computer-readable storage medium comprising executable instructions, which when executed by a processor, cause the processor to effectuate operations comprising: receiving a telephonic communication comprising speech; transcribing the telephonic communication to generate a transcript; detecting an instruction generated by a telephone within the telephonic communication; determining that the telephone is associated with an authorized user; and responsive to detecting the instruction and determining that the telephone is associated with the authorized user, supplementing the transcript with additional information. 16. The computer-readable storage medium of claim 15 , wherein the additional information comprises at least one of a tag, highlighting, a hyperlink, text, or a marking. | 0.690476 |
9,530,431 | 4 | 5 | 4. The voice processing device according to claim 1 , wherein the processor further operates as: a frequency storage unit that stores therein occurrence frequencies of a plurality of contexts included in voices acquired in the past, as the frequency values; an updating unit that updates the frequency values, which are stored in the frequency storage unit, of the contexts corresponding to the phonemes included in the voice of the operator reading aloud the text in accordance with the score; and a text selector that selects, as the text, one piece of text from among a plurality of pieces of candidate text, wherein the text selector selects the text on the basis of the frequency values of contexts corresponding to a plurality of phonemes included in the pieces of candidate text when the pieces of candidate text are read aloud. | 4. The voice processing device according to claim 1 , wherein the processor further operates as: a frequency storage unit that stores therein occurrence frequencies of a plurality of contexts included in voices acquired in the past, as the frequency values; an updating unit that updates the frequency values, which are stored in the frequency storage unit, of the contexts corresponding to the phonemes included in the voice of the operator reading aloud the text in accordance with the score; and a text selector that selects, as the text, one piece of text from among a plurality of pieces of candidate text, wherein the text selector selects the text on the basis of the frequency values of contexts corresponding to a plurality of phonemes included in the pieces of candidate text when the pieces of candidate text are read aloud. 5. The voice processing device according to claim 4 , wherein the text selector selects the candidate text in preference to the other candidate text, the preferred candidate text including the phonemes for which the contexts have the frequency values larger than a threshold at the head of and the end of the text and the phonemes for which the contexts have the frequency values smaller than the threshold at a part of the text other than the head and the end of the text. | 0.807724 |
7,603,355 | 21 | 23 | 21. A computer program product for controlling access to a portion of a document, the document comprising a plurality of portions, the computer program product comprising a computer readable storage medium storing a computer program for performing a method, the method comprising: receiving a request to access the document portion; identifying a variable accessibility rule associated with the requested document portion; evaluating the rule based on data describing past accesses of other ones of the plurality of document portions; determining whether to provide access to the requested document portion responsive to the evaluation of the rule; and responding to the request based on the determination. | 21. A computer program product for controlling access to a portion of a document, the document comprising a plurality of portions, the computer program product comprising a computer readable storage medium storing a computer program for performing a method, the method comprising: receiving a request to access the document portion; identifying a variable accessibility rule associated with the requested document portion; evaluating the rule based on data describing past accesses of other ones of the plurality of document portions; determining whether to provide access to the requested document portion responsive to the evaluation of the rule; and responding to the request based on the determination. 23. The computer program product of claim 21 , wherein the rule indicates that access to the requested document portion is denied responsive to the data describing past accesses indicating that access was provided to all document portions other than the requested document portion. | 0.652228 |
7,523,137 | 15 | 16 | 15. A computer implemented method for event analysis comprising: reading from a computer readable memory an information source model to determine an information source; retrieving an article from the information source; reading from a computer readable memory an environment model comprising a first model entity and a focus entity, and a focus relationship from the focus entity to the first model entity; initiating, with a processor coupled to the computer readable memory, execution of an event detection engine on the article to detect an event involving the first model entity represented in the article which is relevant to the focus entity based on the focus relationship and generate an event object comprising: an event type field; an event type probability field; an importance field; and a public interest field; reading from a computer readable memory an event implication model; initiating execution, with a processor, of an event implication engine on the event object to determine an inferred event on behalf of the focus entity in view of the focus relationship and an implication message which are relevant to the focus entity; recognizing that the focus relationship exists between the focus entity and the first model entity and responsively generating the inferred event due to detection of the event involving the first model entity; and creating a new event object from the inferred event. | 15. A computer implemented method for event analysis comprising: reading from a computer readable memory an information source model to determine an information source; retrieving an article from the information source; reading from a computer readable memory an environment model comprising a first model entity and a focus entity, and a focus relationship from the focus entity to the first model entity; initiating, with a processor coupled to the computer readable memory, execution of an event detection engine on the article to detect an event involving the first model entity represented in the article which is relevant to the focus entity based on the focus relationship and generate an event object comprising: an event type field; an event type probability field; an importance field; and a public interest field; reading from a computer readable memory an event implication model; initiating execution, with a processor, of an event implication engine on the event object to determine an inferred event on behalf of the focus entity in view of the focus relationship and an implication message which are relevant to the focus entity; recognizing that the focus relationship exists between the focus entity and the first model entity and responsively generating the inferred event due to detection of the event involving the first model entity; and creating a new event object from the inferred event. 16. The method of claim 15 , where reading an event implication model comprises: reading a trigger constraint and a resulting implication. | 0.953284 |
8,165,899 | 1 | 11 | 1. A system for managing form-generated data related to a patient encounter, the system comprising: a form having designated information fields at different locations on the form; an electronic writing system configured to generate location information that identifies the location of a user writing on the form; a contextualizer configured to translate location information related to the user writing to a contextualized data element, wherein the contextualized data element comprises contextual information that is associated with the user writing, wherein the contextualizer includes a mapping data set that maps user areas on the form to labels that are associated with the designated information fields and wherein the contextualizer is configured to identify a label from the location information by comparing the location information to the mapping data set, the contextualized data element comprising the label; and an Electronic Medical Record (EMR)/Electronic Health Record (EHR) application that utilizes the label in the contextualized data element to perform a function that is related to the user writing on the form; wherein the contextualized data element is distributed to the EMR/EHR application via a publish/subscribe protocol in which the EMR/EHR application subscribes to a specific contextualized data element by identifying the label associated with the contextualized data element. | 1. A system for managing form-generated data related to a patient encounter, the system comprising: a form having designated information fields at different locations on the form; an electronic writing system configured to generate location information that identifies the location of a user writing on the form; a contextualizer configured to translate location information related to the user writing to a contextualized data element, wherein the contextualized data element comprises contextual information that is associated with the user writing, wherein the contextualizer includes a mapping data set that maps user areas on the form to labels that are associated with the designated information fields and wherein the contextualizer is configured to identify a label from the location information by comparing the location information to the mapping data set, the contextualized data element comprising the label; and an Electronic Medical Record (EMR)/Electronic Health Record (EHR) application that utilizes the label in the contextualized data element to perform a function that is related to the user writing on the form; wherein the contextualized data element is distributed to the EMR/EHR application via a publish/subscribe protocol in which the EMR/EHR application subscribes to a specific contextualized data element by identifying the label associated with the contextualized data element. 11. The system of claim 1 wherein the contextualized data element comprises a region label, an area label, and an area type indicator. | 0.79321 |
8,886,661 | 2 | 5 | 2. The information extraction system according to claim 1 , wherein the pattern determining unit determines a forward character string and a backward character string of the phrase included in the input word list as patterns, the phrase candidate extracting unit extracts a character string interposed between the forward character string and the backward character string from the document and determines the extracted character string as a candidate of a phrase, and the phrase selecting unit selects a phrase of an output subject from the candidates of the phrases, which are extracted by the phrase candidate extracting unit. | 2. The information extraction system according to claim 1 , wherein the pattern determining unit determines a forward character string and a backward character string of the phrase included in the input word list as patterns, the phrase candidate extracting unit extracts a character string interposed between the forward character string and the backward character string from the document and determines the extracted character string as a candidate of a phrase, and the phrase selecting unit selects a phrase of an output subject from the candidates of the phrases, which are extracted by the phrase candidate extracting unit. 5. The information extraction system according to claim 2 , wherein the phrase selecting unit calculates a phrase score indicating a value of a degree of importance of a candidate of the pattern used in specifying the candidate of the phrase or the amount of documents where the candidate of the phrase appears for each of the candidates of the phrases, sorts the candidates of the phrases in the order of high phrase scores, and selects the candidate of the phrase at high ranks of a predetermined ratio as the phrase of the output subject. | 0.856117 |
10,019,489 | 6 | 7 | 6. The computer-implemented method of claim 5 , wherein the data capture device comprises a microphone and the data related to the item comprises audio data representing an utterance of the user. | 6. The computer-implemented method of claim 5 , wherein the data capture device comprises a microphone and the data related to the item comprises audio data representing an utterance of the user. 7. The computer-implemented method of claim 6 , wherein the indirect feedback comprises a mood of the user and wherein the mood of the user is detected from at least one of: an acoustic property of the audio data; and a word included in the utterance of the user. | 0.920831 |
9,338,459 | 2 | 3 | 2. The method of claim 1 , wherein if the size of the current prediction unit is (3/2)N×2N, the left spatial merge candidate is set as unavailable. | 2. The method of claim 1 , wherein if the size of the current prediction unit is (3/2)N×2N, the left spatial merge candidate is set as unavailable. 3. The method of claim 2 , wherein the left spatial merge candidate is motion information of the left prediction unit of the current prediction unit. | 0.943774 |
9,817,726 | 7 | 11 | 7. A system comprising: a secondary data center comprising: one or more processors; a search and indexing manager comprising: an index core; and a search core; a distributed file system; and a distributed storage system; the search and indexing manager of the secondary data center configured to: detect a disaster at a primary data center and, in response to the detecting, for each document stored in the search core of the secondary data center: request a count for the document from a first client application; determine whether the count for the document from the first client application matches a count for the document from the search core of the secondary data center; and in response to a determination that the count for the document from the first client application does not match a count for the document from the search core of the secondary data center, request a full publish for the document from the first client application, wherein the requesting the count, the determining, and the requesting of the full publish are performed for each document for each tenant represented in the search core of the secondary data center. | 7. A system comprising: a secondary data center comprising: one or more processors; a search and indexing manager comprising: an index core; and a search core; a distributed file system; and a distributed storage system; the search and indexing manager of the secondary data center configured to: detect a disaster at a primary data center and, in response to the detecting, for each document stored in the search core of the secondary data center: request a count for the document from a first client application; determine whether the count for the document from the first client application matches a count for the document from the search core of the secondary data center; and in response to a determination that the count for the document from the first client application does not match a count for the document from the search core of the secondary data center, request a full publish for the document from the first client application, wherein the requesting the count, the determining, and the requesting of the full publish are performed for each document for each tenant represented in the search core of the secondary data center. 11. The system of claim 7 , wherein the index core of the primary data center and the index core of the secondary data center are further configured to organize the first shard with a plurality of additional shards into the search core of the primary data center. | 0.886344 |
8,046,226 | 28 | 33 | 28. A system for a user to prepare a current report comprising: a user input device to enter information from a user input; a reporting system to receive and process the information by executing a heuristic algorithm, said reporting system structured to perform a task and prepare a response based on the performance of the task, wherein the task is a heuristic selection of one or more macros from a macro library; and a voice output device to communicate the response aurally as voice output. | 28. A system for a user to prepare a current report comprising: a user input device to enter information from a user input; a reporting system to receive and process the information by executing a heuristic algorithm, said reporting system structured to perform a task and prepare a response based on the performance of the task, wherein the task is a heuristic selection of one or more macros from a macro library; and a voice output device to communicate the response aurally as voice output. 33. The system of claim 28 , wherein the response is a prompt to enter additional information. | 0.881013 |
8,521,769 | 13 | 16 | 13. The computer implemented method of claim 12 , wherein the value comprises a first number and wherein the plurality of matching attributes comprises a first attribute that matches the value and a second attribute that matches the value, wherein the first attribute comprises a first category associated with the first number, wherein the second attribute comprises a second category associated with the first number, and wherein a determination cannot be made by examining only the first number whether the first number should belong, as perceived by a user or a computer program, to the first category or to the second category. | 13. The computer implemented method of claim 12 , wherein the value comprises a first number and wherein the plurality of matching attributes comprises a first attribute that matches the value and a second attribute that matches the value, wherein the first attribute comprises a first category associated with the first number, wherein the second attribute comprises a second category associated with the first number, and wherein a determination cannot be made by examining only the first number whether the first number should belong, as perceived by a user or a computer program, to the first category or to the second category. 16. The computer implemented method of claim 13 , wherein displaying further comprises providing a first link associated with the first category and a second link associated with the second category, wherein the first link points to first information associated with the first category, and wherein the second link points to second information associated with the second category. | 0.887106 |
9,015,143 | 13 | 19 | 13. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: obtaining a set of search results that a search engine identifies as responsive to a search query; obtaining a respective snippet for each of first multiple search results, wherein the first multiple search results are selected from among the set of search results; providing, for display, a search engine results page that includes (i) the first multiple search results from among the set of search results that the search engine identifies as responsive to the search query, (ii) the respective snippet for each of the first multiple search results, and (iii) a text entry field for entering a refinement to the search query; receiving data indicating the refinement to the search query that is entered through the text entry field on the search engine results page; in response to receiving the data indicating the refinement to the search query, obtaining a subset of the set of search results, wherein each search result of the subset of search results references a respective resource that satisfies the refinement, and wherein the subset of search results are obtained without instructing the search engine to perform a subsequent search; obtaining a respective updated snippet for each of second multiple search results, wherein the second multiple search results are selected from among the subset of search results; and providing, for display, an updated search engine results page that includes (i) the second multiple search results that are selected from among the subset of the search results, and (ii) the respective updated snippet for each of the second multiple search results. | 13. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: obtaining a set of search results that a search engine identifies as responsive to a search query; obtaining a respective snippet for each of first multiple search results, wherein the first multiple search results are selected from among the set of search results; providing, for display, a search engine results page that includes (i) the first multiple search results from among the set of search results that the search engine identifies as responsive to the search query, (ii) the respective snippet for each of the first multiple search results, and (iii) a text entry field for entering a refinement to the search query; receiving data indicating the refinement to the search query that is entered through the text entry field on the search engine results page; in response to receiving the data indicating the refinement to the search query, obtaining a subset of the set of search results, wherein each search result of the subset of search results references a respective resource that satisfies the refinement, and wherein the subset of search results are obtained without instructing the search engine to perform a subsequent search; obtaining a respective updated snippet for each of second multiple search results, wherein the second multiple search results are selected from among the subset of search results; and providing, for display, an updated search engine results page that includes (i) the second multiple search results that are selected from among the subset of the search results, and (ii) the respective updated snippet for each of the second multiple search results. 19. The computer storage medium of claim 13 , wherein providing, for display, the updated search engine results page comprises hiding a snippet included with a particular search result. | 0.737216 |
8,577,726 | 2 | 4 | 2. A method in a computing device for calculating a bid amount for a keyword, the method comprising: collecting, at one or more computer systems, conversion information for the keyword indicating financial benefit resulting from users selecting advertisements displayed with content that relates to the keyword, the financial benefit being organized into categories; determining, at the one or more computer systems, a category-specific advertising expense factor for each category; calculating, at the one or more computer systems, a category-specific product for each category, the category specific product calculated by multiplying the financial benefit for the category by the category-specific advertising expense factor determined for the category; generating, at the one or more computer systems, a summation of the calculated category-specific products; generating, at the one or more computer systems, a quotient, wherein the quotient is the summation of the category-specific products divided by a number of sessions with financial benefit; and generating, at the one or more computer systems, a bid amount for the keyword based at least in part on the quotient multiplied by a forecast conversion rate, the forecast conversion rate comprising a predicted percentage of clickthroughs associated with the keyword that results in a conversion. | 2. A method in a computing device for calculating a bid amount for a keyword, the method comprising: collecting, at one or more computer systems, conversion information for the keyword indicating financial benefit resulting from users selecting advertisements displayed with content that relates to the keyword, the financial benefit being organized into categories; determining, at the one or more computer systems, a category-specific advertising expense factor for each category; calculating, at the one or more computer systems, a category-specific product for each category, the category specific product calculated by multiplying the financial benefit for the category by the category-specific advertising expense factor determined for the category; generating, at the one or more computer systems, a summation of the calculated category-specific products; generating, at the one or more computer systems, a quotient, wherein the quotient is the summation of the category-specific products divided by a number of sessions with financial benefit; and generating, at the one or more computer systems, a bid amount for the keyword based at least in part on the quotient multiplied by a forecast conversion rate, the forecast conversion rate comprising a predicted percentage of clickthroughs associated with the keyword that results in a conversion. 4. The method of claim 2 wherein the financial benefit is profit generated from purchases of items within a category during a session initiated with the selection of an advertisement for the keyword and the category-specific advertising expense factor is a percent of profit to be spent on advertising for the category of the purchased item. | 0.659 |
8,594,285 | 1 | 8 | 1. A method for analyzing an electronic communication between a customer and a contact center, wherein the electronic communication is a telephonic communication, the method comprising: receiving a single telephonic communication between a first communicant to the telephonic communication and a second communicant to the telephonic communication; separating the telephonic communication into at least first and second constituent voice data, the first constituent voice data being generated by the first communicant and the second constituent voice data being generated by the second communicant; analyzing one of the separated first and second constituent voice data by mining the separated one of the first and second constituent voice data and applying a predetermined linguistic-based psychological behavioral model to the one of the separated first and second constituent voice data; and, generating behavioral assessment data including a personality type corresponding to the analyzed one of the separated first and second constituent voice data based on the step of analyzing one of the first and second constituent voice data. | 1. A method for analyzing an electronic communication between a customer and a contact center, wherein the electronic communication is a telephonic communication, the method comprising: receiving a single telephonic communication between a first communicant to the telephonic communication and a second communicant to the telephonic communication; separating the telephonic communication into at least first and second constituent voice data, the first constituent voice data being generated by the first communicant and the second constituent voice data being generated by the second communicant; analyzing one of the separated first and second constituent voice data by mining the separated one of the first and second constituent voice data and applying a predetermined linguistic-based psychological behavioral model to the one of the separated first and second constituent voice data; and, generating behavioral assessment data including a personality type corresponding to the analyzed one of the separated first and second constituent voice data based on the step of analyzing one of the first and second constituent voice data. 8. The method of claim 1 , wherein the telephonic communication is one of a plurality of telephonic communications, the method further comprising the step of categorizing each of the telephonic communications of the plurality of telephonic communications into one of a plurality of customer categories. | 0.858614 |
9,052,844 | 1 | 3 | 1. A computer-implemented method of arranging text items in a predefined order, comprising: storing, in the memory of a peripheral device, a collection of multiple text items arranged in multiple sets of text items and in multiple groups of text items; and storing a respective code item with a respective group of text items; storing a sort key that has values that designate a predefined order of the text items in each set; wherein the sort key is appended to the text items and comprises at least one character with a value within the Private Use range of the Unicode format sorting the list according to a predetermined sort order using the program and receiving from the program a sorted list with the text items in said sort order; appending the sort key to the text items in the sorted list in a way to designate said sort order; and providing the sorted list with the sort key for storing as a set of the collection of text items in the memory of the peripheral device. | 1. A computer-implemented method of arranging text items in a predefined order, comprising: storing, in the memory of a peripheral device, a collection of multiple text items arranged in multiple sets of text items and in multiple groups of text items; and storing a respective code item with a respective group of text items; storing a sort key that has values that designate a predefined order of the text items in each set; wherein the sort key is appended to the text items and comprises at least one character with a value within the Private Use range of the Unicode format sorting the list according to a predetermined sort order using the program and receiving from the program a sorted list with the text items in said sort order; appending the sort key to the text items in the sorted list in a way to designate said sort order; and providing the sorted list with the sort key for storing as a set of the collection of text items in the memory of the peripheral device. 3. A computer-implemented method according to claim 1 , comprising: selecting at least one of the group of text items in response to a user selection. | 0.748322 |
7,945,602 | 1 | 4 | 1. A method for storing documents in web server document libraries, wherein each document corresponds to only a particular web server document library, the method comprising: a computing system maintaining access to a plurality of web server document libraries having corresponding document library databases and document library file system folders, the computing system including a memory connected to at least one processor that executes stored instructions for implementing the method; receiving a document for storing in association with a selected web server document library, the selected web server document library including a document library database and a document library file system folder; associating a collective set of properties with only the selected web server document library among the plurality of web server document libraries, such that the collective set of properties are unique to the selected web server document library; receiving property value information for the received document that provides values for at least some of the collective set of properties that are unique to the selected web server document library; writing the property value information to the document library database of the selected web server document library, so that the document library database of the selected web server document library includes an entry that stores the property value information for the received document and that uniquely associates the received document with the selected web server document library; and storing the received document in the document library file system folder of the selected web server document library, wherein the document and any other documents stored in the selected document library file system folder have consistent properties selected from the collective set of properties, and wherein all documents stored in the document library file system folder are specific to only in the selected web server document library of the plurality of plurality of web server document libraries and such that the received document is only stored in one folder of the plurality of web server document libraries. | 1. A method for storing documents in web server document libraries, wherein each document corresponds to only a particular web server document library, the method comprising: a computing system maintaining access to a plurality of web server document libraries having corresponding document library databases and document library file system folders, the computing system including a memory connected to at least one processor that executes stored instructions for implementing the method; receiving a document for storing in association with a selected web server document library, the selected web server document library including a document library database and a document library file system folder; associating a collective set of properties with only the selected web server document library among the plurality of web server document libraries, such that the collective set of properties are unique to the selected web server document library; receiving property value information for the received document that provides values for at least some of the collective set of properties that are unique to the selected web server document library; writing the property value information to the document library database of the selected web server document library, so that the document library database of the selected web server document library includes an entry that stores the property value information for the received document and that uniquely associates the received document with the selected web server document library; and storing the received document in the document library file system folder of the selected web server document library, wherein the document and any other documents stored in the selected document library file system folder have consistent properties selected from the collective set of properties, and wherein all documents stored in the document library file system folder are specific to only in the selected web server document library of the plurality of plurality of web server document libraries and such that the received document is only stored in one folder of the plurality of web server document libraries. 4. The method of claim 1 , wherein at least some of the set of collective properties are set to one or more default values, the one or more default values being dependent upon the selected web server document library for the document. | 0.683784 |
7,650,597 | 1 | 19 | 1. A method for transforming an XML data structure into an application programming language data structure comprising: receiving a request for an XML data structure from an application; retrieving the requested XML data structure; executing a transformation program associated with an application programming language data structure, the transformation program including a directional serialization construct and a directional deserialization construct which specify different respective behaviors for transforming the XML data structure into the application programming language data structure and for transforming the application programming language data structure into the XML data structure, wherein an application of source data to both directional constructs yields result data which exactly matches the source data, the directional serialization construct comprising a first construct which, during serialization, terminates with an error when a current referenced node does not have a same value as a node referenced in an attribute, and the directional deserialization construct comprising a second construct which, during deserialization, assigns a value of a node referenced in the attribute to the current referenced node; parsing the XML data structure in a strictly linear fashion using the transformation program, without constructing a tree representation of the XML data structure; evaluating the deserialization construct of the transformation program; and transforming the parsed XML data structure into the application programming language data structure based on the evaluated deserialization construct; and sending the application programming language data structure to the application. | 1. A method for transforming an XML data structure into an application programming language data structure comprising: receiving a request for an XML data structure from an application; retrieving the requested XML data structure; executing a transformation program associated with an application programming language data structure, the transformation program including a directional serialization construct and a directional deserialization construct which specify different respective behaviors for transforming the XML data structure into the application programming language data structure and for transforming the application programming language data structure into the XML data structure, wherein an application of source data to both directional constructs yields result data which exactly matches the source data, the directional serialization construct comprising a first construct which, during serialization, terminates with an error when a current referenced node does not have a same value as a node referenced in an attribute, and the directional deserialization construct comprising a second construct which, during deserialization, assigns a value of a node referenced in the attribute to the current referenced node; parsing the XML data structure in a strictly linear fashion using the transformation program, without constructing a tree representation of the XML data structure; evaluating the deserialization construct of the transformation program; and transforming the parsed XML data structure into the application programming language data structure based on the evaluated deserialization construct; and sending the application programming language data structure to the application. 19. The method of claim 1 , wherein the directional constructs further comprises a <TT:SERIALIZE> construct evaluated during serialization only, and a <TT:DESERIALIZE> construct evaluated during deserialization only. | 0.593985 |
9,507,862 | 1 | 7 | 1. A method performed by at least one processor, the method comprising: accessing a document containing a plurality of facts; detecting a chronological value for each of the plurality of facts contained in the document; detecting a subject reference for each of the plurality of facts contained in the document, wherein the subject reference includes at least one of a person, a place, an object, or an event; determining an identity of the subject reference for each of the plurality of facts from a context in the document and a detection rule; and assembling the plurality of facts into a record based on the determined identity and the chronological value for each of the plurality of facts. | 1. A method performed by at least one processor, the method comprising: accessing a document containing a plurality of facts; detecting a chronological value for each of the plurality of facts contained in the document; detecting a subject reference for each of the plurality of facts contained in the document, wherein the subject reference includes at least one of a person, a place, an object, or an event; determining an identity of the subject reference for each of the plurality of facts from a context in the document and a detection rule; and assembling the plurality of facts into a record based on the determined identity and the chronological value for each of the plurality of facts. 7. The method of claim 1 further comprising: dividing the document into a plurality of portions including at least a first portion and a second portion; determining that the second portion of the document does not include a subject reference; and associating an identity of a subject reference detected in the first portion of the document with the second portion of the document. | 0.693053 |
9,122,540 | 12 | 13 | 12. The computer program product of claim 11 , said method further comprising: prior to said generating, parsing, by the one or more processors, each program statement in the first computer program to generate the parsed first computer program. | 12. The computer program product of claim 11 , said method further comprising: prior to said generating, parsing, by the one or more processors, each program statement in the first computer program to generate the parsed first computer program. 13. The computer program product of claim 12 , wherein said parsing comprises: (i) identifying, in the first computer program, the first program statement that includes the first error and has thrown a parsing exception with respect to the first error prior to said parsing, and (ii) replacing the first program statement by a predefined program statement that is an executable equivalent program statement to the first program statement and can be parsed without throwing any parsing exception. | 0.854924 |
9,218,815 | 19 | 20 | 19. The computer-readable storage device of claim 17 , wherein the recording of the audio and the video yields a dynamic image feature. | 19. The computer-readable storage device of claim 17 , wherein the recording of the audio and the video yields a dynamic image feature. 20. The computer-readable storage device of claim 19 , wherein the dynamic image feature comprises a pattern of movement. | 0.915621 |
7,844,562 | 8 | 9 | 8. A computer system as in claim 1 , wherein the link types include any one or more of causes, triggers, served by, subsumes, leads to, retroduct, and has-method. | 8. A computer system as in claim 1 , wherein the link types include any one or more of causes, triggers, served by, subsumes, leads to, retroduct, and has-method. 9. A computer system as in claim 8 , wherein the regular expression sequences include any one or more of Situation(ImpliesSituation)*TriggersNeedServedByProduct(Subsum- esProduct)*, Need(SubsumesNeed)*ServedByProduct(SubsumesProduct)*, (BehaviorRetroductSituationlBehaviorCausesSituation)(ImpliesSituation)*Tr-iggersNeedServedByProduct(SubsumesProduct)*, Product(IsaProduct)CausesSitu- ation(ImpliesSituation)*, ProductCausesSituation(ImpliesSituation)*TriggersNeed, ProductCausesSituation(ImpliesSituation)*TriggersNeedServedByProduct(SubsumesPro duct)*, Product(IsaProduct)*ServesNeed(IsaNeed)*, Product(SubsumesProduct)*, Situation(ImpliesSituation)*TriggersNeedServedByProduct,Need(SubsumesNeed)* ServedByProduct,BehaviorRetroductSituation|BehaviorCausesSituation)(ImpliesSituation)*Trig gersNeedServedByPr- oduct, and Product(SubsumesProduct). | 0.819267 |
9,280,970 | 1 | 2 | 1. A computer-implemented method performed by a data processing apparatus, the method comprising: receiving, by a data processing apparatus, lattice parse data describing a lattice parse of a command sentence input at a user device as a voice command input sentence and converted to a plurality of terms, the lattice parse data defining a plurality of N nodes and edges connecting the N nodes, each respective edge corresponding to a respective term in the command sentence and connecting a respective first node to a respective second node, wherein one of the first nodes is a source node having only one edge corresponding to a first term in the command sentence and one of the second nodes is a sink node; annotating each respective term of an edge as one of a terminal or a non-terminal; accessing, by the data processing apparatus, a plurality of parsing rules, each parsing rule defined by one or more constituent parsing rules and each parsing rule associated with a particular action, wherein at least some of the paring rules include constituent parsing rules that include non-terminals, and wherein each particular action is an action to be taken by the user device in response to a successful parse of a command sentence by the parsing rule; for each of the parsing rules, determining lattice spans of two or more nodes that define corresponding term spans in the command sentence that are consumed by one or more constituent parsing rules; for each parsing rule for which the determined lattice spans from the source node to the sink node of the lattice parse, selecting the parsing rule as a candidate parse of the command sentence; determining, from the candidate parses of the command sentence, an action to be performed in response to the command sentence; and causing the determined action to be performed. | 1. A computer-implemented method performed by a data processing apparatus, the method comprising: receiving, by a data processing apparatus, lattice parse data describing a lattice parse of a command sentence input at a user device as a voice command input sentence and converted to a plurality of terms, the lattice parse data defining a plurality of N nodes and edges connecting the N nodes, each respective edge corresponding to a respective term in the command sentence and connecting a respective first node to a respective second node, wherein one of the first nodes is a source node having only one edge corresponding to a first term in the command sentence and one of the second nodes is a sink node; annotating each respective term of an edge as one of a terminal or a non-terminal; accessing, by the data processing apparatus, a plurality of parsing rules, each parsing rule defined by one or more constituent parsing rules and each parsing rule associated with a particular action, wherein at least some of the paring rules include constituent parsing rules that include non-terminals, and wherein each particular action is an action to be taken by the user device in response to a successful parse of a command sentence by the parsing rule; for each of the parsing rules, determining lattice spans of two or more nodes that define corresponding term spans in the command sentence that are consumed by one or more constituent parsing rules; for each parsing rule for which the determined lattice spans from the source node to the sink node of the lattice parse, selecting the parsing rule as a candidate parse of the command sentence; determining, from the candidate parses of the command sentence, an action to be performed in response to the command sentence; and causing the determined action to be performed. 2. The computer-implemented method of claim 1 , wherein for each of the parsing rules, determining lattice spans of two or more nodes that define corresponding term spans in the command sentence that are consumed by one or more constituent parsing rules comprises incrementally determining lattice spans on increasing node lengths until one of a lattice span from the source node to the sink node or a failure determine a lattice span from the source node to the sink node occurs. | 0.612278 |
9,910,588 | 2 | 6 | 2. The method of claim 1 , further comprising: in response to determining that the candidate partition of the next highest rank set of predicted input characters is unallocated, allocating the next highest rank set of predicted input characters to the candidate partition. | 2. The method of claim 1 , further comprising: in response to determining that the candidate partition of the next highest rank set of predicted input characters is unallocated, allocating the next highest rank set of predicted input characters to the candidate partition. 6. The method of claim 2 , wherein the partitions are defined by a number of columns in an area of the virtual keyboard. | 0.955556 |
8,849,830 | 1 | 11 | 1. A method of delivering a search result comprising: assigning destination scores to a document with respect to a plurality of categories based on a plurality random walks of a linked corpus including the document with random teleportation hops biased toward a plurality of seed sets corresponding to the plurality of categories; assigning source scores to the document with respect to the plurality of categories, the source scores for the document indicating a contribution of the document to one or more destination scores of other nodes in the linked corpus; assigning combined scores to the document based on a combinations of the destination and source scores; associating a category of the plurality of categories with the document based at least in part on the combined scores; obtaining a search query; and delivering a plurality of search results to a user in a manner that includes an indication to the user of at least one category associated with each search result of the plurality of search results, wherein each search result of the plurality of search results is accompanied by one or more controls configured to: allow the user to selectively refine whether additional results from the at least one associated category should be displayed or excluded, and allow the user to selectively display or exclude all results from a particular associated category. | 1. A method of delivering a search result comprising: assigning destination scores to a document with respect to a plurality of categories based on a plurality random walks of a linked corpus including the document with random teleportation hops biased toward a plurality of seed sets corresponding to the plurality of categories; assigning source scores to the document with respect to the plurality of categories, the source scores for the document indicating a contribution of the document to one or more destination scores of other nodes in the linked corpus; assigning combined scores to the document based on a combinations of the destination and source scores; associating a category of the plurality of categories with the document based at least in part on the combined scores; obtaining a search query; and delivering a plurality of search results to a user in a manner that includes an indication to the user of at least one category associated with each search result of the plurality of search results, wherein each search result of the plurality of search results is accompanied by one or more controls configured to: allow the user to selectively refine whether additional results from the at least one associated category should be displayed or excluded, and allow the user to selectively display or exclude all results from a particular associated category. 11. The method of claim 1 wherein the associated category is formed by performing one or more operations on a plurality of base categories. | 0.813172 |
9,864,781 | 1 | 6 | 1. A computing device, comprising: a memory; a storage; a display; and a processor coupled to the memory, to the storage, and to the display, the processor being configured to execute instructions stored in the memory to: receive an input from a single user, the received input comprising at least one search term; access, over a computer network, at least one of a Network Attached Storage (NAS) and a Direct Attached Storage (DAS); associate the received input with a search result comprising at least one digital item stored in the at least one of the NAS and the DAS based upon: the received input; prior inputs of search terms to the at least one of the NAS and DAS by the single user; prior accesses of the at least one digital item stored in at least one of the NAS and the DAS based upon the prior inputs of the search terms; and prior associations of the search terms of the prior inputs with prior search results comprising the at least one stored digital item, wherein at least some of the search terms of the prior inputs are unrelated to a name, original metadata and content of the at least one stored digital item and have previously led the single user to find and access the at least one digital item; and present the at least one digital item to the single user on the display of the computing device. | 1. A computing device, comprising: a memory; a storage; a display; and a processor coupled to the memory, to the storage, and to the display, the processor being configured to execute instructions stored in the memory to: receive an input from a single user, the received input comprising at least one search term; access, over a computer network, at least one of a Network Attached Storage (NAS) and a Direct Attached Storage (DAS); associate the received input with a search result comprising at least one digital item stored in the at least one of the NAS and the DAS based upon: the received input; prior inputs of search terms to the at least one of the NAS and DAS by the single user; prior accesses of the at least one digital item stored in at least one of the NAS and the DAS based upon the prior inputs of the search terms; and prior associations of the search terms of the prior inputs with prior search results comprising the at least one stored digital item, wherein at least some of the search terms of the prior inputs are unrelated to a name, original metadata and content of the at least one stored digital item and have previously led the single user to find and access the at least one digital item; and present the at least one digital item to the single user on the display of the computing device. 6. The computing device of claim 1 , wherein the at least one stored digital item comprises at least one of a document, a file, a movie, a picture, a website, music and a location. | 0.77887 |
7,536,364 | 1 | 4 | 1. A computerized method for performing multi-objective asset optimization and decision-making using predictive modeling, comprising: building, via a process manager application executing on a processor, at least two predictive models for an asset, the asset comprising a physical machine that is communicatively coupled to the processor, the building comprising: categorizing operational historical data of the asset that is retrieved from a storage device, the operation historical data categorized by at least one of: controllable variables; uncontrollable variables; output objectives; and constraints; selecting at least two output objectives or constraints; and identifying at least one controllable or uncontrollable variable suitable for achieving the at least two output objectives or constraints; inputting, via the process manager application, the at least one controllable or uncontrollable variable to each of the at least two predictive models; validating, via the process manager application, each predictive model; if results of the validating indicate a confidence level above a specified threshold, applying, via the process manager application, a live data stream of inputs from the asset to the predictive models; if results of the validating indicate a confidence level at or below a specified threshold, selecting, via the process manager application, at least one alternative controllable or uncontrollable variable for input to the predictive models; performing, via the process manager application, multi-objective optimization using the predictive models, comprising: specifying search constraints, comprising: upper and lower bounds for each input variable; and tolerance levels representing a range of values for achieving optimal output objectives, and constraints; applying a multi-objective optimization algorithm; and generating a Pareto Frontier, the Pareto Frontier including optimal input-output vectors; using results of the multi-objective optimization, selecting, via the process manager application, from the Pareto Frontier, a Pareto optimal input-output vector for deployment to the asset, the selected Pareto optimal input-output vector specifying an optimal operational state for the asset; and re-configuring the asset, via the process manager application, using the Pareto optimal input-output vector to realize the optimal operational state. | 1. A computerized method for performing multi-objective asset optimization and decision-making using predictive modeling, comprising: building, via a process manager application executing on a processor, at least two predictive models for an asset, the asset comprising a physical machine that is communicatively coupled to the processor, the building comprising: categorizing operational historical data of the asset that is retrieved from a storage device, the operation historical data categorized by at least one of: controllable variables; uncontrollable variables; output objectives; and constraints; selecting at least two output objectives or constraints; and identifying at least one controllable or uncontrollable variable suitable for achieving the at least two output objectives or constraints; inputting, via the process manager application, the at least one controllable or uncontrollable variable to each of the at least two predictive models; validating, via the process manager application, each predictive model; if results of the validating indicate a confidence level above a specified threshold, applying, via the process manager application, a live data stream of inputs from the asset to the predictive models; if results of the validating indicate a confidence level at or below a specified threshold, selecting, via the process manager application, at least one alternative controllable or uncontrollable variable for input to the predictive models; performing, via the process manager application, multi-objective optimization using the predictive models, comprising: specifying search constraints, comprising: upper and lower bounds for each input variable; and tolerance levels representing a range of values for achieving optimal output objectives, and constraints; applying a multi-objective optimization algorithm; and generating a Pareto Frontier, the Pareto Frontier including optimal input-output vectors; using results of the multi-objective optimization, selecting, via the process manager application, from the Pareto Frontier, a Pareto optimal input-output vector for deployment to the asset, the selected Pareto optimal input-output vector specifying an optimal operational state for the asset; and re-configuring the asset, via the process manager application, using the Pareto optimal input-output vector to realize the optimal operational state. 4. The computerized method of claim 1 , wherein the output objective includes a target goal for a process. | 0.846377 |
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