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7,933,771 | 18 | 20 | 18. The method as claimed in claim 13 , wherein one of said plurality of strategies of said step (c) is to inform a user of environment conditions and signal quality, and provide said user with corresponding solutions. | 18. The method as claimed in claim 13 , wherein one of said plurality of strategies of said step (c) is to inform a user of environment conditions and signal quality, and provide said user with corresponding solutions. 20. The method as claimed in claim 18 , wherein said corresponding solutions include ways to improve said environment conditions and signal quality. | 0.732852 |
9,697,180 | 1 | 5 | 1. A method for placing a text string on a page, comprising: obtaining an electronic document specifying a margin of the page, an exclusion region having a perimeter for placement on the page, a texture to fill the exclusion region, and the text string; calculating, by a path-fill algorithm and based on the perimeter, a first plurality of geometric primitives corresponding to the exclusion region, wherein the perimeter is an input to the path-fill algorithm, and wherein the first plurality of geometric primitives is an output of the path-fill algorithm; defining a vector path comprising: a closed margin subpath corresponding to the margin and having a first direction; and a closed exclusion region subpath corresponding to the perimeter of the exclusion region and having a second direction that is opposite the first direction, wherein the closed exclusion region subpath is contained within the closed margin subpath; calculating, by the same path-fill algorithm and based on a winding number and the vector path associated with the perimeter and the margin, a second plurality of geometric primitives corresponding to a text region on the page excluding the margin and the exclusion region, wherein the vector path and the winding number are inputs to the path-fill algorithm, and wherein the second plurality of geometric primitives is an output of the path-fill algorithm; receiving, by a line extent interface, the text string and the second plurality of geometric primitives; calculating, by the line extent interface and for a first line band crossing the page, a first plurality of segments corresponding to an intersection of the first line band with the second plurality of geometric primitives; and rendering the page by: filling the first plurality of geometric primitives with the texture; and placing a first portion of the text string within the first plurality of segments. | 1. A method for placing a text string on a page, comprising: obtaining an electronic document specifying a margin of the page, an exclusion region having a perimeter for placement on the page, a texture to fill the exclusion region, and the text string; calculating, by a path-fill algorithm and based on the perimeter, a first plurality of geometric primitives corresponding to the exclusion region, wherein the perimeter is an input to the path-fill algorithm, and wherein the first plurality of geometric primitives is an output of the path-fill algorithm; defining a vector path comprising: a closed margin subpath corresponding to the margin and having a first direction; and a closed exclusion region subpath corresponding to the perimeter of the exclusion region and having a second direction that is opposite the first direction, wherein the closed exclusion region subpath is contained within the closed margin subpath; calculating, by the same path-fill algorithm and based on a winding number and the vector path associated with the perimeter and the margin, a second plurality of geometric primitives corresponding to a text region on the page excluding the margin and the exclusion region, wherein the vector path and the winding number are inputs to the path-fill algorithm, and wherein the second plurality of geometric primitives is an output of the path-fill algorithm; receiving, by a line extent interface, the text string and the second plurality of geometric primitives; calculating, by the line extent interface and for a first line band crossing the page, a first plurality of segments corresponding to an intersection of the first line band with the second plurality of geometric primitives; and rendering the page by: filling the first plurality of geometric primitives with the texture; and placing a first portion of the text string within the first plurality of segments. 5. The method of claim 1 , wherein the first line band is horizontal. | 0.904696 |
10,025,817 | 15 | 17 | 15. A non-transitory computer-readable media 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: receiving transaction information associated with user actions during use by a first user of a business intelligence tool, each user action associated with an operation in a particular stage of processing on business data obtained from one or more databases, the transaction information for a particular user action including: a user identifier identifying the first user performing the particular user action; stage information identifying the particular stage of the processing in which the particular user action occurs; the operation associated with the particular user action; and one or more parameters used in the operation; storing the transaction information; monitoring subsequent user actions by the first user in a current session, wherein monitoring subsequent user actions includes determining a time at which stage conditions associated with the current session for the first user match a portion of the stored transaction information corresponding to the first user and the stage information; and in response to determining that stage conditions exist in the stored transaction information that match the first user and the stage conditions of the current context: identifying pertinent transactions associated with the matching stage conditions; creating one or more suggestions for presentation to the first user, each suggestion of the one or more suggestions being associated with groups of one or more transactions of the pertinent transactions; and providing the one or more suggestions for presentation to the first user. | 15. A non-transitory computer-readable media 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: receiving transaction information associated with user actions during use by a first user of a business intelligence tool, each user action associated with an operation in a particular stage of processing on business data obtained from one or more databases, the transaction information for a particular user action including: a user identifier identifying the first user performing the particular user action; stage information identifying the particular stage of the processing in which the particular user action occurs; the operation associated with the particular user action; and one or more parameters used in the operation; storing the transaction information; monitoring subsequent user actions by the first user in a current session, wherein monitoring subsequent user actions includes determining a time at which stage conditions associated with the current session for the first user match a portion of the stored transaction information corresponding to the first user and the stage information; and in response to determining that stage conditions exist in the stored transaction information that match the first user and the stage conditions of the current context: identifying pertinent transactions associated with the matching stage conditions; creating one or more suggestions for presentation to the first user, each suggestion of the one or more suggestions being associated with groups of one or more transactions of the pertinent transactions; and providing the one or more suggestions for presentation to the first user. 17. The non-transitory computer-readable media of claim 15 , wherein stages are sequential and are selected from the group comprising a data preparation stage in which data is prepared, a visualization stage in which data is presented in a visualization to the first user, a synthesis stage in which a business story is created from one or more visualizations, and a sharing stage in which business information associated with previous stages is shared. | 0.659398 |
8,300,023 | 44 | 46 | 44. The non-transitory computer-readable medium of claim 39 , wherein the stored processor-executable instructions are configured to cause the processor to perform operations further comprising: monitoring typing on the virtual keypad on the touch sensitive surface; identifying an adjacent key typing error; determining a correct key associated with the adjacent key typing error; updating the average coordinate for the correct key based upon received coordinates for the typed keystroke; and saving the updated average coordinates with the correct key in the keypad layout data. | 44. The non-transitory computer-readable medium of claim 39 , wherein the stored processor-executable instructions are configured to cause the processor to perform operations further comprising: monitoring typing on the virtual keypad on the touch sensitive surface; identifying an adjacent key typing error; determining a correct key associated with the adjacent key typing error; updating the average coordinate for the correct key based upon received coordinates for the typed keystroke; and saving the updated average coordinates with the correct key in the keypad layout data. 46. The non-transitory computer-readable medium of claim 44 , wherein the stored processor-executable instructions configured to cause the processor to identify an adjacent key typing error cause the processor to perform operations further comprising: recognizing a user correction of a letter associated with a key; and determining whether the user correction involves a switch of two keys that are adjacent to each other in the virtual keypad. | 0.5 |
8,335,802 | 1 | 6 | 1. A computer-implemented method of distributing information retrieved from one or more data repositories, the method comprising: invoking, at a computer device separate from the one or more data repositories, a producer method to generate a document using data retrieved from one or more data repositories, the producer method selected, at a user interface, from a plurality of producer methods, wherein the plurality of producer methods are configured to generate different documents based on same data retrieved from the one or more data repositories; invoking, at the computer device separate from the one or more data repositories, a converter method to convert the generated document to an output format, the converter method selected, at the user interface, from a plurality of converter methods; and invoking, at the computer device separate from the one or more data repositories, a distributor method to distribute the converted document through a distribution channel, the distributor method selected, at the user interface, from a plurality of distributor methods, wherein the invoking of the producer, converter, and distributor methods is triggered by an event, and wherein the producer, converter, and distributor methods are registered to be selected when the trigger is received; wherein the event is associated, at the user interface, with one or more settings defining the producer, converter, and distributor methods and at least one of the producer, converter, and distributor methods can be added to the one or more settings without affecting existing at least one of producer, converter, and distributor methods defined by the one or more settings, wherein the at least one of the added producer, converter, and distributor methods is configured to operate with the at least one of the invoked producer, converter, and distributor methods; wherein the one or more settings is processed based upon a condition that the event meets a predefined criterion. | 1. A computer-implemented method of distributing information retrieved from one or more data repositories, the method comprising: invoking, at a computer device separate from the one or more data repositories, a producer method to generate a document using data retrieved from one or more data repositories, the producer method selected, at a user interface, from a plurality of producer methods, wherein the plurality of producer methods are configured to generate different documents based on same data retrieved from the one or more data repositories; invoking, at the computer device separate from the one or more data repositories, a converter method to convert the generated document to an output format, the converter method selected, at the user interface, from a plurality of converter methods; and invoking, at the computer device separate from the one or more data repositories, a distributor method to distribute the converted document through a distribution channel, the distributor method selected, at the user interface, from a plurality of distributor methods, wherein the invoking of the producer, converter, and distributor methods is triggered by an event, and wherein the producer, converter, and distributor methods are registered to be selected when the trigger is received; wherein the event is associated, at the user interface, with one or more settings defining the producer, converter, and distributor methods and at least one of the producer, converter, and distributor methods can be added to the one or more settings without affecting existing at least one of producer, converter, and distributor methods defined by the one or more settings, wherein the at least one of the added producer, converter, and distributor methods is configured to operate with the at least one of the invoked producer, converter, and distributor methods; wherein the one or more settings is processed based upon a condition that the event meets a predefined criterion. 6. The method of claim 1 , wherein the producer, converter and distributor methods are invoked by processing a setting that references the producer, converter and distributor methods. | 0.772953 |
8,326,850 | 1 | 3 | 1. A data converting apparatus comprising: a storage unit that stores encoded meta-definition information that assigns a metadata code as a unique code to an element making up metadata in meta-definition information that defines metadata indicative of a property related to data of a conversion source and a conversion destination, a data converting function that converts conversion source data having a property prescribed by the metadata for the conversion source into conversion destination data having a property prescribed by the metadata for the conversion destination, a conversion rule table that assigns the data converting function according to a combination of a metadata code for the conversion source and a metadata code for the conversion destination, and a conversion rule that correlates with each of the conversion rule tables, a relevant metadata code as a conversion rule code; an input unit that receives input of data to be converted; a detecting unit that refers to the encoded meta-definition information stored in the storage unit and detects the metadata codes for the conversion source and the conversion destination for which the conversion rule code matches between the conversion source and the conversion destination; a determining unit that determines whether the detected metadata codes for the conversion source and for the conversion destination match; a converting function specifying unit that, by referring to a conversion rule stored in the storage unit and based on the determination result obtained by the determining unit, specifies the data converting function, according to the combination of the metadata code for the conversion source and the metadata code for the conversion destination; and a converting unit that, by using the data converting function specified by the converting function specifying unit, converts the conversion source data, which is the data to be converted, to have a property prescribed by metadata for the conversion destination. | 1. A data converting apparatus comprising: a storage unit that stores encoded meta-definition information that assigns a metadata code as a unique code to an element making up metadata in meta-definition information that defines metadata indicative of a property related to data of a conversion source and a conversion destination, a data converting function that converts conversion source data having a property prescribed by the metadata for the conversion source into conversion destination data having a property prescribed by the metadata for the conversion destination, a conversion rule table that assigns the data converting function according to a combination of a metadata code for the conversion source and a metadata code for the conversion destination, and a conversion rule that correlates with each of the conversion rule tables, a relevant metadata code as a conversion rule code; an input unit that receives input of data to be converted; a detecting unit that refers to the encoded meta-definition information stored in the storage unit and detects the metadata codes for the conversion source and the conversion destination for which the conversion rule code matches between the conversion source and the conversion destination; a determining unit that determines whether the detected metadata codes for the conversion source and for the conversion destination match; a converting function specifying unit that, by referring to a conversion rule stored in the storage unit and based on the determination result obtained by the determining unit, specifies the data converting function, according to the combination of the metadata code for the conversion source and the metadata code for the conversion destination; and a converting unit that, by using the data converting function specified by the converting function specifying unit, converts the conversion source data, which is the data to be converted, to have a property prescribed by metadata for the conversion destination. 3. The data converting apparatus according to claim 1 , further comprising a table specifying unit that, based on the conversion rule code for the conversion source, specifies a corresponding conversion rule table from the data type conversion rule table or the cleansing rule table by referring to the conversion rule, when mismatch is determined by the determining unit, wherein the converting function specifying unit, by referring to the conversion rule table specified by the table specifying unit, specifies the data converting function, according to the combination of the metadata code for the conversion source and the metadata code for the conversion destination. | 0.664172 |
7,886,266 | 14 | 17 | 14. A system for enhancing performance of a data-pattern recognizer for an individual, the system comprising: one or more processors; a memory; a personalization component that customizes the recognizer to the individual, the personalization being based at least in part upon a sample generated by the individual, the personalization component utilizes regularization biased to a base set of parameters of the recognizer; a base-parameter component that obtains the base set of parameters of the recognizer; and a regularization component that utilizes regularization to determine a new set of parameters for the recognizer based upon the regularization and the sample, wherein one or more of the components comprise a set of processor-executable instructions stored in the memory that, when executed by the one or more processors, perform its described operation. | 14. A system for enhancing performance of a data-pattern recognizer for an individual, the system comprising: one or more processors; a memory; a personalization component that customizes the recognizer to the individual, the personalization being based at least in part upon a sample generated by the individual, the personalization component utilizes regularization biased to a base set of parameters of the recognizer; a base-parameter component that obtains the base set of parameters of the recognizer; and a regularization component that utilizes regularization to determine a new set of parameters for the recognizer based upon the regularization and the sample, wherein one or more of the components comprise a set of processor-executable instructions stored in the memory that, when executed by the one or more processors, perform its described operation. 17. The system of claim 14 , further comprising: a deviation component that determines the deviation from the base set of parameters to a possible set of parameters; an error-rate component that determines the error rate over the sample using the possible set of parameters; and a minimization component that selects the new set of parameters to minimize the sum of the error rate and the deviation. | 0.5 |
8,666,961 | 9 | 10 | 9. Non-transitory computer storage that stores executable instructions that direct a computing system to perform a process that comprises: receiving a code that identifies a printed publication, said code obtained from a photograph of a representation of the code on a hardcopy of the printed publication, wherein the code is an ISBN code obtained from an ISBN bar code on the hardcopy; receiving a user-selected content portion of the printed publication, wherein receiving the user-selected content portion comprises receiving a photograph of a user-selected portion of the hardcopy and applying OCR to the photograph to generate textual data; retrieving information regarding the printed publication using said code; generating a bibliographic citation for the content portion using the retrieved information regarding the printed publication; and storing the content portion in association with the bibliographic citation; wherein the executable instructions include instructions of a mobile application that provides functionality for automatically generating citations based on photographic images taken with a mobile device on which the mobile application runs. | 9. Non-transitory computer storage that stores executable instructions that direct a computing system to perform a process that comprises: receiving a code that identifies a printed publication, said code obtained from a photograph of a representation of the code on a hardcopy of the printed publication, wherein the code is an ISBN code obtained from an ISBN bar code on the hardcopy; receiving a user-selected content portion of the printed publication, wherein receiving the user-selected content portion comprises receiving a photograph of a user-selected portion of the hardcopy and applying OCR to the photograph to generate textual data; retrieving information regarding the printed publication using said code; generating a bibliographic citation for the content portion using the retrieved information regarding the printed publication; and storing the content portion in association with the bibliographic citation; wherein the executable instructions include instructions of a mobile application that provides functionality for automatically generating citations based on photographic images taken with a mobile device on which the mobile application runs. 10. The non-transitory computer storage of claim 9 , wherein the mobile application includes a user interface and associated functionality for inserting the content portion and bibliographic citation into a user-selected document. | 0.526749 |
9,384,217 | 15 | 16 | 15. The method of claim 1 , further comprising receiving a command operation, wherein the command operation causes an instruction associated with the command to be performed with respect to the telestration. | 15. The method of claim 1 , further comprising receiving a command operation, wherein the command operation causes an instruction associated with the command to be performed with respect to the telestration. 16. The method of claim 15 , further comprising determining a context associated with the command operation, wherein the context is used to determine an action to perform for the instruction associated with the command. | 0.5 |
7,917,480 | 17 | 18 | 17. A multi-tier document decompression method, comprising: selecting a range of token positions in a set of documents, each token position in the range of token positions corresponding to a respective token in the set of documents; obtaining a set of first token identifiers from locations in a repository, the set of first token identifiers corresponding to the selected range of token positions in the set of documents, wherein the set of first token identifiers represent document content in the selected range of token positions in the set of documents; mapping each of the first token identifiers in the set of first token identifiers to a respective second token identifier, wherein each second token identifier uniquely represents a corresponding token in the set of documents, and each token comprises document content in the set of documents; mapping each respective second token identifier to a corresponding token in the set of documents; and reconstructing at least a portion of a document in the set of documents using the tokens from the mapping of the second token identifiers to corresponding tokens, and using the token positions corresponding to the first token identifiers; wherein the mapping of each first token identifier is in accordance with a respective first lexicon for a portion of the repository that includes the first token identifier, and the mapping of each second token identifier is in accordance with a second lexicon that maps second token identifiers to unique tokens in the set of documents. | 17. A multi-tier document decompression method, comprising: selecting a range of token positions in a set of documents, each token position in the range of token positions corresponding to a respective token in the set of documents; obtaining a set of first token identifiers from locations in a repository, the set of first token identifiers corresponding to the selected range of token positions in the set of documents, wherein the set of first token identifiers represent document content in the selected range of token positions in the set of documents; mapping each of the first token identifiers in the set of first token identifiers to a respective second token identifier, wherein each second token identifier uniquely represents a corresponding token in the set of documents, and each token comprises document content in the set of documents; mapping each respective second token identifier to a corresponding token in the set of documents; and reconstructing at least a portion of a document in the set of documents using the tokens from the mapping of the second token identifiers to corresponding tokens, and using the token positions corresponding to the first token identifiers; wherein the mapping of each first token identifier is in accordance with a respective first lexicon for a portion of the repository that includes the first token identifier, and the mapping of each second token identifier is in accordance with a second lexicon that maps second token identifiers to unique tokens in the set of documents. 18. The method of claim 17 , wherein each second token identifier comprises an M bit integer value. | 0.5 |
7,716,199 | 53 | 69 | 53. A computer-readable medium encoded with a computer program comprising commands that, when executed, operate to cause a computer to perform operations comprising: receiving multiple context files from one or more third-party content providers, wherein each set of commands contains one or more commands for controlling an operation of the search engine in processing a search query input and in presenting search results, each context file is one of a plurality of predefined context files; receiving in a search engine the search query input, the search query input received from an interface provided by one of the third party content providers; aggregating the commands in the multiple context files into a set of aggregated commands; using the aggregated commands to control an organization and a presentation of the search results resulting from the processing of the search query input, including: processing the search query input using the aggregated commands to produce a context processed search query; generating context processed search results responsive to the context processed search query; and providing the context processed search results in accordance with the aggregated commands. | 53. A computer-readable medium encoded with a computer program comprising commands that, when executed, operate to cause a computer to perform operations comprising: receiving multiple context files from one or more third-party content providers, wherein each set of commands contains one or more commands for controlling an operation of the search engine in processing a search query input and in presenting search results, each context file is one of a plurality of predefined context files; receiving in a search engine the search query input, the search query input received from an interface provided by one of the third party content providers; aggregating the commands in the multiple context files into a set of aggregated commands; using the aggregated commands to control an organization and a presentation of the search results resulting from the processing of the search query input, including: processing the search query input using the aggregated commands to produce a context processed search query; generating context processed search results responsive to the context processed search query; and providing the context processed search results in accordance with the aggregated commands. 69. The computer-readable medium of claim 53 , wherein the operations further comprise: identifying a third-party content provider having specialized knowledge of a subject identified by the search query input, based on accessing the search engine query; and querying the identified third-party content provider for a first context file associated with the search query input. | 0.5 |
9,357,022 | 17 | 18 | 17. The system of claim 13 , further comprising: determining for each of the plurality of actions, a weight associated with the action; and calculating the activity score based on the weight associated with each of the plurality of actions. | 17. The system of claim 13 , further comprising: determining for each of the plurality of actions, a weight associated with the action; and calculating the activity score based on the weight associated with each of the plurality of actions. 18. The system of claim 17 , wherein the activity score comprises a weighted sum of the total number of unique users performing each of the plurality of actions based on the weight associated with each of the plurality of actions. | 0.5 |
8,583,421 | 1 | 2 | 1. A method of key press prediction on a touch-based device, comprising: registering a position of a touch press attempt on an icon among a plurality of icons presented on the touch-base device; calculating a distance from a reference point of the icon to the position; calculating a psychomotor probability for each icon in the plurality of icons; calculating a linguistic probability for each icon in the plurality of icons; calculating a predictive index for each icon in the plurality of icons based on the psychomotor probability and the linguistic probability; and registering as a user selected icon, an icon with one among a highest predictive index and a probability higher than a predetermined absolute value, wherein for the psychomotor probability calculation, a distribution of finger presses is defined by one among a distance of an x-y position from a center of an icon or key or by a distance of an x-y position from a centroid of pertinent finger presses related to the icon or key, and wherein the distribution of finger presses is a parameter that is standardized using z-scores which allow the determination of a likelihood of an intended key press for specific keys. | 1. A method of key press prediction on a touch-based device, comprising: registering a position of a touch press attempt on an icon among a plurality of icons presented on the touch-base device; calculating a distance from a reference point of the icon to the position; calculating a psychomotor probability for each icon in the plurality of icons; calculating a linguistic probability for each icon in the plurality of icons; calculating a predictive index for each icon in the plurality of icons based on the psychomotor probability and the linguistic probability; and registering as a user selected icon, an icon with one among a highest predictive index and a probability higher than a predetermined absolute value, wherein for the psychomotor probability calculation, a distribution of finger presses is defined by one among a distance of an x-y position from a center of an icon or key or by a distance of an x-y position from a centroid of pertinent finger presses related to the icon or key, and wherein the distribution of finger presses is a parameter that is standardized using z-scores which allow the determination of a likelihood of an intended key press for specific keys. 2. The method of claim 1 , wherein the method calculates the psychomotor probability and the linguistic probability if there is no single icon with a larger probability than the predetermined absolute value. | 0.622263 |
8,209,178 | 13 | 17 | 13. The computer program product of claim 12 , further operable to perform operations comprising: sequentially identifying additional locations of degree one and removing the corresponding n-gram-location pairs until each n-gram of the collection is matched with a unique location in the array. | 13. The computer program product of claim 12 , further operable to perform operations comprising: sequentially identifying additional locations of degree one and removing the corresponding n-gram-location pairs until each n-gram of the collection is matched with a unique location in the array. 17. The computer program product of claim 13 , further operable to perform operations comprising: selecting a plurality of hash functions to apply to each n-gram of the collection in order to identify locations in the array. | 0.53719 |
9,369,711 | 42 | 45 | 42. A non-transitory computer readable storage medium storing instructions for processing video data that upon execution by one or more processors cause the one or more processors to: receive a coded video sequence comprising encoded pictures of a video sequence; receive timing parameters for the coded video sequence that include a condition for signaling a number of clock ticks corresponding to a difference of picture order count (POC) values equal to 1 directly in at least one of a video parameter set (VPS) syntax structure referenced by the coded video sequence and a sequence parameter set (SPS) syntax structure referenced by the coded video sequence; and process the coded video sequence according to the timing parameters. | 42. A non-transitory computer readable storage medium storing instructions for processing video data that upon execution by one or more processors cause the one or more processors to: receive a coded video sequence comprising encoded pictures of a video sequence; receive timing parameters for the coded video sequence that include a condition for signaling a number of clock ticks corresponding to a difference of picture order count (POC) values equal to 1 directly in at least one of a video parameter set (VPS) syntax structure referenced by the coded video sequence and a sequence parameter set (SPS) syntax structure referenced by the coded video sequence; and process the coded video sequence according to the timing parameters. 45. The non-transitory computer readable storage medium of claim 42 , wherein the timing parameters comprise timing parameters for hypothetical reference decoding operations. | 0.834286 |
8,515,948 | 7 | 10 | 7. A system, comprising: a processor; and storage coupled to the processor, wherein the storage stores a computer program for execution by the processor to perform operations, the operations comprising: creating a materialized query table from a base table without applying one or more fine-grained access control rules associated with the base table when obtaining data from the base table; associating a rule with the materialized query table, wherein no data is returned from the materialized query table when there are no fine-grained access control rules associated directly with the materialized query table; in response to receiving a direct access request to the materialized query table in a first query referencing the materialized query table, providing access to the data in the materialized query table by applying a union of the rule and one or more additional fine-grained access control rules associated directly with the materialized query table to the data in the materialized query table before returning the data; and in response to receiving an internal query rewrite request for a second query that uses the base table, rewriting the second query to reflect the one or more additional fine-grained access control rules associated with the base table to form a third query; rewriting the third query to make use of the materialized query table to form a fourth query; and executing the fourth query without applying the union of the rule and the one or more additional fine-grained access control rules associated directly with the materialized query table. | 7. A system, comprising: a processor; and storage coupled to the processor, wherein the storage stores a computer program for execution by the processor to perform operations, the operations comprising: creating a materialized query table from a base table without applying one or more fine-grained access control rules associated with the base table when obtaining data from the base table; associating a rule with the materialized query table, wherein no data is returned from the materialized query table when there are no fine-grained access control rules associated directly with the materialized query table; in response to receiving a direct access request to the materialized query table in a first query referencing the materialized query table, providing access to the data in the materialized query table by applying a union of the rule and one or more additional fine-grained access control rules associated directly with the materialized query table to the data in the materialized query table before returning the data; and in response to receiving an internal query rewrite request for a second query that uses the base table, rewriting the second query to reflect the one or more additional fine-grained access control rules associated with the base table to form a third query; rewriting the third query to make use of the materialized query table to form a fourth query; and executing the fourth query without applying the union of the rule and the one or more additional fine-grained access control rules associated directly with the materialized query table. 10. The system of claim 7 , wherein the operations further comprise: performing materialized query table matching to determine whether to make use of the materialized query table. | 0.72205 |
9,679,251 | 21 | 22 | 21. The at least one server according to claim 16 , wherein the at least one hardware processor further: creates a largest composite sets of evidences G according to a union of a plurality of composite sets of evidences G 1 v , subject to the relationship constraints κ , which support the composite rule L 0 v ; and computes a composite object ω 2 v indicative according to a deductive reasoning of a second validity value for target rule L. | 21. The at least one server according to claim 16 , wherein the at least one hardware processor further: creates a largest composite sets of evidences G according to a union of a plurality of composite sets of evidences G 1 v , subject to the relationship constraints κ , which support the composite rule L 0 v ; and computes a composite object ω 2 v indicative according to a deductive reasoning of a second validity value for target rule L. 22. The at least one server according to claim 21 , wherein the at least one hardware processor further: obtains a set complement of the largest composite sets of evidences G that supports negation of the target rule L; and computes a composite object ω 2 p indicative according to a deductive reasoning of a second plausibility value for the target rule L. | 0.5 |
7,636,662 | 12 | 13 | 12. The method as claimed in claim 11 , further comprising: analyzing an input audio signal of a speaker's speech, wherein analyzing includes: extracting audio features of the speaker's speech from the input audio signal; finding corresponding video representations for the extracted audio features using a semantic association procedure; and matching the corresponding video representations with the audiovisual configurations. | 12. The method as claimed in claim 11 , further comprising: analyzing an input audio signal of a speaker's speech, wherein analyzing includes: extracting audio features of the speaker's speech from the input audio signal; finding corresponding video representations for the extracted audio features using a semantic association procedure; and matching the corresponding video representations with the audiovisual configurations. 13. The method as claimed in claim 12 , further comprising the steps of: creating a computer generated animated face for each selected audiovisual configuration; synchronizing each computer generated animated face with the speaker's speech of the input audio signal; and outputting an audio-visual representation of the speaker's face synchronized with the speaker's speech. | 0.5 |
8,294,919 | 3 | 4 | 3. The apparatus of claim 1 wherein the self-inking printing device includes an elastomeric foam substrate material impregnated with a printing ink and faced with a selectively-permeable outer membrane so as to form a character segment when pressed against the document. | 3. The apparatus of claim 1 wherein the self-inking printing device includes an elastomeric foam substrate material impregnated with a printing ink and faced with a selectively-permeable outer membrane so as to form a character segment when pressed against the document. 4. The apparatus of claim 3 wherein the self-inking printing device comprises a cylindrical, self-inking print roller. | 0.5 |
9,229,927 | 4 | 5 | 4. The method of claim 1 , further comprising determining, by the one or more computing devices, a suggested value of the second term or phrase. | 4. The method of claim 1 , further comprising determining, by the one or more computing devices, a suggested value of the second term or phrase. 5. The method of claim 4 , wherein determining the suggested value of the second term or phrase is based on an analysis, by the one or more computing devices implementing NL processing techniques, of the first term or phrase. | 0.5 |
9,990,641 | 9 | 10 | 9. An advertising server network for finding predictive cross-category search queries for behavioral targeting, comprising: a module for aggregating, using a computer, at least one training model dataset formed by a particular configuration of a data structure, the training model dataset comprising multiple configured data structures each representing an advertisement impression and including at least a history of clicks corresponding to historical advertisement information, a plurality of page features including a position of an advertisement within the page as shown to a particular user, and a plurality of internet property features, and the training model dataset comprising a plurality of targeting categories derived from the historical advertisement information; a module for training a baseline training model dataset with an initial feature set including page information features and advertisement information features, wherein the initial feature set is used to model a prior distribution of clicks and absence of clicks in a training set; a module for determining historical query and targeting category pairs such that the user historical query of the pair is predictive of clicks on display ads with the targeting category of the pair; a module for selecting, using a computer, a plurality of features from the at least one training model dataset, wherein the selected plurality of features include initial features and at least one candidate feature, wherein the candidate feature varies to fit training data and provides measuring likelihood gain of the candidate feature when added to the baseline training model dataset; a module for calculating a click probability for a subject advertisement to be clicked by a user from a page, said calculating using at least the selected plurality of features, wherein the initial features include features of the page, and wherein the at least one candidate feature is different from the initial features of the at least one training model dataset, and said calculating being normalized for queries that have a high click propensity and no relation to any user interest in a behavioral targeting taxonomy; and serving the subject advertisement to the user, when the click probability of the subject advertisement is predictive of clicks on display ads based on the determined historical query and targeting category pairs. | 9. An advertising server network for finding predictive cross-category search queries for behavioral targeting, comprising: a module for aggregating, using a computer, at least one training model dataset formed by a particular configuration of a data structure, the training model dataset comprising multiple configured data structures each representing an advertisement impression and including at least a history of clicks corresponding to historical advertisement information, a plurality of page features including a position of an advertisement within the page as shown to a particular user, and a plurality of internet property features, and the training model dataset comprising a plurality of targeting categories derived from the historical advertisement information; a module for training a baseline training model dataset with an initial feature set including page information features and advertisement information features, wherein the initial feature set is used to model a prior distribution of clicks and absence of clicks in a training set; a module for determining historical query and targeting category pairs such that the user historical query of the pair is predictive of clicks on display ads with the targeting category of the pair; a module for selecting, using a computer, a plurality of features from the at least one training model dataset, wherein the selected plurality of features include initial features and at least one candidate feature, wherein the candidate feature varies to fit training data and provides measuring likelihood gain of the candidate feature when added to the baseline training model dataset; a module for calculating a click probability for a subject advertisement to be clicked by a user from a page, said calculating using at least the selected plurality of features, wherein the initial features include features of the page, and wherein the at least one candidate feature is different from the initial features of the at least one training model dataset, and said calculating being normalized for queries that have a high click propensity and no relation to any user interest in a behavioral targeting taxonomy; and serving the subject advertisement to the user, when the click probability of the subject advertisement is predictive of clicks on display ads based on the determined historical query and targeting category pairs. 10. The advertising server network of claim 9 , further comprising: mapping a particular query to at least one targeting category; and presenting, on a computer display, the subject advertisement on the page, the subject advertisement selected on the basis of the value of the click probability. | 0.5 |
8,805,772 | 1 | 2 | 1. A method for providing contextual feedback of rules similarity based on co-occurrence history, the method comprising: selecting a rule for editing in a rules editor executing in memory of a computer; identifying different rules also having been applied to an input in common with the selected rule; and, displaying the identified different rules in the rules editor in connection with the selected rule. | 1. A method for providing contextual feedback of rules similarity based on co-occurrence history, the method comprising: selecting a rule for editing in a rules editor executing in memory of a computer; identifying different rules also having been applied to an input in common with the selected rule; and, displaying the identified different rules in the rules editor in connection with the selected rule. 2. The method of claim 1 , wherein selecting a rule for editing in a rules editor executing in memory of a computer, comprises selecting a rule for editing in a rules editor of a business rules management system (BRMS) executing in memory of a computer. | 0.633333 |
10,074,097 | 6 | 10 | 6. A business classification system comprising: one or more processors, and a computer-readable medium comprising instructions stored therein, which when executed by the one or more processors, causes the one or more processors to perform operations comprising: receiving a plurality of business categories, wherein each of the business categories is associated with (i) at least one category profile and (ii) a set of electronic messages, wherein the set of electronic messages are maintained in a storage device; receiving business information for an unclassified business, wherein the business information comprises at least information describing power consumption of the unclassified business and a zoning restriction classification associated with a location at which the unclassified business operates; comparing the business information to one or more of the category profiles to determine if the unclassified business corresponds with at least one of the plurality of business categories based at least in part on the power consumption of the unclassified business, wherein for a first business category of the plurality of business categories, the comparing comprises: (i) determining a degree of similarity value describing a degree to which the business information matches information contained within the one or more of the category profiles associated with the first business category; and (ii) determining that the unclassified business corresponds with the first business category when the degree of similarity value exceeds a predetermined threshold; in response to determining that the unclassified business corresponds with the first business category, associating the unclassified business with the first business category, wherein a first subset of the set of electronic messages are maintained in the storage device in association with the first business category; and controlling transmission of the set of electronic messages based on associations between businesses and the business categories, comprising: (i) selecting the first subset of the set of electronic messages from the storage device for transmission to remote devices associated with the unclassified business based on the unclassified business being associated with the first business category; and (ii) sending the first subset of the set of electronic messages to the remote devices associated with the unclassified business. | 6. A business classification system comprising: one or more processors, and a computer-readable medium comprising instructions stored therein, which when executed by the one or more processors, causes the one or more processors to perform operations comprising: receiving a plurality of business categories, wherein each of the business categories is associated with (i) at least one category profile and (ii) a set of electronic messages, wherein the set of electronic messages are maintained in a storage device; receiving business information for an unclassified business, wherein the business information comprises at least information describing power consumption of the unclassified business and a zoning restriction classification associated with a location at which the unclassified business operates; comparing the business information to one or more of the category profiles to determine if the unclassified business corresponds with at least one of the plurality of business categories based at least in part on the power consumption of the unclassified business, wherein for a first business category of the plurality of business categories, the comparing comprises: (i) determining a degree of similarity value describing a degree to which the business information matches information contained within the one or more of the category profiles associated with the first business category; and (ii) determining that the unclassified business corresponds with the first business category when the degree of similarity value exceeds a predetermined threshold; in response to determining that the unclassified business corresponds with the first business category, associating the unclassified business with the first business category, wherein a first subset of the set of electronic messages are maintained in the storage device in association with the first business category; and controlling transmission of the set of electronic messages based on associations between businesses and the business categories, comprising: (i) selecting the first subset of the set of electronic messages from the storage device for transmission to remote devices associated with the unclassified business based on the unclassified business being associated with the first business category; and (ii) sending the first subset of the set of electronic messages to the remote devices associated with the unclassified business. 10. The business classification system of claim 6 , wherein the business information further comprises a square footage associated with a building in which the unclassified business operates. | 0.814202 |
9,398,030 | 13 | 18 | 13. A computing device comprising: one or more processors; and one or more computer-readable storage media comprising computer executable instructions stored thereon that, responsive to execution by the one or more processors, cause the one or more processors to: receive a call from a third party object that requests a domain context; ascertain the domain context of the third party object; return the domain context to the third party object; require the third party object to include its associated domain context in subsequent calls that the third party object makes; receive a subsequent call from the third party object; ascertain, from the subsequent call, the domain context of the third party object; and make a domain context-based decision based on the ascertained domain context by refusing to allow the subsequent call to execute if the third party object's ascertained domain context does not match a target window domain context or allowing the subsequent call to execute if the third party object's ascertained domain context matches the target window domain context. | 13. A computing device comprising: one or more processors; and one or more computer-readable storage media comprising computer executable instructions stored thereon that, responsive to execution by the one or more processors, cause the one or more processors to: receive a call from a third party object that requests a domain context; ascertain the domain context of the third party object; return the domain context to the third party object; require the third party object to include its associated domain context in subsequent calls that the third party object makes; receive a subsequent call from the third party object; ascertain, from the subsequent call, the domain context of the third party object; and make a domain context-based decision based on the ascertained domain context by refusing to allow the subsequent call to execute if the third party object's ascertained domain context does not match a target window domain context or allowing the subsequent call to execute if the third party object's ascertained domain context matches the target window domain context. 18. The computing device as recited in claim 13 , wherein the receiving the call that requests the domain context is performed by a web application. | 0.764331 |
8,719,262 | 14 | 18 | 14. A system comprising: a server, including a processor, to: identify documents relating to a query; generate a plurality of substrings from the query; calculate, for a particular substring of the plurality of substrings, a value relating to one or more documents, of the identified documents, that contain the particular substring; determine that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; select, for a semantic unit, the particular substring from the plurality of substrings based on the calculated value for the particular substring satisfying the particular threshold; and obtain a refined list of documents by refining the identified documents based on the semantic unit. | 14. A system comprising: a server, including a processor, to: identify documents relating to a query; generate a plurality of substrings from the query; calculate, for a particular substring of the plurality of substrings, a value relating to one or more documents, of the identified documents, that contain the particular substring; determine that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; select, for a semantic unit, the particular substring from the plurality of substrings based on the calculated value for the particular substring satisfying the particular threshold; and obtain a refined list of documents by refining the identified documents based on the semantic unit. 18. The system of claim 14 , where the value is weighted based on a ranking defined by relevance of the identified documents. | 0.802839 |
10,127,022 | 1 | 17 | 1. A method comprising: providing a development environment for a dataflow programming language allowing specifying of at least one matcher state machine that can perform pattern matching in a received input stream and generate output data, wherein the development environment comprises a plurality of tools to perform at least one of the following: identifying a plurality of potential data streams; identifying a set of reactive functions and parameters corresponding to patterns of data in the streams; identifying a set of handling functions and parameters for transforming data matching declared patterns; identifying a set of timed events against which patterns of data flow are compared; creating a dataflow program from expressed intent which describes the identified streams, reactions, functions, and timed events; providing the dataflow program as input to a two-phase translation tool comprising a first-phase translation tool incorporating a matcher generator for translating program statements to corresponding matchers, data flow topologies, functions, and related symbolic components, and a second-phase translation tool for generating optimized platform-specific hardware instructions corresponding to the translated statements for execution on a hardware platform; and receiving the output of each phase of the translation tool. | 1. A method comprising: providing a development environment for a dataflow programming language allowing specifying of at least one matcher state machine that can perform pattern matching in a received input stream and generate output data, wherein the development environment comprises a plurality of tools to perform at least one of the following: identifying a plurality of potential data streams; identifying a set of reactive functions and parameters corresponding to patterns of data in the streams; identifying a set of handling functions and parameters for transforming data matching declared patterns; identifying a set of timed events against which patterns of data flow are compared; creating a dataflow program from expressed intent which describes the identified streams, reactions, functions, and timed events; providing the dataflow program as input to a two-phase translation tool comprising a first-phase translation tool incorporating a matcher generator for translating program statements to corresponding matchers, data flow topologies, functions, and related symbolic components, and a second-phase translation tool for generating optimized platform-specific hardware instructions corresponding to the translated statements for execution on a hardware platform; and receiving the output of each phase of the translation tool. 17. The method of claim 1 wherein the timed events comprise a specific point in time after which data is to be collected. | 0.909701 |
9,298,702 | 1 | 6 | 1. A computer implemented method for processing natural language information in conjunction with a semantic network editing tool, the method comprising: providing a user interface in communication with the semantic network editing tool disposed to facilitate processing of information in a natural language processing (NLP) system from a collection of documents stored in a document repository so as to provide a set of processed information; communicatively coupling the semantic network editing tool and the NLP system so as to facilitate transfer of data or information between the semantic network editing tool and the NLP system, the communicatively coupling including automatically converting one or more semantic network entity types and associated semantic network templates into NLP extractor definitions wherein the extractor definitions are trained using sample documents prior to being utilized to facilitate the processing of the information in the NLP system; mapping, using the semantic network editing tool, entity types and relation types of a first ontology of the NLP system to element types and relation types, respectively, of a second ontology of a semantic network, the first ontology being different from the second ontology wherein ones of the element types are associated with ones of the semantic network templates, each of the semantic network templates including a plurality of roles corresponding to a plurality of additional element types; responsive to a user input provided at the user interface, extracting the set of processed information from the NLP system for use in the semantic network; and using the semantic network editing tool to view and edit entities and triplets included within the semantic network. | 1. A computer implemented method for processing natural language information in conjunction with a semantic network editing tool, the method comprising: providing a user interface in communication with the semantic network editing tool disposed to facilitate processing of information in a natural language processing (NLP) system from a collection of documents stored in a document repository so as to provide a set of processed information; communicatively coupling the semantic network editing tool and the NLP system so as to facilitate transfer of data or information between the semantic network editing tool and the NLP system, the communicatively coupling including automatically converting one or more semantic network entity types and associated semantic network templates into NLP extractor definitions wherein the extractor definitions are trained using sample documents prior to being utilized to facilitate the processing of the information in the NLP system; mapping, using the semantic network editing tool, entity types and relation types of a first ontology of the NLP system to element types and relation types, respectively, of a second ontology of a semantic network, the first ontology being different from the second ontology wherein ones of the element types are associated with ones of the semantic network templates, each of the semantic network templates including a plurality of roles corresponding to a plurality of additional element types; responsive to a user input provided at the user interface, extracting the set of processed information from the NLP system for use in the semantic network; and using the semantic network editing tool to view and edit entities and triplets included within the semantic network. 6. The method of claim 1 wherein the user interface is incorporated in a user interface of the semantic network editing tool. | 0.815089 |
8,643,652 | 2 | 3 | 2. The method of claim 1 , further comprising: prior to said receiving, sending a request to a server computer for the font subset, wherein the request includes a glyph identification bitmap that identifies the consecutive sequence of the one or more glyphs already in the extensible data structure, wherein the font subset is received from the server computer in response to the request; and receiving from the server computer an updated version of the glyph identification bitmap that indicates each glyph contained in the received requested font subset. | 2. The method of claim 1 , further comprising: prior to said receiving, sending a request to a server computer for the font subset, wherein the request includes a glyph identification bitmap that identifies the consecutive sequence of the one or more glyphs already in the extensible data structure, wherein the font subset is received from the server computer in response to the request; and receiving from the server computer an updated version of the glyph identification bitmap that indicates each glyph contained in the received requested font subset. 3. The method of claim 2 , wherein the request specifies Unicode values for the requested font subset. | 0.5 |
7,644,286 | 1 | 9 | 1. A computer-implemented method of restricting data access, comprising: performing the following on a computer: detecting an attempt by a first requester to access a first data resource, said first requester comprising computer executable instructions for accessing data; if the attempted access is to retrieve data: allowing the attempted access; and adding a get token corresponding to the first data resource to a first set of get tokens maintained for the first requester; and if the attempted access is to send data: if said first set of get tokens is empty, allowing the attempted access; if said first set of get tokens includes only a single get token, allowing the attempted access if the first data resource is the same data resource corresponding to said single get token; and if said first set of get tokens includes multiple get tokens, restricting the attempted access if the first requestor previously sent data to the first data resource and said first set of get tokens has changed since the first requester last sent data to the first data resource. | 1. A computer-implemented method of restricting data access, comprising: performing the following on a computer: detecting an attempt by a first requester to access a first data resource, said first requester comprising computer executable instructions for accessing data; if the attempted access is to retrieve data: allowing the attempted access; and adding a get token corresponding to the first data resource to a first set of get tokens maintained for the first requester; and if the attempted access is to send data: if said first set of get tokens is empty, allowing the attempted access; if said first set of get tokens includes only a single get token, allowing the attempted access if the first data resource is the same data resource corresponding to said single get token; and if said first set of get tokens includes multiple get tokens, restricting the attempted access if the first requestor previously sent data to the first data resource and said first set of get tokens has changed since the first requester last sent data to the first data resource. 9. The method of claim 1 , wherein the first data resource comprises a second requester for which a second set of get tokens is maintained, the method further comprising: examining said second set of get tokens; and if one or more get tokens in said second set of get tokens are not included in said first set of get tokens: merging said first set of get tokens and said second set of get tokens. | 0.5 |
8,037,069 | 3 | 5 | 3. The system of claim 1 , wherein the data structure comprises a summary structure pre-populated with token-signature pairs of the database members and wherein relatively less definitive member tokens are eliminated to decrease an overall size of the summary structure. | 3. The system of claim 1 , wherein the data structure comprises a summary structure pre-populated with token-signature pairs of the database members and wherein relatively less definitive member tokens are eliminated to decrease an overall size of the summary structure. 5. The system of claim 3 , wherein the filter component is configured to ascertain a local memory allocation for the summary structure and to eliminate sufficient numbers of the relatively less definitive member tokens such that the summary structure can be stored in the local memory allocation. | 0.5 |
8,812,507 | 12 | 15 | 12. A system for positioning one or more documents in a visual file space associated with a personal corpus, said method comprising: a memory that stores computer-readable code; and a processor operatively coupled to said memory, said processor configured to implement said computer-readable code, said computer-readable code configured to: store each of said documents with an indication of term weight for terms appearing in said corresponding document, wherein said term weight is obtained by dividing a fractional frequency of said term in said document by a fractional frequency of said term in said reference corpus, wherein said fractional frequency of said term in said document is the number of occurrences of the term in the document divided by the total number of terms in the document and wherein said fractional frequency of said term in said reference corpus is the number of occurrences of the term in the reference corpus divided by the total number of words in the reference corpus; and perform a singular value decomposition based on said term weights to position a given document in said visual file space based on a relative frequency distribution of terms of said document compared to the occurrence of such terms in a reference corpus. | 12. A system for positioning one or more documents in a visual file space associated with a personal corpus, said method comprising: a memory that stores computer-readable code; and a processor operatively coupled to said memory, said processor configured to implement said computer-readable code, said computer-readable code configured to: store each of said documents with an indication of term weight for terms appearing in said corresponding document, wherein said term weight is obtained by dividing a fractional frequency of said term in said document by a fractional frequency of said term in said reference corpus, wherein said fractional frequency of said term in said document is the number of occurrences of the term in the document divided by the total number of terms in the document and wherein said fractional frequency of said term in said reference corpus is the number of occurrences of the term in the reference corpus divided by the total number of words in the reference corpus; and perform a singular value decomposition based on said term weights to position a given document in said visual file space based on a relative frequency distribution of terms of said document compared to the occurrence of such terms in a reference corpus. 15. The system of claim 12 , wherein said additional orthogonal axes allow a user to drag one of said additional orthogonal axes on top of an already existing axis, resulting in a new set of reference coordinates and a rerendering of relevant documents and landmarks. | 0.5 |
9,269,355 | 5 | 6 | 5. The system of claim 4 , further comprising a third computing device configured to: determine speech recognition results using information relating to nodes from the first set of active nodes or the second set of active nodes. | 5. The system of claim 4 , further comprising a third computing device configured to: determine speech recognition results using information relating to nodes from the first set of active nodes or the second set of active nodes. 6. The system of claim 5 , wherein the speech recognition results comprise text, a lattice, or a tree. | 0.5 |
8,239,216 | 1 | 5 | 1. One or more non-transitory computer-storage media having computer executable instructions embodied thereon that when executed by a computer perform a method of finding information in an electronic medical record, the method comprising: receiving a search query from a user to search the electronic medical record, wherein the electronic medical record is associated with a patient, and wherein the electronic medical record includes a plurality of electronic documents that describe a medical history for the patient and is stored on the computer-storage media; identifying one or more components of the electronic medical record that contain text that matches the search query, wherein each of the one or more components is a section of text within the electronic medical record that includes one or more words; determining a query-responsiveness score for each of the one or more components that match the search query, wherein the query-responsiveness score indicates how responsive an individual component is to the search query, wherein determining the query-responsiveness score of each of the one or more components further comprises: determining a patient-subject status for each particular-clinical concept recited in the one or more components, wherein the patient-subject status indicates whether the patient is an object of a particular-clinical concept recited in a particular component of the one or more components; determining a truth status for said each particular-clinical concept recited in the one or more components, wherein the truth status indicates whether said each particular-clinical concept was expressed positively, negatively, ambiguously, or unknown; determining a clinical-usage context for each particular-clinical concept recited in the one or more components, wherein the clinical-usage context describes how the clinical concept was used in the component; determining a document-importance factor for each particular-clinical concept recited in the one or more components, wherein the document-importance factor measures the relevance of the particular-clinical concept to the main subject of a particular document by analyzing other clinical concepts that are used in the particular document with the particular-clinical concept; determining a specificity factor for each particular-clinical concept recited in the one or more components based on a degree of narrowness for a scope of said each particular-clinical concept; and presenting search results that communicate information describing each of the one or more components, wherein the search results are displayed ordered according to the query-responsiveness score assigned to each of the one or more components. | 1. One or more non-transitory computer-storage media having computer executable instructions embodied thereon that when executed by a computer perform a method of finding information in an electronic medical record, the method comprising: receiving a search query from a user to search the electronic medical record, wherein the electronic medical record is associated with a patient, and wherein the electronic medical record includes a plurality of electronic documents that describe a medical history for the patient and is stored on the computer-storage media; identifying one or more components of the electronic medical record that contain text that matches the search query, wherein each of the one or more components is a section of text within the electronic medical record that includes one or more words; determining a query-responsiveness score for each of the one or more components that match the search query, wherein the query-responsiveness score indicates how responsive an individual component is to the search query, wherein determining the query-responsiveness score of each of the one or more components further comprises: determining a patient-subject status for each particular-clinical concept recited in the one or more components, wherein the patient-subject status indicates whether the patient is an object of a particular-clinical concept recited in a particular component of the one or more components; determining a truth status for said each particular-clinical concept recited in the one or more components, wherein the truth status indicates whether said each particular-clinical concept was expressed positively, negatively, ambiguously, or unknown; determining a clinical-usage context for each particular-clinical concept recited in the one or more components, wherein the clinical-usage context describes how the clinical concept was used in the component; determining a document-importance factor for each particular-clinical concept recited in the one or more components, wherein the document-importance factor measures the relevance of the particular-clinical concept to the main subject of a particular document by analyzing other clinical concepts that are used in the particular document with the particular-clinical concept; determining a specificity factor for each particular-clinical concept recited in the one or more components based on a degree of narrowness for a scope of said each particular-clinical concept; and presenting search results that communicate information describing each of the one or more components, wherein the search results are displayed ordered according to the query-responsiveness score assigned to each of the one or more components. 5. The media of claim 1 , wherein the method further includes receiving a selection of a search mode, wherein the search mode is a medical synonym match, wherein the one or more components of the electronic medical record matches the search query when at least a medical synonym of the one or more words in the search query is found within the one or more components of the electronic medical record, and wherein the medical synonyms match search mode includes matching two or more words or phrases that have a similar medical meaning. | 0.721354 |
8,521,528 | 11 | 12 | 11. A method for distributed speech recognition, comprising: obtaining audio data from a caller participating in a call with an agent; receiving on a main recognizer, a main grammar template and the audio data; receiving on each of a plurality of secondary recognizers, the audio data and a reference that identifies a secondary grammar, wherein each secondary grammar is a non-overlapping section of the main grammar template; performing speech recognition on each of the secondary recognizers, comprising: identifying speech recognition results by applying the secondary grammar to the audio data; and selecting an n number of most likely speech recognition results; constructing by the main recognizer, a new grammar using the speech recognition results from each of the secondary recognizers as a new vocabulary based on the main grammar template; and identifying further speech recognition results by applying the new grammar to the audio data. | 11. A method for distributed speech recognition, comprising: obtaining audio data from a caller participating in a call with an agent; receiving on a main recognizer, a main grammar template and the audio data; receiving on each of a plurality of secondary recognizers, the audio data and a reference that identifies a secondary grammar, wherein each secondary grammar is a non-overlapping section of the main grammar template; performing speech recognition on each of the secondary recognizers, comprising: identifying speech recognition results by applying the secondary grammar to the audio data; and selecting an n number of most likely speech recognition results; constructing by the main recognizer, a new grammar using the speech recognition results from each of the secondary recognizers as a new vocabulary based on the main grammar template; and identifying further speech recognition results by applying the new grammar to the audio data. 12. A method according to claim 11 , further comprising: displaying the further speech recognition results to the agent. | 0.911894 |
8,301,356 | 13 | 15 | 13. Apparatus for estimating NOx creation in a combustion process of a four-stroke internal combustion engine including a variable volume combustion chamber defined by a piston reciprocating within a cylinder between top-dead center and bottom-dead center points, intake and exhaust passages, and intake and exhaust valves controlled during repetitive, sequential exhaust, intake, compression and expansion strokes of said piston, said apparatus comprising: a pressure sensor generating pressure sensor readings describing conditions within said combustion chamber; a NOx estimation module including logic operations comprising: monitoring said pressure sensor readings; modeling a mass fraction burn value for combustion within the combustion chamber based upon said pressure sensor readings, wherein said mass fraction burn value indexes a crank angle at which a selected percentage of injected fuel is burned in a combustion cycle; estimating a state of combustion within the combustion chamber based upon the mass fraction burn value, the state of combustion comprising a combustion phasing and a combustion strength; and and estimating NOx creation with an artificial neural network based upon said state of combustion; and an aftertreatment system receiving an exhaust gas flow from said engine and modulating aftertreatment based upon said NOx creation estimate. | 13. Apparatus for estimating NOx creation in a combustion process of a four-stroke internal combustion engine including a variable volume combustion chamber defined by a piston reciprocating within a cylinder between top-dead center and bottom-dead center points, intake and exhaust passages, and intake and exhaust valves controlled during repetitive, sequential exhaust, intake, compression and expansion strokes of said piston, said apparatus comprising: a pressure sensor generating pressure sensor readings describing conditions within said combustion chamber; a NOx estimation module including logic operations comprising: monitoring said pressure sensor readings; modeling a mass fraction burn value for combustion within the combustion chamber based upon said pressure sensor readings, wherein said mass fraction burn value indexes a crank angle at which a selected percentage of injected fuel is burned in a combustion cycle; estimating a state of combustion within the combustion chamber based upon the mass fraction burn value, the state of combustion comprising a combustion phasing and a combustion strength; and and estimating NOx creation with an artificial neural network based upon said state of combustion; and an aftertreatment system receiving an exhaust gas flow from said engine and modulating aftertreatment based upon said NOx creation estimate. 15. The apparatus of claim 13 , wherein said aftertreatment system comprises a lean NOx trap; and wherein said modulating aftertreatment comprises scheduling regeneration events. | 0.616379 |
8,140,322 | 1 | 8 | 1. A system for preparing a translation of a labeling document from a source to at least one target language, the system comprising: a medical device having a quantifiable risk classification; a medical device labeling document in the source language, the labeling document having an intended use in connection with the medical device and being translated from the source language to the at least one target language; and a risk calculator for assessing the translated labeling document for potential risk to a human from use of the medical device as a function of: the medical device risk classification, the intended use of the labeling document in the at least one target language, the source language, and the at least one target language, wherein the risk calculator requires additional translation efforts when the assessed potential risk exceeds a risk threshold. | 1. A system for preparing a translation of a labeling document from a source to at least one target language, the system comprising: a medical device having a quantifiable risk classification; a medical device labeling document in the source language, the labeling document having an intended use in connection with the medical device and being translated from the source language to the at least one target language; and a risk calculator for assessing the translated labeling document for potential risk to a human from use of the medical device as a function of: the medical device risk classification, the intended use of the labeling document in the at least one target language, the source language, and the at least one target language, wherein the risk calculator requires additional translation efforts when the assessed potential risk exceeds a risk threshold. 8. The system of claim 1 , wherein said assessment-providing device is adapted to provide said assessment as a function of a potential for serious consumer harm using a database having a table of error seriousness applied to the back-edition. | 0.576923 |
7,680,764 | 10 | 11 | 10. The method of claim 6 , further comprising: calling a first index entry generation function with first information utilizing a first cursor instance; and calling a second index entry generation function with second information utilizes a second cursor instance. | 10. The method of claim 6 , further comprising: calling a first index entry generation function with first information utilizing a first cursor instance; and calling a second index entry generation function with second information utilizes a second cursor instance. 11. The method of claim 10 , wherein said first pull parser process and said first index entry generation function execute within a same process. | 0.704082 |
10,037,315 | 12 | 20 | 12. A computer program product that, when executed by one or more processors, causes a segmented data analysis process to be carried out using a data reporting interface that simulates the appearance of a digital form, wherein the process comprises: rendering a digital form in a form simulation interface, wherein the digital form comprises a plurality of fields; receiving first input from a form author via the form simulation interface, wherein the first input designates a selected one of the plurality of fields as a dimension for subsequent form interaction analysis; receiving consumer data provided using the selected one of the plurality of fields; receiving consumer interaction data characterizing a consumer interaction with the digital form; rendering the digital form in a data reporting interface; receiving second input from the form author via the data reporting interface, wherein the second input designates a form interactivity metric; assigning an initial value to the form interactivity metric based on the received consumer interaction data; causing display of the initial value in the data reporting interface; receiving third input from the form author via the selected field in the data reporting interface, wherein the third input defines a consumer segmentation; modifying the initial value assigned to the form interactivity metric based on the consumer segmentation; assigning a modified value to the form interactivity metric; and causing display of the modified value for the form interactivity metric in response to receiving the third input. | 12. A computer program product that, when executed by one or more processors, causes a segmented data analysis process to be carried out using a data reporting interface that simulates the appearance of a digital form, wherein the process comprises: rendering a digital form in a form simulation interface, wherein the digital form comprises a plurality of fields; receiving first input from a form author via the form simulation interface, wherein the first input designates a selected one of the plurality of fields as a dimension for subsequent form interaction analysis; receiving consumer data provided using the selected one of the plurality of fields; receiving consumer interaction data characterizing a consumer interaction with the digital form; rendering the digital form in a data reporting interface; receiving second input from the form author via the data reporting interface, wherein the second input designates a form interactivity metric; assigning an initial value to the form interactivity metric based on the received consumer interaction data; causing display of the initial value in the data reporting interface; receiving third input from the form author via the selected field in the data reporting interface, wherein the third input defines a consumer segmentation; modifying the initial value assigned to the form interactivity metric based on the consumer segmentation; assigning a modified value to the form interactivity metric; and causing display of the modified value for the form interactivity metric in response to receiving the third input. 20. The computer program product of claim 12 , wherein the process further comprises receiving supplemental first input from the form author via the form simulation interface, wherein the supplemental first input defines a customized transformation of the selected field, and wherein the customized transformation maps a range of values to the consumer segmentation. | 0.705788 |
9,110,979 | 1 | 6 | 1. A system, comprising: at least one or more processors; a citation search engine with the at least one or more processors that in operation retrieves a plurality of citations composed by a plurality of subjects citing a plurality of objects that fit one or more search criteria, a citation graph coupled to the citation engine, the citation graph used to determine an influence of each of the subjects and the objects, the citation graph including the plurality of citations each describing an opinion of an object by a subject, the citation graph including nodes or entities that are 1) subjects that have an opinion or making citations, and 2) objects cited by citations relative to subjects that have opinions or make citations; an influence evaluation engine with the at least one or more processors that in operation, determines an expertise of a subject as a measure of the subject's expertise in a topic relative to a larger population of multiple subjects and allows for determination of expertise on any query term in real-time; and an object/subject selection engine with the at least one or more processors, which in operation: ranks the cited objects of the plurality of citations using the influence and relative expertise of the subjects, and selects objects as the search result for the user based on the matching of the objects with the search criteria as well as the relative expertise of the citing subjects. | 1. A system, comprising: at least one or more processors; a citation search engine with the at least one or more processors that in operation retrieves a plurality of citations composed by a plurality of subjects citing a plurality of objects that fit one or more search criteria, a citation graph coupled to the citation engine, the citation graph used to determine an influence of each of the subjects and the objects, the citation graph including the plurality of citations each describing an opinion of an object by a subject, the citation graph including nodes or entities that are 1) subjects that have an opinion or making citations, and 2) objects cited by citations relative to subjects that have opinions or make citations; an influence evaluation engine with the at least one or more processors that in operation, determines an expertise of a subject as a measure of the subject's expertise in a topic relative to a larger population of multiple subjects and allows for determination of expertise on any query term in real-time; and an object/subject selection engine with the at least one or more processors, which in operation: ranks the cited objects of the plurality of citations using the influence and relative expertise of the subjects, and selects objects as the search result for the user based on the matching of the objects with the search criteria as well as the relative expertise of the citing subjects. 6. The system of claim 1 , wherein: each of the plurality of citations includes one or more of: expression of opinions on the objects, expressions of authors in the form of Tweets, blog posts, reviews of objects on Internet web sites Wikipedia entries, postings to social media, postings to websites, postings in the form of reviews, recommendations, or any other form of citation made to mailing lists, newsgroups, discussion forums, comments to websites or any other form of Internet publication. | 0.5 |
9,117,249 | 12 | 20 | 12. A computer program product comprising a non-transitory computer-readable storage medium containing computer program code for performing the steps: storing a view state for a user of a social networking system, the view state including a first order of a plurality of news feed stories previously presented to the user in a user interface; receiving a request for new news feed stories from the user; obtaining the requested new news feed stories for the user; responsive to determining that the plurality of previously presented news feed stories have been consumed by the user, providing the new news feed stories in a user interface for display to the user; updating the view state for the user with a second order of a plurality of news feed stories presented to the user in the user interface, the plurality of presented news feed stories including the new news feed stories and the plurality of news feed stories previously presented to the user; and responsive to determining that the plurality of previously presented news feed stories have not been consumed by the user, providing a link in the user interface to indicate that the new news feed stories have been generated. | 12. A computer program product comprising a non-transitory computer-readable storage medium containing computer program code for performing the steps: storing a view state for a user of a social networking system, the view state including a first order of a plurality of news feed stories previously presented to the user in a user interface; receiving a request for new news feed stories from the user; obtaining the requested new news feed stories for the user; responsive to determining that the plurality of previously presented news feed stories have been consumed by the user, providing the new news feed stories in a user interface for display to the user; updating the view state for the user with a second order of a plurality of news feed stories presented to the user in the user interface, the plurality of presented news feed stories including the new news feed stories and the plurality of news feed stories previously presented to the user; and responsive to determining that the plurality of previously presented news feed stories have not been consumed by the user, providing a link in the user interface to indicate that the new news feed stories have been generated. 20. The computer program product of claim 12 , wherein determining that the plurality of previously presented news feed stories have been consumed by the user further comprises detecting user activity in the user interface. | 0.742494 |
9,373,155 | 9 | 14 | 9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: determining an initial height and an initial width of an image that is associated with a search result, wherein the image is to be displayed in the search result in line with text associated with the search result, and wherein the search result includes an in-line image region for displaying the image in line with the text, and a text region for displaying the text; determining an initial height of the text region of the search result based at least on (i) the text associated with the search result, and (ii) an initial width of the text region; determining an initial width of the in-line image region of the search result based at least on (i) the initial height of the text region of the search result, (ii) the initial height of the image, and (iii) the initial width of the image; determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region; and in response to determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region: determining an adjusted height of the text region of the search result based at least on the initial width of the in-line image region of the search result; determining an adjusted width of the in-line image region of the search result based at least on the adjusted height of the text region of the search result; determining an adjusted height and an adjusted width of the image based at least on the adjusted width of the in-line image region of the search result; scaling at least a portion of the image based at least on the adjusted height and the adjusted width of the image; and outputting the scaled image for display in the search result in line with the text. | 9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: determining an initial height and an initial width of an image that is associated with a search result, wherein the image is to be displayed in the search result in line with text associated with the search result, and wherein the search result includes an in-line image region for displaying the image in line with the text, and a text region for displaying the text; determining an initial height of the text region of the search result based at least on (i) the text associated with the search result, and (ii) an initial width of the text region; determining an initial width of the in-line image region of the search result based at least on (i) the initial height of the text region of the search result, (ii) the initial height of the image, and (iii) the initial width of the image; determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region; and in response to determining that a) space in the in-line image region or space in the text region will include undesired whitespace, or b) text associated with the search result and for presentation in the search result will be removed from the text region: determining an adjusted height of the text region of the search result based at least on the initial width of the in-line image region of the search result; determining an adjusted width of the in-line image region of the search result based at least on the adjusted height of the text region of the search result; determining an adjusted height and an adjusted width of the image based at least on the adjusted width of the in-line image region of the search result; scaling at least a portion of the image based at least on the adjusted height and the adjusted width of the image; and outputting the scaled image for display in the search result in line with the text. 14. The system of claim 9 , wherein the initial height of the text region is the same as the adjusted height of the text region. | 0.93899 |
9,128,993 | 1 | 7 | 1. A computer-implemented method comprising: receiving a search query; identifying a plurality of matching resources, matching resources being resources that satisfy the search query; determining that a particular resource of the matching resources has an entry in a database of identified music web pages, wherein each music web page is a resource from which music content can be accessed, wherein each music web page includes markup language music data identifying one or more songs, and wherein each entry is associated with music data identifying one or more songs from a corresponding music web page; generating a presentation of respective search results for the plurality of matching resources, wherein each search result in the presentation includes a title, a snippet, and a link to a corresponding one of the matching resources, including generating, for the particular resource, a particular search result in the presentation having one or more secondary music search result links to respective music web pages in the database of identified music web pages; and providing the presentation of search results in response to the search query. | 1. A computer-implemented method comprising: receiving a search query; identifying a plurality of matching resources, matching resources being resources that satisfy the search query; determining that a particular resource of the matching resources has an entry in a database of identified music web pages, wherein each music web page is a resource from which music content can be accessed, wherein each music web page includes markup language music data identifying one or more songs, and wherein each entry is associated with music data identifying one or more songs from a corresponding music web page; generating a presentation of respective search results for the plurality of matching resources, wherein each search result in the presentation includes a title, a snippet, and a link to a corresponding one of the matching resources, including generating, for the particular resource, a particular search result in the presentation having one or more secondary music search result links to respective music web pages in the database of identified music web pages; and providing the presentation of search results in response to the search query. 7. The method of claim 1 , wherein the particular search result does not include any other types of secondary search result links. | 0.810496 |
7,493,333 | 1 | 12 | 1. A computer-implemented system for parsing and exporting data from one or more multi-relational ontologies, the system comprising: one or more master multi-relational ontologies including a plurality of individual assertions, wherein an individual assertion comprises a first concept, a second concept, and a relationship between the first concept and the second concept, wherein at least one concept in a first assertion of the plurality of individual assertions is a concept in at least a second assertion of the plurality of assertions, wherein one or more relationships in the plurality of individual assertions comprise relationships unconstrained by any hierarchical arrangement of concepts, and wherein each of individual assertions of the one or more master multi-relational ontologies is associated with a confidence weight that is an indication of the confidence in the truth of the assertion; an export module that; receives a selection of two or more concepts from the plurality of assertions of the one of the one or more master multi-relational ontologies, applies one or more path-finding constraints to the two or more concepts to yield a subset of individual assertions from the plurality of assertions, wherein the path finding constraints identify one or more individual assertions from the plurality of individual assertions of the one or more master multi-relational ontologies that connect, directly or indirectly, the two or more concepts, receives a selection of a starting concept from the subset of individual assertions, and applies one or more expansion parameters to the starting concept to yield a redacted subset of assertions from the subset of individual assertions, wherein the one or more expansion parameters include one or more selectable characteristics of the subset of individual assertions, and wherein the redacted subset of assertions includes at least one assertion that includes the starting concept; and a storage device that stores the redacted subset of assertions as individual assertions, wherein the export module outputs the redacted subset of assertions to a predetermined location in a predetermined format. | 1. A computer-implemented system for parsing and exporting data from one or more multi-relational ontologies, the system comprising: one or more master multi-relational ontologies including a plurality of individual assertions, wherein an individual assertion comprises a first concept, a second concept, and a relationship between the first concept and the second concept, wherein at least one concept in a first assertion of the plurality of individual assertions is a concept in at least a second assertion of the plurality of assertions, wherein one or more relationships in the plurality of individual assertions comprise relationships unconstrained by any hierarchical arrangement of concepts, and wherein each of individual assertions of the one or more master multi-relational ontologies is associated with a confidence weight that is an indication of the confidence in the truth of the assertion; an export module that; receives a selection of two or more concepts from the plurality of assertions of the one of the one or more master multi-relational ontologies, applies one or more path-finding constraints to the two or more concepts to yield a subset of individual assertions from the plurality of assertions, wherein the path finding constraints identify one or more individual assertions from the plurality of individual assertions of the one or more master multi-relational ontologies that connect, directly or indirectly, the two or more concepts, receives a selection of a starting concept from the subset of individual assertions, and applies one or more expansion parameters to the starting concept to yield a redacted subset of assertions from the subset of individual assertions, wherein the one or more expansion parameters include one or more selectable characteristics of the subset of individual assertions, and wherein the redacted subset of assertions includes at least one assertion that includes the starting concept; and a storage device that stores the redacted subset of assertions as individual assertions, wherein the export module outputs the redacted subset of assertions to a predetermined location in a predetermined format. 12. The system of claim 1 , wherein one or more of the path-finding constraints or the expansion parameters includes user access rights, such that one or more of the subset of individual assertions or the redacted subset of assertions include only assertions to which a particular user is permitted access. | 0.816766 |
4,792,909 | 1 | 2 | 1. A method for reducing the size of binary decision tree representations of boolean expressions on integrated circuits having ordered inputs, said method comprising the steps of: decomposing each boolean expression into its sub-expressions based on the ordering of said inputs, such that each term of said decomposed expression introduces a respective one of said inputs; factoring the input introduced by each term of said decomposed expression and the complement of that input from said term, whereby each term is converted into a pair of partial functions such that EQU F=x.multidot.F.sub.1 +.about.x.multidot.F.sub.0 where: F=any given term of the decomposed expression, x=the input introduced by said given term, and F.sub.1 and F.sub.0 =the partial expressions of said given term; testing the partial functions of each term of said decomposed expression to determine which of the following conditions is true: TBL ______________________________________ Test Conclusion if True Operator Indicated ______________________________________ F.sub.1 = F.sub.0 = 1 or 0 F = 1 or F = 0 Constant F.sub.1 = .about.F.sub.0 = 1 or 0 F = x or F = .about.x Identity F.sub.1 = 1 F = x + F.sub.0 OR F.sub.0 = 0 F = x F.sub.1 AND F.sub.0 = 1 F = F.sub.1 + .about.x ORNOT F.sub.1 = 0 F = .about.x F.sub.0 ANDNOT F.sub.1 = F.sub.0 F = F.sub.1 NoDependence F.sub.1 = .about.F.sub.0 F = x F.sub.1 + .about.x .about.F.sub.1 XORNOT ELSE F = x F.sub.1 + .about.x F.sub.0 IF ______________________________________ selecting the operator required for each term of said decomposed expression based on the condition found to be true; and laying out said integrated circuit to provide the operator required for each term of said decomposed expression. | 1. A method for reducing the size of binary decision tree representations of boolean expressions on integrated circuits having ordered inputs, said method comprising the steps of: decomposing each boolean expression into its sub-expressions based on the ordering of said inputs, such that each term of said decomposed expression introduces a respective one of said inputs; factoring the input introduced by each term of said decomposed expression and the complement of that input from said term, whereby each term is converted into a pair of partial functions such that EQU F=x.multidot.F.sub.1 +.about.x.multidot.F.sub.0 where: F=any given term of the decomposed expression, x=the input introduced by said given term, and F.sub.1 and F.sub.0 =the partial expressions of said given term; testing the partial functions of each term of said decomposed expression to determine which of the following conditions is true: TBL ______________________________________ Test Conclusion if True Operator Indicated ______________________________________ F.sub.1 = F.sub.0 = 1 or 0 F = 1 or F = 0 Constant F.sub.1 = .about.F.sub.0 = 1 or 0 F = x or F = .about.x Identity F.sub.1 = 1 F = x + F.sub.0 OR F.sub.0 = 0 F = x F.sub.1 AND F.sub.0 = 1 F = F.sub.1 + .about.x ORNOT F.sub.1 = 0 F = .about.x F.sub.0 ANDNOT F.sub.1 = F.sub.0 F = F.sub.1 NoDependence F.sub.1 = .about.F.sub.0 F = x F.sub.1 + .about.x .about.F.sub.1 XORNOT ELSE F = x F.sub.1 + .about.x F.sub.0 IF ______________________________________ selecting the operator required for each term of said decomposed expression based on the condition found to be true; and laying out said integrated circuit to provide the operator required for each term of said decomposed expression. 2. The method of claim 1 wherein said inputs are laid out on said integrated circuit to run in one direction and said expressions and subexpressions are laid out to run in an orthogonal direction. | 0.749361 |
7,844,608 | 15 | 16 | 15. A network device for processing data over a network, comprising: a transceiver for sending or receiving data; a database query interface in communication with the transceiver, wherein the database query interface sends and receives relational database queries; a processor that performs actions comprising: receiving a plurality of queries of a database; transforming each of the plurality of queries into a plurality of query trees; selecting at least one of the plurality of query trees as a master query tree; combining another one of the plurality of query trees into the master query tree, wherein a portion of the master query tree and a portion of the other one of the plurality of query trees are determined as children of a split node in the master query tree, and wherein the split node is added as a new node based in part on a match of a path in the master query tree and another path in the other one of the of the plurality of query trees and the split node is unfound previously in any of the plurality of query trees including the master query tree; and applying the master query tree to at least one portion of one table from the database to provide a plurality of results, wherein each of the plurality of results is associated with one of the received plurality of queries. | 15. A network device for processing data over a network, comprising: a transceiver for sending or receiving data; a database query interface in communication with the transceiver, wherein the database query interface sends and receives relational database queries; a processor that performs actions comprising: receiving a plurality of queries of a database; transforming each of the plurality of queries into a plurality of query trees; selecting at least one of the plurality of query trees as a master query tree; combining another one of the plurality of query trees into the master query tree, wherein a portion of the master query tree and a portion of the other one of the plurality of query trees are determined as children of a split node in the master query tree, and wherein the split node is added as a new node based in part on a match of a path in the master query tree and another path in the other one of the of the plurality of query trees and the split node is unfound previously in any of the plurality of query trees including the master query tree; and applying the master query tree to at least one portion of one table from the database to provide a plurality of results, wherein each of the plurality of results is associated with one of the received plurality of queries. 16. The network device of claim 15 , wherein at least one of the plurality of queries is a Structured Query Language (SQL) statement. | 0.773038 |
9,785,312 | 2 | 3 | 2. A system in accordance with claim 1 wherein an administrator can use the interface to define the question by specifying a question name and by choosing a question type from a plurality of predetermined possible types, the question appearing on the intake form. | 2. A system in accordance with claim 1 wherein an administrator can use the interface to define the question by specifying a question name and by choosing a question type from a plurality of predetermined possible types, the question appearing on the intake form. 3. A system in accordance with claim 2 wherein the question types comprise at least three of the following: yes-no, text, number, date, and select one. | 0.5 |
9,304,991 | 10 | 13 | 10. A computer program product for identifying one or more of a plurality of enterprise-level business processes of an enterprise and a plurality of monitoring templates, said computer program product comprising a tangible computer readable recordable storage medium having computer readable program code embodied therewith, said computer readable program code comprising: computer readable program code configured to obtain, using at least one processing device, at least one of said plurality of enterprise-level business processes and said plurality of monitoring templates, wherein at least one of said obtained enterprise-level business processes and said obtained monitoring template has an associated monitoring intent comprising one or more monitoring keywords, wherein said monitoring intent links one or more business goals of said enterprise to a given enterprise-level business process such that said monitoring intent can be searched to identify at least one existing enterprise-level business process that is related to a new enterprise-level business process being created; computer readable program code configured to obtain, using at least one processing device, a user-specified monitoring intent from said user, said user-specified monitoring intent comprising one or more search keywords; computer readable program code configured to assign. using at least one processing device, a score to at least one of said obtained enterprise-level business process and said monitoring template, wherein said score is based on a matching of a semantic context of said associated monitoring intent and one or more of said monitoring keywords from said associated monitoring intent with a semantic context of said user-specified monitoring intent and said search keywords of said user-specified monitoring intent; and computer readable program code configured to identify, using at least one processing device, said one or more of said plurality of enterprise-level business processes and said plurality of monitoring templates based on said assigned score. | 10. A computer program product for identifying one or more of a plurality of enterprise-level business processes of an enterprise and a plurality of monitoring templates, said computer program product comprising a tangible computer readable recordable storage medium having computer readable program code embodied therewith, said computer readable program code comprising: computer readable program code configured to obtain, using at least one processing device, at least one of said plurality of enterprise-level business processes and said plurality of monitoring templates, wherein at least one of said obtained enterprise-level business processes and said obtained monitoring template has an associated monitoring intent comprising one or more monitoring keywords, wherein said monitoring intent links one or more business goals of said enterprise to a given enterprise-level business process such that said monitoring intent can be searched to identify at least one existing enterprise-level business process that is related to a new enterprise-level business process being created; computer readable program code configured to obtain, using at least one processing device, a user-specified monitoring intent from said user, said user-specified monitoring intent comprising one or more search keywords; computer readable program code configured to assign. using at least one processing device, a score to at least one of said obtained enterprise-level business process and said monitoring template, wherein said score is based on a matching of a semantic context of said associated monitoring intent and one or more of said monitoring keywords from said associated monitoring intent with a semantic context of said user-specified monitoring intent and said search keywords of said user-specified monitoring intent; and computer readable program code configured to identify, using at least one processing device, said one or more of said plurality of enterprise-level business processes and said plurality of monitoring templates based on said assigned score. 13. The computer program product of claim 10 , wherein said computer readable program code is further configured to store said one or more of said plurality of enterprise-level business processes and said plurality of monitoring templates in a format that can be searched. | 0.69161 |
8,645,107 | 17 | 18 | 17. A non-transitory machine-readable storage medium having computer-readable program codes embodied therein for automatically adding one or more constraints between entities in a subject computer-aided design (CAD) model of a real-world object, the computer-readable data storage medium program codes including instructions that, when executed by a processor, cause the processor to: for one entity of a given component that is one of to be added to and in the subject CAD model, access a computer database to determine one or more constraints that have previously been used for at least the one entity of the given component, each determined constraint having been previously used in at least one of the subject CAD model and other CAD models, and wherein the database stores information regarding CAD model entities and related constraints for the given component in at least one of the subject CAD model and the other CAD models; and automatically add to the subject CAD model at least one new constraint between at least the one entity of the given component and another entity in the subject CAD model based on the previously used constraints. | 17. A non-transitory machine-readable storage medium having computer-readable program codes embodied therein for automatically adding one or more constraints between entities in a subject computer-aided design (CAD) model of a real-world object, the computer-readable data storage medium program codes including instructions that, when executed by a processor, cause the processor to: for one entity of a given component that is one of to be added to and in the subject CAD model, access a computer database to determine one or more constraints that have previously been used for at least the one entity of the given component, each determined constraint having been previously used in at least one of the subject CAD model and other CAD models, and wherein the database stores information regarding CAD model entities and related constraints for the given component in at least one of the subject CAD model and the other CAD models; and automatically add to the subject CAD model at least one new constraint between at least the one entity of the given component and another entity in the subject CAD model based on the previously used constraints. 18. The computer-readable data storage medium of claim 17 further comprising program codes that cause the processor to access the computer database to determine an additional component commonly used with the given component. | 0.515152 |
7,735,621 | 15 | 16 | 15. A method of operating a multi-output receptacle currency evaluating device in a manner employing both one or more fixed output receptacles and one or more dynamic output receptacles wherein the currency evaluation device comprises an input receptacle configured to receive currency bills and a plurality of output receptacles, the currency bills each having an associated denomination, , each of the one or more fixed output receptacles having one or more denominations assigned thereto and each of the dynamic output receptacles being capable of being dynamically assigned to a denomination, the method comprising the acts of: (a) determining the denomination of a bill; (b) determining if the denomination of the bill has been assigned to one of the output receptacles and, if so, transporting the bill to the assigned output receptacle; (c) if the denomination of the bill has not been assigned to an output receptacle, dynamically assigning the denomination to an output receptacle and transporting the bill to the assigned output receptacle. | 15. A method of operating a multi-output receptacle currency evaluating device in a manner employing both one or more fixed output receptacles and one or more dynamic output receptacles wherein the currency evaluation device comprises an input receptacle configured to receive currency bills and a plurality of output receptacles, the currency bills each having an associated denomination, , each of the one or more fixed output receptacles having one or more denominations assigned thereto and each of the dynamic output receptacles being capable of being dynamically assigned to a denomination, the method comprising the acts of: (a) determining the denomination of a bill; (b) determining if the denomination of the bill has been assigned to one of the output receptacles and, if so, transporting the bill to the assigned output receptacle; (c) if the denomination of the bill has not been assigned to an output receptacle, dynamically assigning the denomination to an output receptacle and transporting the bill to the assigned output receptacle. 16. The method of claim 15 wherein the currency evaluating device is operated in a manner employing two or more dynamic output receptacles. | 0.583832 |
8,209,665 | 1 | 11 | 1. A method, implemented at least in part by a computing device, for identifying topics in source code using Latent Dirichlet Allocation (LDA), the method comprising: receiving software source code; identifying domain specific keywords from the software source code; generating a keyword matrix, wherein the keyword matrix comprises weighted sums of occurrences of the domain specific keywords in the software source code; processing, using LDA, the keyword matrix and the software source code; and outputting, from the processing, collections of domain specific keywords and probabilities, wherein the collections corresponds to respective topics identified by LDA in the software source code. | 1. A method, implemented at least in part by a computing device, for identifying topics in source code using Latent Dirichlet Allocation (LDA), the method comprising: receiving software source code; identifying domain specific keywords from the software source code; generating a keyword matrix, wherein the keyword matrix comprises weighted sums of occurrences of the domain specific keywords in the software source code; processing, using LDA, the keyword matrix and the software source code; and outputting, from the processing, collections of domain specific keywords and probabilities, wherein the collections corresponds to respective topics identified by LDA in the software source code. 11. The method of claim 1 wherein the processing using LDA uses Gibbs sampling. | 0.920523 |
9,612,830 | 18 | 19 | 18. The computer readable storage medium of claim 17 , wherein said step of discovering includes: selecting a collection of standardized specification elements that are related and discovering a pair of work-item elements that are mapped to said selected collection of standardized specification elements, and if said pair of work-item elements do not have a relationship, linking said pair of work-item elements. | 18. The computer readable storage medium of claim 17 , wherein said step of discovering includes: selecting a collection of standardized specification elements that are related and discovering a pair of work-item elements that are mapped to said selected collection of standardized specification elements, and if said pair of work-item elements do not have a relationship, linking said pair of work-item elements. 19. The computer readable storage medium of claim 18 , further including: repeating the step of selecting until all work-item elements have links corresponding to the mapped standardized specification elements. | 0.5 |
7,734,559 | 9 | 11 | 9. The system of claim 8 , wherein the processor is further configured to renumber nodes to provide insertion of marker nodes within a sequence of initial nodes of the at least one Exclude ZDD rule component. | 9. The system of claim 8 , wherein the processor is further configured to renumber nodes to provide insertion of marker nodes within a sequence of initial nodes of the at least one Exclude ZDD rule component. 11. The system of claim 9 , wherein the processor is further configured to: reorder nodes of the ZDD rule model so that marker node groups appear at a bottom of the ZDD rule model; remove nodes that point to a same node as the marker node; remove marker nodes that point to a one node; and reorder nodes of the ZDD rule model back to an initial index. | 0.5 |
8,307,403 | 15 | 18 | 15. The method of claim 14 , wherein the search class comprises: a set search method operable to initiate the search of the at least one broadcast stream of the television show and to register at least one callback method; a search function template method used as a template by the set search method to register the at least one callback method; and a clear search method operable to clear the system resources associated with the search performed by the search object. | 15. The method of claim 14 , wherein the search class comprises: a set search method operable to initiate the search of the at least one broadcast stream of the television show and to register at least one callback method; a search function template method used as a template by the set search method to register the at least one callback method; and a clear search method operable to clear the system resources associated with the search performed by the search object. 18. The method of claim 15 , wherein the set search method comprises a delta time shift call parameter to specify a delay in presentation time from when the at least one search criteria is found and when at least one callback method is called. | 0.510081 |
10,057,707 | 16 | 19 | 16. An apparatus, comprising: an interface system; and a control system capable of: receiving, via the interface system, audio data corresponding to a recording of a conference involving a plurality of conference participants, the audio data including at least one of: (a) audio data from multiple endpoints, the audio data for each of the multiple endpoints having been recorded separately or (b) audio data from a single endpoint corresponding to multiple conference participants and including spatial information for each conference participant of the multiple conference participants; analyzing the audio data to determine conversational dynamics data that includes at least one data type selected from a list of data types consisting of: data indicating the frequency and duration of conference participant speech; data indicating instances of conference participant doubletalk during which at least two conference participants are speaking simultaneously; and data indicating instances of conference participant conversations; applying the conversational dynamics data as one or more variables of a spatial optimization cost function of a vector describing a virtual conference participant position for each of the conference participants in a virtual acoustic space; applying an optimization technique to the spatial optimization cost function to determine a locally optimal solution; and assigning the virtual conference participant positions in the virtual acoustic space based, at least in part, on the locally optimal solution. | 16. An apparatus, comprising: an interface system; and a control system capable of: receiving, via the interface system, audio data corresponding to a recording of a conference involving a plurality of conference participants, the audio data including at least one of: (a) audio data from multiple endpoints, the audio data for each of the multiple endpoints having been recorded separately or (b) audio data from a single endpoint corresponding to multiple conference participants and including spatial information for each conference participant of the multiple conference participants; analyzing the audio data to determine conversational dynamics data that includes at least one data type selected from a list of data types consisting of: data indicating the frequency and duration of conference participant speech; data indicating instances of conference participant doubletalk during which at least two conference participants are speaking simultaneously; and data indicating instances of conference participant conversations; applying the conversational dynamics data as one or more variables of a spatial optimization cost function of a vector describing a virtual conference participant position for each of the conference participants in a virtual acoustic space; applying an optimization technique to the spatial optimization cost function to determine a locally optimal solution; and assigning the virtual conference participant positions in the virtual acoustic space based, at least in part, on the locally optimal solution. 19. The apparatus of claim 16 , wherein the virtual acoustic space is determined relative to a position of a virtual listener's head in the virtual acoustic space and wherein the spatial optimization cost function applies a penalty for placing conference participants who speak frequently at virtual conference participant positions that are beside, behind, above, or below the position of the virtual listener's head. | 0.670347 |
7,483,891 | 1 | 11 | 1. A system configured to associate base content with relevant content, the system comprising: A processor; a parsing module configured to parse the base content to form parsed base content; a unit-dictionary module coupled with the parsing module and including a plurality of query units; a query processing engine coupled with the unit-dictionary module and configured to receive and remove query units from the plurality of query units in the unit-dictionary module; a unit-extraction module coupled with the unit-dictionary module and configured to selectively extract at least one query unit of the plurality of query units from the parsed base content, wherein the parsed base content includes the extracted at least one query unit; a unit-ranking module coupled with the unit-extraction module and configured to rank the extracted query units based on a relevance score and a revenue-generation amount for the extracted query units to identify relevant content, wherein the relevance score is based at least partially on a location of the extracted query unit within the base content; and a unit-matching module coupled with the unit-ranking module and configured to generate at least one association between the base content and the relevant content based on a similarity between the extracted query units and a query unit associated with the relevant content, wherein the relevant content includes at least one advertisement. | 1. A system configured to associate base content with relevant content, the system comprising: A processor; a parsing module configured to parse the base content to form parsed base content; a unit-dictionary module coupled with the parsing module and including a plurality of query units; a query processing engine coupled with the unit-dictionary module and configured to receive and remove query units from the plurality of query units in the unit-dictionary module; a unit-extraction module coupled with the unit-dictionary module and configured to selectively extract at least one query unit of the plurality of query units from the parsed base content, wherein the parsed base content includes the extracted at least one query unit; a unit-ranking module coupled with the unit-extraction module and configured to rank the extracted query units based on a relevance score and a revenue-generation amount for the extracted query units to identify relevant content, wherein the relevance score is based at least partially on a location of the extracted query unit within the base content; and a unit-matching module coupled with the unit-ranking module and configured to generate at least one association between the base content and the relevant content based on a similarity between the extracted query units and a query unit associated with the relevant content, wherein the relevant content includes at least one advertisement. 11. The system of claim 1 , wherein the system is configured to receive a uniform resource locator from a property server, and wherein the URL points at the base content on the property server. | 0.73489 |
8,438,494 | 10 | 14 | 10. A method for formulating a computerized presentation of a sequence of scripts comprising fixed content and agent content, the method comprising: providing scripts comprising fixed content; providing users to control presentation of the scripts; allowing agents to interject into the presentation of the scripts with agent content; observing the agents during presentation to a contact and recording the execution of the script segments and interjection of agent content as presented at the discretion of the agent during an interaction between the user and the contact; and providing a script structure comprising a script sequence and script content, the script structure reflecting at least one choice made by the user during the presenting of scripts to a contact, as recorded during the execution of the script segments and interjection of agent content by the user. | 10. A method for formulating a computerized presentation of a sequence of scripts comprising fixed content and agent content, the method comprising: providing scripts comprising fixed content; providing users to control presentation of the scripts; allowing agents to interject into the presentation of the scripts with agent content; observing the agents during presentation to a contact and recording the execution of the script segments and interjection of agent content as presented at the discretion of the agent during an interaction between the user and the contact; and providing a script structure comprising a script sequence and script content, the script structure reflecting at least one choice made by the user during the presenting of scripts to a contact, as recorded during the execution of the script segments and interjection of agent content by the user. 14. The method of claim 10 , further comprising modifying the script to incorporate the content and sequences of agent content observed. | 0.719008 |
8,150,842 | 26 | 27 | 26. The computer-readable medium of claim 25 , wherein the author can have a first alias relating to the first topic and associated with a first reputation score and can have a second alias relating to a second topic and associated with a second reputation score. | 26. The computer-readable medium of claim 25 , wherein the author can have a first alias relating to the first topic and associated with a first reputation score and can have a second alias relating to a second topic and associated with a second reputation score. 27. The computer-readable medium of claim 26 , wherein the first and second aliases are related to each other. | 0.5 |
9,443,209 | 1 | 2 | 1. A system comprising: a memory to store an index comprising a plurality of brand relationships based on an analysis of a collection of user queries, each of the brand relationships comprising a first brand-category pair of a first brand and a first category, a second brand-category pair of a second brand and a second category, and a recommendation score calculated between the first brand-category pair and the second brand-category pair, the recommendation score of each brand relationship determined from user sessions having queries of both the first brand and first category and the second brand and second category; a processor to implement a recommendation module to provide a recommendation based on an identified brand preference from an activity of a user by querying the index in the memory using the first brand and first category of the identified brand preference to identify the second brand-category pair having a highest recommendation score in the index; and an expansion module to expand a seed set of brands corresponding to a category by analyzing the collection of user queries to determine a new brand to add to the seed set, the analyzing including mining a corpus containing a plurality of user queries by evaluating user queries containing a disjunction of brand terms. | 1. A system comprising: a memory to store an index comprising a plurality of brand relationships based on an analysis of a collection of user queries, each of the brand relationships comprising a first brand-category pair of a first brand and a first category, a second brand-category pair of a second brand and a second category, and a recommendation score calculated between the first brand-category pair and the second brand-category pair, the recommendation score of each brand relationship determined from user sessions having queries of both the first brand and first category and the second brand and second category; a processor to implement a recommendation module to provide a recommendation based on an identified brand preference from an activity of a user by querying the index in the memory using the first brand and first category of the identified brand preference to identify the second brand-category pair having a highest recommendation score in the index; and an expansion module to expand a seed set of brands corresponding to a category by analyzing the collection of user queries to determine a new brand to add to the seed set, the analyzing including mining a corpus containing a plurality of user queries by evaluating user queries containing a disjunction of brand terms. 2. The system of claim 1 , further comprising a mapping module to identify the brand relationships based on user activity. | 0.822157 |
7,774,767 | 9 | 10 | 9. The apparatus of claim 8 , wherein the description of the identified interprocedural optimization is appended at an end of the at least one recompiled object file. | 9. The apparatus of claim 8 , wherein the description of the identified interprocedural optimization is appended at an end of the at least one recompiled object file. 10. The apparatus of claim 9 , wherein the at least one processor is capable of storing the at least one recompiled object file within the library of object files, together with the at least one extracted object file. | 0.5 |
9,575,994 | 1 | 5 | 1. A method for data retrieval of a final result list, the method comprising: generating a semantic annotation database that maps text from a report that describe at least one image to at least one unique resource identifier (URI) that identifies structures illustrated in the at least one image by, analyzing the at least one image to detect structures, mapping the detected structures to a first URI of the at least one URI associated with similar structures stored in a knowledge database, storing the detected structures and the first URI as a first semantic annotation in the semantic annotation database, analyzing the report to identify a content of a text passage, mapping the identified content of the text passage to a second URI of the at least one URI to generate a mapped text passage, and storing a begin and an end of the mapped text passage and the second URI as a second semantic annotation in the semantic annotation database such that the first semantic annotation and the second semantic annotation are stored together in the semantic annotation database, generating an image feature database that stores features contained in the at least one image by, detecting a region of interest (ROI) in the at least one image that includes the detected structures, analyzing the ROI to compute at least one low-level feature therein, the at least one low-level feature being one of a gradient and histogram features of the ROI, and storing the at least one level feature with a reference to the at least one image and an index for fast retrieval in the image feature database; and searching for a resulting set of images by comparing both features of a reference image received by a user with at least one feature in the image feature database and textual search terms input by the user and the semantic annotation database by, receiving an input query describing a search to be executed, the input query containing both the reference image and the textual search terms input by the user, forming a first query based on the textual search terms contained in the input query and on additional anatomic information provided by the knowledge database, the additional anatomic information being an expanded list of synonyms associated with the textual search terms, generating a first result list providing search results of the first query based on the first semantic annotation and the second semantic annotation of the semantic annotation database, forming a second query based on the reference image contained in the input query and on at least one computed feature based on the input query, generating a second result list providing search results of the second query based on the at least one low-level feature in the image feature database, and aggregating the first result list and the second result list to form a final result list that provides reference to at least one of the at least one image and an image region of the at least one of the at least one image. | 1. A method for data retrieval of a final result list, the method comprising: generating a semantic annotation database that maps text from a report that describe at least one image to at least one unique resource identifier (URI) that identifies structures illustrated in the at least one image by, analyzing the at least one image to detect structures, mapping the detected structures to a first URI of the at least one URI associated with similar structures stored in a knowledge database, storing the detected structures and the first URI as a first semantic annotation in the semantic annotation database, analyzing the report to identify a content of a text passage, mapping the identified content of the text passage to a second URI of the at least one URI to generate a mapped text passage, and storing a begin and an end of the mapped text passage and the second URI as a second semantic annotation in the semantic annotation database such that the first semantic annotation and the second semantic annotation are stored together in the semantic annotation database, generating an image feature database that stores features contained in the at least one image by, detecting a region of interest (ROI) in the at least one image that includes the detected structures, analyzing the ROI to compute at least one low-level feature therein, the at least one low-level feature being one of a gradient and histogram features of the ROI, and storing the at least one level feature with a reference to the at least one image and an index for fast retrieval in the image feature database; and searching for a resulting set of images by comparing both features of a reference image received by a user with at least one feature in the image feature database and textual search terms input by the user and the semantic annotation database by, receiving an input query describing a search to be executed, the input query containing both the reference image and the textual search terms input by the user, forming a first query based on the textual search terms contained in the input query and on additional anatomic information provided by the knowledge database, the additional anatomic information being an expanded list of synonyms associated with the textual search terms, generating a first result list providing search results of the first query based on the first semantic annotation and the second semantic annotation of the semantic annotation database, forming a second query based on the reference image contained in the input query and on at least one computed feature based on the input query, generating a second result list providing search results of the second query based on the at least one low-level feature in the image feature database, and aggregating the first result list and the second result list to form a final result list that provides reference to at least one of the at least one image and an image region of the at least one of the at least one image. 5. The method of claim 1 , wherein the storing of the detected structures includes storing a reference information to the at least one image that is stored on an image database. | 0.863426 |
7,793,224 | 4 | 6 | 4. A computer readable storage medium comprising executable instructions encoded thereon operable on a computerized device, the instructions comprising: instructions for receiving a selection of content displayed in a first portion of a first document; instructions for identifying a reference in the first document to first formatting information currently applied to the selected content; instructions for identifying second formatting information in the first portion of the first document that currently formats non-selected content displayed in a second portion of the first document, the non-selected content exclusive of the selected content; instructions for including an identification of the non-selected content in the first formatting information; instructions for pasting the selected content into the second document upon receiving a request to paste the selected content into a second document, the selected content formatted in the second document according to the first formatting information; and instructions for carrying over the non-selected content from the first document into the second document based on the identification of the non-selected content in the first formatting information; wherein the instructions for identifying the reference in the first document include: instructions for identifying a reference to a source located outside of the first document, the source providing the first formatting information currently applied to the selected content; instructions for accessing the first formatting information from the source; instructions for displaying the first formatting information via a prompt; instructions for receiving a selection of a subset of the first formatting information; wherein the instructions for pasting the selected content into the second document include: instructions for formatting the selected content according to the subset of the first formatting information; wherein the instructions for including the identification of the non-selected content in the first formatting information include: instructions for including, in the subset of the first formatting information, an identification of: (i) a displayed first document title and (ii) a graphic located, in the first document, within a particular distance from the selected content; and wherein the instructions for carrying over the non-selected content include: instructions for pasting the graphic in the second document; and instructions for pasting the first document title as a title of the second document. | 4. A computer readable storage medium comprising executable instructions encoded thereon operable on a computerized device, the instructions comprising: instructions for receiving a selection of content displayed in a first portion of a first document; instructions for identifying a reference in the first document to first formatting information currently applied to the selected content; instructions for identifying second formatting information in the first portion of the first document that currently formats non-selected content displayed in a second portion of the first document, the non-selected content exclusive of the selected content; instructions for including an identification of the non-selected content in the first formatting information; instructions for pasting the selected content into the second document upon receiving a request to paste the selected content into a second document, the selected content formatted in the second document according to the first formatting information; and instructions for carrying over the non-selected content from the first document into the second document based on the identification of the non-selected content in the first formatting information; wherein the instructions for identifying the reference in the first document include: instructions for identifying a reference to a source located outside of the first document, the source providing the first formatting information currently applied to the selected content; instructions for accessing the first formatting information from the source; instructions for displaying the first formatting information via a prompt; instructions for receiving a selection of a subset of the first formatting information; wherein the instructions for pasting the selected content into the second document include: instructions for formatting the selected content according to the subset of the first formatting information; wherein the instructions for including the identification of the non-selected content in the first formatting information include: instructions for including, in the subset of the first formatting information, an identification of: (i) a displayed first document title and (ii) a graphic located, in the first document, within a particular distance from the selected content; and wherein the instructions for carrying over the non-selected content include: instructions for pasting the graphic in the second document; and instructions for pasting the first document title as a title of the second document. 6. The computer readable storage medium as in claim 4 , wherein the instructions for receiving the selection of a subset of the first formatting information include: instructions for receiving a user selection applied in response to the prompt, the user selection indicating which part of the first formatting information to apply to the selected content upon pasting the selected content into the second document. | 0.5 |
8,688,669 | 6 | 7 | 6. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving, from a user device, a search query for a content item, the search query including one or more search terms; identifying a corpus of content items previously delivered to the user device, wherein the content items included in the corpus of content items are advertisements corresponding to content sponsors; creating an index of the corpus of content items previously delivered to the user device, wherein the index of the corpus of content items previously delivered to the user device is populated of a cookie stored at the user device; using the received search terms to search the index of the corpus of content items; determining that at least one content item in the index corresponds to the received search terms; and delivering, to the user device, a content item search result, the content item search result including the at least one content item corresponding to the received search terms. | 6. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving, from a user device, a search query for a content item, the search query including one or more search terms; identifying a corpus of content items previously delivered to the user device, wherein the content items included in the corpus of content items are advertisements corresponding to content sponsors; creating an index of the corpus of content items previously delivered to the user device, wherein the index of the corpus of content items previously delivered to the user device is populated of a cookie stored at the user device; using the received search terms to search the index of the corpus of content items; determining that at least one content item in the index corresponds to the received search terms; and delivering, to the user device, a content item search result, the content item search result including the at least one content item corresponding to the received search terms. 7. The non-transitory computer storage medium of claim 6 , wherein using the received search terms to search the corpus of content items previously delivered to the user device comprises using the received search terms to search the index. | 0.5 |
8,387,122 | 32 | 33 | 32. The method of claim 31 , further comprising the step of employing the one or more shared knowledge questions that are reused to control access to the second resource only if the party attempting to access the second resource has first failed to provide a predefined password initially required to access the second resource, or if there is at least one concern about granting the party access to the second resource based on use of only a different procedure for controlling access. | 32. The method of claim 31 , further comprising the step of employing the one or more shared knowledge questions that are reused to control access to the second resource only if the party attempting to access the second resource has first failed to provide a predefined password initially required to access the second resource, or if there is at least one concern about granting the party access to the second resource based on use of only a different procedure for controlling access. 33. The method of claim 32 , wherein the at least one concern is selected from the group of concerns consisting of: (a) the second resource has a substantially higher value than other resources for which access is granted based only on the different procedure; (b) a possible fraud by the party in attempting to access the second resource has been detected; and (c) a suspect behavior has been detected in connection with an attempt by the party to access the second resource. | 0.5 |
8,121,902 | 5 | 10 | 5. A method of implementing an electronic catalog of a merchant website, the method comprising: under control of one or more computing systems of the merchant website, the one or more computing systems configured with executable instructions, causing display of, to a user of the merchant website and by the one or more computing systems, an image that illustrates an item within the electronic catalog and having an associated page; and enabling, by the one or more computing systems, the user to associate a hyperlink to the associated page with the illustrated item. | 5. A method of implementing an electronic catalog of a merchant website, the method comprising: under control of one or more computing systems of the merchant website, the one or more computing systems configured with executable instructions, causing display of, to a user of the merchant website and by the one or more computing systems, an image that illustrates an item within the electronic catalog and having an associated page; and enabling, by the one or more computing systems, the user to associate a hyperlink to the associated page with the illustrated item. 10. A method as recited in claim 5 , wherein the image comprises a digital photograph and wherein the user or another user of the merchant website uploads the digital photograph to the merchant website. | 0.778993 |
9,881,611 | 1 | 5 | 1. A method comprising: detecting an ongoing voice call, between a first party and a second party, at a user device associated with the first party; presenting, by the user device and during the ongoing voice call, a user interface that includes a control option that allows selection of a pre-recorded word or phrase, from a plurality of pre-recorded words or phrases, the pre-recorded word or phrase having been received from a user of the user device prior to the ongoing voice call; receiving, by the user device, via the user interface, and during the ongoing voice call, a selection of a particular pre-recorded word or phrase from the plurality of words or phrases; receiving, by the user device, via the user interface, and during the ongoing voice call, another word or phrase and an indication to pre-pend or post-pend the another word or phrase to the particular pre-recorded word or phrase; and interjecting, by the user device and in accordance with the indication, the selected particular pre-recorded word or phrase and the another word or phrase, into the ongoing voice call, the interjecting including outputting, via the ongoing voice call and to the second party, the selected particular pre-recorded word or phrase and the another word or phrase, the another word or phrase being pre-pended or post-pended to the selected particular pre-recorded word or phrase, based on the indication. | 1. A method comprising: detecting an ongoing voice call, between a first party and a second party, at a user device associated with the first party; presenting, by the user device and during the ongoing voice call, a user interface that includes a control option that allows selection of a pre-recorded word or phrase, from a plurality of pre-recorded words or phrases, the pre-recorded word or phrase having been received from a user of the user device prior to the ongoing voice call; receiving, by the user device, via the user interface, and during the ongoing voice call, a selection of a particular pre-recorded word or phrase from the plurality of words or phrases; receiving, by the user device, via the user interface, and during the ongoing voice call, another word or phrase and an indication to pre-pend or post-pend the another word or phrase to the particular pre-recorded word or phrase; and interjecting, by the user device and in accordance with the indication, the selected particular pre-recorded word or phrase and the another word or phrase, into the ongoing voice call, the interjecting including outputting, via the ongoing voice call and to the second party, the selected particular pre-recorded word or phrase and the another word or phrase, the another word or phrase being pre-pended or post-pended to the selected particular pre-recorded word or phrase, based on the indication. 5. The method of claim 1 , further comprising: performing a statistical tracking of the particular pre-recorded word or phrase. | 0.864606 |
7,840,912 | 12 | 13 | 12. A method of providing to a user a dictionary of multi-touch gestures, each of the gestures comprising a chord and a motion associated with the chord, the method comprising: identifying a chord presented to a multi-touch interface by the user to begin a gesture, the identified chord comprising a combination of hand parts associated with the gesture but distinct from motion associated with the identified chord to complete the gesture, wherein the identified chord is presented during use of a non-dictionary application; detecting an absence of motion associated with the identified chord to complete the gesture for a predetermined period of time after the identifying of the chord presented to begin the gesture; and in response to the detecting of the absence of motion for the predetermined period of time, displaying a dictionary entry for the identified chord, the displayed dictionary entry comprising a visual depiction of multiple motions associated with the identified chord and, for each of the multiple motions associated with the identified chord, a meaning of a gesture comprising the identified chord and the corresponding motion. | 12. A method of providing to a user a dictionary of multi-touch gestures, each of the gestures comprising a chord and a motion associated with the chord, the method comprising: identifying a chord presented to a multi-touch interface by the user to begin a gesture, the identified chord comprising a combination of hand parts associated with the gesture but distinct from motion associated with the identified chord to complete the gesture, wherein the identified chord is presented during use of a non-dictionary application; detecting an absence of motion associated with the identified chord to complete the gesture for a predetermined period of time after the identifying of the chord presented to begin the gesture; and in response to the detecting of the absence of motion for the predetermined period of time, displaying a dictionary entry for the identified chord, the displayed dictionary entry comprising a visual depiction of multiple motions associated with the identified chord and, for each of the multiple motions associated with the identified chord, a meaning of a gesture comprising the identified chord and the corresponding motion. 13. The method of claim 12 further comprising: identifying a subsequent chord presented to the multi-touch interface by the user; and displaying a dictionary entry for the identified subsequent chord, the dictionary entry comprising a visual depiction of one or more motions associated with the identified subsequent chord and, for each of the one or more motions associated with the identified subsequent chord, a meaning of a gesture comprising the identified subsequent chord and the motion. | 0.5 |
9,928,234 | 8 | 10 | 8. A system, comprising: a memory; a processor, coupled to the memory, the processor configured to: perform semantico-syntactic analysis of a natural language text to produce a semantic structure representing a set of semantic classes; associate a first semantic class of the set of semantic classes with a first value reflecting a specified semantic class attribute; identify a second semantic class associated with the first semantic class by a pre-defined semantic relationship; associate the second semantic class with a second value reflecting the specified semantic class attribute, wherein the second value is determined by applying a pre-defined transformation to the first value, wherein applying the pre-defined transformation comprises multiplying the first value by a pre-defined multiplier; evaluate a feature of the natural language text based on the first value and the second value; determine, by a classifier model using the evaluated feature of the natural language text, a degree of association of the natural language text with a particular category of a pre-defined set of categories; and perform, using the degree of association, a natural language processing operation. | 8. A system, comprising: a memory; a processor, coupled to the memory, the processor configured to: perform semantico-syntactic analysis of a natural language text to produce a semantic structure representing a set of semantic classes; associate a first semantic class of the set of semantic classes with a first value reflecting a specified semantic class attribute; identify a second semantic class associated with the first semantic class by a pre-defined semantic relationship; associate the second semantic class with a second value reflecting the specified semantic class attribute, wherein the second value is determined by applying a pre-defined transformation to the first value, wherein applying the pre-defined transformation comprises multiplying the first value by a pre-defined multiplier; evaluate a feature of the natural language text based on the first value and the second value; determine, by a classifier model using the evaluated feature of the natural language text, a degree of association of the natural language text with a particular category of a pre-defined set of categories; and perform, using the degree of association, a natural language processing operation. 10. The system of claim 8 , wherein the semantic structure is represented by a graph comprising a plurality of nodes corresponding to the set of semantic classes and further comprising a plurality of edges corresponding to a plurality of semantic relationships. | 0.5 |
9,477,729 | 8 | 9 | 8. The method of claim 1 , wherein launching the asynchronous thread for executing the search comprises: accessing a virtual table definition that is a view into a data model of the database represented in a domain structure; translating the string permutation into a set of data model queries for searching the data model using the virtual table definition; and searching the data stored in the database based on the set of data model queries to produce the plurality of search results. | 8. The method of claim 1 , wherein launching the asynchronous thread for executing the search comprises: accessing a virtual table definition that is a view into a data model of the database represented in a domain structure; translating the string permutation into a set of data model queries for searching the data model using the virtual table definition; and searching the data stored in the database based on the set of data model queries to produce the plurality of search results. 9. The method of claim 8 , wherein the data in the database is represented by one or more tokenized data segments, each tokenized data segment being associated with a different set of columns included in the database and specifying all unique values in the set of columns. | 0.5 |
9,405,807 | 11 | 12 | 11. The system of claim 1 , wherein the system is configured to calculate a probability of the candidate responding to a job offer. | 11. The system of claim 1 , wherein the system is configured to calculate a probability of the candidate responding to a job offer. 12. The system of claim 11 , wherein the probability calculation is based on quantitative estimation of the candidate's job search activity. | 0.5 |
9,491,179 | 1 | 3 | 1. A method for detecting unauthorized user account communications, comprising: sampling messages associated with an authorized user of an account to provide a plurality of message samples; creating an authorized profile based on language patterns extracted from the plurality of message samples; comparing by a processor a language pattern extracted from a recent message with the authorized profile to determine a deviation between the language pattern extracted from the recent message and the authorized profile; determining that the recent message is an unauthorized user account communication when the deviation is not within an allowable amount of deviation, the allowable amount of deviation being based on an amount of samples in the plurality of message samples; and generating an alert indicating that the recent message is an unauthorized user account communication in response to the determining that the recent message is an unauthorized user account communication. | 1. A method for detecting unauthorized user account communications, comprising: sampling messages associated with an authorized user of an account to provide a plurality of message samples; creating an authorized profile based on language patterns extracted from the plurality of message samples; comparing by a processor a language pattern extracted from a recent message with the authorized profile to determine a deviation between the language pattern extracted from the recent message and the authorized profile; determining that the recent message is an unauthorized user account communication when the deviation is not within an allowable amount of deviation, the allowable amount of deviation being based on an amount of samples in the plurality of message samples; and generating an alert indicating that the recent message is an unauthorized user account communication in response to the determining that the recent message is an unauthorized user account communication. 3. The method as recited in claim 1 , wherein generating the alert comprises: generating the alert comprising a location of a device which the recent message was received from. | 0.694444 |
9,818,401 | 1 | 7 | 1. A computer-implemented method for recognizing and understanding spoken commands that include one or more proper name entities, comprising: receiving an utterance from a user; performing primary automatic speech recognition (ASR) processing upon said utterance with a primary automatic speech recognizer to output a dataset comprising at least a sequence of nominal transcribed words and putative start and end times for each nominal transcribed word within said utterance; performing understanding processing upon said dataset with a natural language understanding (NLU) processor to generate and augment the dataset with a nominal meaning for the utterance and to determine putative presence and type of one or more spoken proper name entities within said utterance, wherein a contiguous section of audio within said utterance corresponding to each putative proper name entity, as determined from said start and end times of the words of the putative proper name entity as transcribed by the primary automatic speech recognizer, comprises an acoustic span; performing secondary automatic speech recognition (ASR) processing upon each said acoustic span with a secondary automatic speech recognizer, in each instance said secondary automatic speech recognizer specialized to process a given putative type of acoustic span to generate a nominal correct transcription and associated meaning for each said acoustic span; substituting the nominal correct transcription and associated meaning obtained from each secondary recognition as appropriate within the dataset to revise the results of the primary automatic speech recognizer and natural language understanding processor and to create a plurality of complete transcriptions and associated meanings; preparing a complete hypothesis ranking grammar comprised of said plurality of complete transcriptions and decoding the utterance against said complete hypothesis ranking grammar to determine an acoustic confidence score for each complete transcription; determining, for each acoustic span of each complete transcription, an NLU confidence score for each transcription of each acoustic span; normalizing said NLU confidence scores across the plurality of complete transcriptions to determine a normalized NLU confidence score of each complete transcription; combining said acoustic confidence score and NLU confidence score of each complete transcription to generate a final confidence score that each complete transcription and associated meaning is correct, which is used to rank the plurality of aforesaid complete transcriptions and associated meanings; and outputting a ranked list of complete transcriptions and associated meanings for the entire utterance. | 1. A computer-implemented method for recognizing and understanding spoken commands that include one or more proper name entities, comprising: receiving an utterance from a user; performing primary automatic speech recognition (ASR) processing upon said utterance with a primary automatic speech recognizer to output a dataset comprising at least a sequence of nominal transcribed words and putative start and end times for each nominal transcribed word within said utterance; performing understanding processing upon said dataset with a natural language understanding (NLU) processor to generate and augment the dataset with a nominal meaning for the utterance and to determine putative presence and type of one or more spoken proper name entities within said utterance, wherein a contiguous section of audio within said utterance corresponding to each putative proper name entity, as determined from said start and end times of the words of the putative proper name entity as transcribed by the primary automatic speech recognizer, comprises an acoustic span; performing secondary automatic speech recognition (ASR) processing upon each said acoustic span with a secondary automatic speech recognizer, in each instance said secondary automatic speech recognizer specialized to process a given putative type of acoustic span to generate a nominal correct transcription and associated meaning for each said acoustic span; substituting the nominal correct transcription and associated meaning obtained from each secondary recognition as appropriate within the dataset to revise the results of the primary automatic speech recognizer and natural language understanding processor and to create a plurality of complete transcriptions and associated meanings; preparing a complete hypothesis ranking grammar comprised of said plurality of complete transcriptions and decoding the utterance against said complete hypothesis ranking grammar to determine an acoustic confidence score for each complete transcription; determining, for each acoustic span of each complete transcription, an NLU confidence score for each transcription of each acoustic span; normalizing said NLU confidence scores across the plurality of complete transcriptions to determine a normalized NLU confidence score of each complete transcription; combining said acoustic confidence score and NLU confidence score of each complete transcription to generate a final confidence score that each complete transcription and associated meaning is correct, which is used to rank the plurality of aforesaid complete transcriptions and associated meanings; and outputting a ranked list of complete transcriptions and associated meanings for the entire utterance. 7. The method of claim 1 , further comprising: specializing the secondary ASR recognizer by using an adaptation grammar of structure and content appropriate to a putative span type, as determined by NLU processing, said adaptation grammar additionally including acoustic prefix words, acoustic suffix words, or both, as transcribed by the primary ASR recognizer to ensure high accuracy secondary ASR recognition in view of coarticulation effects in the processed utterance and potential imprecise determination of span start and end times; and correspondingly expanding said span to include said acoustic prefix words, acoustic suffix words, or both. | 0.5 |
7,584,161 | 1 | 6 | 1. A computer-based method associated with business process logic configured to capture, structure and standardize subject matter expertise, tasks and activities into a process taxonomy, the method comprising: defining a first taxonomy of a plurality of nodes that define relationships among a plurality of activities and sub-activities; defining a second taxonomy of a plurality of nodes that define relationships among a plurality of business objects; defining a relationship between at least one of the plurality of business objects from the second taxonomy and at least one of the plurality of activities and sub-activities from the first taxonomy, the relationship being defined such that at least a portion of the at least one of the plurality of business objects can be accessed via the at least one of the plurality of activities and sub-activities based on the relationship; defining a business process by manipulating at least one of the activities and sub-activities from the first taxonomy and at least one business object from the second taxonomy; and displaying on a graphical user interface the defined business process based on the manipulating the at least one of the activities and sub-activities from the first taxonomy and the at least one business object from the second taxonomy. | 1. A computer-based method associated with business process logic configured to capture, structure and standardize subject matter expertise, tasks and activities into a process taxonomy, the method comprising: defining a first taxonomy of a plurality of nodes that define relationships among a plurality of activities and sub-activities; defining a second taxonomy of a plurality of nodes that define relationships among a plurality of business objects; defining a relationship between at least one of the plurality of business objects from the second taxonomy and at least one of the plurality of activities and sub-activities from the first taxonomy, the relationship being defined such that at least a portion of the at least one of the plurality of business objects can be accessed via the at least one of the plurality of activities and sub-activities based on the relationship; defining a business process by manipulating at least one of the activities and sub-activities from the first taxonomy and at least one business object from the second taxonomy; and displaying on a graphical user interface the defined business process based on the manipulating the at least one of the activities and sub-activities from the first taxonomy and the at least one business object from the second taxonomy. 6. The method of claim 1 further comprising: automatically determining whether metadata associated with different business objects is in common; and removing or merging duplicate business objects and linking similar business objects based on the determining. | 0.814388 |
7,987,421 | 3 | 5 | 3. An apparatus according to claim 2 , further comprising: a resource file map to store at least two combinations of a layout information file and languages in which the layout strings files store the layout strings; a ranked list of languages specifying a plurality of languages preferred by the user and an order based on the user's preferences; and a selector to select one of the plurality of layout information files and one layout strings file based on the ranked list of languages and the resource file map. | 3. An apparatus according to claim 2 , further comprising: a resource file map to store at least two combinations of a layout information file and languages in which the layout strings files store the layout strings; a ranked list of languages specifying a plurality of languages preferred by the user and an order based on the user's preferences; and a selector to select one of the plurality of layout information files and one layout strings file based on the ranked list of languages and the resource file map. 5. An apparatus according to claim 3 , wherein: each layout information file defines how a particular layout string is displayed in a different language on a different device; and the resource file map stores combinations of layout information files, languages in which the layout strings files store the layout strings, and identities of devices for display of the information. | 0.5 |
7,937,402 | 19 | 21 | 19. A natural language based and keyword based location query method, the method comprising: receiving a request for a query for a location of an target entity having a specified geographical relationship to a known entity in the keyword query from a user terminal; a determining step of determining whether the received request is one of a request for a natural language query or a request for a keyword query; when the request is a request for the natural language query, a natural language query processing step of parsing the natural language query to determine the known entity of the natural language query and performing at least one of a fuzzy processing and an indirection processing on the request for natural language query sent from the user terminal by searching a location ontology database and a location query language database for the known entity, and retrieving location information corresponding to the known entity from a location database, wherein the location query language database is generated by creation of a domain query language and a common query language, wherein the domain query language is created by collecting question sentences for each domain, extracting syntax and a constant table from the question sentences, and combing the extracted syntax and a query action corresponding to the syntax, and the common query language is created by calculating a similarity among all domain query languages, and extracting a common query language, wherein the fuzzy processing step comprises at least one step of deleting redundant words based on a grammar feature, detecting and completing incomplete words based on the location ontology, and finding words omitted by the user by using context-aware technology based on the user's query history, and the indirection processing step comprises converting an indirect description in the query corresponding category name in the location ontology database by searching the category table in the location ontology base; and a first transmitting step of sending the location information of the known entity to the user terminal; when the request is a request for keyword query, a keyword query processing step of parsing the keyword query to determine the known entity of the keyword query and performing at least one of a fuzzy processing and an indirection processing on a request for keyword query sent from a user terminal by searching the location ontology database and the location query language database for the known entity, retrieving location information corresponding to the known entity form a location database; and a second transmitting step of sending the location information of the known entity to the user terminal, wherein the location ontology database includes an index that geographically relates the target entity to the known entity and the location query language database includes a syntax for a query to access a database having a location of the target entity. | 19. A natural language based and keyword based location query method, the method comprising: receiving a request for a query for a location of an target entity having a specified geographical relationship to a known entity in the keyword query from a user terminal; a determining step of determining whether the received request is one of a request for a natural language query or a request for a keyword query; when the request is a request for the natural language query, a natural language query processing step of parsing the natural language query to determine the known entity of the natural language query and performing at least one of a fuzzy processing and an indirection processing on the request for natural language query sent from the user terminal by searching a location ontology database and a location query language database for the known entity, and retrieving location information corresponding to the known entity from a location database, wherein the location query language database is generated by creation of a domain query language and a common query language, wherein the domain query language is created by collecting question sentences for each domain, extracting syntax and a constant table from the question sentences, and combing the extracted syntax and a query action corresponding to the syntax, and the common query language is created by calculating a similarity among all domain query languages, and extracting a common query language, wherein the fuzzy processing step comprises at least one step of deleting redundant words based on a grammar feature, detecting and completing incomplete words based on the location ontology, and finding words omitted by the user by using context-aware technology based on the user's query history, and the indirection processing step comprises converting an indirect description in the query corresponding category name in the location ontology database by searching the category table in the location ontology base; and a first transmitting step of sending the location information of the known entity to the user terminal; when the request is a request for keyword query, a keyword query processing step of parsing the keyword query to determine the known entity of the keyword query and performing at least one of a fuzzy processing and an indirection processing on a request for keyword query sent from a user terminal by searching the location ontology database and the location query language database for the known entity, retrieving location information corresponding to the known entity form a location database; and a second transmitting step of sending the location information of the known entity to the user terminal, wherein the location ontology database includes an index that geographically relates the target entity to the known entity and the location query language database includes a syntax for a query to access a database having a location of the target entity. 21. The method of claim 19 , wherein the keyword query processing step comprises: a parsing step of parses the request for keyword query by searching a category table, an entity table in the location ontology database and a constant table in a syntax part of the location query language database; a fuzzy processing step of performing, to the fuzzy description in the parsed request, at least one step of deleting redundant words based on a grammar feature, detecting and completing incomplete words based on the location ontology, and finding words omitted by the user by using context-aware technology based on the user's query history; an indirection processing step of converts indirect description in the query into the corresponding category name in the location ontology base by searching the category table in the location ontology database; a partial syntax matching step of partially matches the processed request with the location query language database, and obtains a collection of the syntax matching; an answer deciding step of selecting form the collection of the syntax matching the optimum matched syntax according to predetermined determination rules, and generating a query action corresponding to the request; a database searching step of retrieves the corresponding query result from the location database based on the query action; and an answer fusing and generating step of fusing the query result to generate an answer, and sending the answer to the user terminal. | 0.5 |
8,527,523 | 19 | 60 | 19. The method according to claim 1 further comprising: classifying each document from among said N electronic documents as relevant or irrelevant to an issue; and generating a computer display of at least one user-selected document within said N electronic documents, wherein at least some words in said user-selected document are differentially presented depending on their contribution to said classifying of the document as relevant or irrelevant, wherein said words differentially presented are differentially colored and intensity of color is used to represent strength of said contribution for each word. | 19. The method according to claim 1 further comprising: classifying each document from among said N electronic documents as relevant or irrelevant to an issue; and generating a computer display of at least one user-selected document within said N electronic documents, wherein at least some words in said user-selected document are differentially presented depending on their contribution to said classifying of the document as relevant or irrelevant, wherein said words differentially presented are differentially colored and intensity of color is used to represent strength of said contribution for each word. 60. The method according to claim 19 wherein said iteration I+1 uses a control subset larger than the control subset of iteration I, said control subset including the control subset of iteration I merged with an additional group of documents of pre-determined size randomly selected from said at least N electronic documents. | 0.5 |
9,582,613 | 8 | 9 | 8. The PDM system of claim 7 , wherein the PDM system receives performs a lookup process on an occurrence equivalency table and anchor occurrence table, and determines the query result that identifies occurrence chains corresponding to the query. | 8. The PDM system of claim 7 , wherein the PDM system receives performs a lookup process on an occurrence equivalency table and anchor occurrence table, and determines the query result that identifies occurrence chains corresponding to the query. 9. The PDM system of claim 8 , wherein the PDM system also creates the occurrence equivalency table, from the hierarchical product data structure, that identifies at least one anchor occurrence node, and identifies at least one equivalent occurrence node that connects a same parent component node and a same child component node as the anchor occurrence node, the product component corresponding to the equivalent occurrence node being spatially located within a specified distance threshold of product component corresponding to the anchor occurrence node; and creates the anchor occurrence table, corresponding to the hierarchical product data structure, that lists a plurality of unique occurrence chain represented by the hierarchical product data structure, where each equivalent occurrence node is replaced by its corresponding anchor occurrence node, and that associates each listed unique occurrence chain with an associated cell index value; and stores the occurrence equivalency table and anchor occurrence table in the PDM system. | 0.5 |
4,357,687 | 5 | 6 | 5. Apparatus for pulling down the word line voltage when a word is to be deaddressed in a memory of the kind having a plurality of words and a top word line and a bottom word line associated with each word, said apparatus comprising, detecting means for detecting a signal that the address of a word is to be changed, amplifying means operatively associated with the detecting means for amplifying the detected signal, steering means operatively associated with the amplifying means for steering a pull-down current to the bottom word line to commence pulling the word down in response to the amplified signal and for maintaining that pull-down current on the bottom word line until the word is deaddressed, said amplifying means including current switch means operatively associated with a word line for detecting the fact that the word has been pulled down and effective to cause the level shifter and steering means to steer the pull-down current away from the bottom pull-down line after the word has been deaddressed. | 5. Apparatus for pulling down the word line voltage when a word is to be deaddressed in a memory of the kind having a plurality of words and a top word line and a bottom word line associated with each word, said apparatus comprising, detecting means for detecting a signal that the address of a word is to be changed, amplifying means operatively associated with the detecting means for amplifying the detected signal, steering means operatively associated with the amplifying means for steering a pull-down current to the bottom word line to commence pulling the word down in response to the amplified signal and for maintaining that pull-down current on the bottom word line until the word is deaddressed, said amplifying means including current switch means operatively associated with a word line for detecting the fact that the word has been pulled down and effective to cause the level shifter and steering means to steer the pull-down current away from the bottom pull-down line after the word has been deaddressed. 6. The invention defined in claim 5 including level shifter means connected between the amplifying means and the steering means for shifting a voltage down to insure operation of the steering means in a normal manner. | 0.661994 |
9,075,493 | 29 | 30 | 29. An article of manufacture comprising a storage medium containing instructions that when executed enable a system to: generate a tile for each node of hierarchical information; arrange tiles for nodes of a same hierarchical level into a planar layer; arrange the planar layers in a vertical stack; generate a three dimensional orthographic projection with the vertical stack of planar layers each having multiple tiles; render, in a user interface, the three dimensional orthographic projection of the vertical stack of planar layers, wherein the vertical stack of planar layers each has multiple tiles for presentation on a display; and animate a transition between different graphical user interface views for the three dimensional orthographic projection. | 29. An article of manufacture comprising a storage medium containing instructions that when executed enable a system to: generate a tile for each node of hierarchical information; arrange tiles for nodes of a same hierarchical level into a planar layer; arrange the planar layers in a vertical stack; generate a three dimensional orthographic projection with the vertical stack of planar layers each having multiple tiles; render, in a user interface, the three dimensional orthographic projection of the vertical stack of planar layers, wherein the vertical stack of planar layers each has multiple tiles for presentation on a display; and animate a transition between different graphical user interface views for the three dimensional orthographic projection. 30. The article of claim 29 , further comprising instructions that if executed enable the system to receive user control directives and generate different graphical user interface views for the three dimensional orthographic projection based on the received user control directives. | 0.5 |
8,140,980 | 18 | 30 | 18. A system for providing multi-media conferencing, the system comprising one or more processors having: a conference scheduling application configured to receive textual information for display during a conference session among a plurality of participants, and to retrieve configuration information specifying language assistance for the textual information, wherein the configuration information is associated with one of the participants; and a language assistance application configured to augment the textual information according to the configuration information for comprehension of the textual information by the one participant, wherein the language assistance application determines whether the textual information is contained in a predetermined list of terms and associated supplemental information, and if the textual information is in the list, the language assistance application marks the textual information to notify the one participant that the supplemental information is available for selective display, the supplemental information including definitions of the corresponding terms, and wherein the textual information having the marking is forwarded to the one participant for display during the conference session without replacement of the textual information. | 18. A system for providing multi-media conferencing, the system comprising one or more processors having: a conference scheduling application configured to receive textual information for display during a conference session among a plurality of participants, and to retrieve configuration information specifying language assistance for the textual information, wherein the configuration information is associated with one of the participants; and a language assistance application configured to augment the textual information according to the configuration information for comprehension of the textual information by the one participant, wherein the language assistance application determines whether the textual information is contained in a predetermined list of terms and associated supplemental information, and if the textual information is in the list, the language assistance application marks the textual information to notify the one participant that the supplemental information is available for selective display, the supplemental information including definitions of the corresponding terms, and wherein the textual information having the marking is forwarded to the one participant for display during the conference session without replacement of the textual information. 30. A system according to claim 18 , wherein an icon displayed to the one participant is responsive to at least one of the start time of the conference session, the stop time of the conference or the duration of the conference. | 0.661194 |
7,751,511 | 9 | 10 | 9. The method of claim 8 , wherein normalizing the modeled impairment correlation terms comprises scaling the modeled impairment correlation terms to obtain a unit impairment-power contribution for individual ones of the modeled impairment correlation terms. | 9. The method of claim 8 , wherein normalizing the modeled impairment correlation terms comprises scaling the modeled impairment correlation terms to obtain a unit impairment-power contribution for individual ones of the modeled impairment correlation terms. 10. The method of claim 9 , wherein scaling the modeled impairment correlation terms to obtain a unit impairment-power contribution for individual ones of the modeled impairment correlation terms comprises dividing individual ones of the modeled impairment correlation terms by their corresponding trace. | 0.5 |
4,773,009 | 31 | 33 | 31. A method according to claim 30, further including the step of displaying an interpretive message with the readability output. | 31. A method according to claim 30, further including the step of displaying an interpretive message with the readability output. 33. A method according to claim 31, wherein a readability output includes a Bormuth reading power score. | 0.587302 |
10,013,331 | 5 | 7 | 5. A computer program product comprising a computer readable storage medium storing computer readable program code that, when executed on a processor of a computer, causes the computer to: set, with a processor executing on a computer, one or more breakpoints in source code of a client application based on locations of Application Programming Interface (API) calls in the source code; while running the client application through a debugger, upon reaching each of the one or more breakpoints, identify one or more debugger rules associated with a query at a breakpoint; in response to determining that conditions of the one or more debugger rules are satisfied, obtain a stack trace before the query makes a call to a database; derive query text of the query and a location of the query in the source code of the client application; parsing the query text to identify database objects used by the query; and storing correlator results for the query that identify a source file of the client application, locations of an API call in the source code, parameters of the API call, and the database objects, wherein one of the parameters is the query text of the query; and displaying user interface views in a user interface to present the correlator results for problem determination and where used analysis. | 5. A computer program product comprising a computer readable storage medium storing computer readable program code that, when executed on a processor of a computer, causes the computer to: set, with a processor executing on a computer, one or more breakpoints in source code of a client application based on locations of Application Programming Interface (API) calls in the source code; while running the client application through a debugger, upon reaching each of the one or more breakpoints, identify one or more debugger rules associated with a query at a breakpoint; in response to determining that conditions of the one or more debugger rules are satisfied, obtain a stack trace before the query makes a call to a database; derive query text of the query and a location of the query in the source code of the client application; parsing the query text to identify database objects used by the query; and storing correlator results for the query that identify a source file of the client application, locations of an API call in the source code, parameters of the API call, and the database objects, wherein one of the parameters is the query text of the query; and displaying user interface views in a user interface to present the correlator results for problem determination and where used analysis. 7. The computer program product of claim 5 , wherein the computer readable program code, when executed on a processor of a computer, causes the computer to: in response to deriving the query of the API call, obtain the query text of the query; invoke a query parser to parse the query to identify one or more tables and one or more columns used by the query; and perform analysis using the correlator results. | 0.5 |
10,079,911 | 1 | 2 | 1. A method, in a data processing system comprising at least one processor and at least one memory, at least one memory comprising instructions that are executed by the at least one processor to specifically configure the at least one processor to implement a community selection system for content analysis based automatic selection of user communities or groups of users, the method comprising: receiving, by the community selection system from a client data processing system of a user, content authored by the user to be published; performing, by a content analysis engine executing within the community selection system, content analysis on the content to identify a context of the content; identifying, by the community selection system, one or more social collaboration communities to which the user belongs using a user registry data structure; selecting, by the community selection system, a social collaboration community based on the identified one or more social collaboration communities to which the user belongs, the context of the content, and a community registry data structure of social collaboration communities; publishing, by the community selection system, the content to a community server data processing system in the selected social collaboration community; receiving, by the community selection system, feedback from the selected social collaboration community regarding the content; analyzing, by a feedback analysis engine executing within the community selection system, the feedback; and determining, by the community selection system, whether to republish the content to a second social collaboration community within the community registry data structure based on results of analyzing the feedback. | 1. A method, in a data processing system comprising at least one processor and at least one memory, at least one memory comprising instructions that are executed by the at least one processor to specifically configure the at least one processor to implement a community selection system for content analysis based automatic selection of user communities or groups of users, the method comprising: receiving, by the community selection system from a client data processing system of a user, content authored by the user to be published; performing, by a content analysis engine executing within the community selection system, content analysis on the content to identify a context of the content; identifying, by the community selection system, one or more social collaboration communities to which the user belongs using a user registry data structure; selecting, by the community selection system, a social collaboration community based on the identified one or more social collaboration communities to which the user belongs, the context of the content, and a community registry data structure of social collaboration communities; publishing, by the community selection system, the content to a community server data processing system in the selected social collaboration community; receiving, by the community selection system, feedback from the selected social collaboration community regarding the content; analyzing, by a feedback analysis engine executing within the community selection system, the feedback; and determining, by the community selection system, whether to republish the content to a second social collaboration community within the community registry data structure based on results of analyzing the feedback. 2. The method of claim 1 , wherein the second community has a wider audience than the social collaboration community. | 0.615132 |
8,953,844 | 10 | 11 | 10. A software pipeline for generating a state estimate for a given frame of captured image data, the state estimate representing an estimate of a position of a user within a field of view captured within the image data, comprising: one or more experts for receiving information including one or more body part proposals and generating a plurality of computer models, each computer model representing an estimation of the position of the user in the given frame of captured image data at least one of the experts generating skeletal hypotheses from at least one of a tree structure of a human body including a torso and limbs as branches, a head triangle including a triangle formed by a head and shoulders and a torso volume including a torso; and an arbiter for receiving the plurality of computer models, scoring the computer models by one or more methodologies, and outputting at least one computer model estimated by the arbiter to best approximate the position of the user in the frame. | 10. A software pipeline for generating a state estimate for a given frame of captured image data, the state estimate representing an estimate of a position of a user within a field of view captured within the image data, comprising: one or more experts for receiving information including one or more body part proposals and generating a plurality of computer models, each computer model representing an estimation of the position of the user in the given frame of captured image data at least one of the experts generating skeletal hypotheses from at least one of a tree structure of a human body including a torso and limbs as branches, a head triangle including a triangle formed by a head and shoulders and a torso volume including a torso; and an arbiter for receiving the plurality of computer models, scoring the computer models by one or more methodologies, and outputting at least one computer model estimated by the arbiter to best approximate the position of the user in the frame. 11. A software pipeline as recited in claim 10 , the arbiter further including a depth score methodology for scoring each of the plurality of computer models by examining the computer model against the depth data for the given frame. | 0.757292 |
9,401,159 | 21 | 23 | 21. A device, comprising: means for receiving a selection of a first control action associated with an application stored in the device, means for providing a plurality of choices associated with the first control action, means for receiving a word or a phrase to use as a voice command corresponding to the first control action, wherein the word or phrase is selected from the plurality of choices, means for associating the word or phrase with the first control action, means for receiving voice input from a user, means for identifying the voice input as corresponding to the word or phrase, and means for performing the first control action based on the identified voice input. | 21. A device, comprising: means for receiving a selection of a first control action associated with an application stored in the device, means for providing a plurality of choices associated with the first control action, means for receiving a word or a phrase to use as a voice command corresponding to the first control action, wherein the word or phrase is selected from the plurality of choices, means for associating the word or phrase with the first control action, means for receiving voice input from a user, means for identifying the voice input as corresponding to the word or phrase, and means for performing the first control action based on the identified voice input. 23. The device of claim 21 , further comprising: means for displaying, in response to an input from the user, a plurality of control actions associated with the application and voice commands associated with the plurality of control actions. | 0.687013 |
9,141,853 | 4 | 6 | 4. The computer program product of claim 3 , wherein the example prior block and example post block each comprise block information, and wherein the block information includes token frequency information, token occurrence information, token weight information, block occurrence information, or block weight information. | 4. The computer program product of claim 3 , wherein the example prior block and example post block each comprise block information, and wherein the block information includes token frequency information, token occurrence information, token weight information, block occurrence information, or block weight information. 6. The computer program product of claim 4 , wherein updating the token weight information comprises updating a token weight for each token within the example prior block or the example post block. | 0.5 |
9,460,068 | 25 | 29 | 25. The system of claim 22 , wherein the operations further comprise non-destructively excluding one or more of the digital media files. | 25. The system of claim 22 , wherein the operations further comprise non-destructively excluding one or more of the digital media files. 29. The system of claim 25 , wherein non-destructively excluding is performed by initially displaying the digital media files in a sequence and providing a side bar, a top bar or a gutter where the user can move the digital media files to be excluded from the narration. | 0.600592 |
8,433,570 | 10 | 20 | 10. A speech for recognizing speech, comprising: a microphone configured to receive an utterance from a source, the utterance potentially containing a particular expression, wherein the particular expression is capable of being associated with at least two different meanings; a processor selectively and operatively connected to the microphone, the processor including: computer readable code for determining that the utterance contains the particular expression; computer readable code for splitting the utterance into a plurality of speech frames, each frame being assigned a predetermined time segment and a frame number; and computer readable code for indexing the utterance to i) a predetermined frame number, or ii) a predetermined time segment, the indexing identifying that one of the plurality of frames includes the particular expression; and means for re-presenting the one of the plurality of frames including the particular expression to the speech recognition system to verify that the particular expression was actually recited in the utterance. | 10. A speech for recognizing speech, comprising: a microphone configured to receive an utterance from a source, the utterance potentially containing a particular expression, wherein the particular expression is capable of being associated with at least two different meanings; a processor selectively and operatively connected to the microphone, the processor including: computer readable code for determining that the utterance contains the particular expression; computer readable code for splitting the utterance into a plurality of speech frames, each frame being assigned a predetermined time segment and a frame number; and computer readable code for indexing the utterance to i) a predetermined frame number, or ii) a predetermined time segment, the indexing identifying that one of the plurality of frames includes the particular expression; and means for re-presenting the one of the plurality of frames including the particular expression to the speech recognition system to verify that the particular expression was actually recited in the utterance. 20. The system as defined in claim 10 wherein the system is configured to be used in a mobile vehicle. | 0.926301 |
9,754,210 | 16 | 19 | 16. A computer-implemented system for determining user interests, comprising: one or more processors; one or more computer storage media storing computer-useable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving user activity data that describes an interaction between a user and digital content; identifying a first entity and a second entity that are matched to the digital content by mapping data, said first entity and said second entity being a topic of said digital content, wherein said first entity and said second entity are included within a knowledge base comprising a plurality of entities, said knowledge base comprising an ontology comprising a knowledge graph that indicates relationships between said plurality of entities; identifying a candidate entity based on said candidate entity having a relationship to both the first entity and the second entity within the knowledge base; generating second interest-level data that represents a second level of interest between said user and said candidate entity based on an analysis of said relationship, said analysis comprising comparing one or more attributes of said ontology assigned to said first entity and said second entity in said ontology to one or more attributes of said ontology assigned to said candidate entity in said ontology; linking a user ID associated with the user to the candidate entity, thereby indicating the user is interested in the candidate entity; receiving a search query from the user; and generating a search result comprising digital contents, in response to the received search query, wherein the digital contents are ranked using the generated first interest-level data and the generated second interest-level data. | 16. A computer-implemented system for determining user interests, comprising: one or more processors; one or more computer storage media storing computer-useable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving user activity data that describes an interaction between a user and digital content; identifying a first entity and a second entity that are matched to the digital content by mapping data, said first entity and said second entity being a topic of said digital content, wherein said first entity and said second entity are included within a knowledge base comprising a plurality of entities, said knowledge base comprising an ontology comprising a knowledge graph that indicates relationships between said plurality of entities; identifying a candidate entity based on said candidate entity having a relationship to both the first entity and the second entity within the knowledge base; generating second interest-level data that represents a second level of interest between said user and said candidate entity based on an analysis of said relationship, said analysis comprising comparing one or more attributes of said ontology assigned to said first entity and said second entity in said ontology to one or more attributes of said ontology assigned to said candidate entity in said ontology; linking a user ID associated with the user to the candidate entity, thereby indicating the user is interested in the candidate entity; receiving a search query from the user; and generating a search result comprising digital contents, in response to the received search query, wherein the digital contents are ranked using the generated first interest-level data and the generated second interest-level data. 19. A computer-implemented system of claim 16 , wherein said generating said second interest-level data is based on determining a similarity between said one or more attributes of said first entity and said second entity and said one or more attributes of said candidate entity. | 0.690423 |
7,711,725 | 1 | 4 | 1. A computer implemented method for offering complementary products/services comprising: monitoring, via a computing device, one or more actions taken by a user while browsing a website; automatically assigning, via the computing device, one or more search terms to at least one of the one or more actions taken by the user based upon, at least in part, metadata associated with said one or more actions; assigning, via the computing device, one or more complementary terms that define one or more products/services that complement the one or more actions taken by the user; in response to at least one of the actions, executing a query on a datastore based on at least a portion of the one or more search terms and at least a portion of the one or more complementary terms to generate a result set; and displaying, via the computing device, the result set including a link to an ecommerce website that offers for sale the one or more products/services, the link embedded with a referring party identifier configured to identify a referring party to a merchant operating the ecommerce website for payment of a referral fee. | 1. A computer implemented method for offering complementary products/services comprising: monitoring, via a computing device, one or more actions taken by a user while browsing a website; automatically assigning, via the computing device, one or more search terms to at least one of the one or more actions taken by the user based upon, at least in part, metadata associated with said one or more actions; assigning, via the computing device, one or more complementary terms that define one or more products/services that complement the one or more actions taken by the user; in response to at least one of the actions, executing a query on a datastore based on at least a portion of the one or more search terms and at least a portion of the one or more complementary terms to generate a result set; and displaying, via the computing device, the result set including a link to an ecommerce website that offers for sale the one or more products/services, the link embedded with a referring party identifier configured to identify a referring party to a merchant operating the ecommerce website for payment of a referral fee. 4. The computer implemented method of claim 1 wherein the one or more products/services that complement the one or more actions taken by the user is chosen from the group consisting of: concert tickets; clothing; memorabilia; compact discs; digital video discs; audio tapes; video tapes; books; magazines, photographs; autographs; posters; airline tickets; train tickets; ground transportation; consumer products; consumer services; business products; and business services. | 0.5 |
8,180,754 | 1 | 18 | 1. A system for processing user search requests comprising: a memory; a processor configured to execute instructions stored on the memory; a semantic neural network configured to create semantic connections between one or more of words, documents, and sentences; a session manager configured to process a user search query and provide the user search query to the semantic neural network; a user map module configured to generate a user map of search terms based on a subset of the semantic neural network and provide the user map to the user such that the user can select relevant search terms from the user map of search terms, wherein the search terms are semantically related to the user search query; a search controller module configured to provide a plurality of search result documents corresponding to the selected relevant search terms, wherein the user can identify relevant documents from the plurality of search result documents; and a semantic neural network update module configured to update the semantic neural network according to at least one of the selected relevant search terms from the user map or the identified relevant documents selected by the user. | 1. A system for processing user search requests comprising: a memory; a processor configured to execute instructions stored on the memory; a semantic neural network configured to create semantic connections between one or more of words, documents, and sentences; a session manager configured to process a user search query and provide the user search query to the semantic neural network; a user map module configured to generate a user map of search terms based on a subset of the semantic neural network and provide the user map to the user such that the user can select relevant search terms from the user map of search terms, wherein the search terms are semantically related to the user search query; a search controller module configured to provide a plurality of search result documents corresponding to the selected relevant search terms, wherein the user can identify relevant documents from the plurality of search result documents; and a semantic neural network update module configured to update the semantic neural network according to at least one of the selected relevant search terms from the user map or the identified relevant documents selected by the user. 18. The method of claim 1 , wherein the neural network comprises semantic connections between the one or more of words, documents, and sentences based on aggregated semantic information generated from preferences of a plurality of previous users. | 0.619195 |
8,069,182 | 15 | 27 | 15. One or more tangible computer readable storage media storing computer-executable instructions for performing a computer process, the computer process comprising: receiving a request from a source to access content of a target Web domain, the request being addressed to a domain address of the target Web domain; retrieving historical relevance data associated with at least one previous request from another source to the target Web domain from a database; identifying a new content Web domain that is determined to be relevant to the request based on a combination of the domain address of the target Web domain and the historical relevance data, the historical relevance data including one or more context factors collected from the at least one previous request to the target Web domain; and redirecting the source to access advertising content of the identified new content Web domain, responsive to the request. | 15. One or more tangible computer readable storage media storing computer-executable instructions for performing a computer process, the computer process comprising: receiving a request from a source to access content of a target Web domain, the request being addressed to a domain address of the target Web domain; retrieving historical relevance data associated with at least one previous request from another source to the target Web domain from a database; identifying a new content Web domain that is determined to be relevant to the request based on a combination of the domain address of the target Web domain and the historical relevance data, the historical relevance data including one or more context factors collected from the at least one previous request to the target Web domain; and redirecting the source to access advertising content of the identified new content Web domain, responsive to the request. 27. The tangible computer readable storage media of claim 15 , wherein the computer process further comprises: storing the new content Web domain on the computer-readable storage media. | 0.820388 |
7,685,209 | 1 | 5 | 1. An annotation method for annotating content comprising: dynamically receiving annotation information from one or more users wherein annotation information includes an annotation rating; determining one or more suggested keywords based on a related annotation rating and used by a user to annotate one or more items of content; performing text recognition on a given item of content to generate recognized text; determining a subject of the given item of content from the recognized text; determining one or more suggested keywords based on the subject of the given item of content; determining one or more suggested keywords used by at least one other user to annotate the given item of content; displaying a set of suggested keywords comprising the one or more suggested keywords used by a user to annotate one or more items of content, the one or more suggested keywords based on the subject of the item of content and the one or more suggested keywords used by at least one other user to annotate the given item of content on an editing interface page configured to receive one or more annotations for the given item of content; positioning at least one user keyword higher in the set of suggested keywords than another user keyword if the at least one keyword is used by the user to annotate the one or more items of content a larger number of times than the another user keyword; receiving a request via the editing interface page to annotate the given item of content with at least one keyword from the set of suggested keywords; and associating the at least one keyword with the content. | 1. An annotation method for annotating content comprising: dynamically receiving annotation information from one or more users wherein annotation information includes an annotation rating; determining one or more suggested keywords based on a related annotation rating and used by a user to annotate one or more items of content; performing text recognition on a given item of content to generate recognized text; determining a subject of the given item of content from the recognized text; determining one or more suggested keywords based on the subject of the given item of content; determining one or more suggested keywords used by at least one other user to annotate the given item of content; displaying a set of suggested keywords comprising the one or more suggested keywords used by a user to annotate one or more items of content, the one or more suggested keywords based on the subject of the item of content and the one or more suggested keywords used by at least one other user to annotate the given item of content on an editing interface page configured to receive one or more annotations for the given item of content; positioning at least one user keyword higher in the set of suggested keywords than another user keyword if the at least one keyword is used by the user to annotate the one or more items of content a larger number of times than the another user keyword; receiving a request via the editing interface page to annotate the given item of content with at least one keyword from the set of suggested keywords; and associating the at least one keyword with the content. 5. The method of claim 1 , further comprising retrieving the user keywords from an annotation database. | 0.752404 |
6,070,007 | 34 | 35 | 34. The method of claim 33, further including: when the navigation of the left operand is completed by the user inputting a second indicator, setting a current selection to a selection of the representation of the computational construct and its operands in a tree selection mode so that when the user then inputs a binary operator the computational construct will be replaced by the binary operator. | 34. The method of claim 33, further including: when the navigation of the left operand is completed by the user inputting a second indicator, setting a current selection to a selection of the representation of the computational construct and its operands in a tree selection mode so that when the user then inputs a binary operator the computational construct will be replaced by the binary operator. 35. The method of claim 34 wherein the first indicator is a tab and the second indicator is a shift-tab. | 0.5 |
9,076,039 | 8 | 9 | 8. The method of claim 7 , further comprising calculating a background suppressed signature by subtracting the background expected value signature from the first signature. | 8. The method of claim 7 , further comprising calculating a background suppressed signature by subtracting the background expected value signature from the first signature. 9. The method of claim 8 , wherein determining the cumulative probability further comprises determining a spectral fit between the first spectral signature and each spectral signature of a plurality of spectral signatures from the library, wherein each of the spectral fits corresponds to a correlation coefficient between the background suppressed signature and each of the plurality of spectral signatures. | 0.5 |
8,316,348 | 2 | 3 | 2. The framework of claim 1 , further comprising a JavaScript library that is accessed by the data conglomeration engine. | 2. The framework of claim 1 , further comprising a JavaScript library that is accessed by the data conglomeration engine. 3. The framework of claim 2 , the JavaScript library containing a set of JavaScript objects that represents JavaScript data, and a set of JavaScript functions that is used to format the set of JavaScript objects. | 0.5 |
8,275,772 | 11 | 26 | 11. A system using a model to filter documents according to quality comprising: A) a storage device; B) at least one processor to implement the following steps: C) obtaining from the storage device a first set of documents labeled according to content quality; D) extracting and representing features from the first set of documents; E) modifying the extracted represented features; F) constructing models for labeling documents based on content quality using pattern recognitional algorithms stored in the storage device consisting of the following steps; 1) dividing the first set of documents into N subsets such that the union of all the subsets is the first set of documents; 2) choosing at least one pattern recognition algorithm; a) instantiating a set of parameters for the pattern recognition algorithm; i) processing each of the N subsets comprising the following steps; a′) defining a first subset and defining a second subset mutually exclusive of the first subset; b′) training the pattern recognition algorithm to build a model using the first subset and the parameter set; c′) applying the model to the second subset of documents to obtain labels and scores for each document; d′) evaluating the labels and scores; e′) storing the evaluation measure, set of parameters, and current pattern recognition algorithm; and b) repeating step 2 a ) until all appropriate sets of parameters for the pattern recognition algorithm have been applied; and 3) repeating step 2) until all pattern recognition algorithms have been applied; 4) aggregating the evaluation measures for the N subsets, the pattern recognition algorithms with the set of parameters; 5) selecting the parameter set and pattern recognition algorithm with an aggregate evaluation measure that meets a selection criteria; 6) applying the parameter set and the pattern recognition algorithm identified from step 5) to the first set of documents to build a final model; and G) obtaining a second set of non-labeled documents related to the first set of documents; H) using the final model to label and score the second set of documents according to content quality; and I) displaying the label and/or score of at least one of the previously unlabeled documents. | 11. A system using a model to filter documents according to quality comprising: A) a storage device; B) at least one processor to implement the following steps: C) obtaining from the storage device a first set of documents labeled according to content quality; D) extracting and representing features from the first set of documents; E) modifying the extracted represented features; F) constructing models for labeling documents based on content quality using pattern recognitional algorithms stored in the storage device consisting of the following steps; 1) dividing the first set of documents into N subsets such that the union of all the subsets is the first set of documents; 2) choosing at least one pattern recognition algorithm; a) instantiating a set of parameters for the pattern recognition algorithm; i) processing each of the N subsets comprising the following steps; a′) defining a first subset and defining a second subset mutually exclusive of the first subset; b′) training the pattern recognition algorithm to build a model using the first subset and the parameter set; c′) applying the model to the second subset of documents to obtain labels and scores for each document; d′) evaluating the labels and scores; e′) storing the evaluation measure, set of parameters, and current pattern recognition algorithm; and b) repeating step 2 a ) until all appropriate sets of parameters for the pattern recognition algorithm have been applied; and 3) repeating step 2) until all pattern recognition algorithms have been applied; 4) aggregating the evaluation measures for the N subsets, the pattern recognition algorithms with the set of parameters; 5) selecting the parameter set and pattern recognition algorithm with an aggregate evaluation measure that meets a selection criteria; 6) applying the parameter set and the pattern recognition algorithm identified from step 5) to the first set of documents to build a final model; and G) obtaining a second set of non-labeled documents related to the first set of documents; H) using the final model to label and score the second set of documents according to content quality; and I) displaying the label and/or score of at least one of the previously unlabeled documents. 26. A process according to claim 11 in step (F)(2)(a)(i)(d′) wherein the evaluation measure may include a plurality of methods that summarize how well the assigned label matches the true label of a document or how well an assigned scores ranks the document in content quality. | 0.514085 |
7,672,951 | 7 | 8 | 7. The navigation system according to claim 6 wherein the processor is configured to operate different ones of the intra-document classifiers for different ones of the facets and to automatically identify portions less than all of the documents associated with the text representing the facets. | 7. The navigation system according to claim 6 wherein the processor is configured to operate different ones of the intra-document classifiers for different ones of the facets and to automatically identify portions less than all of the documents associated with the text representing the facets. 8. The navigation system according to claim 7 wherein the processor is further configured to use different intra-document classification gradations for identifying different granularities of document portions associated with the facets. | 0.5 |
8,892,549 | 6 | 7 | 6. The method of claim 1 , where determining the topic score for the topic with respect to the document includes determining the topic score based on features of occurrence of the topic in the document. | 6. The method of claim 1 , where determining the topic score for the topic with respect to the document includes determining the topic score based on features of occurrence of the topic in the document. 7. The method of claim 6 , where features of an occurrence include one or more of: a location within the document of the occurrence; and typographical properties of the occurrence. | 0.5 |
9,280,587 | 1 | 2 | 1. A non-transitory computer-readable storage medium storing instructions executable by a computer to perform a retrieval method on a database of documents including text and names of participants associated with the documents by operations including: receiving a multi-faceted retrieval query having a text query facet comprising one or more keywords and a persons query facet comprising one or more participant names; computing an enriched text query as an aggregation of the text query facet, a monomodal expansion of the text query facet based on the one or more keywords, a cross-modal expansion of the text query facet based on the one or more participant names, and a topic expansion of the text query facet based on a topic model associating words and topics; computing an enriched persons query as an aggregation of the persons query facet, a mono-modal expansion of the persons query facet based on the one or more participant names, a cross-modal expansion of the persons query facet based on the one or more keywords, and a community expansion of the persons query facet based on a community model associating persons and communities; and performing ranking including at least one of: (1) generating a ranking of documents by sorting similarities between the enriched text query and documents of the database, and (2) generating a ranking of persons by sorting the enriched persons query; and wherein at least one of: (I) the cross-modal expansion of the text query facet is proportional to X w T X u u q where u q is a vector representing the persons query facet, X w is a term-document matrix associating words with documents of the database and X u is a participant-document matrix associating participants with documents of the database; and (II) the cross-modal expansion of the persons query facet is proportional to X u T X w w q where w q is a vector representing the text query facet, X w is a term-document matrix associating words with documents of the database and X u is a participant-document matrix associating participants with documents of the database; and displaying the ranking of the documents or person query. | 1. A non-transitory computer-readable storage medium storing instructions executable by a computer to perform a retrieval method on a database of documents including text and names of participants associated with the documents by operations including: receiving a multi-faceted retrieval query having a text query facet comprising one or more keywords and a persons query facet comprising one or more participant names; computing an enriched text query as an aggregation of the text query facet, a monomodal expansion of the text query facet based on the one or more keywords, a cross-modal expansion of the text query facet based on the one or more participant names, and a topic expansion of the text query facet based on a topic model associating words and topics; computing an enriched persons query as an aggregation of the persons query facet, a mono-modal expansion of the persons query facet based on the one or more participant names, a cross-modal expansion of the persons query facet based on the one or more keywords, and a community expansion of the persons query facet based on a community model associating persons and communities; and performing ranking including at least one of: (1) generating a ranking of documents by sorting similarities between the enriched text query and documents of the database, and (2) generating a ranking of persons by sorting the enriched persons query; and wherein at least one of: (I) the cross-modal expansion of the text query facet is proportional to X w T X u u q where u q is a vector representing the persons query facet, X w is a term-document matrix associating words with documents of the database and X u is a participant-document matrix associating participants with documents of the database; and (II) the cross-modal expansion of the persons query facet is proportional to X u T X w w q where w q is a vector representing the text query facet, X w is a term-document matrix associating words with documents of the database and X u is a participant-document matrix associating participants with documents of the database; and displaying the ranking of the documents or person query. 2. The non-transitory computer-readable storage medium of claim 1 , wherein the cross-modal expansion of the text query facet comprises text of person profiles of the named participants. | 0.818359 |
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