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7,613,676 | 8 | 9 | 8. An article of manufacture for generating a normalized database model from natural language expressions of business rules comprising: a machine-accessible storage medium including data that, when accessed by a machine, cause the machine to perform the operations of claim 1 . | 8. An article of manufacture for generating a normalized database model from natural language expressions of business rules comprising: a machine-accessible storage medium including data that, when accessed by a machine, cause the machine to perform the operations of claim 1 . 9. The article of manufacture of claim 8 wherein the data further comprise data that, when accessed by the machine, cause the machine to perform operations comprising: for each business rule, determining whether the business rule imposes a limit that a role of a fact type has a maximum cardinality of one; and if the business rule imposes such limit, adding the role of a fact type that has a maximum cardinality of one to a third list of single-valued roles. | 0.936657 |
8,712,979 | 17 | 19 | 17. A configuration management database system, comprising: a configuration management database server; a configuration management database, coupled to the configuration management database server; a reconciliation engine, coupled to the configuration management database server, and configured to match a plurality of configuration items provided to the configuration management database system from a plurality of source datasets with configuration items contained in the configuration management database using identification rules, the identification rules being without automatically modifiable acceptance criteria; and a statistical rules engine, coupled to the configuration management database server and configured to apply a statistical rule to match a first configuration item of the plurality of configuration items with a second configuration item contained in the configuration management database, the matching being successful when a threshold value for the statistical rule exceeds a default acceptance value after the rule has been successfully applied, the threshold value being automatically modified responsive to application outcomes of the rule, the application of the rule occurring when the first configuration item was not matched with any configuration items contained in the configuration management database using the identification rules. | 17. A configuration management database system, comprising: a configuration management database server; a configuration management database, coupled to the configuration management database server; a reconciliation engine, coupled to the configuration management database server, and configured to match a plurality of configuration items provided to the configuration management database system from a plurality of source datasets with configuration items contained in the configuration management database using identification rules, the identification rules being without automatically modifiable acceptance criteria; and a statistical rules engine, coupled to the configuration management database server and configured to apply a statistical rule to match a first configuration item of the plurality of configuration items with a second configuration item contained in the configuration management database, the matching being successful when a threshold value for the statistical rule exceeds a default acceptance value after the rule has been successfully applied, the threshold value being automatically modified responsive to application outcomes of the rule, the application of the rule occurring when the first configuration item was not matched with any configuration items contained in the configuration management database using the identification rules. 19. The system of claim 17 , wherein the reconciliation engine is configured to mark configuration items of the plurality of configuration items for statistical identification or manual identification when the configuration items are not matched with any configuration items in the configuration management database using the identification rules, and wherein the first configuration item is marked for statistical identification. | 0.50116 |
9,465,850 | 10 | 15 | 10. A reporting server comprising: a memory in communication with a processor; wherein the processor is operable to: normalize a variable of a first query running on a first database, wherein the first query is included in a query list in a second database, wherein in normalizing the first query the processor is further operable to determine that a field of the first query includes a first value, and replace the first value with a variable; analyze the second database to find a second query in the query list, wherein the second query is found based upon the normalized first query; report the second query to a user, wherein the reporting is based upon the analyzing of the second database to find the second query; determine a first loading on a first database based upon a first frequency of occurrence of the second query and upon a first duration of the second query; analyze the second database to find a third query in the query list; and report the third query to the user, wherein the reporting is based upon the analyzing of the second database to find the third query. | 10. A reporting server comprising: a memory in communication with a processor; wherein the processor is operable to: normalize a variable of a first query running on a first database, wherein the first query is included in a query list in a second database, wherein in normalizing the first query the processor is further operable to determine that a field of the first query includes a first value, and replace the first value with a variable; analyze the second database to find a second query in the query list, wherein the second query is found based upon the normalized first query; report the second query to a user, wherein the reporting is based upon the analyzing of the second database to find the second query; determine a first loading on a first database based upon a first frequency of occurrence of the second query and upon a first duration of the second query; analyze the second database to find a third query in the query list; and report the third query to the user, wherein the reporting is based upon the analyzing of the second database to find the third query. 15. The reporting server of claim 10 , wherein a monitoring server includes a first database management system that is associated with the first database. | 0.77551 |
8,185,427 | 3 | 4 | 3. The method of claim 2 , wherein in the language structure one or more terms modify one another. | 3. The method of claim 2 , wherein in the language structure one or more terms modify one another. 4. The method of claim 3 , wherein a modifying term reduces the scope of another term. | 0.967742 |
8,620,990 | 20 | 21 | 20. A computer program product for parsing contents of an e-Form, the contents of said e-Form having been divided into more than one section with a different content identification code assigned to each said section of said e-Form, the computer program product comprising: a computer readable storage memory having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to scan an e-Form submitted for processing to determine, based on said content identification codes, which of said sections have a corresponding parsed result already in a cache system; computer readable program code configured to parse contents of said sections without a parsed result already in said cache system; computer readable program code configured to combine parsed results from said cache system with parsed results from said parsing of sections without a parsed result already in said cache system; and computer readable program code configured to generate a content identification code for any section of said e-Form that does not have an associated content identification code, where the content identification code is generated based on contents of the section found not to already have an associated content identification code. | 20. A computer program product for parsing contents of an e-Form, the contents of said e-Form having been divided into more than one section with a different content identification code assigned to each said section of said e-Form, the computer program product comprising: a computer readable storage memory having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to scan an e-Form submitted for processing to determine, based on said content identification codes, which of said sections have a corresponding parsed result already in a cache system; computer readable program code configured to parse contents of said sections without a parsed result already in said cache system; computer readable program code configured to combine parsed results from said cache system with parsed results from said parsing of sections without a parsed result already in said cache system; and computer readable program code configured to generate a content identification code for any section of said e-Form that does not have an associated content identification code, where the content identification code is generated based on contents of the section found not to already have an associated content identification code. 21. The computer program product of claim 20 , further comprising computer readable program code configured to update the cache system with said parsed results from parsing sections without a parsed result already in said cache system. | 0.502119 |
8,015,141 | 15 | 20 | 15. A system comprising: one or more processors; one or more memory units coupled to at least one of the one or more processors; and instructions comprised in at least one of the one or more memory units, the instructions, when executed at least in part by at least one of the one or more processors, configured to perform a method of programming an entity in an environment with a rule set: respective rules grouped according to at least one rule group having a rule group name; at least one group designated as a start rule group for the entity; the entity configured to accept input from an entity controller; at least one rule specified according to a rule-based programming language comprising: at least one language condition, comprising: at least one entity controller input condition; and at least one environment test comprising: a sensory condition comprising at least one of: an entity type condition; an entity status condition; an entity possessory condition; an entity sensory input condition; and an environment status condition; a language verb parameter representing a sensory object; and at least zero language adjectives representing the sensory object; at least one language verb, comprising at least one rule group transition verb; at least one language verb parameter, comprising: names associated with the respective rules; and a sensory object reference representing the sensory object of the language condition of the at least one rule; at least one language adjective; and at least one Boolean logic connector; the at least one rule comprising a rule priority, at least one language condition representing an action condition, at least one language verb representing an action, and at least one language verb parameter representing an action object; the entity comprising a rule group identifier; and the method comprising: receiving the rule set comprising the at least one rule; and programming the entity to: upon initialization of the entity, set the rule group identifier to one of the start rule groups; and for a rule cycle, to: evaluate one or more action conditions of respective rules of the one of the start rule groups identified by the rule group identifier and in descending priority order, within the environment to identify a satisfied rule having satisfied action conditions according to Boolean logic connectors of the satisfied rule; upon identifying a first satisfied rule, perform the first satisfied rule within the environment; and upon failing to identify a second satisfied rule, remain idle for the rule cycle. | 15. A system comprising: one or more processors; one or more memory units coupled to at least one of the one or more processors; and instructions comprised in at least one of the one or more memory units, the instructions, when executed at least in part by at least one of the one or more processors, configured to perform a method of programming an entity in an environment with a rule set: respective rules grouped according to at least one rule group having a rule group name; at least one group designated as a start rule group for the entity; the entity configured to accept input from an entity controller; at least one rule specified according to a rule-based programming language comprising: at least one language condition, comprising: at least one entity controller input condition; and at least one environment test comprising: a sensory condition comprising at least one of: an entity type condition; an entity status condition; an entity possessory condition; an entity sensory input condition; and an environment status condition; a language verb parameter representing a sensory object; and at least zero language adjectives representing the sensory object; at least one language verb, comprising at least one rule group transition verb; at least one language verb parameter, comprising: names associated with the respective rules; and a sensory object reference representing the sensory object of the language condition of the at least one rule; at least one language adjective; and at least one Boolean logic connector; the at least one rule comprising a rule priority, at least one language condition representing an action condition, at least one language verb representing an action, and at least one language verb parameter representing an action object; the entity comprising a rule group identifier; and the method comprising: receiving the rule set comprising the at least one rule; and programming the entity to: upon initialization of the entity, set the rule group identifier to one of the start rule groups; and for a rule cycle, to: evaluate one or more action conditions of respective rules of the one of the start rule groups identified by the rule group identifier and in descending priority order, within the environment to identify a satisfied rule having satisfied action conditions according to Boolean logic connectors of the satisfied rule; upon identifying a first satisfied rule, perform the first satisfied rule within the environment; and upon failing to identify a second satisfied rule, remain idle for the rule cycle. 20. The system of claim 15 , at least one language verb parameter of the rule-based programming language presented to a user comprising one or more language verb parameters that are grammatically compatible with a selected language verb. | 0.598305 |
9,396,412 | 1 | 2 | 1. A method for person re-identification, the method comprising: mapping color values separately for different regions from first and second images to first and second probability distributions over a plurality of colors, the plurality of colors in a first color space different than a second color space of the color values; calculating separately, with a processor, for the different regions a similarity score between the first and second probability distributions; determining an affinity score as a function of the similarity scores from the different regions, and different weights applied to different similarity scores, the weight being a rank-boosted machine-learnt value; and identifying a person in the second image as a person in the first image, the identifying being a function of the affinity scores. | 1. A method for person re-identification, the method comprising: mapping color values separately for different regions from first and second images to first and second probability distributions over a plurality of colors, the plurality of colors in a first color space different than a second color space of the color values; calculating separately, with a processor, for the different regions a similarity score between the first and second probability distributions; determining an affinity score as a function of the similarity scores from the different regions, and different weights applied to different similarity scores, the weight being a rank-boosted machine-learnt value; and identifying a person in the second image as a person in the first image, the identifying being a function of the affinity scores. 2. The method of claim 1 wherein the second color space comprises Red, Green, Blue (RGB) color space, wherein the first color space comprises color terms non subsumable into each other, and wherein mapping comprises mapping from RGB values to probabilities across the color terms. | 0.753086 |
10,147,038 | 21 | 22 | 21. The method of claim 20 , wherein the step of updating the project results data includes updating the results based on usage of the application. | 21. The method of claim 20 , wherein the step of updating the project results data includes updating the results based on usage of the application. 22. The method of claim 21 , further comprising updating the trained model based on the updated project results data. | 0.939378 |
8,825,570 | 8 | 13 | 8. A non-transitory computer readable medium encoded with executable instructions for execution by a processor to: receive a pool of unlabeled cases; receive per-case symmetrical importance scores, each unlabeled case having an associated per-case symmetrical importance score; apply a selection algorithm with a classifier to a training set and the pool, without the per-case symmetrical importance scores, to determine selection scores, each unlabeled case having an associated selection score; combine the selection scores and the corresponding per-case symmetrical importance scores to form combined scores, each unlabeled case having an associated combined score; provide a high scoring unlabeled case to an oracle to label; receive a labeled case back from the oracle and augment the training set with the labeled case; train the classifier with the augmented training set; and apply the classifier to an additional unlabeled case. | 8. A non-transitory computer readable medium encoded with executable instructions for execution by a processor to: receive a pool of unlabeled cases; receive per-case symmetrical importance scores, each unlabeled case having an associated per-case symmetrical importance score; apply a selection algorithm with a classifier to a training set and the pool, without the per-case symmetrical importance scores, to determine selection scores, each unlabeled case having an associated selection score; combine the selection scores and the corresponding per-case symmetrical importance scores to form combined scores, each unlabeled case having an associated combined score; provide a high scoring unlabeled case to an oracle to label; receive a labeled case back from the oracle and augment the training set with the labeled case; train the classifier with the augmented training set; and apply the classifier to an additional unlabeled case. 13. The medium of claim 8 , wherein a combined score comprises: taking as is, taking a square root, taking a logarithm, adding a constant, or applying thresholding to a per-case symmetrical importance score; taking as is, transforming, subtracting from a constant, inverting, adding a constant, or applying thresholding to an selection score; and multiplying the per-case symmetrical importance score and the selection score, adding the per-case symmetrical importance score and the selection score, raising the per-case symmetrical importance score to an exponent of the selection score, or raising the selection score to an exponent of the per-case symmetrical importance score. | 0.500734 |
7,873,643 | 13 | 14 | 13. A computer implemented method of predicting comprising the steps of: receiving a group of classification structures; receiving an instance with an at least one attribute to predict; querying each member of a subset of the group of classification structures to perform a prediction process on the instance, wherein the prediction process is based at least in part on a relevance factor associated with the attribute; and returning a coalesced prediction profile. | 13. A computer implemented method of predicting comprising the steps of: receiving a group of classification structures; receiving an instance with an at least one attribute to predict; querying each member of a subset of the group of classification structures to perform a prediction process on the instance, wherein the prediction process is based at least in part on a relevance factor associated with the attribute; and returning a coalesced prediction profile. 14. The computer implemented method of claim 13 , wherein the coalesced prediction profile comprises an Ameliorate prediction profile. | 0.948062 |
8,244,534 | 4 | 5 | 4. A method for generating speech based on text, implemented at least in part by a computer, the method comprising: building a first language specific decision tree; building a second language specific decision tree; mapping a leaf node from the first tree to a leaf node of the second tree using a Kullback-Leibler divergence (KLD) technique based on a spectral feature located in a subset of less than all of a frequency range for measuring the KLD between two hidden Markov models (HMMs); receiving text in the second language; and generating speech in the second language, for the received text, based at least in part on the mapping the leaf node from the first tree to the leaf node of the second tree. | 4. A method for generating speech based on text, implemented at least in part by a computer, the method comprising: building a first language specific decision tree; building a second language specific decision tree; mapping a leaf node from the first tree to a leaf node of the second tree using a Kullback-Leibler divergence (KLD) technique based on a spectral feature located in a subset of less than all of a frequency range for measuring the KLD between two hidden Markov models (HMMs); receiving text in the second language; and generating speech in the second language, for the received text, based at least in part on the mapping the leaf node from the first tree to the leaf node of the second tree. 5. The method of claim 4 further comprising mapping a leaf node from the second tree to a leaf node of the first tree. | 0.868009 |
8,996,473 | 1 | 8 | 1. A computer-implemented method for evaluating a validity of an extended status and action management (SAM) schema, the method being executed using one or more processors and comprising: receiving, by the one or more processors, the extended SAM schema, the extended SAM schema being stored as a computer-readable document in memory and being an extension of a core SAM schema; providing, by the one or more processors, one or more goals, each goal representing an intention of the core SAM schema, the one or more goals being provided in a computer-readable document stored in memory and comprising one or more primary goals and one or more recovery goals that each express an intention of a process underlying the core SAM schema, each primary goal being an end goal that is preserved in the extended SAM schema and each recovery goal being an acceptable intermediate goal that is replaceable in the extended SAM schema; providing an extended finite state machine (FSM) based on the extended SAM schema, the extended FSM representing states of the extended SAM schema and transitions between states, the extended FSM being provided as a computer-readable document and being stored in memory, wherein processing further comprises processing the extended FSM; and processing, by the one or more processors, the one or more goals using a computer-executable model checking tool for evaluating the validity of the extended SAM schema, wherein the extended SAM schema is determined to be valid, if at least one of the one or more primary goals or at least one of the one or more recovery goals is achieved for each of the core SAM schema and the extended SAM schema. | 1. A computer-implemented method for evaluating a validity of an extended status and action management (SAM) schema, the method being executed using one or more processors and comprising: receiving, by the one or more processors, the extended SAM schema, the extended SAM schema being stored as a computer-readable document in memory and being an extension of a core SAM schema; providing, by the one or more processors, one or more goals, each goal representing an intention of the core SAM schema, the one or more goals being provided in a computer-readable document stored in memory and comprising one or more primary goals and one or more recovery goals that each express an intention of a process underlying the core SAM schema, each primary goal being an end goal that is preserved in the extended SAM schema and each recovery goal being an acceptable intermediate goal that is replaceable in the extended SAM schema; providing an extended finite state machine (FSM) based on the extended SAM schema, the extended FSM representing states of the extended SAM schema and transitions between states, the extended FSM being provided as a computer-readable document and being stored in memory, wherein processing further comprises processing the extended FSM; and processing, by the one or more processors, the one or more goals using a computer-executable model checking tool for evaluating the validity of the extended SAM schema, wherein the extended SAM schema is determined to be valid, if at least one of the one or more primary goals or at least one of the one or more recovery goals is achieved for each of the core SAM schema and the extended SAM schema. 8. The method of claim 1 , wherein each transition is associated with an action that can be performed to change a status vector. | 0.763838 |
3,975,598 | 3 | 4 | 3. The apparatus according to claim 1 wherein said analog data storage tracks each further include a threshold recording of a signal to represent the end of each analog storage track, said apparatus further comprising threshold detector means responsive to the electrical signal delivered by said means for producing, to reset said digitally addressible control signal means. | 3. The apparatus according to claim 1 wherein said analog data storage tracks each further include a threshold recording of a signal to represent the end of each analog storage track, said apparatus further comprising threshold detector means responsive to the electrical signal delivered by said means for producing, to reset said digitally addressible control signal means. 4. The apparatus according to claim 3 further comprising register means for receiving electrical signals corresponding to different scan rate inflection patterns for said electron beam and decoder means receiving the electrical signals corresponding to different scan rate inflection patterns for biasing the control by said second control means. | 0.891604 |
8,996,406 | 18 | 19 | 18. The computer-readable storage medium of claim 17 , wherein the search terms are included in an indexed list of key words. | 18. The computer-readable storage medium of claim 17 , wherein the search terms are included in an indexed list of key words. 19. The computer-readable storage medium of claim 18 , wherein the instructions are further executable to receive an updated indexed list of key words. | 0.943657 |
9,317,551 | 1 | 4 | 1. A method comprising: receiving information associated with a plurality of technical computing environment (TCE) models, the receiving the information being performed by a device; executing the plurality of TCE models to generate execution information associated with the plurality of TCE models, the executing the plurality of TCE models being performed by the device; storing the plurality of TCE models and the execution information for association with a TCE-based search engine, the storing the plurality of TCE models being performed by the device; providing, for display, a user interface associated with the TCE-based search engine, the providing, for display, the user interface being performed by the device; receiving a query via the user interface, the receiving the query being performed by the device; dividing the query into one or more query elements, the dividing the query being performed by the device; identifying a group of query elements of the one or more query elements, the identifying being performed by the device; processing the group of the query elements based on at least one of query content or information requested by the query, the processing the group of the query elements being performed by the device; transforming the query into another query based on the processed group of the query elements, the other query being different than the query, and the transforming the query being performed by the device; determining a respective input type for each processed query element of the processed group of the query elements, each respective input type corresponding to a respective TCE model of the plurality of TCE models, and the determining the respective input type being performed by the device; selecting at least one TCE model, of the plurality of TCE models, based on the determined respective input type, the selecting the at least one TCE model being performed by the device; and providing the other query to the selected at least one TCE model for further processing, the providing the other query being performed by the device. | 1. A method comprising: receiving information associated with a plurality of technical computing environment (TCE) models, the receiving the information being performed by a device; executing the plurality of TCE models to generate execution information associated with the plurality of TCE models, the executing the plurality of TCE models being performed by the device; storing the plurality of TCE models and the execution information for association with a TCE-based search engine, the storing the plurality of TCE models being performed by the device; providing, for display, a user interface associated with the TCE-based search engine, the providing, for display, the user interface being performed by the device; receiving a query via the user interface, the receiving the query being performed by the device; dividing the query into one or more query elements, the dividing the query being performed by the device; identifying a group of query elements of the one or more query elements, the identifying being performed by the device; processing the group of the query elements based on at least one of query content or information requested by the query, the processing the group of the query elements being performed by the device; transforming the query into another query based on the processed group of the query elements, the other query being different than the query, and the transforming the query being performed by the device; determining a respective input type for each processed query element of the processed group of the query elements, each respective input type corresponding to a respective TCE model of the plurality of TCE models, and the determining the respective input type being performed by the device; selecting at least one TCE model, of the plurality of TCE models, based on the determined respective input type, the selecting the at least one TCE model being performed by the device; and providing the other query to the selected at least one TCE model for further processing, the providing the other query being performed by the device. 4. The method of claim 1 , further comprising: executing the selected at least one TCE model to generate an execution result. | 0.763258 |
9,946,794 | 28 | 29 | 28. The system of claim 27 , wherein the recommendation device is configured to: in response to one of (i) the first module score being less than the first minimum threshold score, and (ii) the third module score being less than a third minimum threshold score, send a negative recommendation to the remote general purpose search system, wherein the negative recommendation includes an instruction to not obtain application search results from the special purpose search system. | 28. The system of claim 27 , wherein the recommendation device is configured to: in response to one of (i) the first module score being less than the first minimum threshold score, and (ii) the third module score being less than a third minimum threshold score, send a negative recommendation to the remote general purpose search system, wherein the negative recommendation includes an instruction to not obtain application search results from the special purpose search system. 29. The system of claim 28 , wherein: the negative recommendation comprises an integer value of zero; and the positive recommendation comprises an integer value of one. | 0.978495 |
9,563,646 | 15 | 17 | 15. A computer-implemented system, comprising: an input device enabled to generate an idea-image association that associates an image with an idea based on data that indicates user interaction with the image in a presentation of search results that correspond to a first search query, wherein the idea is determined to be related to the first search query; a database enabled to store the idea-image association and other idea-image associations; and a processor enabled to provide the image for display in a presentation of search results that correspond to a different, second search query, wherein the processor is enabled to select the image for display in the presentation of search results that correspond to the second search query based on (i) determining that the second search query relates to the idea and (ii) identifying from the stored idea-image association that a match exists between the idea that the second search query relates to and the idea to which the image is associated. | 15. A computer-implemented system, comprising: an input device enabled to generate an idea-image association that associates an image with an idea based on data that indicates user interaction with the image in a presentation of search results that correspond to a first search query, wherein the idea is determined to be related to the first search query; a database enabled to store the idea-image association and other idea-image associations; and a processor enabled to provide the image for display in a presentation of search results that correspond to a different, second search query, wherein the processor is enabled to select the image for display in the presentation of search results that correspond to the second search query based on (i) determining that the second search query relates to the idea and (ii) identifying from the stored idea-image association that a match exists between the idea that the second search query relates to and the idea to which the image is associated. 17. The system of claim 15 , wherein the system is further enabled to provide the image in the presentation of search results based at least on a determined relevance of a textual description of the image to the first search query. | 0.853053 |
9,401,140 | 16 | 23 | 16. A system comprising: an electronic data store configured to store a plurality of acoustic models; and one or more computer processors implemented in hardware and in communication with the electronic data store, the one or more computer processors configured to at least: receive a first signal comprising first speech; generate first speech recognition results using the first signal and an acoustic model of the plurality of acoustic models, wherein the first speech recognition results comprise a textual transcription of the first speech; and subsequent to generating the first speech recognition results: determine a first confidence value associated with the first speech recognition results; generate a first updated acoustic model based at least in part on the first confidence value associated with the first speech recognition results; generate second speech recognition results using a second signal and the first updated acoustic model, wherein the second speech recognition results comprise a textual transcription of second speech in the second signal; determine a second confidence value associated with the second speech recognition results; determine that the first speech recognition results were generated outside a window; and generate a second updated acoustic model based at least in part on the second confidence value. | 16. A system comprising: an electronic data store configured to store a plurality of acoustic models; and one or more computer processors implemented in hardware and in communication with the electronic data store, the one or more computer processors configured to at least: receive a first signal comprising first speech; generate first speech recognition results using the first signal and an acoustic model of the plurality of acoustic models, wherein the first speech recognition results comprise a textual transcription of the first speech; and subsequent to generating the first speech recognition results: determine a first confidence value associated with the first speech recognition results; generate a first updated acoustic model based at least in part on the first confidence value associated with the first speech recognition results; generate second speech recognition results using a second signal and the first updated acoustic model, wherein the second speech recognition results comprise a textual transcription of second speech in the second signal; determine a second confidence value associated with the second speech recognition results; determine that the first speech recognition results were generated outside a window; and generate a second updated acoustic model based at least in part on the second confidence value. 23. The system of claim 16 , wherein the one or more computer processors are further configured to determine that the first signal comprises the first speech by applying a classification algorithm. | 0.8186 |
8,442,970 | 13 | 14 | 13. A computer-implemented method for constructing a search query, comprising: constructing a query including a category and one or more facets; selecting a plurality of facet values corresponding to a facet in the constructed query, the plurality of facet values being selected from a pre-defined list; forming test queries comprising the constructed query and the selected plurality of facet values; submitting the formed test queries to a search engine; excluding facet values that correspond to test queries that generate less than a threshold number of matching documents when submitted to the search engine; providing one or more facet values corresponding to the facet, the provided one or more facet values being different from the excluded facet values; and adding a facet value to the constructed query in response to receiving a selection of the facet value from the provided one or more facet values. | 13. A computer-implemented method for constructing a search query, comprising: constructing a query including a category and one or more facets; selecting a plurality of facet values corresponding to a facet in the constructed query, the plurality of facet values being selected from a pre-defined list; forming test queries comprising the constructed query and the selected plurality of facet values; submitting the formed test queries to a search engine; excluding facet values that correspond to test queries that generate less than a threshold number of matching documents when submitted to the search engine; providing one or more facet values corresponding to the facet, the provided one or more facet values being different from the excluded facet values; and adding a facet value to the constructed query in response to receiving a selection of the facet value from the provided one or more facet values. 14. The computer-implemented method of claim 13 , wherein the threshold number of matching documents is one. | 0.928287 |
9,043,195 | 1 | 8 | 1. A system for teaching phonemic awareness, the system comprising: a plurality of phonemes, each phoneme comprising a unique sound and an indivisible unit of sound in a spoken language; a plurality of graphemes, each grapheme comprising a written representation of one of the plurality of phonemes; a plurality of distinct graphical images; a plurality of unique names: each unique name associated with only one of the graphical images; each graphical image associated with only one of the unique names: and each unique name comprising a unique grouping of multiple graphemes selected from the plurality of graphemes; a plurality of sets of display pieces, each set of display pieces comprising: one of the graphical images and the unique name associated with that graphical image; and a plurality of individual display pieces and each individual display piece comprising; at least a portion of the graphical image associated with the set of display pieces; and one or more graphemes from the unique grouping of multiple graphemes constituting the unique name associated with that graphical image; wherein each grapheme and its associated phoneme is separately represented within any given individual display piece; and a predefined instructional environment, the instructional environment comprising a predefined spatial context and predefined rules governing acquisition, dispersement and utilization of individual display pieces within the predefined spatial context. | 1. A system for teaching phonemic awareness, the system comprising: a plurality of phonemes, each phoneme comprising a unique sound and an indivisible unit of sound in a spoken language; a plurality of graphemes, each grapheme comprising a written representation of one of the plurality of phonemes; a plurality of distinct graphical images; a plurality of unique names: each unique name associated with only one of the graphical images; each graphical image associated with only one of the unique names: and each unique name comprising a unique grouping of multiple graphemes selected from the plurality of graphemes; a plurality of sets of display pieces, each set of display pieces comprising: one of the graphical images and the unique name associated with that graphical image; and a plurality of individual display pieces and each individual display piece comprising; at least a portion of the graphical image associated with the set of display pieces; and one or more graphemes from the unique grouping of multiple graphemes constituting the unique name associated with that graphical image; wherein each grapheme and its associated phoneme is separately represented within any given individual display piece; and a predefined instructional environment, the instructional environment comprising a predefined spatial context and predefined rules governing acquisition, dispersement and utilization of individual display pieces within the predefined spatial context. 8. The system of claim 1 , wherein at least one unique name comprises a multisyllabic word. | 0.907332 |
9,818,401 | 7 | 8 | 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. | 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. 8. The method of claim 7 , further comprising: including acoustic prefix words, acoustic suffix words, or both within the adaptation grammar by preparing said adaptation grammar as a slotted grammar with appropriate one or more prefix slots, suffix slots, or both and populating said slots as appropriate with acoustic prefix words, acoustic suffix words, or both, as transcribed by the primary ASR recognizer. | 0.924577 |
7,921,416 | 8 | 14 | 8. One or more computer-readable non-transitory storage media Embodying software operable when executed by one or more computer systems to: accept as input a program written in a formal language, wherein the input program comprises a plurality of operators that enable a declarative co-grouping of one or more tables, each with an alignment function, and a specification of zero or more procedural operations to be performed on each resulting co-group; co-group one or more tables referenced in the program into one or more co-groups according to one or more operators of the formal language used in the program; determine zero or more user-specified operations to be performed on each co-group according to the one or more operators of the formal language used in the program; and translate the program into one or more jobs according to the one or more operators of the formal language used in the program and based on the one or more co-groups and the zero or more operations to be performed on each co-group, wherein each job comprises one or more structured calls to an application programming interface for encoded logic that is operable to generate a plurality of tasks for the parallel processing of the job on one or more data processing devices in a distributed system. | 8. One or more computer-readable non-transitory storage media Embodying software operable when executed by one or more computer systems to: accept as input a program written in a formal language, wherein the input program comprises a plurality of operators that enable a declarative co-grouping of one or more tables, each with an alignment function, and a specification of zero or more procedural operations to be performed on each resulting co-group; co-group one or more tables referenced in the program into one or more co-groups according to one or more operators of the formal language used in the program; determine zero or more user-specified operations to be performed on each co-group according to the one or more operators of the formal language used in the program; and translate the program into one or more jobs according to the one or more operators of the formal language used in the program and based on the one or more co-groups and the zero or more operations to be performed on each co-group, wherein each job comprises one or more structured calls to an application programming interface for encoded logic that is operable to generate a plurality of tasks for the parallel processing of the job on one or more data processing devices in a distributed system. 14. The media of claim 8 , wherein the number of structured calls is minimized through query optimization. | 0.805147 |
8,214,366 | 13 | 17 | 13. A method for enabling natural language communication with a computer, the method comprising: receiving a text expression comprising (n) operands and (n−1) operators; combining sub-concepts in the text expression into higher order sub-concepts, according to precedence defined by the operators, until the higher order sub-concepts join to form a concept that represents the entire text expression, associating each of the concept and sub-concepts with a concept identifier, and storing the concept, sub-concepts, and associated concept identifiers in a database. | 13. A method for enabling natural language communication with a computer, the method comprising: receiving a text expression comprising (n) operands and (n−1) operators; combining sub-concepts in the text expression into higher order sub-concepts, according to precedence defined by the operators, until the higher order sub-concepts join to form a concept that represents the entire text expression, associating each of the concept and sub-concepts with a concept identifier, and storing the concept, sub-concepts, and associated concept identifiers in a database. 17. The method of claim 13 , further comprising constructing a concept identifier from a first letter of each word comprising the associated concept or sub-concept. | 0.929371 |
8,738,600 | 5 | 7 | 5. An article of manufacture comprising: a query to a database that specifies a sequential string search of a computer database record having a beginning position to search for a text string; a query optimizer that optimizes the query by determining a start position other than the beginning position of the computer database record to start the sequential string search wherein the determined starting position is based on a starting position table containing historical information of previous text string searches and the starting position is determined to be a location in the record just prior to where a percentage of records in the starting position table that match the query found the text string in previous searches; wherein the query optimizer updates the starting position table with each query that does a text string search to provide historical information for future searches; and non-transitory computer media bearing the query optimizer. | 5. An article of manufacture comprising: a query to a database that specifies a sequential string search of a computer database record having a beginning position to search for a text string; a query optimizer that optimizes the query by determining a start position other than the beginning position of the computer database record to start the sequential string search wherein the determined starting position is based on a starting position table containing historical information of previous text string searches and the starting position is determined to be a location in the record just prior to where a percentage of records in the starting position table that match the query found the text string in previous searches; wherein the query optimizer updates the starting position table with each query that does a text string search to provide historical information for future searches; and non-transitory computer media bearing the query optimizer. 7. The article of manufacture of claim 5 wherein the query includes a “Like” clause that requires a text string search of the database record. | 0.859961 |
7,565,372 | 5 | 8 | 5. A computer-readable storage medium containing computer executable instructions for controlling a computer system to generate a document summary and evaluate an effectiveness of the generated document summary, by a method comprising: generating a first document model for a document, the first document model is a statistical language model with a probability distribution that reflects a frequency with which n-grams occur in the document, the probability distribution is generated by: counting a number of occurrences of each n-gram within the document, for each (n-1)-gram, determining a number of occurrences of the (n-1)-gram within the document by summing the number of occurrences of each n-gram within the document that begins with the (n-1)-gram, and for each n-gram, dividing the number of occurrences within the document of the n-gram by the number of occurrences within the document of the (n-1)-gram that comprises a first n-1 words of the n-gram, wherein only the document itself serves as basis for generating the first document model; for each of a plurality of selected portions of the document, calculating a score based on normalized probability for the selected portion from the n-grams of words of the selected portion given the first document model, the normalized probability is based on a cross entropy between the selected portion of the document and the document adjusted by a length of the selected portion; selecting one or more portions based on their scores as the summary of the document; generating a second document model for the document and the generated summary that indicates probabilities by which the various n-grams occur in the document and the generated summary; for each portion of the summary, calculating a score based on the probabilities indicated by the second document model; and combining the calculated score of each portion of the summary to generate an overall score for assessing the effectiveness of the summary. | 5. A computer-readable storage medium containing computer executable instructions for controlling a computer system to generate a document summary and evaluate an effectiveness of the generated document summary, by a method comprising: generating a first document model for a document, the first document model is a statistical language model with a probability distribution that reflects a frequency with which n-grams occur in the document, the probability distribution is generated by: counting a number of occurrences of each n-gram within the document, for each (n-1)-gram, determining a number of occurrences of the (n-1)-gram within the document by summing the number of occurrences of each n-gram within the document that begins with the (n-1)-gram, and for each n-gram, dividing the number of occurrences within the document of the n-gram by the number of occurrences within the document of the (n-1)-gram that comprises a first n-1 words of the n-gram, wherein only the document itself serves as basis for generating the first document model; for each of a plurality of selected portions of the document, calculating a score based on normalized probability for the selected portion from the n-grams of words of the selected portion given the first document model, the normalized probability is based on a cross entropy between the selected portion of the document and the document adjusted by a length of the selected portion; selecting one or more portions based on their scores as the summary of the document; generating a second document model for the document and the generated summary that indicates probabilities by which the various n-grams occur in the document and the generated summary; for each portion of the summary, calculating a score based on the probabilities indicated by the second document model; and combining the calculated score of each portion of the summary to generate an overall score for assessing the effectiveness of the summary. 8. The computer-readable storage medium of claim 5 wherein the portions are paragraphs. | 0.771053 |
10,031,970 | 10 | 14 | 10. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for facilitating text inputs with long-tail keywords from a user in a social question and answer (Q&A) application, the method comprising: receiving, at a server, a text input from the user at a client computer, wherein the text input poses a query within a community associated with the social Q&A application, wherein the server comprises a processor and a memory within a community associated with the social Q&A application; applying, by the processor, a predictive model to the received text input; determining, by the processor, a predicted business outcome associated with the received text input based on the applied predictive model, wherein the predicted business outcome comprises an increase in user traffic resulting from an external search engine, referring users of the external search engine to the community, that is predicted to be generated from the received text input based in part on long-tail keywords within the received text input; determining, by the processor, a type of user interface (UI) to be generated for display to the user for subsequent interaction based on the evaluation predicted business outcome, wherein the type of UI facilitates one of: a tailored navigation through one or more answers databases before providing a UI component to post the received text input to the community if the predicted business value is below a certain threshold value, or a direct posting of the received text to the community and receiving a subsequent text input from the user to include in the direct posting of the received text if the predicted business value is above a certain threshold value; and sending the determined type of UI to the client computer for display at the client computer to facilitate subsequent user-interaction with the Q&A application. | 10. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for facilitating text inputs with long-tail keywords from a user in a social question and answer (Q&A) application, the method comprising: receiving, at a server, a text input from the user at a client computer, wherein the text input poses a query within a community associated with the social Q&A application, wherein the server comprises a processor and a memory within a community associated with the social Q&A application; applying, by the processor, a predictive model to the received text input; determining, by the processor, a predicted business outcome associated with the received text input based on the applied predictive model, wherein the predicted business outcome comprises an increase in user traffic resulting from an external search engine, referring users of the external search engine to the community, that is predicted to be generated from the received text input based in part on long-tail keywords within the received text input; determining, by the processor, a type of user interface (UI) to be generated for display to the user for subsequent interaction based on the evaluation predicted business outcome, wherein the type of UI facilitates one of: a tailored navigation through one or more answers databases before providing a UI component to post the received text input to the community if the predicted business value is below a certain threshold value, or a direct posting of the received text to the community and receiving a subsequent text input from the user to include in the direct posting of the received text if the predicted business value is above a certain threshold value; and sending the determined type of UI to the client computer for display at the client computer to facilitate subsequent user-interaction with the Q&A application. 14. The computer-readable storage medium of claim 10 , wherein applying the predictive model involves obtaining model attributes from one or more of: content of the received input; data associated with the user; and data associated with a product. | 0.738347 |
8,069,028 | 13 | 21 | 13. A handheld electronic device, comprising: a keyboard having a plurality of input members, at least some of the input members having assigned thereto a plurality of linguistic elements; a display; a processor apparatus comprising a processor and a memory in electronic communication with the processor, the memory having stored therein a plurality of input method languages and a text disambiguation function structured to employ one of the plurality of the input method languages, the processor apparatus being structured to: input an actuation of one or more of the input members; detect a selection of an input method language; detect as an ambiguous input the actuation of one or more of the input members; output a plurality of language objects that correspond with the ambiguous input to enable one of the plurality of language objects to be selected; output at a location adjacent to the plurality of language objects an indicator specifying one of the plurality of input method languages which is currently employed by the disambiguation function to enable the indicator to be selected in lieu of one of the plurality of language objects; and upon the indicator being selected in lieu of one of the plurality of language objects, enable a selection of one of a plurality of alternate indicators adjacent to the indicator specifying an alternate one of the plurality of input method languages to be selected, wherein the selection of one of the plurality of alternate indicators is enabled while the inputting an actuation of one or more of the input members is ongoing. | 13. A handheld electronic device, comprising: a keyboard having a plurality of input members, at least some of the input members having assigned thereto a plurality of linguistic elements; a display; a processor apparatus comprising a processor and a memory in electronic communication with the processor, the memory having stored therein a plurality of input method languages and a text disambiguation function structured to employ one of the plurality of the input method languages, the processor apparatus being structured to: input an actuation of one or more of the input members; detect a selection of an input method language; detect as an ambiguous input the actuation of one or more of the input members; output a plurality of language objects that correspond with the ambiguous input to enable one of the plurality of language objects to be selected; output at a location adjacent to the plurality of language objects an indicator specifying one of the plurality of input method languages which is currently employed by the disambiguation function to enable the indicator to be selected in lieu of one of the plurality of language objects; and upon the indicator being selected in lieu of one of the plurality of language objects, enable a selection of one of a plurality of alternate indicators adjacent to the indicator specifying an alternate one of the plurality of input method languages to be selected, wherein the selection of one of the plurality of alternate indicators is enabled while the inputting an actuation of one or more of the input members is ongoing. 21. The handheld electronic device of claim 13 , wherein the processor is further structured to enabling the selection of the indicator by enabling scrolling through the plurality of language objects to reach the indicator. | 0.707349 |
7,720,720 | 1 | 20 | 1. A computer-based method of generating recommendations for potential purchase by a customer, comprising: generating association rules from a transaction history data set; receiving a recommendation context from a customer; using the recommendation context at a computer system to identify a plurality of candidate recommendation rules from the association rules that match the recommendation context, where each candidate recommendation rule recommends at least one recommended item; determining a score for each candidate recommendation rule using a margin value factor for the recommended item, a confidence value factor for the candidate recommendation rule and a predetermined scoring criteria factor; ranking the plurality of candidate recommendation rules using the score for each candidate recommendation rule to identify at least a highest ranking candidate recommendation rule; and issuing at least the highest ranking candidate recommendation rule as a recommendation. | 1. A computer-based method of generating recommendations for potential purchase by a customer, comprising: generating association rules from a transaction history data set; receiving a recommendation context from a customer; using the recommendation context at a computer system to identify a plurality of candidate recommendation rules from the association rules that match the recommendation context, where each candidate recommendation rule recommends at least one recommended item; determining a score for each candidate recommendation rule using a margin value factor for the recommended item, a confidence value factor for the candidate recommendation rule and a predetermined scoring criteria factor; ranking the plurality of candidate recommendation rules using the score for each candidate recommendation rule to identify at least a highest ranking candidate recommendation rule; and issuing at least the highest ranking candidate recommendation rule as a recommendation. 20. The method of claim 1 , wherein the predetermined scoring criteria is a profile estimate or a message strength value for a selling message associated with the candidate recommendation rule. | 0.728933 |
7,917,455 | 16 | 17 | 16. The method as recited in claim 14 , wherein a subset of the logical expressions that are true is determined with computational effort proportional to a number of times the primitives are evaluated. | 16. The method as recited in claim 14 , wherein a subset of the logical expressions that are true is determined with computational effort proportional to a number of times the primitives are evaluated. 17. The method as recited in claim 16 , wherein the subset of the true logical expressions is determined in real time. | 0.960323 |
7,860,716 | 1 | 11 | 1. A computer-implemented error checking system, comprising: a duration component for computing word duration probability data based on a speech model, and a corpus of transcription data and wave data; a confidence component for computing a confidence score based on recognition processing of the speech model and wave data, and alignment output of the transcription data and the wave data; an error component for detecting error based on the duration probability data and the confidence score; and a training component for retraining the speech model based on removal of the error from the corpus. | 1. A computer-implemented error checking system, comprising: a duration component for computing word duration probability data based on a speech model, and a corpus of transcription data and wave data; a confidence component for computing a confidence score based on recognition processing of the speech model and wave data, and alignment output of the transcription data and the wave data; an error component for detecting error based on the duration probability data and the confidence score; and a training component for retraining the speech model based on removal of the error from the corpus. 11. The system of claim 1 , further comprising a threshold component for detecting transcription error based on the confidence score relative to a threshold value. | 0.681641 |
7,836,391 | 27 | 29 | 27. A system comprising: one or more devices comprising: means for identifying links to a plurality of documents related to a search query, each of the documents having an associated relevance score; means for ranking the identified links; means for calculating whether the relevance score associated with a particular one of the plurality of documents differs from the relevance scores associated with all the other ones of the plurality of documents by at least a first threshold value; means for calculating whether a click through rate associated with the particular one of the plurality of documents differs from the click through rates associated with all the other ones of the plurality of documents by at least a second threshold value; means for associating, with a link associated with the particular one of the plurality of documents, a graphic rendering corresponding to the particular one of the plurality of documents when the relevance score associated with the particular one of the plurality of documents differs from the relevance scores associated with all the other ones of the plurality of documents by at least the first threshold value and when the click through rate associated with the particular one of the plurality of documents differs from the click through rates of all the other ones of the plurality of documents by at least the second threshold value; and means for providing the identified links for display, where the associated graphic rendering is provided visually together with the link associated with the particular one of the plurality of documents. | 27. A system comprising: one or more devices comprising: means for identifying links to a plurality of documents related to a search query, each of the documents having an associated relevance score; means for ranking the identified links; means for calculating whether the relevance score associated with a particular one of the plurality of documents differs from the relevance scores associated with all the other ones of the plurality of documents by at least a first threshold value; means for calculating whether a click through rate associated with the particular one of the plurality of documents differs from the click through rates associated with all the other ones of the plurality of documents by at least a second threshold value; means for associating, with a link associated with the particular one of the plurality of documents, a graphic rendering corresponding to the particular one of the plurality of documents when the relevance score associated with the particular one of the plurality of documents differs from the relevance scores associated with all the other ones of the plurality of documents by at least the first threshold value and when the click through rate associated with the particular one of the plurality of documents differs from the click through rates of all the other ones of the plurality of documents by at least the second threshold value; and means for providing the identified links for display, where the associated graphic rendering is provided visually together with the link associated with the particular one of the plurality of documents. 29. The device of claim 27 , where the graphic rendering is representative of contents of the particular document. | 0.871041 |
8,214,354 | 29 | 31 | 29. Apparatus for enforcing a referential integrity constraint between a constraint set and a constrained object in a relational database management system, the constraint set and the constrained object having values that are terms of an ontology, the relational database management system being implemented in a workstation having a processor and a storage device to which the processor has access, and the apparatus comprising: the storage device having an association between the constrained object and an ontology query, wherein the ontology query returns a set of terms of the ontology, the returned terms being the constraint set to be used to define the referential integrity constraint, wherein different constraint sets having different sets of terms can be derived by querying the same ontology, the constrained object comprising a constrained column that is defined in the relational database management system; the set of terms associated with the constrained object is a term object with a column, values in the column being the set of terms; and a referential integrity constraint for the constrained column which references the column in the term object; and the processor for executing a constraint enforcer in the relational database management system which, when an operation in the relational database management system adds a value to the constrained object, permits the operation only if the added value is a value belonging to the constraint set, and when a modification is performed on the ontology in the relational database management system that results in a different set of terms being returned by the ontology query, altering one or more values in the constrained object that are not contained in the different set of terms. | 29. Apparatus for enforcing a referential integrity constraint between a constraint set and a constrained object in a relational database management system, the constraint set and the constrained object having values that are terms of an ontology, the relational database management system being implemented in a workstation having a processor and a storage device to which the processor has access, and the apparatus comprising: the storage device having an association between the constrained object and an ontology query, wherein the ontology query returns a set of terms of the ontology, the returned terms being the constraint set to be used to define the referential integrity constraint, wherein different constraint sets having different sets of terms can be derived by querying the same ontology, the constrained object comprising a constrained column that is defined in the relational database management system; the set of terms associated with the constrained object is a term object with a column, values in the column being the set of terms; and a referential integrity constraint for the constrained column which references the column in the term object; and the processor for executing a constraint enforcer in the relational database management system which, when an operation in the relational database management system adds a value to the constrained object, permits the operation only if the added value is a value belonging to the constraint set, and when a modification is performed on the ontology in the relational database management system that results in a different set of terms being returned by the ontology query, altering one or more values in the constrained object that are not contained in the different set of terms. 31. The apparatus set forth in claim 29 wherein the term object comprises a materialized view. | 0.880407 |
9,280,535 | 20 | 25 | 20. One or more non-transitory computer-readable storage media having stored thereon computer-executable instructions which when executed by a computer cause the computer to perform a method, the method comprising: receiving natural language input at a computing device; processing the natural language input in cascaded conditional random fields comprising a linear-chain conditional random field and a skip-chain conditional random field to obtain an output from the cascaded conditional random fields, wherein: the linear-chain conditional random field is used to extract entity information; the skip-chain conditional random field is used to extract relationship information; and the skip-chain conditional random field is sequential to the linear-chain conditional random field so that an output of the linear-chain conditional random field is an input to the skip-chain conditional random field, wherein the linear-chain conditional random field and the skip-chain conditional random field are trained using a training dataset comprising entity labels and relationship labels; and based on the output from the cascaded conditional random fields, forming a database query, wherein forming the query comprises determining a query type, wherein the query type is at least one of a range query, a logical query, a join query, or an aggregate query, and wherein the query is based at least in part on the query type. | 20. One or more non-transitory computer-readable storage media having stored thereon computer-executable instructions which when executed by a computer cause the computer to perform a method, the method comprising: receiving natural language input at a computing device; processing the natural language input in cascaded conditional random fields comprising a linear-chain conditional random field and a skip-chain conditional random field to obtain an output from the cascaded conditional random fields, wherein: the linear-chain conditional random field is used to extract entity information; the skip-chain conditional random field is used to extract relationship information; and the skip-chain conditional random field is sequential to the linear-chain conditional random field so that an output of the linear-chain conditional random field is an input to the skip-chain conditional random field, wherein the linear-chain conditional random field and the skip-chain conditional random field are trained using a training dataset comprising entity labels and relationship labels; and based on the output from the cascaded conditional random fields, forming a database query, wherein forming the query comprises determining a query type, wherein the query type is at least one of a range query, a logical query, a join query, or an aggregate query, and wherein the query is based at least in part on the query type. 25. The computer-readable storage media of claim 20 , wherein the output comprises entity information and relationship information. | 0.928959 |
8,237,719 | 3 | 4 | 3. The method of claim 1 , wherein replacing the first hold animation structure comprises: determining if the animation data defining the portion of the first pose of the object at the first shot time is included in a beat animation associated with the second pose of the object; in response to the determination that the first pose of the object is included in the beat animation, defining a first beat animation within the first hold animation structure, such that the first beat animation changes the object from the second pose to the portion of the first pose within the first hold animation structure; and in response to the determination that the first pose of the object is not included in the beat animation, replacing the first hold animation structure with the second hold animation structure. | 3. The method of claim 1 , wherein replacing the first hold animation structure comprises: determining if the animation data defining the portion of the first pose of the object at the first shot time is included in a beat animation associated with the second pose of the object; in response to the determination that the first pose of the object is included in the beat animation, defining a first beat animation within the first hold animation structure, such that the first beat animation changes the object from the second pose to the portion of the first pose within the first hold animation structure; and in response to the determination that the first pose of the object is not included in the beat animation, replacing the first hold animation structure with the second hold animation structure. 4. The method of claim 3 , wherein determining if the animation data defining the portion of the first pose of the object is included in a beat animation comprises: determining if the animation data has been designated as defining beat animation. | 0.91258 |
8,438,028 | 9 | 10 | 9. The system of claim 8 , wherein the nametag input is an utterance from the user and the decoder decodes the utterance using a statistical language model (SLM) and a semantic classifier trained on the nametag domain, the number domain, and the command domain, and the post-processor retrains the SLM and semantic classifier using the nametag input if the nametag input is not determined to be confusable. | 9. The system of claim 8 , wherein the nametag input is an utterance from the user and the decoder decodes the utterance using a statistical language model (SLM) and a semantic classifier trained on the nametag domain, the number domain, and the command domain, and the post-processor retrains the SLM and semantic classifier using the nametag input if the nametag input is not determined to be confusable. 10. The system of claim 9 , wherein the decoder produces an N-best list of hypotheses and associated confidence scores, and the post-processor calculates the confusability based on at least one of the confidence scores. | 0.929582 |
10,149,123 | 1 | 11 | 1. A method, comprising: receiving a first message comprising a first key word; receiving a request to display the first message; in response to receiving the request to display the first message, displaying a first part of information associated with the first key word; receiving a trigger associated with the first part of information; in response to receiving the trigger associated with the first part of information, obtaining a second part of information associated with the first key word; outputting a second message based at least in part on the second part of information associated with the first key word; extracting a second key word from the second message; determining whether the second key word matches the first key word; and in response to a determination that the second key word matches the first key word, deleting information associated with the first message. | 1. A method, comprising: receiving a first message comprising a first key word; receiving a request to display the first message; in response to receiving the request to display the first message, displaying a first part of information associated with the first key word; receiving a trigger associated with the first part of information; in response to receiving the trigger associated with the first part of information, obtaining a second part of information associated with the first key word; outputting a second message based at least in part on the second part of information associated with the first key word; extracting a second key word from the second message; determining whether the second key word matches the first key word; and in response to a determination that the second key word matches the first key word, deleting information associated with the first message. 11. The method of claim 1 , wherein the first key word comprises product information or order information. | 0.896484 |
7,895,116 | 8 | 10 | 8. The system of claim 7 wherein price optimizing within the seller engine is effected by an implementation selected from the group consisting of target-directed implementation, market-share implementation, model optimization with exploration implementation, utility derivative-following implementation, and rules-engine implementation. | 8. The system of claim 7 wherein price optimizing within the seller engine is effected by an implementation selected from the group consisting of target-directed implementation, market-share implementation, model optimization with exploration implementation, utility derivative-following implementation, and rules-engine implementation. 10. The system of claim 8 wherein, when a price request is received, an expected contribution to the seller utility from that request is calculated such that the optimal price will be the price that maximizes such contribution. | 0.923877 |
10,061,867 | 1 | 7 | 1. A method for tracking known topics in a plurality of interactions, the method comprising: extracting, by a processor, a plurality of fragments from the plurality of interactions, the plurality of interactions occurring over a particular time period, each fragment of the plurality of fragments comprising one or more words; initializing, by the processor, a collection of tracked topics to an empty collection; computing, by the processor, a similarity between each fragment of the fragments and each of the known topics, each of the known topics comprising a template fragment comprising one or more template words, the similarity between a fragment of the fragments and a topic of the known topics being computed based on the one or more words of the fragment and the one or more template words of the template fragment of the topic; adding, by the processor, a known topic of the known topics to the tracked topics in response to the similarity between a fragment and the known topic exceeding a threshold value; and returning, by the processor, a collection of the tracked topics detected in the plurality of interactions, the collection comprising indications of frequencies at which the tracked topics occur in the plurality of interactions during the particular time period. | 1. A method for tracking known topics in a plurality of interactions, the method comprising: extracting, by a processor, a plurality of fragments from the plurality of interactions, the plurality of interactions occurring over a particular time period, each fragment of the plurality of fragments comprising one or more words; initializing, by the processor, a collection of tracked topics to an empty collection; computing, by the processor, a similarity between each fragment of the fragments and each of the known topics, each of the known topics comprising a template fragment comprising one or more template words, the similarity between a fragment of the fragments and a topic of the known topics being computed based on the one or more words of the fragment and the one or more template words of the template fragment of the topic; adding, by the processor, a known topic of the known topics to the tracked topics in response to the similarity between a fragment and the known topic exceeding a threshold value; and returning, by the processor, a collection of the tracked topics detected in the plurality of interactions, the collection comprising indications of frequencies at which the tracked topics occur in the plurality of interactions during the particular time period. 7. The method of claim 1 , further comprising: generating, by the processor, a visualization of the tracked topics. | 0.934733 |
8,666,300 | 1 | 3 | 1. A computer-implemented method of assessing an educational program having multiple ordered activities defining multiple learner tracks, the method comprising: receiving baseline performance index scores and post-activity performance index scores for a plurality of learners engaging in the educational program by executing first instructions in a computer system, wherein the baseline performance index scores are derived from a performance index test administered to the learners prior to any of the activities, and the post-activity performance index scores are derived from the performance index test administered to the learners after each of the activities; organizing the learners into learner groups based on how many of the activities a learner has completed by executing second instructions in the computer system; for each given learner group, calculating a baseline average score using the baseline performance index scores of learners in the given learner group, calculating a post-activity average score for each of the activities which have been completed by learners in the given learner group, and calculating first statistical differences between the baseline average score and a final one of the post-activity average scores for the given learner group, and between each post-activity average score and any successive post-activity average scores for the given learner group by executing third instructions in the computer system; receiving pre-test scores and corresponding post-test scores for learners who have completed at least one of the activities, wherein the pre-test scores and post-test scores are derived from separate activity tests administered prior to and after each activity, and the separate activity tests include questions in each of a plurality of domains including at least knowledge, competence, confidence and performance by executing fourth instructions in the computer system; receiving post-curriculum assessment scores for learners who have completed a selection of the activities, wherein the post-curriculum assessment scores are derived from the performance index test and the separate activity tests administered to the learners no earlier than a designated period of time after completion of the selection of the activities by executing fifth instructions in the computer system; for each given domain, calculating pre-test domain average scores using the pre-test scores for questions in the given domain, calculating post-test domain average scores using the post-test scores for questions in the given domain, and calculating second statistical differences between the pre-test domain average scores and corresponding post-test domain average scores by executing sixth instructions in the computer system; for each given activity, calculating a pre-test activity average score using the pre-test scores for the given activity, calculating a post-test activity average score using the post-test scores for the given activity, and calculating third statistical differences between the pre-test activity average scores and corresponding post-test activity average scores by executing seventh instructions in the computer system; calculating a post-curriculum assessment average score using the post-curriculum assessment scores by executing eighth instructions in the computer system; calculating fourth statistical differences between the baseline average score and the post-curriculum assessment average score and between the post-activity average scores and the post-curriculum assessment average score by executing ninth instructions in the computer system; and identifying any of the first, second, third or fourth statistical differences which are equal to or less than a predetermined probability threshold by executing tenth instructions in the computer system. | 1. A computer-implemented method of assessing an educational program having multiple ordered activities defining multiple learner tracks, the method comprising: receiving baseline performance index scores and post-activity performance index scores for a plurality of learners engaging in the educational program by executing first instructions in a computer system, wherein the baseline performance index scores are derived from a performance index test administered to the learners prior to any of the activities, and the post-activity performance index scores are derived from the performance index test administered to the learners after each of the activities; organizing the learners into learner groups based on how many of the activities a learner has completed by executing second instructions in the computer system; for each given learner group, calculating a baseline average score using the baseline performance index scores of learners in the given learner group, calculating a post-activity average score for each of the activities which have been completed by learners in the given learner group, and calculating first statistical differences between the baseline average score and a final one of the post-activity average scores for the given learner group, and between each post-activity average score and any successive post-activity average scores for the given learner group by executing third instructions in the computer system; receiving pre-test scores and corresponding post-test scores for learners who have completed at least one of the activities, wherein the pre-test scores and post-test scores are derived from separate activity tests administered prior to and after each activity, and the separate activity tests include questions in each of a plurality of domains including at least knowledge, competence, confidence and performance by executing fourth instructions in the computer system; receiving post-curriculum assessment scores for learners who have completed a selection of the activities, wherein the post-curriculum assessment scores are derived from the performance index test and the separate activity tests administered to the learners no earlier than a designated period of time after completion of the selection of the activities by executing fifth instructions in the computer system; for each given domain, calculating pre-test domain average scores using the pre-test scores for questions in the given domain, calculating post-test domain average scores using the post-test scores for questions in the given domain, and calculating second statistical differences between the pre-test domain average scores and corresponding post-test domain average scores by executing sixth instructions in the computer system; for each given activity, calculating a pre-test activity average score using the pre-test scores for the given activity, calculating a post-test activity average score using the post-test scores for the given activity, and calculating third statistical differences between the pre-test activity average scores and corresponding post-test activity average scores by executing seventh instructions in the computer system; calculating a post-curriculum assessment average score using the post-curriculum assessment scores by executing eighth instructions in the computer system; calculating fourth statistical differences between the baseline average score and the post-curriculum assessment average score and between the post-activity average scores and the post-curriculum assessment average score by executing ninth instructions in the computer system; and identifying any of the first, second, third or fourth statistical differences which are equal to or less than a predetermined probability threshold by executing tenth instructions in the computer system. 3. The method of claim 1 , further comprising generating a report describing statistical conclusions and inferences associated with any identified differences. | 0.800752 |
7,796,142 | 1 | 2 | 1. A method of displaying a document on a display screen capable of being subjected to a scroll procedure, comprising: allocating to the document a quantity of graphics memory to create a buffer memory for a visible part of the document and for an anticipation band of zones closest in physical proximity to the visible part of the document, wherein the anticipation band comprises content anticipated to be shown in the visible part of the document after the document is scrolled; calculating and chopping the buffer memory into pixmaps as a function of a size of the document, of the visible part, and of the anticipation band, relative positioning of the pixmaps with respect to the complete document and the visible part, filling the content of the pixmaps with a priority system dependent on the proximity of the pixmap with respect to a visible zone, when the document is subjected to a display procedure or to scrolling, copying the content in the pixmaps of the anticipation band into the visible window and redrawing the anticipation band, wherein when the content is not ready for display, forcing updating of the pixmaps to be displayed in the visible part prior to copying the content and, relatively positioning the pixmaps with respect to the document as a function of the new position of the visible part. | 1. A method of displaying a document on a display screen capable of being subjected to a scroll procedure, comprising: allocating to the document a quantity of graphics memory to create a buffer memory for a visible part of the document and for an anticipation band of zones closest in physical proximity to the visible part of the document, wherein the anticipation band comprises content anticipated to be shown in the visible part of the document after the document is scrolled; calculating and chopping the buffer memory into pixmaps as a function of a size of the document, of the visible part, and of the anticipation band, relative positioning of the pixmaps with respect to the complete document and the visible part, filling the content of the pixmaps with a priority system dependent on the proximity of the pixmap with respect to a visible zone, when the document is subjected to a display procedure or to scrolling, copying the content in the pixmaps of the anticipation band into the visible window and redrawing the anticipation band, wherein when the content is not ready for display, forcing updating of the pixmaps to be displayed in the visible part prior to copying the content and, relatively positioning the pixmaps with respect to the document as a function of the new position of the visible part. 2. The method as claimed in claim 1 , wherein the anticipation band comprises a minimum of: one column of pixmaps on the right and on the left of the visible window and a row of pixmaps at the bottom and at the top of the visible window, except in the case where the visible part approaches an edge of the document. | 0.647651 |
8,509,826 | 9 | 10 | 9. The method of claim 8 further comprising: providing a hyperlink to a webpage comprising additional information related to the biosensor data. | 9. The method of claim 8 further comprising: providing a hyperlink to a webpage comprising additional information related to the biosensor data. 10. The method of claim 9 , wherein the webpage comprises a social networking webpage of a sender of the text-message component. | 0.950958 |
9,569,728 | 1 | 8 | 1. A computerized method for suggesting web pages to users comprising: receiving, at a first suggestion assistant executing on a first client computer, a first request from a first user to create a first folder; creating, in response to the first request, a first folder ID in a content repository on a server computer, wherein the first folder ID represents the first folder; receiving, at the first suggestion assistant, a second request from the first user to save a first web page to the first folder; creating, in response to the second request, a first link ID that represents the first web page, and a first folder association between the first link ID and the first folder ID in the content repository; receiving, at the first suggestion assistant, a third request from the first user to save a second web page to the first folder; creating, in response to the third request, a second link ID that represents the second web page, and a second folder association between the second link ID and the first folder ID in the content repository; automatically, based on the first folder association and the second folder association: associating the second link ID with the first link ID by adding the second link ID to a first set of related link IDs in the content repository, wherein each link ID in the first set of related link IDs is associated with the first link ID, and associating the first link ID with the second link ID by adding the first link ID to a second set of related link IDs in the content repository, wherein each link ID in the second set of related link IDs is associated with the second link ID; receiving, at a second suggestion assistant executing on a second client computer, a fourth request from a second user to create a second folder; creating, in response to the fourth request, a second folder ID in the content repository, wherein the second folder ID represents the second folder; receiving, at the second suggestion assistant, a fifth request from the second user to save the first web page to the second folder; creating, in response to the fifth request, a third folder association between the first link ID and the second folder ID in the content repository; receiving, at the second suggestion assistant, a sixth request from the second user to save a third web page to the second folder; creating, in response to the sixth request, a third link ID that represents the third web page, and a fourth folder association between the third link ID and the second folder in the content repository; automatically, based on the third folder association and the fourth folder association: associating the third link ID with the first link ID by adding the third link ID to the first set of related link IDs in the content repository, and associating the first link ID with the third link ID by adding the first link ID to a third set of related link IDs in the content repository, wherein each link ID in the third set of related link IDs is associated with the third link ID; receiving, at a third suggestion assistant executing on a third client computer, a suggestion request from a third user based on the first web page; providing, at the third suggestion assistant in response to the suggestion request, the second web page and the third web page as suggestions based on the presence of the second link ID and the third link ID in the first set of related link IDs. | 1. A computerized method for suggesting web pages to users comprising: receiving, at a first suggestion assistant executing on a first client computer, a first request from a first user to create a first folder; creating, in response to the first request, a first folder ID in a content repository on a server computer, wherein the first folder ID represents the first folder; receiving, at the first suggestion assistant, a second request from the first user to save a first web page to the first folder; creating, in response to the second request, a first link ID that represents the first web page, and a first folder association between the first link ID and the first folder ID in the content repository; receiving, at the first suggestion assistant, a third request from the first user to save a second web page to the first folder; creating, in response to the third request, a second link ID that represents the second web page, and a second folder association between the second link ID and the first folder ID in the content repository; automatically, based on the first folder association and the second folder association: associating the second link ID with the first link ID by adding the second link ID to a first set of related link IDs in the content repository, wherein each link ID in the first set of related link IDs is associated with the first link ID, and associating the first link ID with the second link ID by adding the first link ID to a second set of related link IDs in the content repository, wherein each link ID in the second set of related link IDs is associated with the second link ID; receiving, at a second suggestion assistant executing on a second client computer, a fourth request from a second user to create a second folder; creating, in response to the fourth request, a second folder ID in the content repository, wherein the second folder ID represents the second folder; receiving, at the second suggestion assistant, a fifth request from the second user to save the first web page to the second folder; creating, in response to the fifth request, a third folder association between the first link ID and the second folder ID in the content repository; receiving, at the second suggestion assistant, a sixth request from the second user to save a third web page to the second folder; creating, in response to the sixth request, a third link ID that represents the third web page, and a fourth folder association between the third link ID and the second folder in the content repository; automatically, based on the third folder association and the fourth folder association: associating the third link ID with the first link ID by adding the third link ID to the first set of related link IDs in the content repository, and associating the first link ID with the third link ID by adding the first link ID to a third set of related link IDs in the content repository, wherein each link ID in the third set of related link IDs is associated with the third link ID; receiving, at a third suggestion assistant executing on a third client computer, a suggestion request from a third user based on the first web page; providing, at the third suggestion assistant in response to the suggestion request, the second web page and the third web page as suggestions based on the presence of the second link ID and the third link ID in the first set of related link IDs. 8. The method of claim 1 , further comprising: receiving, via the network, an indication that the third user has taken an action on the second web page. | 0.787115 |
6,061,063 | 5 | 6 | 5. A computer program product comprising: a computer usable medium having computer readable code embodied therein for configuring a computer, said computer program product comprising: computer readable code configured to cause a computer to define a display region having a height h.times.m where h is a height and m is an integer, computer readable code configured to cause a computer to display at least one field of a list of n fields, where n is an integer and each field has a height h, such that m-1 fields are fully displayed in said display region; computer readable code configured to cause a computer to display a first blank region having a height h/k at a first end of said display region when the first field of said list of n fields is displayed within said display region, where k is a positive number less than h. | 5. A computer program product comprising: a computer usable medium having computer readable code embodied therein for configuring a computer, said computer program product comprising: computer readable code configured to cause a computer to define a display region having a height h.times.m where h is a height and m is an integer, computer readable code configured to cause a computer to display at least one field of a list of n fields, where n is an integer and each field has a height h, such that m-1 fields are fully displayed in said display region; computer readable code configured to cause a computer to display a first blank region having a height h/k at a first end of said display region when the first field of said list of n fields is displayed within said display region, where k is a positive number less than h. 6. The computer product of claim 5 further including computer readable code configured to cause a computer to displace said m-1 fields within said display region a distance h in a first direction when a first button is clicked. | 0.879894 |
7,761,700 | 13 | 17 | 13. A computing system comprising: one or more processors; and one or more computer-readable media having computer-readable instructions thereon which, when executed by the one or more processors, cause the one or more processors to: while booting the computing system and prior to allowing a user to logon to the computing system, spawning a process, separate from a user logon process, to load a markup language rendering engine at the beginning of an operating system initialization procedure; retrieve user data from the operating system via a control that communicates between the markup language rendering engine and the user logon process; render markup language code associated with a logon screen configured to selectively allow a user to logon to the computing system using at least a portion of the user data; collect at least one user input associated with the logon screen; and establish a logon session if the user input is valid. | 13. A computing system comprising: one or more processors; and one or more computer-readable media having computer-readable instructions thereon which, when executed by the one or more processors, cause the one or more processors to: while booting the computing system and prior to allowing a user to logon to the computing system, spawning a process, separate from a user logon process, to load a markup language rendering engine at the beginning of an operating system initialization procedure; retrieve user data from the operating system via a control that communicates between the markup language rendering engine and the user logon process; render markup language code associated with a logon screen configured to selectively allow a user to logon to the computing system using at least a portion of the user data; collect at least one user input associated with the logon screen; and establish a logon session if the user input is valid. 17. The computing system of claim 13 , wherein the markup language code comprises markup language code selected from at least one markup language in a group comprising hypertext markup language (HTML), Dynamic Hypertext Markup Language (DHTML), eXtensible Markup Language (XML), eXtensible Hypertext Markup Language (XHTML), or Standard Generalized Markup Language (SGML). | 0.50134 |
8,301,451 | 2 | 17 | 2. A method according to claim 1 , wherein each of the first speech parameter vectors x i includes a spectral domain representation of speech. | 2. A method according to claim 1 , wherein each of the first speech parameter vectors x i includes a spectral domain representation of speech. 17. A method according to claim 2 , wherein each of the first speech parameter vectors x i includes at least one of cepstral parameters and line spectral frequency parameters. | 0.978834 |
7,684,987 | 1 | 4 | 1. A speech processing system receiving an input related to one of speech and text and process the input to provide an output related to one of speech and text, the speech processing system comprising: a module derived from a phone set having a plurality of phones for a tonal language, wherein the tonal language comprises a plurality of different tones with different levels of pitch, the phones being used to model syllables used in the module, the syllables having an initial part and a final part, wherein at least some of the syllables of the tonal language include a glide, the glide being embodied in the initial part, and wherein the final part comprises a first temporal portion corresponding to a first relative pitch and a second temporal portion corresponding to a second relative pitch, wherein the first portion and the second portion jointly and implicitly carry tonal information, and wherein the different levels of pitch comprise at least two discrete categorical levels, and wherein each portion has a discrete categorical level associated with it; and a processor configured to receive an input related to one of speech and text and access the module to process the input to provide an output related to one of speech and text. | 1. A speech processing system receiving an input related to one of speech and text and process the input to provide an output related to one of speech and text, the speech processing system comprising: a module derived from a phone set having a plurality of phones for a tonal language, wherein the tonal language comprises a plurality of different tones with different levels of pitch, the phones being used to model syllables used in the module, the syllables having an initial part and a final part, wherein at least some of the syllables of the tonal language include a glide, the glide being embodied in the initial part, and wherein the final part comprises a first temporal portion corresponding to a first relative pitch and a second temporal portion corresponding to a second relative pitch, wherein the first portion and the second portion jointly and implicitly carry tonal information, and wherein the different levels of pitch comprise at least two discrete categorical levels, and wherein each portion has a discrete categorical level associated with it; and a processor configured to receive an input related to one of speech and text and access the module to process the input to provide an output related to one of speech and text. 4. The speech processing system of claim 1 wherein the speech processing system comprises one of a speech recognition system and a text-to-speech converter. | 0.630332 |
7,519,589 | 56 | 57 | 56. A method to enable improved analysis and use of sociological data, the method comprising: identifying causal relationships between a plurality of documents; identifying a plurality of characteristics of a communication, including a modality used, actors involved, and proximate events of relevance; enabling a user to query based on all of the characteristics available; and enabling a user to select multiple matters, and perform queries across the multiple matters. | 56. A method to enable improved analysis and use of sociological data, the method comprising: identifying causal relationships between a plurality of documents; identifying a plurality of characteristics of a communication, including a modality used, actors involved, and proximate events of relevance; enabling a user to query based on all of the characteristics available; and enabling a user to select multiple matters, and perform queries across the multiple matters. 57. The method of claim 56 , further comprising: enabling a user to conjoin information from the multiple matters to form a new discussion. | 0.904138 |
9,053,489 | 12 | 16 | 12. A system comprising one or more hardware processors configured to: receive a message from a sender communication device, wherein the message is configured to be sent to a recipient communication device using an identifier of the recipient communication device; identify a word, for which advertising is available, from the message; receive geographical location information from the recipient communication device; determine temporal information pertaining to the recipient communication device based at least on the geographical location information received from the recipient communication device; send the word identified from the message and the temporal information to a third party; obtain a plurality of advertisements from the third party based at least in part on the word identified in the message and the temporal information, wherein each advertisement of the plurality of advertisements is associated with a respective payment level, and wherein each respective payment level is based at least in part on the temporal information pertaining to the recipient communication device; associate in a data store of the one or more computing devices the word identified in the message with the plurality of advertisements and the identifier of the recipient communication device, wherein the one or more computing devices are remote from the sender communication device and the recipient communication device; send the message to the recipient communication device; receive, from the recipient communication device, the identifier of the recipient communication device; receive, from the recipient communication device, a transcribed utterance that includes the word identified in the message; select at least one advertisement of the plurality of advertisements, wherein the selection is based at least in part on the respective payment level of the at least one advertisement; and based at least in part on the word identified in the message being present in the transcribed utterance and being associated with the plurality of advertisements and the identifier of the recipient communication device, send the at least one advertisement to the recipient communication device using the identifier of the recipient communication device. | 12. A system comprising one or more hardware processors configured to: receive a message from a sender communication device, wherein the message is configured to be sent to a recipient communication device using an identifier of the recipient communication device; identify a word, for which advertising is available, from the message; receive geographical location information from the recipient communication device; determine temporal information pertaining to the recipient communication device based at least on the geographical location information received from the recipient communication device; send the word identified from the message and the temporal information to a third party; obtain a plurality of advertisements from the third party based at least in part on the word identified in the message and the temporal information, wherein each advertisement of the plurality of advertisements is associated with a respective payment level, and wherein each respective payment level is based at least in part on the temporal information pertaining to the recipient communication device; associate in a data store of the one or more computing devices the word identified in the message with the plurality of advertisements and the identifier of the recipient communication device, wherein the one or more computing devices are remote from the sender communication device and the recipient communication device; send the message to the recipient communication device; receive, from the recipient communication device, the identifier of the recipient communication device; receive, from the recipient communication device, a transcribed utterance that includes the word identified in the message; select at least one advertisement of the plurality of advertisements, wherein the selection is based at least in part on the respective payment level of the at least one advertisement; and based at least in part on the word identified in the message being present in the transcribed utterance and being associated with the plurality of advertisements and the identifier of the recipient communication device, send the at least one advertisement to the recipient communication device using the identifier of the recipient communication device. 16. The system of claim 12 , wherein the selection is further based at least in part on a location of the recipient communication device. | 0.867761 |
9,542,436 | 12 | 13 | 12. A method comprising using a computer to manage a lifecycle of a platform, including: populating associative memory with plurality of matrices pertaining to lifecycle information about the platform, each matrix including related entity values and attribute values; causing the associative memory to create correlations between each matrix relative to the other matrices; searching the correlations for lifecycle entity and attribute values to investigate a component of the platform; and displaying any highly correlated entity and attribute values that do not include the component under investigation but are highly correlated to the component under investigation; wherein the highly correlated entity is the entity with the highest value that corresponds to a number of times the entity is returned within a repetitive search executed by an entity analytic engine; and updating a plurality of information tools with reports based on other similar components that are either further ahead or behind in the lifecycle of the specified component. | 12. A method comprising using a computer to manage a lifecycle of a platform, including: populating associative memory with plurality of matrices pertaining to lifecycle information about the platform, each matrix including related entity values and attribute values; causing the associative memory to create correlations between each matrix relative to the other matrices; searching the correlations for lifecycle entity and attribute values to investigate a component of the platform; and displaying any highly correlated entity and attribute values that do not include the component under investigation but are highly correlated to the component under investigation; wherein the highly correlated entity is the entity with the highest value that corresponds to a number of times the entity is returned within a repetitive search executed by an entity analytic engine; and updating a plurality of information tools with reports based on other similar components that are either further ahead or behind in the lifecycle of the specified component. 13. The method of claim 12 , wherein managing the lifecycle further includes populating the associative memory with a plurality of matrices pertaining to platform non-conformances. | 0.730539 |
8,543,398 | 15 | 16 | 15. The article of manufacture of claim 10 , wherein selecting the sample utterance-to-text-string mappings from the corpus of utterance-to-text-string mappings based on the compressed word frequencies comprises: determining a first word selection probability for a first word based on a first compressed word frequency of the first word divided by a first word frequency of the first word, wherein the sample utterance-to-text-string mappings include a particular utterance mapped to a particular text string, and wherein the particular text string contains the first word; and selecting the particular utterance based on the first word selection probability. | 15. The article of manufacture of claim 10 , wherein selecting the sample utterance-to-text-string mappings from the corpus of utterance-to-text-string mappings based on the compressed word frequencies comprises: determining a first word selection probability for a first word based on a first compressed word frequency of the first word divided by a first word frequency of the first word, wherein the sample utterance-to-text-string mappings include a particular utterance mapped to a particular text string, and wherein the particular text string contains the first word; and selecting the particular utterance based on the first word selection probability. 16. The article of manufacture of claim 15 , wherein selecting the sample utterance-to-text-string mappings from the corpus of utterance-to-text-string mappings based on the compressed word frequencies further comprises: determining a second word selection probability for a second word based on a second compressed word frequency of the second word divided by a second word frequency of the second word, wherein the particular text string also contains the second word; and selecting the particular utterance based on the first word selection probability and second word selection probability. | 0.734821 |
7,840,547 | 1 | 8 | 1. A method comprising: populating a computer memory, by receiving a plurality of first search queries from a first plurality of computer users at a computer system, rewriting the plurality of first search queries into modified search queries, and mapping ones of the plurality of first search queries to corresponding modified search queries to produce a mapping in computer memory that correlates ones of the plurality of first search queries with corresponding ones of the rewritten search queries; wherein rewriting the plurality of first search queries into the modified search queries comprises: determining a phrase or term that is more common or popular than content of a first one of the plurality of first search queries; and rewriting the first one of the plurality of first search queries into a first one of the modified search queries such that the first one of the modified search queries includes the determined phrase or term in place of the content of the first one of the plurality of first search queries; providing search results for the rewritten search queries to the plurality of computer users; subsequently processing a second search query received from a user who is different than the first plurality of computer users, by determining whether a portion of content from the second query matches a portion of content from at least one of the plurality of first search queries, and executing, based on a determination of whether a portion of the content from the second query matches a portion of content from at least one of the plurality of first search queries, (i) a computerized search using one of the rewritten queries that corresponds to the query from the plurality of first search queries that includes the matching portion of content in place of the second search query, or (ii) a search using information corresponding to the received second search query or a modified version of the second search query; and providing search results from processing the second search query to the second user. | 1. A method comprising: populating a computer memory, by receiving a plurality of first search queries from a first plurality of computer users at a computer system, rewriting the plurality of first search queries into modified search queries, and mapping ones of the plurality of first search queries to corresponding modified search queries to produce a mapping in computer memory that correlates ones of the plurality of first search queries with corresponding ones of the rewritten search queries; wherein rewriting the plurality of first search queries into the modified search queries comprises: determining a phrase or term that is more common or popular than content of a first one of the plurality of first search queries; and rewriting the first one of the plurality of first search queries into a first one of the modified search queries such that the first one of the modified search queries includes the determined phrase or term in place of the content of the first one of the plurality of first search queries; providing search results for the rewritten search queries to the plurality of computer users; subsequently processing a second search query received from a user who is different than the first plurality of computer users, by determining whether a portion of content from the second query matches a portion of content from at least one of the plurality of first search queries, and executing, based on a determination of whether a portion of the content from the second query matches a portion of content from at least one of the plurality of first search queries, (i) a computerized search using one of the rewritten queries that corresponds to the query from the plurality of first search queries that includes the matching portion of content in place of the second search query, or (ii) a search using information corresponding to the received second search query or a modified version of the second search query; and providing search results from processing the second search query to the second user. 8. The method of claim 1 , wherein the plurality of first queries and the second search query are received at a first system of a search site, and the search of the modified search query is issued by a search engine in the first system. | 0.766798 |
8,645,284 | 1 | 6 | 1. A method for computerized employment recruiting, comprising the steps of: accessing, by a computerized employment recruiting system, a candidate database of candidate data for a plurality of candidates, including a first candidate, said candidate data for each candidate including candidate qualifications and candidate personal information; accessing, by the computerized employment recruiting system, a job posting database including job posting data for a plurality of job postings, the job posting data for each job posting including employer information and job criteria; comparing, by said employment recruiting system, said candidate qualifications of said first candidate to said job criteria for a plurality of said job postings; determining, by said employment recruiting system, a match between said candidate qualifications of said first candidate and job criteria for a first job posting within said plurality of job postings; identifying, by said employment recruiting system, a softlink between said first candidate and said first job posting by matching candidate information with saved business information regarding the employer of the first job posting using a softlink algorithm; determining a softlink relevance index for said softlink; generating, by said employment recruiting system, a ranking of said first candidate among a plurality of candidates for said first job posting based, at least in part, upon said softlink relevance index. | 1. A method for computerized employment recruiting, comprising the steps of: accessing, by a computerized employment recruiting system, a candidate database of candidate data for a plurality of candidates, including a first candidate, said candidate data for each candidate including candidate qualifications and candidate personal information; accessing, by the computerized employment recruiting system, a job posting database including job posting data for a plurality of job postings, the job posting data for each job posting including employer information and job criteria; comparing, by said employment recruiting system, said candidate qualifications of said first candidate to said job criteria for a plurality of said job postings; determining, by said employment recruiting system, a match between said candidate qualifications of said first candidate and job criteria for a first job posting within said plurality of job postings; identifying, by said employment recruiting system, a softlink between said first candidate and said first job posting by matching candidate information with saved business information regarding the employer of the first job posting using a softlink algorithm; determining a softlink relevance index for said softlink; generating, by said employment recruiting system, a ranking of said first candidate among a plurality of candidates for said first job posting based, at least in part, upon said softlink relevance index. 6. The method of claim 1 , wherein said softlink is a potential personal reference softlink. | 0.924217 |
10,019,491 | 9 | 10 | 9. An apparatus for machine learning in the selection of a ranked response to a structured data input having a natural language processing output schema received from a requesting device, the apparatus comprising: one or more data processors; a memory, coupled to the data processors, having code stored therein to cause the one or more data processors to: receive the structured data input, wherein the structured data input includes filtering parameters for conversion into response template filtering criteria; convert the filtering parameters into the response template filtering criteria; query a library of response templates to identify candidate response templates that meet the response template filtering criteria to filter the response templates; receive a selection of the candidate response templates that meet the response template filtering criteria and respond to the structured input data, wherein the candidate response templates include static data; operate a ranking engine to rank the selection of candidate response templates in accordance with ranking criteria; select a highest ranked candidate response template to provide a response to a device; derive the response to the structured data input from the selected, highest ranked, candidate response template; provide the response to a recipient device; and provide feedback to the ranking engine to refine the ranking criteria. | 9. An apparatus for machine learning in the selection of a ranked response to a structured data input having a natural language processing output schema received from a requesting device, the apparatus comprising: one or more data processors; a memory, coupled to the data processors, having code stored therein to cause the one or more data processors to: receive the structured data input, wherein the structured data input includes filtering parameters for conversion into response template filtering criteria; convert the filtering parameters into the response template filtering criteria; query a library of response templates to identify candidate response templates that meet the response template filtering criteria to filter the response templates; receive a selection of the candidate response templates that meet the response template filtering criteria and respond to the structured input data, wherein the candidate response templates include static data; operate a ranking engine to rank the selection of candidate response templates in accordance with ranking criteria; select a highest ranked candidate response template to provide a response to a device; derive the response to the structured data input from the selected, highest ranked, candidate response template; provide the response to a recipient device; and provide feedback to the ranking engine to refine the ranking criteria. 10. The apparatus of claim 9 wherein the requesting device accesses data that provides insight into an individual and formulates the structured data input as a proactive query to obtain a proactive response to provide to the recipient device that is germane to the individual based on the insight. | 0.6625 |
9,098,567 | 1 | 4 | 1. A method that uses a processor to determine a document rank, comprising: calculating, using the processor, a document rank score of a second document based on a first term relationship score of a first document and a first contribution score, the first contribution score being determined based on a common keyword between the first document and the second document; changing the first term relationship score to a second term relationship score; and updating the document rank score of the second document based on the second term relationship score, wherein the first document is linked by a link to the second document, wherein the first term relationship score is determined based on content of the first document and the link, and wherein updating the document rank score comprises determining whether each of a plurality of contribution scores is greater than a predetermined threshold value, whereby if one of the contribution scores is less than or equal to the predetermined threshold value, that contribution score is set to a zero value. | 1. A method that uses a processor to determine a document rank, comprising: calculating, using the processor, a document rank score of a second document based on a first term relationship score of a first document and a first contribution score, the first contribution score being determined based on a common keyword between the first document and the second document; changing the first term relationship score to a second term relationship score; and updating the document rank score of the second document based on the second term relationship score, wherein the first document is linked by a link to the second document, wherein the first term relationship score is determined based on content of the first document and the link, and wherein updating the document rank score comprises determining whether each of a plurality of contribution scores is greater than a predetermined threshold value, whereby if one of the contribution scores is less than or equal to the predetermined threshold value, that contribution score is set to a zero value. 4. The method of claim 1 , wherein: the first term relationship score is changed in response to changing the content associated with the first document; and the second term relationship score is a term relationship score with respect to the common keyword of the changed content. | 0.918659 |
8,484,024 | 19 | 20 | 19. The system of claim 18 , wherein the class identity for each sub-matrix in the second matrix is created from a set of one or more indexes corresponding to a class identity in a same sub-matrix in the sensitivity matrix. | 19. The system of claim 18 , wherein the class identity for each sub-matrix in the second matrix is created from a set of one or more indexes corresponding to a class identity in a same sub-matrix in the sensitivity matrix. 20. The system of claim 19 , wherein the one or more indexes corresponding to a class identity in a same sub-matrix correspond to one or more class labels. | 0.931111 |
7,945,596 | 14 | 15 | 14. The system of claim 13 further comprising means for loading all data associated with the set of properties of the entity when programming against said first or second entity view class. | 14. The system of claim 13 further comprising means for loading all data associated with the set of properties of the entity when programming against said first or second entity view class. 15. The system of claim 14 wherein properties present in the generated second entity view class include only some of the properties included in the definition of the entity. | 0.942179 |
9,262,535 | 1 | 6 | 1. A computer-implemented method comprising: receiving, via a network at a first client computer, a plurality of content items from one or more content sources, wherein each of the plurality of content items is a copy of a content item or a reference to a content item; presenting the plurality of content items in an organizational tool at the first client computer; receiving a first user's interactions with the plurality of content items via the organizational tool, wherein the first user's interactions comprise steps to organize the plurality of content items within a first local hierarchy of folders maintained by the organizational tool; and transmitting the first user's interactions, via the network, from the first client computer to a server computer, wherein a policy engine at the server computer determines whether to update a global hierarchy of folders comprising the plurality of content items based on the first user's interactions and interactions of at least one other user. | 1. A computer-implemented method comprising: receiving, via a network at a first client computer, a plurality of content items from one or more content sources, wherein each of the plurality of content items is a copy of a content item or a reference to a content item; presenting the plurality of content items in an organizational tool at the first client computer; receiving a first user's interactions with the plurality of content items via the organizational tool, wherein the first user's interactions comprise steps to organize the plurality of content items within a first local hierarchy of folders maintained by the organizational tool; and transmitting the first user's interactions, via the network, from the first client computer to a server computer, wherein a policy engine at the server computer determines whether to update a global hierarchy of folders comprising the plurality of content items based on the first user's interactions and interactions of at least one other user. 6. The method of claim 1 , wherein the first user's interactions include moving at least one of the plurality of content items from one folder to another folder within the first local hierarchy of folders. | 0.748775 |
9,418,056 | 1 | 27 | 1. An authoring tool, embedded in a non-transitory tangible computer readable medium, the authoring tool comprising tools for: enabling an author to create and define a presentation of a wrap package by: (a) selecting a card type among a plurality of card types; (b) selecting a card template from one or more card templates of the selected card type; (c) creating a new card by authoring a copy of the selected card template; (d) creating a plurality of cards by repeating (a) through (c); and (e) defining a sequence order for viewing the plurality of cards, the presentation of the wrap package defined by (i) the plurality of cards as created and authored and (ii) the defined sequence order for viewing the plurality of cards; the authoring tool further comprising: generating a plurality of JSON card descriptors, each JSON card descriptor defining content, a structure and a layout of an associated one of the plurality of cards of the wrap package respectively; and generating a JSON wrap descriptor including the plurality of JSON card descriptors, wherein the JSON wrap descriptor is used by a runtime viewer at a consuming device to create a runtime instance of the wrap package having the same presentation as defined by the author, the runtime instance of the wrap package including the plurality of cards arranged to be viewed in the sequence order, wherein the presentation of the wrap package includes a set of cards, among the plurality of cards, each characterized by: a same size; a first aspect ratio; and content where the relative position of the content of each card in the set remains fixed, regardless of the size and/or type of display, associated with the consuming device. | 1. An authoring tool, embedded in a non-transitory tangible computer readable medium, the authoring tool comprising tools for: enabling an author to create and define a presentation of a wrap package by: (a) selecting a card type among a plurality of card types; (b) selecting a card template from one or more card templates of the selected card type; (c) creating a new card by authoring a copy of the selected card template; (d) creating a plurality of cards by repeating (a) through (c); and (e) defining a sequence order for viewing the plurality of cards, the presentation of the wrap package defined by (i) the plurality of cards as created and authored and (ii) the defined sequence order for viewing the plurality of cards; the authoring tool further comprising: generating a plurality of JSON card descriptors, each JSON card descriptor defining content, a structure and a layout of an associated one of the plurality of cards of the wrap package respectively; and generating a JSON wrap descriptor including the plurality of JSON card descriptors, wherein the JSON wrap descriptor is used by a runtime viewer at a consuming device to create a runtime instance of the wrap package having the same presentation as defined by the author, the runtime instance of the wrap package including the plurality of cards arranged to be viewed in the sequence order, wherein the presentation of the wrap package includes a set of cards, among the plurality of cards, each characterized by: a same size; a first aspect ratio; and content where the relative position of the content of each card in the set remains fixed, regardless of the size and/or type of display, associated with the consuming device. 27. The authoring tool of claim 1 , wherein the presentation of the plurality of cards of the wrap package remains the same, including in different rendering environments associated with but not limited to mobile phones, tablet computers, laptop computers, desktop computers, smart TVs respectively. | 0.714149 |
7,957,974 | 22 | 23 | 22. The apparatus of claim 21 , wherein the action planning unit determines whether or not a prerequisite included in the action data corresponding to the logical command is satisfied, and wherein if the result of determining whether or not a prerequisite included in the action data corresponding to the logical command is satisfied indicates that the prerequisite is not satisfied and an action capable of satisfying the prerequisite is not in the action library, the action planning unit outputs an error message. | 22. The apparatus of claim 21 , wherein the action planning unit determines whether or not a prerequisite included in the action data corresponding to the logical command is satisfied, and wherein if the result of determining whether or not a prerequisite included in the action data corresponding to the logical command is satisfied indicates that the prerequisite is not satisfied and an action capable of satisfying the prerequisite is not in the action library, the action planning unit outputs an error message. 23. The apparatus of claim 22 , wherein the action planning unit determines whether or not the prerequisite included in the action data corresponding to the logical command is satisfied by referring to a device state library which stores the state information of the home electronic devices connected to the home network. | 0.884116 |
8,095,870 | 7 | 12 | 7. A data processing system for generating documents in native application formats, the system comprising: a processor; and a memory coupled to the processor, the memory configured to store a plurality of code modules which when executed by the processor cause the processor to: receive a first document file in a predetermined native application format, data stored in the first document file formatted according to the predetermined native application format, the first document file providing an overall document layout for the data stored in the first document file; generate an XDTL template that represents a document template of at least the overall document layout for the data stored in the first document file in response to parsing the first document file according to the predetermined native application format, the XDTL template including one or more tags configured as data placeholders for different data, the one or more tags replicating locations of the data stored in the first document file for the different data; generate an XDTL execution document based on the XDTL template; and render a second document file in the predetermined native application format based on the XDTL document template, data stored in the second document file being different from the data stored in the first document file, the data stored in the second document file formatted according to the predetermined native application format and having the same overall document layout as provided by the first document file for the data stored in the first document file. | 7. A data processing system for generating documents in native application formats, the system comprising: a processor; and a memory coupled to the processor, the memory configured to store a plurality of code modules which when executed by the processor cause the processor to: receive a first document file in a predetermined native application format, data stored in the first document file formatted according to the predetermined native application format, the first document file providing an overall document layout for the data stored in the first document file; generate an XDTL template that represents a document template of at least the overall document layout for the data stored in the first document file in response to parsing the first document file according to the predetermined native application format, the XDTL template including one or more tags configured as data placeholders for different data, the one or more tags replicating locations of the data stored in the first document file for the different data; generate an XDTL execution document based on the XDTL template; and render a second document file in the predetermined native application format based on the XDTL document template, data stored in the second document file being different from the data stored in the first document file, the data stored in the second document file formatted according to the predetermined native application format and having the same overall document layout as provided by the first document file for the data stored in the first document file. 12. The system of claim 7 wherein the processor is further configured to: receive context information associated with the first document file; and render the second document based on the context information. | 0.789206 |
8,429,158 | 19 | 23 | 19. A system for incrementally searching among multiple documents and incrementally searching for subsections within individual documents using a single incremental search interface on an input-constrained user device having a screen and a keypad, the system comprising: computer memory store comprising instructions in computer readable form that when executed cause a computer system to: display, in a first portion of the screen, a user interface text input component operable to receive incremental keystrokes entered using the keypad; receive a sequence of incremental keystrokes entered into the text input component by a user of the device, wherein the sequence of incremental keystrokes represents a search query input; in response to each incremental keystroke of the sequence of incremental keystrokes, receive a set of document index section indicators, wherein each document index section indicator uniquely identifies a specific point within a document associated with a subsection within said document, and wherein the subsection associated with the specific point matches at least a portion of the sequence of incremental keystrokes; in response to each incremental keystroke of the sequence of incremental keystrokes, receive a set of document pointers, where each pointer uniquely identifies a document; display, in a second portion of the screen, said document index section indicators and document pointers; receive browse actions from the user to browse through and to select one of said document index section indicators and document pointers; display, if a document index section indicator is selected, the identified document, beginning at the identified point within said document so that the user is presented with the subsection within said document that is relatively more relevant to the matched portion of the sequence of incremental keystrokes without having to first scan through one or more other subsections within said document that are relatively less relevant to the matched portion of the sequence of incremental keystrokes, or displaying, if a document pointer is selected, the beginning of the identified document; set, responsive to the document selection, a query context that includes at least one document context associated with the selected document, wherein the document context represents an attribute of the selected document; subsequent to displaying the selected document, receive a subsequent sequence of incremental keystrokes entered into the text input component by the user of the device, wherein the subsequent sequence of incremental keystrokes represents a subsequent search query input; and in response to each incremental keystroke of the subsequent sequence of incremental keystrokes, display a set of document index section indicators for the selected document in the second portion of the screen based on the set query context and at least a portion of the subsequent sequence of incremental keystrokes. | 19. A system for incrementally searching among multiple documents and incrementally searching for subsections within individual documents using a single incremental search interface on an input-constrained user device having a screen and a keypad, the system comprising: computer memory store comprising instructions in computer readable form that when executed cause a computer system to: display, in a first portion of the screen, a user interface text input component operable to receive incremental keystrokes entered using the keypad; receive a sequence of incremental keystrokes entered into the text input component by a user of the device, wherein the sequence of incremental keystrokes represents a search query input; in response to each incremental keystroke of the sequence of incremental keystrokes, receive a set of document index section indicators, wherein each document index section indicator uniquely identifies a specific point within a document associated with a subsection within said document, and wherein the subsection associated with the specific point matches at least a portion of the sequence of incremental keystrokes; in response to each incremental keystroke of the sequence of incremental keystrokes, receive a set of document pointers, where each pointer uniquely identifies a document; display, in a second portion of the screen, said document index section indicators and document pointers; receive browse actions from the user to browse through and to select one of said document index section indicators and document pointers; display, if a document index section indicator is selected, the identified document, beginning at the identified point within said document so that the user is presented with the subsection within said document that is relatively more relevant to the matched portion of the sequence of incremental keystrokes without having to first scan through one or more other subsections within said document that are relatively less relevant to the matched portion of the sequence of incremental keystrokes, or displaying, if a document pointer is selected, the beginning of the identified document; set, responsive to the document selection, a query context that includes at least one document context associated with the selected document, wherein the document context represents an attribute of the selected document; subsequent to displaying the selected document, receive a subsequent sequence of incremental keystrokes entered into the text input component by the user of the device, wherein the subsequent sequence of incremental keystrokes represents a subsequent search query input; and in response to each incremental keystroke of the subsequent sequence of incremental keystrokes, display a set of document index section indicators for the selected document in the second portion of the screen based on the set query context and at least a portion of the subsequent sequence of incremental keystrokes. 23. The system according to claim 19 , the computer memory store further comprising instructions that cause the computer system to display indicators adjacent to the displayed document pointers, in order to distinguish the displayed document pointers from the displayed document index section indicators. | 0.546269 |
7,933,843 | 1 | 13 | 1. A computer-implemented method for a highly automated media analysis of influencer networks, comprising: defining, by an application of a computerized selection process of a computer that considers user-entered criteria, one or more scopes of media content to be included in an analysis project; retrieving, by the computer, relevant media content from a plurality of providers as defined by the one or more scopes of the analysis project, the media content including published text articles and a body of text for each of the text articles; extracting, by an application of an automatic computerized, linguistic-based and statistically-supported entity extraction process, entities from the text articles, the entities being data including names of people, organizations, locations, and brands recited in the body of text of the text articles in the retrieved media content; manually associating, selectively and with the aid of the computer, for each of the entities, a functional role of each of the entities for each text article of the retrieved media content; manually associating, selectively and with the aid of the computer, for each of the entities, a favorability score for each of the entities for each text article of the received media content; storing the entities in a relational database, where the entities that are co-cited in a body of text of the text articles are linked to each other for an associated text article; performing, by the computer, a first computation characterizing a network of influence relationships between each of the entities and each text article of the retrieved media content based on the extracted information and the manually associated functional role and favorability of each of the entities; and performing, by the computer, a second computation characterizing connection properties of individual entities with respect to the other entities; performing, by the computer, a third computation characterizing connection properties of at least a portion of the overall network of influence, the third computation to include a value for the network's cohesion property and density property; and outputting a result of the first, second, and third computations to produce a graphical, interactive representation of the network of influence in which a user may select individual entities to examine their associated connection properties, link to other documents, and link to web pages related to the entities, and combinations thereof. | 1. A computer-implemented method for a highly automated media analysis of influencer networks, comprising: defining, by an application of a computerized selection process of a computer that considers user-entered criteria, one or more scopes of media content to be included in an analysis project; retrieving, by the computer, relevant media content from a plurality of providers as defined by the one or more scopes of the analysis project, the media content including published text articles and a body of text for each of the text articles; extracting, by an application of an automatic computerized, linguistic-based and statistically-supported entity extraction process, entities from the text articles, the entities being data including names of people, organizations, locations, and brands recited in the body of text of the text articles in the retrieved media content; manually associating, selectively and with the aid of the computer, for each of the entities, a functional role of each of the entities for each text article of the retrieved media content; manually associating, selectively and with the aid of the computer, for each of the entities, a favorability score for each of the entities for each text article of the received media content; storing the entities in a relational database, where the entities that are co-cited in a body of text of the text articles are linked to each other for an associated text article; performing, by the computer, a first computation characterizing a network of influence relationships between each of the entities and each text article of the retrieved media content based on the extracted information and the manually associated functional role and favorability of each of the entities; and performing, by the computer, a second computation characterizing connection properties of individual entities with respect to the other entities; performing, by the computer, a third computation characterizing connection properties of at least a portion of the overall network of influence, the third computation to include a value for the network's cohesion property and density property; and outputting a result of the first, second, and third computations to produce a graphical, interactive representation of the network of influence in which a user may select individual entities to examine their associated connection properties, link to other documents, and link to web pages related to the entities, and combinations thereof. 13. The computer-implemented method of claim 1 , further comprising extracting values for structured fields associated with each text article of the retrieved media content, including values associated with at least one of the structured fields of: an author, a title, a date of publication, and a name of a publication associated with each text article. | 0.688928 |
8,805,861 | 18 | 19 | 18. The system of claim 4 , wherein the instructions to select the page grammar for the first set of source documents comprises heuristically identifying a first sequence of grammar transformations {(G→G′) 1 , . . . , (G→G′) n } that transforms the domain grammar to the page grammar. | 18. The system of claim 4 , wherein the instructions to select the page grammar for the first set of source documents comprises heuristically identifying a first sequence of grammar transformations {(G→G′) 1 , . . . , (G→G′) n } that transforms the domain grammar to the page grammar. 19. The system of claim 18 , wherein each respective grammar transformations (G→G′) i in the first sequence of grammar transformations is invertible by a corresponding grammar transformation (G′→G) i , in a second sequence of grammar transformations {(G′→G) 1 , . . . , (G′→G) n }, that undoes an effect of the transformation (G→G′) i with respect to the domain grammar, and the instructions to transform information comprise using the second sequence of grammar transformations to structurally transform information extracted from the second set of source documents to the format of the domain grammar. | 0.835874 |
4,877,408 | 2 | 8 | 2. A competitive computer educational game for teaching a plurality of students in the classroom enviornment, utilizing a computer network where all students are simultaneously asked a question, each student having access to an input device with which to enter an answer, with a master computer asking the questions and keeping score, and comprising: a means of computing an instantaneous handicap for each student based on a predetermined function of the difference between his score and the player with the highest score, a means of adding such handicap points to the slower students score when they enter a correct answer in such a manner that all the students scores tend to be equalized, thereby encouraging the slower students to maintain an interest in the learning process. | 2. A competitive computer educational game for teaching a plurality of students in the classroom enviornment, utilizing a computer network where all students are simultaneously asked a question, each student having access to an input device with which to enter an answer, with a master computer asking the questions and keeping score, and comprising: a means of computing an instantaneous handicap for each student based on a predetermined function of the difference between his score and the player with the highest score, a means of adding such handicap points to the slower students score when they enter a correct answer in such a manner that all the students scores tend to be equalized, thereby encouraging the slower students to maintain an interest in the learning process. 8. The competitive computer educational game recited in claim 2, 3, or 4 further incorporating: a means for recording each students score and handicap for further evaluation by the teacher. | 0.643396 |
7,577,569 | 14 | 15 | 14. A computing device as in claim 11 wherein the device is a handheld device. | 14. A computing device as in claim 11 wherein the device is a handheld device. 15. A computing device as in claim 14 wherein the device is a cell phone. | 0.979688 |
10,162,886 | 1 | 12 | 1. A method comprising, by one or more computer systems: receiving, from a client system of a user of an online social network, a query inputted by the user, wherein the query comprises a plurality of n-grams; parsing the query to identify a subset of n-grams of the plurality of n-grams; generating, for each identified n-gram, an embedding of the n-gram, wherein embeddings correspond to points in a d-dimensional embedding space; determining, for each identified n-gram, one or more word senses corresponding to one or more embeddings of the word senses, respectively; calculating, for each determined word sense for each identified n-gram, a relatedness-score for the word sense based on one or more similarity metrics of the embedding of the word sense and the embeddings of each of the one or more other word senses corresponding to the other identified n-grams, respectively; selecting, for each identified n-gram, one of the one or more word senses determined for the identified n-gram having one or more relatedness-scores, respectively, the selected word sense having a highest relatedness-score of the one or more respective relatedness-scores; identifying one or more objects matching at least a portion of the query; ranking each identified object based on a quality of matching of the object to one or more selected word senses; and sending, to the client system in response to the query, a search-results interface for display, wherein the search-results interface comprises one or more search results corresponding to one or more of the identified objects, respectively, each identified object corresponding to a search result having a rank greater than a threshold rank. | 1. A method comprising, by one or more computer systems: receiving, from a client system of a user of an online social network, a query inputted by the user, wherein the query comprises a plurality of n-grams; parsing the query to identify a subset of n-grams of the plurality of n-grams; generating, for each identified n-gram, an embedding of the n-gram, wherein embeddings correspond to points in a d-dimensional embedding space; determining, for each identified n-gram, one or more word senses corresponding to one or more embeddings of the word senses, respectively; calculating, for each determined word sense for each identified n-gram, a relatedness-score for the word sense based on one or more similarity metrics of the embedding of the word sense and the embeddings of each of the one or more other word senses corresponding to the other identified n-grams, respectively; selecting, for each identified n-gram, one of the one or more word senses determined for the identified n-gram having one or more relatedness-scores, respectively, the selected word sense having a highest relatedness-score of the one or more respective relatedness-scores; identifying one or more objects matching at least a portion of the query; ranking each identified object based on a quality of matching of the object to one or more selected word senses; and sending, to the client system in response to the query, a search-results interface for display, wherein the search-results interface comprises one or more search results corresponding to one or more of the identified objects, respectively, each identified object corresponding to a search result having a rank greater than a threshold rank. 12. The method of claim 1 , wherein each identified object is of a particular object-type, and wherein ranking each identified object is further based on a quality of matching of the object-type of the identified object to one or more selected word senses. | 0.887026 |
9,064,001 | 1 | 4 | 1. A method of building a frequently-asked questions (FAQ) portal, the method comprising: in a processor of an electronic device: creating cluster labels, the cluster labels including predefined universal semantic labels and application-specific labels; applying the cluster labels to clusters of queries within an FAQ application; and adjusting the application-specific labels to support combined and newly created clusters of queries based on application-specific queries within the FAQ application on an ongoing basis and reapplying the universal semantic labels and the adjusted application-specific labels to the combined and newly created clusters of queries to enable automated clustering of queries and association with applicable answers to improve response time by the electronic device for providing a user with an answer to a query. | 1. A method of building a frequently-asked questions (FAQ) portal, the method comprising: in a processor of an electronic device: creating cluster labels, the cluster labels including predefined universal semantic labels and application-specific labels; applying the cluster labels to clusters of queries within an FAQ application; and adjusting the application-specific labels to support combined and newly created clusters of queries based on application-specific queries within the FAQ application on an ongoing basis and reapplying the universal semantic labels and the adjusted application-specific labels to the combined and newly created clusters of queries to enable automated clustering of queries and association with applicable answers to improve response time by the electronic device for providing a user with an answer to a query. 4. The method of claim 1 , further comprising creating one-to-many mappings from the universal semantic labels to the application-specific labels, the one-to-many mappings applying to clusters of queries for which the FAQ application is configured to issue at least one of multiple answers. | 0.703476 |
8,078,621 | 32 | 38 | 32. A computer program product, comprising a non-transitory computer usable medium having a computer readable program code embodied therein, the computer readable program code adapted to be executed to implement a method for creating searchable documents on a computer network, the method comprising: accepting signals provided by a document creator via a user input device to create a document, the created document having a plurality of sections; computer code for accepting signals provided by the document creator via the user input device to assign a value for at least one dimension to each section of the created document; storing the plurality of sections of the created document in a retrievable form; and providing different users access to the plurality of sections of the created document based on the value for the at least one dimension assigned to each section of the created document by: identifying a first user value for at least one dimension to which a first user is associated, the first user value indicating a first community with which the first user is associated; for a first section of the created document, comparing the first user value to the value for the at least one dimension assigned to the first section of the created document; conditionally providing the first user access to the first section of the created document, based on the comparison of the first user value to the value for the at least one dimension assigned to the first section of the created document; for a second section of the created document, comparing the first user value to the value for the at least one dimension assigned to the second section of the created document; conditionally providing the first user access to the second section of the created document, based on the comparison of the first user value to the value for the at least one dimension assigned to the second section of the created document; identifying a second user value for at least one dimension to which a second user is associated, the second user value indicating a second community with which the second user is associated; for the first section of the created document, comparing the second user value to the value for the at least one dimension assigned to the first section of the created document; conditionally providing the second user access to the first section of the created document, based on the comparison of the second user value to the value for the at least one dimension assigned to the first section of the created document; for the second section of the created document, comparing the second user value to the value for the at least one dimension assigned to the second section of the created document; and conditionally providing the second user access to the second section of the created document, based on the comparison of the second user value to the value for the at least one dimension assigned to the second section of the created document. | 32. A computer program product, comprising a non-transitory computer usable medium having a computer readable program code embodied therein, the computer readable program code adapted to be executed to implement a method for creating searchable documents on a computer network, the method comprising: accepting signals provided by a document creator via a user input device to create a document, the created document having a plurality of sections; computer code for accepting signals provided by the document creator via the user input device to assign a value for at least one dimension to each section of the created document; storing the plurality of sections of the created document in a retrievable form; and providing different users access to the plurality of sections of the created document based on the value for the at least one dimension assigned to each section of the created document by: identifying a first user value for at least one dimension to which a first user is associated, the first user value indicating a first community with which the first user is associated; for a first section of the created document, comparing the first user value to the value for the at least one dimension assigned to the first section of the created document; conditionally providing the first user access to the first section of the created document, based on the comparison of the first user value to the value for the at least one dimension assigned to the first section of the created document; for a second section of the created document, comparing the first user value to the value for the at least one dimension assigned to the second section of the created document; conditionally providing the first user access to the second section of the created document, based on the comparison of the first user value to the value for the at least one dimension assigned to the second section of the created document; identifying a second user value for at least one dimension to which a second user is associated, the second user value indicating a second community with which the second user is associated; for the first section of the created document, comparing the second user value to the value for the at least one dimension assigned to the first section of the created document; conditionally providing the second user access to the first section of the created document, based on the comparison of the second user value to the value for the at least one dimension assigned to the first section of the created document; for the second section of the created document, comparing the second user value to the value for the at least one dimension assigned to the second section of the created document; and conditionally providing the second user access to the second section of the created document, based on the comparison of the second user value to the value for the at least one dimension assigned to the second section of the created document. 38. The computer program product of claim 32 , wherein the computer program product is implemented using a plurality of instances of a software program. | 0.722628 |
6,061,652 | 8 | 21 | 8. A speech recognition apparatus comprising a cluster storing means in which a feature vector is to be classified, a membership degree calculating means for calculating, with respect to vectors y and z to be compared, a membership degree of each of the vectors to each of the clusters or a posterior probability of each of the clusters to each of the vectors, and calculating membership degree vectors a and b having the membership degrees of the respective vectors to the respective clusters as elements and a similarity degree calculating means for calculating a distance or a similarity degree between the membership degree vectors, wherein the distance or the similarity degree is rendered a distance or a similarity degree of the feature vectors x and y. | 8. A speech recognition apparatus comprising a cluster storing means in which a feature vector is to be classified, a membership degree calculating means for calculating, with respect to vectors y and z to be compared, a membership degree of each of the vectors to each of the clusters or a posterior probability of each of the clusters to each of the vectors, and calculating membership degree vectors a and b having the membership degrees of the respective vectors to the respective clusters as elements and a similarity degree calculating means for calculating a distance or a similarity degree between the membership degree vectors, wherein the distance or the similarity degree is rendered a distance or a similarity degree of the feature vectors x and y. 21. The speech recognition apparatus according to claim 8, wherein, when the membership degree of a feature vector y.sub.t at a frame t of an input pattern to a cluster in is defined as u.sub.tm and a number of clusters is defined as M, the membership degree vector to which y.sub.t is to be transformed has a value calculated such that K of u.sub.t,h(t,1), u.sub.t,h(t,2), . . . ,u.sub.t,h(t,K) taken from u.sub.t1, . . . ,u.sub.tM in an order of largeness (h(t,k) designates label of a k-th largest cluster at the frame t of the input pattern, K.ltoreq.M) remain as they are and remaining terms have a constant value of u.sub.0 establishing u.sub.t,h(t,1) + . . .+u.sub.t,h(t,K) +u.sub.o (M-K)=1. | 0.775418 |
10,152,526 | 1 | 12 | 1. A method for generating and utilizing synthetic context-based objects, the method comprising: defining, by one or more processors, a context object, wherein the context object comports with at least one constraint that defines a scope and bound of the context object; associating, by one or more processors, a non-contextual data object with the context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein the context object provides a descriptor of the non-contextual data object, wherein the descriptor is not part of the non-contextual data object, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; associating, by one or more processors, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store is a data repository of data that is relevant to the context of the synthetic context-based object, wherein the specific subject-matter for said at least one specific data store in a data structure overlaps a subject-matter of another data store in the data structure, and wherein the synthetic context-based object is mapped to multiple data stores such that there is a one-to-many relationship between the synthetic context-based object and the multiple data stores; receiving, from a requester, a request for data from said at least one specific data store that is associated with the synthetic context-based object, wherein said at least one specific data store is within a database of multiple data stores; and returning, to the requester, data from said at least one specific data store that is associated with the synthetic context-based object. | 1. A method for generating and utilizing synthetic context-based objects, the method comprising: defining, by one or more processors, a context object, wherein the context object comports with at least one constraint that defines a scope and bound of the context object; associating, by one or more processors, a non-contextual data object with the context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein the context object provides a descriptor of the non-contextual data object, wherein the descriptor is not part of the non-contextual data object, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; associating, by one or more processors, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store is a data repository of data that is relevant to the context of the synthetic context-based object, wherein the specific subject-matter for said at least one specific data store in a data structure overlaps a subject-matter of another data store in the data structure, and wherein the synthetic context-based object is mapped to multiple data stores such that there is a one-to-many relationship between the synthetic context-based object and the multiple data stores; receiving, from a requester, a request for data from said at least one specific data store that is associated with the synthetic context-based object, wherein said at least one specific data store is within a database of multiple data stores; and returning, to the requester, data from said at least one specific data store that is associated with the synthetic context-based object. 12. The method of claim 1 , wherein said at least one specific data store is a set of objects that include object oriented programming (OOP) attributes and OOP methods, wherein the OOP attributes are from a group consisting of integers, strings, real numbers, and references to another object, etc., wherein the OOP methods are functions that define a behavior of an object, and wherein the method further comprises: retrieving, by one or more processors, an object from said at least one specific data store that is relevant to the synthetic context-based object; and executing, by one or more processors, the retrieved object. | 0.697786 |
9,298,680 | 13 | 14 | 13. A data processing system comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: open a plurality of selected hypertext documents, create an affinity matrix for each of the selected hypertext documents, calculate an affinity indicator for each pair of selected hypertext documents in the affinity matrix according to a comparison between semantic information of a content of each selected hypertext document of the pair, group the selected hypertext documents into a set of groups by assigning each selected hypertext document to at least one group in the set of the groups according to the affinity indicators, wherein a number of selected hypertext documents in each group of the set of groups is limited to a predetermined number of selected hypertext documents and wherein the instructions to group the selected hypertext documents into the set of groups further causes the processor to: group the selected hypertext documents into a particular group up to the predetermined number of selected hypertext documents by: initializing the set of groups by assigning each single hypertext document to its own group and setting an affinity index for each group accordingly, and repeating the steps of: determining a pair of initialized groups with highest affinity indexes, merging the pair of initialized groups into a new group, for each new pair of groups, calculating a sum of the corresponding selected hypertext documents within the group, determining whether the sum of the corresponding selected hypertext documents exceeds the predetermined number of selected hypertext documents, blocking each new pair of groups between the new group and each other group to prevent the merging thereof when the sum of the corresponding selected hypertext documents exceeds the predetermined number of selected hypertext documents, and calculating the affinity index for each new group according to the affinity index between the initialized groups and the corresponding other group, until the highest affinity index is lower than the affinity threshold and the number of the groups is lower than or equal to a predetermined number of groups, and display the selected hypertext documents in an arrangement corresponding to the grouping thereof. | 13. A data processing system comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: open a plurality of selected hypertext documents, create an affinity matrix for each of the selected hypertext documents, calculate an affinity indicator for each pair of selected hypertext documents in the affinity matrix according to a comparison between semantic information of a content of each selected hypertext document of the pair, group the selected hypertext documents into a set of groups by assigning each selected hypertext document to at least one group in the set of the groups according to the affinity indicators, wherein a number of selected hypertext documents in each group of the set of groups is limited to a predetermined number of selected hypertext documents and wherein the instructions to group the selected hypertext documents into the set of groups further causes the processor to: group the selected hypertext documents into a particular group up to the predetermined number of selected hypertext documents by: initializing the set of groups by assigning each single hypertext document to its own group and setting an affinity index for each group accordingly, and repeating the steps of: determining a pair of initialized groups with highest affinity indexes, merging the pair of initialized groups into a new group, for each new pair of groups, calculating a sum of the corresponding selected hypertext documents within the group, determining whether the sum of the corresponding selected hypertext documents exceeds the predetermined number of selected hypertext documents, blocking each new pair of groups between the new group and each other group to prevent the merging thereof when the sum of the corresponding selected hypertext documents exceeds the predetermined number of selected hypertext documents, and calculating the affinity index for each new group according to the affinity index between the initialized groups and the corresponding other group, until the highest affinity index is lower than the affinity threshold and the number of the groups is lower than or equal to a predetermined number of groups, and display the selected hypertext documents in an arrangement corresponding to the grouping thereof. 14. The data processing system according to claim 13 , wherein the selected hypertext documents are web pages. | 0.837758 |
8,781,989 | 7 | 8 | 7. A computer based system for predicting a data value, said system comprising: a processor capable of executing machine instructions; the machine instructions including a means for predicting a predicted data value of a first data set at a predicted dimension value utilizing a focus topic profile; and the means for predicting the predicted data value further comprises a modeling package capable of: receiving a base dimension value having a base focus topic value; receiving a predicted dimension value having a difference dimension value from the base dimension value; analyzing the focus topic profile over at least one dimension value to identify a most similar focus topic value to the base focus topic value; the dimension value at the most similar focus topic value being a selected dimension value; and selecting at least one data value from the first data set at the difference dimension value from the selected dimension value as the predicted data value at the predicted dimension value. | 7. A computer based system for predicting a data value, said system comprising: a processor capable of executing machine instructions; the machine instructions including a means for predicting a predicted data value of a first data set at a predicted dimension value utilizing a focus topic profile; and the means for predicting the predicted data value further comprises a modeling package capable of: receiving a base dimension value having a base focus topic value; receiving a predicted dimension value having a difference dimension value from the base dimension value; analyzing the focus topic profile over at least one dimension value to identify a most similar focus topic value to the base focus topic value; the dimension value at the most similar focus topic value being a selected dimension value; and selecting at least one data value from the first data set at the difference dimension value from the selected dimension value as the predicted data value at the predicted dimension value. 8. The computer based system of claim 7 further comprising: a means for analyzing a second data set using a latent variable method using at least one focus topic; and the focus topic profile comprises at least one focus topic value of the at least one focus topic from the second data set. | 0.669336 |
9,737,759 | 2 | 3 | 2. The method of claim 1 , wherein said parsing further comprises removing all quantity values and quantity units from said parsed text segments, and wherein said ranking said found exercise text matches comprises searching a past history of said user for previous matches, and selecting from said past history a most recent exercise tracked as said exercise to be tracked. | 2. The method of claim 1 , wherein said parsing further comprises removing all quantity values and quantity units from said parsed text segments, and wherein said ranking said found exercise text matches comprises searching a past history of said user for previous matches, and selecting from said past history a most recent exercise tracked as said exercise to be tracked. 3. The method of claim 2 , wherein upon an exercise match not being found in said searching, then searching a user population history for previous matches, and selecting an exercise that has been most often tracked as said exercise to be tracked. | 0.931092 |
9,413,622 | 10 | 11 | 10. A client device to receive server information, comprising: a web browser that receives authorization, via a digital certificate, to permit access of the client device to a web page content server, and that sends a request for web page content to the web page content server, the web page content including logging information associated with at least one of a plurality of monitored servers, the logging information comprising at least one of start/stop time information and error information; and a physical receiver associated with the web browser to receive the web page content; wherein the web page content is parsable to extract particular information about a particular server from the at least one of the plurality of monitored servers. | 10. A client device to receive server information, comprising: a web browser that receives authorization, via a digital certificate, to permit access of the client device to a web page content server, and that sends a request for web page content to the web page content server, the web page content including logging information associated with at least one of a plurality of monitored servers, the logging information comprising at least one of start/stop time information and error information; and a physical receiver associated with the web browser to receive the web page content; wherein the web page content is parsable to extract particular information about a particular server from the at least one of the plurality of monitored servers. 11. The client device to receive server information according to claim 10 , wherein: the web page content is received, via a physical receiver associated with the client device, according to an access level associated with the digital certificate. | 0.525 |
7,647,309 | 2 | 21 | 2. A computer-implemented method for generating a display configuration, the method comprising: under control of one or more computing devices configured with executable instructions, identifying a plurality of items for which a display configuration is operable to be generated, each of the plurality of items being associated with at least one category; identifying browse relevance data for each of the plurality of items with respect to the at least one category for each item; computing a browse relevance score for each of the plurality of items with respect to the at least one category from the browse relevance data, each item capable of having a different browse relevance score for the at least one category associated with that item, each browse relevance score being calculated by summing a category fit score, a browse score, and a popularity score and multiplying a result of the summing by a price range score for the item, the popularity score for each item capable of being adjusted using at least one of newness data relating to an amount of time that the item has been available and a prediction boost score for each item that is part of a market trend or based on a popular theme; for a specified category for which the display configuration is to be generated, identifying items from the plurality of items that correspond to the specified category based on their respective browse relevance scores; and generating the display configuration to include the identified items in an arrangement based at least in part upon the respective browse relevance scores for the specified categories. | 2. A computer-implemented method for generating a display configuration, the method comprising: under control of one or more computing devices configured with executable instructions, identifying a plurality of items for which a display configuration is operable to be generated, each of the plurality of items being associated with at least one category; identifying browse relevance data for each of the plurality of items with respect to the at least one category for each item; computing a browse relevance score for each of the plurality of items with respect to the at least one category from the browse relevance data, each item capable of having a different browse relevance score for the at least one category associated with that item, each browse relevance score being calculated by summing a category fit score, a browse score, and a popularity score and multiplying a result of the summing by a price range score for the item, the popularity score for each item capable of being adjusted using at least one of newness data relating to an amount of time that the item has been available and a prediction boost score for each item that is part of a market trend or based on a popular theme; for a specified category for which the display configuration is to be generated, identifying items from the plurality of items that correspond to the specified category based on their respective browse relevance scores; and generating the display configuration to include the identified items in an arrangement based at least in part upon the respective browse relevance scores for the specified categories. 21. The computer-implemented method of claim 2 , wherein the popularity score is determined based at least in part upon a sales rank score. | 0.636126 |
8,713,024 | 7 | 9 | 7. One or more computer storage media having stored thereon a data structure for storing data representing a forward index that is used to rank search results based on a search query, the data structure comprising: a first data field containing document identification information that identifies a particular document; a second data field containing a compressed token stream of the document, wherein the compressed token stream is a second token stream based on a first token stream, the compressed token stream is a compressed version of the token stream comprising context streams of the document selected from the first token stream, wherein the one or more context streams represent individual portions of the document; a third data field containing document-specific data representing static features of the document that are used to rank the document when a query is received; and a fourth data field containing positional information that indicates the position of one or more relevant data associated with the document that is frequently used to calculate a ranking of the document. | 7. One or more computer storage media having stored thereon a data structure for storing data representing a forward index that is used to rank search results based on a search query, the data structure comprising: a first data field containing document identification information that identifies a particular document; a second data field containing a compressed token stream of the document, wherein the compressed token stream is a second token stream based on a first token stream, the compressed token stream is a compressed version of the token stream comprising context streams of the document selected from the first token stream, wherein the one or more context streams represent individual portions of the document; a third data field containing document-specific data representing static features of the document that are used to rank the document when a query is received; and a fourth data field containing positional information that indicates the position of one or more relevant data associated with the document that is frequently used to calculate a ranking of the document. 9. The one or more computer storage media of claim 7 , wherein the static features include one or more of page rank, language, total anchor count, and type of page. | 0.939617 |
9,124,908 | 13 | 14 | 13. The device of claim 9 , wherein the operations further comprise: filtering the cluster of comments based on subject matter to generate a filtered cluster of comments; and enabling access to the filtered cluster of comments for a recipient device. | 13. The device of claim 9 , wherein the operations further comprise: filtering the cluster of comments based on subject matter to generate a filtered cluster of comments; and enabling access to the filtered cluster of comments for a recipient device. 14. The device of claim 13 , wherein the filtering of the cluster of comments includes replacing a portion of the cluster of comments with substitute content. | 0.932937 |
8,874,428 | 1 | 4 | 1. A method for fast translation memory search, comprising: in response to an input query string, identifying a plurality of hypothesis strings stored in a translation memory as candidates to match the query string; eliminating one or more candidates, using a processor, where string lengths between the candidates and the query string are at least a cutoff value representing a string edit distance; eliminating one or more candidates where differences in word frequency Distributions between the candidates and the query string are at least the cutoff value; eliminating one or more candidates by employing a dynamic programming matrix where string edit distances between the candidates and the query string are at least the cutoff value; and outputting a number of remaining candidates as matches to the query string. | 1. A method for fast translation memory search, comprising: in response to an input query string, identifying a plurality of hypothesis strings stored in a translation memory as candidates to match the query string; eliminating one or more candidates, using a processor, where string lengths between the candidates and the query string are at least a cutoff value representing a string edit distance; eliminating one or more candidates where differences in word frequency Distributions between the candidates and the query string are at least the cutoff value; eliminating one or more candidates by employing a dynamic programming matrix where string edit distances between the candidates and the query string are at least the cutoff value; and outputting a number of remaining candidates as matches to the query string. 4. The method as recited in claim 1 , further comprising: reducing the number of remaining candidates as matches to the query string by determining a top n remaining candidates with a lowest string edit distance as matches to the query string, wherein n is any positive integer. | 0.805322 |
7,882,100 | 2 | 6 | 2. The method of claim 1 , wherein said transforming step includes determining a portion of the left deep nested loop join tree requiring transformation into a bushy tree shape for generating a semantically correct query execution plan. | 2. The method of claim 1 , wherein said transforming step includes determining a portion of the left deep nested loop join tree requiring transformation into a bushy tree shape for generating a semantically correct query execution plan. 6. The method of claim 2 , wherein said portion of the left deep nested loop join tree requiring transformation includes an outer join. | 0.923643 |
7,996,372 | 1 | 2 | 1. A method for automating generation of responses to communications, said method comprising the steps of: A. Receiving an incoming communication from a transmitting party; B. Creating an electronic file for such received communication; C. Extracting a first set of data from said electronic file; D. Storing the first set of data in a database; E. Identifying one or more keywords required to be found in the first set of data; F. Comparing the first set of data to the key words to create a second set of data stored in the database, the second set of data extracted from the first set of data and being key words found in the first set of data; G. Storing a plurality of pre-defined possible responsive templates on a computer system, all of which are related to the first set of data; H. Comparing the second set of data to the plurality of the templates stored on the computer system; I. Performing a statistical analysis on a group of the plurality of templates and second set of data; J. Utilizing a computer system to automatically select a pre-defined responsive template based on at least one of said first set of data, said second set of data, and said statistical analysis; K. Utilizing a computer system to automatically generate an actual responsive communication based on said selected pre-defined responsive template; and L. Transmitting said actual responsive communication. | 1. A method for automating generation of responses to communications, said method comprising the steps of: A. Receiving an incoming communication from a transmitting party; B. Creating an electronic file for such received communication; C. Extracting a first set of data from said electronic file; D. Storing the first set of data in a database; E. Identifying one or more keywords required to be found in the first set of data; F. Comparing the first set of data to the key words to create a second set of data stored in the database, the second set of data extracted from the first set of data and being key words found in the first set of data; G. Storing a plurality of pre-defined possible responsive templates on a computer system, all of which are related to the first set of data; H. Comparing the second set of data to the plurality of the templates stored on the computer system; I. Performing a statistical analysis on a group of the plurality of templates and second set of data; J. Utilizing a computer system to automatically select a pre-defined responsive template based on at least one of said first set of data, said second set of data, and said statistical analysis; K. Utilizing a computer system to automatically generate an actual responsive communication based on said selected pre-defined responsive template; and L. Transmitting said actual responsive communication. 2. The method of claim 1 , wherein the steps of C-L are automated. | 0.94686 |
8,190,439 | 10 | 12 | 10. A method according to claim 6 , wherein assigning the at least one class to the element comprises: comparing the contents of the element to contents of a plurality of predefined lists of words, each of the predefined list of words corresponding to a respective predefined class; and if the contents of the element correspond to a word in one of the predefined lists of words, assigning the class corresponding to the list to the element. | 10. A method according to claim 6 , wherein assigning the at least one class to the element comprises: comparing the contents of the element to contents of a plurality of predefined lists of words, each of the predefined list of words corresponding to a respective predefined class; and if the contents of the element correspond to a word in one of the predefined lists of words, assigning the class corresponding to the list to the element. 12. A method according to claim 10 , wherein assigning the class to the row comprises: assigning to the row a class selected from a plurality of possible classes, the plurality of possible classes comprising the classes assigned to the elements of the row, wherein the assigned class simultaneously optimizes at least two criteria, including: (a) the class is assigned to as large a number of the elements in the row as possible; and (b) the predefined list of words corresponding to the class has as small a number of words as possible. | 0.721184 |
8,515,923 | 7 | 21 | 7. The DRM System of claim 1 , wherein said electronic document repository includes metadata on each document of said accessible documents. | 7. The DRM System of claim 1 , wherein said electronic document repository includes metadata on each document of said accessible documents. 21. The DRM System of claim 7 , wherein said metadata includes document title information. | 0.961961 |
8,010,525 | 1 | 10 | 1. A computer-implemented method comprising: receiving a search query; generating first search results that identify resources that a search engine has identified as being responsive to the search query; identifying search modes based on the search query, the resources, or both the search query and the resources; providing a first user interface that presents for display at least a portion of the first search results and a respective search mode selector for each of one or more of the identified search modes; receiving user input selecting a first search mode by selecting one of the search mode selectors, wherein: the first search mode is associated with a first collection of records that share a first common attribute structure, a second of the search modes is associated with a second collection of records that share a second common attribute structure, and the first common attribute structure is different from the second common attribute structure; generating second search results that satisfy the search query and that refer to mode-specific records from the first collection of records that are associated with the first search mode, each of the search modes being associated with a particular collection of records from among multiple collections of records; formatting a plurality of the second search results using a mode-specific presentation template that is associated with the first search mode to generate formatted search results; and providing a second user interface that presents for display the formatted search results. | 1. A computer-implemented method comprising: receiving a search query; generating first search results that identify resources that a search engine has identified as being responsive to the search query; identifying search modes based on the search query, the resources, or both the search query and the resources; providing a first user interface that presents for display at least a portion of the first search results and a respective search mode selector for each of one or more of the identified search modes; receiving user input selecting a first search mode by selecting one of the search mode selectors, wherein: the first search mode is associated with a first collection of records that share a first common attribute structure, a second of the search modes is associated with a second collection of records that share a second common attribute structure, and the first common attribute structure is different from the second common attribute structure; generating second search results that satisfy the search query and that refer to mode-specific records from the first collection of records that are associated with the first search mode, each of the search modes being associated with a particular collection of records from among multiple collections of records; formatting a plurality of the second search results using a mode-specific presentation template that is associated with the first search mode to generate formatted search results; and providing a second user interface that presents for display the formatted search results. 10. The computer-implemented method of claim 1 , further comprising: identifying mode-specific user interface elements that are associated with the first search mode, wherein the second user interface further presents for display the mode-specific user interface elements; receiving user input selecting one of the mode-specific user interface elements; generating a display of third search results based on the selected mode-specific user interface element; and providing a third user interface that presents for display the generated display of third search results. | 0.713998 |
8,364,509 | 1 | 40 | 1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user. | 1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user. 40. The method of claim 1 , wherein receiving at least one query includes receiving a query for agent productivity data, the agent productivity data being specific to at least one given date. | 0.742588 |
9,300,760 | 11 | 15 | 11. A computer-implemented method comprising: identifying a plurality of computing devices, each computing device of the plurality of computing devices having a software component comprising a first translator component for translating programs in a portable format to a machine-specific instruction set, and a first sandbox component for executing programs translated to the machine-specific instruction set on the computing device using software-based fault isolation; identifying one or more second computing devices, from among of the plurality of computing devices, that have a given hardware configuration; and transmitting a second translator component and a second sandbox component to each of the second computing devices wherein each of the second computing devices is configured to: (i) receive the second translator component and the second sandbox component, and (ii) configure the software component of the second computing device to use the second translator component instead of using the first translator component to translate programs in the portable format to a machine-specific instruction set of the second computing device and to use the second sandbox component instead of using the first sandbox component to execute programs translated to the machine-specific instruction set of the second computing device. | 11. A computer-implemented method comprising: identifying a plurality of computing devices, each computing device of the plurality of computing devices having a software component comprising a first translator component for translating programs in a portable format to a machine-specific instruction set, and a first sandbox component for executing programs translated to the machine-specific instruction set on the computing device using software-based fault isolation; identifying one or more second computing devices, from among of the plurality of computing devices, that have a given hardware configuration; and transmitting a second translator component and a second sandbox component to each of the second computing devices wherein each of the second computing devices is configured to: (i) receive the second translator component and the second sandbox component, and (ii) configure the software component of the second computing device to use the second translator component instead of using the first translator component to translate programs in the portable format to a machine-specific instruction set of the second computing device and to use the second sandbox component instead of using the first sandbox component to execute programs translated to the machine-specific instruction set of the second computing device. 15. The method of claim 11 wherein the second sandbox component comprises a run-time library that provides one or more interfaces, each interface including an invocation mechanism to facilitate access to resources outside the second sandbox component by a program executing in the second sandbox component. | 0.753226 |
9,620,128 | 12 | 13 | 12. The computationally-implemented method of claim 11 , wherein said generating adaptation result data that is based on a result of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data comprises: observing the speech-facilitated transaction; creating adaptation result data based on a result of the observed speech-facilitated transaction; and determining whether to modify the adaptation data based on the created adaptation result data. | 12. The computationally-implemented method of claim 11 , wherein said generating adaptation result data that is based on a result of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data comprises: observing the speech-facilitated transaction; creating adaptation result data based on a result of the observed speech-facilitated transaction; and determining whether to modify the adaptation data based on the created adaptation result data. 13. The computationally-implemented method of claim 12 , wherein said creating adaptation result data based on a result of the observed speech-facilitated transaction comprises: creating adaptation result data based on a measured statistic of the observed speech-facilitated transaction. | 0.956541 |
9,460,076 | 14 | 15 | 14. The method of claim 13 , further comprising generating a plurality of semantic word vectors from the plurality of sentences from the corpus document, and wherein the representation of the context is a sum of the plurality of semantic word vectors. | 14. The method of claim 13 , further comprising generating a plurality of semantic word vectors from the plurality of sentences from the corpus document, and wherein the representation of the context is a sum of the plurality of semantic word vectors. 15. The method of claim 14 , wherein generating the plurality of semantic word vectors includes using a latent semantic analysis algorithm. | 0.962654 |
9,984,392 | 1 | 5 | 1. A computer-implemented method comprising: accessing profiles for a plurality of users of the social networking system, each profile identifying a connection to each of a plurality of other users of the social networking system, the plurality of users comprising a viewing user; receiving a message from a third party system that is in a different domain than the social networking system, the message identifying the third party system and describing an action performed on a web page of the third party system by the viewing user; generating, by a computer of the social networking system, a confirmation message for display in a user interface to the viewing user on the third party system, the confirmation message providing an example of a story that could be provided to a plurality of connections of the viewing user, the story describing the action performed on the third party system by the viewing user; sending, by the computer of the social networking system to the third party system, the generated confirmation message for display in the user interface within a nested iframe on the web page of the third party system, the nested iframe being within a domain of the social networking system and allowing communication from the social networking system to the user on the web page of the third party system without sharing personal information that the social networking system has for the viewing user; receiving an indication of whether the viewing user opts in or opts out of allowing the story describing the action performed on the third party system by the viewing user to be provided to the plurality of connections based on the user having selected an opt in or opt out feature in the nested iframe on the user interface; based on the viewing user opting in to allowing the story to be provided to the plurality of connections, generating a plurality of news feeds each including the story describing the action in addition to a plurality of other stories describing other actions taken by other users of the social networking system; and providing for display to each of the plurality of connections a user interface including the generated news feed for the connection, wherein different connections receive different sets of other stories in the news feed. | 1. A computer-implemented method comprising: accessing profiles for a plurality of users of the social networking system, each profile identifying a connection to each of a plurality of other users of the social networking system, the plurality of users comprising a viewing user; receiving a message from a third party system that is in a different domain than the social networking system, the message identifying the third party system and describing an action performed on a web page of the third party system by the viewing user; generating, by a computer of the social networking system, a confirmation message for display in a user interface to the viewing user on the third party system, the confirmation message providing an example of a story that could be provided to a plurality of connections of the viewing user, the story describing the action performed on the third party system by the viewing user; sending, by the computer of the social networking system to the third party system, the generated confirmation message for display in the user interface within a nested iframe on the web page of the third party system, the nested iframe being within a domain of the social networking system and allowing communication from the social networking system to the user on the web page of the third party system without sharing personal information that the social networking system has for the viewing user; receiving an indication of whether the viewing user opts in or opts out of allowing the story describing the action performed on the third party system by the viewing user to be provided to the plurality of connections based on the user having selected an opt in or opt out feature in the nested iframe on the user interface; based on the viewing user opting in to allowing the story to be provided to the plurality of connections, generating a plurality of news feeds each including the story describing the action in addition to a plurality of other stories describing other actions taken by other users of the social networking system; and providing for display to each of the plurality of connections a user interface including the generated news feed for the connection, wherein different connections receive different sets of other stories in the news feed. 5. The method of claim 1 , further comprising, based on the viewing user opting out, preventing the story describing the action performed on the third party system from being provided to connections of the viewing user. | 0.789017 |
7,836,010 | 13 | 18 | 13. A data processing system for obtaining representative text items from a plurality of text items in an active computer tasks, the system comprising: a data processor for processing data; a data storage device for storing instructions; and a data transmission path coupled to the data processor and the data storage device; wherein the instructions, when executed by the data processor, controls the data processing system to perform the machine-implemented steps of: receiving first information indicative of a first active computer task, the first information including a first plurality of text items and a stylistic attribute associated with a first text item in the first plurality of text items; determining a genre associated with the first active computer task; determining a first representative stylistic attribute value of the first plurality of text items based on a first frequency of occurrence of the stylistic attribute in the first active computer task; for each of the first plurality of text items, assigning a first weight with a first magnitude, the first magnitude being determined based on the genre and the first representative stylistic attribute; ranking the first plurality of text items based on the first weight assigned to each of the first plurality of text items to produce a first plurality of ranked text items; generating and storing first representative text items based on the first plurality of ranked text items; wherein the first active computer task is a task other than entering search terms for the purpose of retrieving information; receiving second information indicative of a second active computer task, the second active computer task being different than the first active computer task, the second information including a second plurality of text items and a stylistic attribute associated with a second text item in the second plurality of text items, wherein the second plurality of text items is different than the first plurality of text items; determining a second representative stylistic attribute value of the second plurality of text items based on a second frequency of occurrence of the stylistic attribute in the second active computer task, the second representative stylistic attribute value being different than the first representative stylistic attribute value; for each of the second plurality of text items, assigning a second weight with a second magnitude that is determined based on the second representative stylistic attribute, the second magnitude being different that the first magnitude; ranking the second plurality of text items based on the second weight assigned to each of the second plurality of text items to produce a second plurality of ranked text items; and generating and storing second representative text items based on the second plurality of ranked text items; wherein the second active computer task is a task other than entering search terms for the purpose of retrieving information. | 13. A data processing system for obtaining representative text items from a plurality of text items in an active computer tasks, the system comprising: a data processor for processing data; a data storage device for storing instructions; and a data transmission path coupled to the data processor and the data storage device; wherein the instructions, when executed by the data processor, controls the data processing system to perform the machine-implemented steps of: receiving first information indicative of a first active computer task, the first information including a first plurality of text items and a stylistic attribute associated with a first text item in the first plurality of text items; determining a genre associated with the first active computer task; determining a first representative stylistic attribute value of the first plurality of text items based on a first frequency of occurrence of the stylistic attribute in the first active computer task; for each of the first plurality of text items, assigning a first weight with a first magnitude, the first magnitude being determined based on the genre and the first representative stylistic attribute; ranking the first plurality of text items based on the first weight assigned to each of the first plurality of text items to produce a first plurality of ranked text items; generating and storing first representative text items based on the first plurality of ranked text items; wherein the first active computer task is a task other than entering search terms for the purpose of retrieving information; receiving second information indicative of a second active computer task, the second active computer task being different than the first active computer task, the second information including a second plurality of text items and a stylistic attribute associated with a second text item in the second plurality of text items, wherein the second plurality of text items is different than the first plurality of text items; determining a second representative stylistic attribute value of the second plurality of text items based on a second frequency of occurrence of the stylistic attribute in the second active computer task, the second representative stylistic attribute value being different than the first representative stylistic attribute value; for each of the second plurality of text items, assigning a second weight with a second magnitude that is determined based on the second representative stylistic attribute, the second magnitude being different that the first magnitude; ranking the second plurality of text items based on the second weight assigned to each of the second plurality of text items to produce a second plurality of ranked text items; and generating and storing second representative text items based on the second plurality of ranked text items; wherein the second active computer task is a task other than entering search terms for the purpose of retrieving information. 18. The system of claim 13 , wherein the at least one style attribute includes at least one of a list element, a heading, a table heading, a table cell, a navigation bar, a menu, a header, and a footer. | 0.610039 |
9,075,988 | 1 | 5 | 1. An apparatus comprising a first computing device including a computer processor and a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions that, when executed by the computer processor, cause the apparatus to carry out the steps of: identifying a candidate application to be installed on the first computing device; identifying a trusted user that a user of the first computing device has identified and indicated as being trusted; receiving from a second computing device, an indication of installation activity of said candidate application by said trusted user on said second computing device; and determining whether to install the candidate application on the first computing device in dependence upon the indication of installation activity. | 1. An apparatus comprising a first computing device including a computer processor and a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions that, when executed by the computer processor, cause the apparatus to carry out the steps of: identifying a candidate application to be installed on the first computing device; identifying a trusted user that a user of the first computing device has identified and indicated as being trusted; receiving from a second computing device, an indication of installation activity of said candidate application by said trusted user on said second computing device; and determining whether to install the candidate application on the first computing device in dependence upon the indication of installation activity. 5. The apparatus of claim 1 further comprising computer program instructions that, when executed by the computer processor, cause the apparatus to carry out the step of storing in a repository, information identifying the installation activity associated with one or more applications for each trusted user. | 0.713084 |
8,548,153 | 1 | 17 | 1. A method for implementing customized rules for controlling incoming customer communications, comprising: providing an initial menu for customizing rules for controlling incoming customer communications, the initial menu including a selectable option to modify an existing customized rule for controlling incoming customer communications and a selectable option to create a new customized rule for controlling incoming customer communications; processing a request to create a new customized rule for controlling incoming customer communications, wherein the new customized rule is configured to challenge a source of inbound communications for information configured to authorize the inbound communications; providing an initial selection criteria menu to create the new customized rule for controlling incoming customer communications, the initial selection criteria menu indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; processing a response indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; when the new customized rule will be built using a preexisting template, providing a list of preexisting templates for creating new customized rules for controlling incoming customer communications, processing a received selection of a preexisting template from the list of preexisting templates, accepting input to populate the selected preexisting template, and storing a new customized rule based on the selected preexisting template and including accepted input, wherein the stored new customized rule is specified to apply to inbound communications; and when the new customized rule will be built starting from initial blank rule criteria, providing initial blank rule criteria for creating a new customized rule for controlling incoming customer communications, processing a received selection of initial criteria from the initial blank rule criteria, providing a list of rule conditions for the selected initial criteria for the new customized rule, processing a received selection of rule conditions for the selected initial criteria for the new customized rule, and creating and storing a new customized rule based on the selected initial criteria and the selected rule conditions; and wherein the stored new customized rule is implemented at an internal network node of a communications service provider to process communications in accordance with requests and selections received from customers using customer equipment, and wherein the stored new customized rule further includes a selected disposition for when the selected initial criteria and selected rule conditions are met. | 1. A method for implementing customized rules for controlling incoming customer communications, comprising: providing an initial menu for customizing rules for controlling incoming customer communications, the initial menu including a selectable option to modify an existing customized rule for controlling incoming customer communications and a selectable option to create a new customized rule for controlling incoming customer communications; processing a request to create a new customized rule for controlling incoming customer communications, wherein the new customized rule is configured to challenge a source of inbound communications for information configured to authorize the inbound communications; providing an initial selection criteria menu to create the new customized rule for controlling incoming customer communications, the initial selection criteria menu indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; processing a response indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; when the new customized rule will be built using a preexisting template, providing a list of preexisting templates for creating new customized rules for controlling incoming customer communications, processing a received selection of a preexisting template from the list of preexisting templates, accepting input to populate the selected preexisting template, and storing a new customized rule based on the selected preexisting template and including accepted input, wherein the stored new customized rule is specified to apply to inbound communications; and when the new customized rule will be built starting from initial blank rule criteria, providing initial blank rule criteria for creating a new customized rule for controlling incoming customer communications, processing a received selection of initial criteria from the initial blank rule criteria, providing a list of rule conditions for the selected initial criteria for the new customized rule, processing a received selection of rule conditions for the selected initial criteria for the new customized rule, and creating and storing a new customized rule based on the selected initial criteria and the selected rule conditions; and wherein the stored new customized rule is implemented at an internal network node of a communications service provider to process communications in accordance with requests and selections received from customers using customer equipment, and wherein the stored new customized rule further includes a selected disposition for when the selected initial criteria and selected rule conditions are met. 17. The method according to claim 1 , further comprising: overriding the stored new customized rule when an originator of a communication enters an override indicator and processing the communication in accordance with the override indicator. | 0.7287 |
9,075,824 | 1 | 17 | 1. A retrieval method comprising: learning a projection for embedding an original image representation in an embedding space, the original image representation being based on features extracted from the image, the projection being learned from category-labeled training data to optimize a classification rate on the training data, the learning of the projection including, for a plurality of iterations: selecting a sample from the training data; embedding the sample with a current projection; scoring the embedded sample with current first and second classifiers, the first classifier corresponding to a category of the label of the sample, the second classifier corresponding to a different category, selected from a set of categories; updated the current projection and at least one of the current first and second classifier for iterations where the second classifier generates a higher score than the first classifier, the updated projection serving as the current projection for a subsequent iteration, each of the updated classifiers serving as the current classifier for the respective category for a subsequent iteration; and storing one of the updated projections as the learned projection; and with a processor, for each of plurality of database images, computing a comparison measure between a query image and the database image, the comparison measure being computed in the embedding space, respective original image representations of the query image and the database image being embedded in the embedding space with the projection; and providing for retrieving at least one of the database images based on the comparison. | 1. A retrieval method comprising: learning a projection for embedding an original image representation in an embedding space, the original image representation being based on features extracted from the image, the projection being learned from category-labeled training data to optimize a classification rate on the training data, the learning of the projection including, for a plurality of iterations: selecting a sample from the training data; embedding the sample with a current projection; scoring the embedded sample with current first and second classifiers, the first classifier corresponding to a category of the label of the sample, the second classifier corresponding to a different category, selected from a set of categories; updated the current projection and at least one of the current first and second classifier for iterations where the second classifier generates a higher score than the first classifier, the updated projection serving as the current projection for a subsequent iteration, each of the updated classifiers serving as the current classifier for the respective category for a subsequent iteration; and storing one of the updated projections as the learned projection; and with a processor, for each of plurality of database images, computing a comparison measure between a query image and the database image, the comparison measure being computed in the embedding space, respective original image representations of the query image and the database image being embedded in the embedding space with the projection; and providing for retrieving at least one of the database images based on the comparison. 17. A computer program product comprising a non-transitory recoding medium storing instructions which when executed by a computer, perform the method of claim 1 . | 0.808511 |
9,740,738 | 5 | 9 | 5. One or more non-transitory computer-readable media storing instructions which, when executed, instruct at least one processor to perform actions comprising: receiving an indication of a report comprising a syntax tree that includes one or more data attributes identified by an attribute identifier and one or more conditions on the one or more data attributes, the syntax tree comprising a format that is abstracted from a particular one of at least two different storage formats of at least two datastores; normalizing the attribute identifiers to generate normalized attribute identifiers for the one or more data attributes to provide a consistent attribute identifier across the at least two datastores; receiving storage metadata describing at least one of the at least two datastores storing data for the normalized attribute identifiers, the metadata including a description of the one or more data attributes and data retrieval latency for the at least two datastores; generating at least one query to retrieve data from one or more datastores using the one or more data attributes from the at least two datastores identified by the normalized attribute identifiers and the description of the one or more data attributes from the received storage metadata; providing, to at least one data consumer associated with the report, at least one time estimate for generating the report based on retrieving the data for the one or more data attributes identified by the normalized attribute identifiers from individual ones of the at least two datastores, the at least one time estimate based at least partly on the data retrieval latency for the individual ones of the at least two datastores; receiving a selection of a datastore by the at least one data consumer, the selection provided by the at least one data consumer based on the at least one time estimate; modifying the at least one query to access the datastore of the at least two datastores based on the selection of the datastore by the at least one data consumer; executing the at least one modified query using the storage metadata and the one or more data attributes identified by the normalized attribute identifiers obtained from the syntax tree to retrieve data for the one or more data attribute identified by the normalized attribute identifiers from the at least two datastores; and generating the report including the data retrieved based on the executing of the at least one modified query. | 5. One or more non-transitory computer-readable media storing instructions which, when executed, instruct at least one processor to perform actions comprising: receiving an indication of a report comprising a syntax tree that includes one or more data attributes identified by an attribute identifier and one or more conditions on the one or more data attributes, the syntax tree comprising a format that is abstracted from a particular one of at least two different storage formats of at least two datastores; normalizing the attribute identifiers to generate normalized attribute identifiers for the one or more data attributes to provide a consistent attribute identifier across the at least two datastores; receiving storage metadata describing at least one of the at least two datastores storing data for the normalized attribute identifiers, the metadata including a description of the one or more data attributes and data retrieval latency for the at least two datastores; generating at least one query to retrieve data from one or more datastores using the one or more data attributes from the at least two datastores identified by the normalized attribute identifiers and the description of the one or more data attributes from the received storage metadata; providing, to at least one data consumer associated with the report, at least one time estimate for generating the report based on retrieving the data for the one or more data attributes identified by the normalized attribute identifiers from individual ones of the at least two datastores, the at least one time estimate based at least partly on the data retrieval latency for the individual ones of the at least two datastores; receiving a selection of a datastore by the at least one data consumer, the selection provided by the at least one data consumer based on the at least one time estimate; modifying the at least one query to access the datastore of the at least two datastores based on the selection of the datastore by the at least one data consumer; executing the at least one modified query using the storage metadata and the one or more data attributes identified by the normalized attribute identifiers obtained from the syntax tree to retrieve data for the one or more data attribute identified by the normalized attribute identifiers from the at least two datastores; and generating the report including the data retrieved based on the executing of the at least one modified query. 9. The one or more non-transitory computer-readable media of claim 5 , wherein the at least two datastores include at least one datastore that employs a non-relational storage format and the at least one datastore that employs a relational storage format. | 0.893216 |
10,031,967 | 12 | 16 | 12. The system of claim 11 , wherein the control circuitry is further configured to: if both the first strength of association and the second strength of association exceed the threshold, execute a search relating to the first conversation; if the first strength of association exceeds the threshold, but the second strength of association does not exceed the threshold, execute a search relating to the second conversation; and if the second strength of association exceeds the threshold, but the first strength of association does not exceed the threshold, execute a search relating to the third conversation. | 12. The system of claim 11 , wherein the control circuitry is further configured to: if both the first strength of association and the second strength of association exceed the threshold, execute a search relating to the first conversation; if the first strength of association exceeds the threshold, but the second strength of association does not exceed the threshold, execute a search relating to the second conversation; and if the second strength of association exceeds the threshold, but the first strength of association does not exceed the threshold, execute a search relating to the third conversation. 16. The system of claim 12 , wherein the control circuitry is further configured, when translating of either the first phrase, the second phrase, or the third phrase, to: extract a word from either the first phrase, the second phrase, or the third phrase; compare the word to entries of a database that indicates word types of known words; determine whether a word type is known based on the comparing; and in response to determining that the word type is known, replace the word with the word type indicated in an entry corresponding with the word. | 0.909226 |
8,051,080 | 13 | 14 | 13. One or more non-transitory computer-readable storage media storing instructions, the instructions including instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: collecting usage data that indicates how frequently users interact with annotations for entities that are referenced in documents presented to the users; based at least in part on the usage data, generating weights for features that are associated with the entities referenced in the documents; wherein a particular weight of a particular feature is based at least in part on how frequently users interact with annotations of entities having the particular feature; identifying a set of identified entities within a document; determining a ranking for the identified entities that belong to said set of identified identities based, at least in part, on (a) feature scores for each of the identified entities, wherein the feature scores correspond to features associated with the identified entities, wherein the particular feature is associated with at least one of the identified entities; and (b) weights, including the particular weight, for the features that are associated with the identified entities; based at least in part on the ranking, automatically selecting a subset of the identified entities for annotation, wherein the subset includes fewer than all of the identified entities; automatically generating an annotated version of the document by, for each entity in the subset, adding to the document a control for displaying additional information about the entity, wherein the additional information about the entity and the control associated with the entity were not in the document before the step of automatically generating the annotated version of the document. | 13. One or more non-transitory computer-readable storage media storing instructions, the instructions including instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: collecting usage data that indicates how frequently users interact with annotations for entities that are referenced in documents presented to the users; based at least in part on the usage data, generating weights for features that are associated with the entities referenced in the documents; wherein a particular weight of a particular feature is based at least in part on how frequently users interact with annotations of entities having the particular feature; identifying a set of identified entities within a document; determining a ranking for the identified entities that belong to said set of identified identities based, at least in part, on (a) feature scores for each of the identified entities, wherein the feature scores correspond to features associated with the identified entities, wherein the particular feature is associated with at least one of the identified entities; and (b) weights, including the particular weight, for the features that are associated with the identified entities; based at least in part on the ranking, automatically selecting a subset of the identified entities for annotation, wherein the subset includes fewer than all of the identified entities; automatically generating an annotated version of the document by, for each entity in the subset, adding to the document a control for displaying additional information about the entity, wherein the additional information about the entity and the control associated with the entity were not in the document before the step of automatically generating the annotated version of the document. 14. The one or more non-transitory computer-readable storage media of claim 13 wherein a particular annotation for a particular entity comprises a hyperlink added to the document, wherein the hyperlink links to additional information about the particular entity, and wherein collecting usage data is performed by storing click-through information that indicates which hyperlinks, within the documents present to the users, were activated. | 0.765525 |
8,069,213 | 18 | 19 | 18. The non-transitory computer-readable medium as recited in claim 16 , wherein the database record is stored in a messaging apparatus that comprises an SMTP mail transfer agent and an HTTP proxy. | 18. The non-transitory computer-readable medium as recited in claim 16 , wherein the database record is stored in a messaging apparatus that comprises an SMTP mail transfer agent and an HTTP proxy. 19. The non-transitory computer-readable medium as recited in claim 18 , further comprising instructions which, when executed, cause receiving the user request to access the specified hyperlink at the HTTP proxy, and receiving the electronic mail message at the SMTP mail transfer agent. | 0.895939 |
7,836,065 | 1 | 4 | 1. A computer-implemented method of configuring an attribute system and performing a global attribute search, the method comprising: a) in a system configuration phase: receiving a first user-actuated input in a distributed computing system that comprises multiple executable software applications, each of which processes data objects having data object identifiers and being stored in the distributed computing system, the data objects having attributes with attribute names and corresponding attribute values that are stored in at least two attribute repositories of an attribute system, the first user-actuated input identifying a first user-selected attribute having a first attribute name, the first user-selected attribute residing in a first attribute repository; receiving, in the distributed computing system, a second user-actuated input identifying a second user-selected attribute having a second attribute name, the second user-selected attribute being different than the first user-selected attribute and residing in a second attribute repository that is different than the first attribute repository; receiving, in the distributed computing system, a third user-actuated input that identifies a user-determined alias name that is to correspond to the first and second user-selected attributes; and storing in the attribute system an association between the user-determined alias name and the first and second user-selected attribute names; and b) subsequently in a system usage phase: receiving query input during execution of a global attribute search in at least two attribute repositories of the distributed computing system, the query input comprising at least one target alias name; identifying, in response to the query input, at least two attribute names corresponding to the target alias name and at least one data object having an attribute value matching the query input, wherein the identification comprises determining which of the attribute repositories to access to retrieve the at least two attribute names corresponding to the target alias name, the determination made using (i) an attribute registry having a hash table of attributes mapped to the first and second attribute repositories, and (ii) an alias mapping table, wherein the alias mapping table contains associations of the first and second attribute repositories with each other and with the target alias name; and providing output in response to the query input, the output comprising the identified at least two attribute names and the at least one data object having an attribute value matching the query input. | 1. A computer-implemented method of configuring an attribute system and performing a global attribute search, the method comprising: a) in a system configuration phase: receiving a first user-actuated input in a distributed computing system that comprises multiple executable software applications, each of which processes data objects having data object identifiers and being stored in the distributed computing system, the data objects having attributes with attribute names and corresponding attribute values that are stored in at least two attribute repositories of an attribute system, the first user-actuated input identifying a first user-selected attribute having a first attribute name, the first user-selected attribute residing in a first attribute repository; receiving, in the distributed computing system, a second user-actuated input identifying a second user-selected attribute having a second attribute name, the second user-selected attribute being different than the first user-selected attribute and residing in a second attribute repository that is different than the first attribute repository; receiving, in the distributed computing system, a third user-actuated input that identifies a user-determined alias name that is to correspond to the first and second user-selected attributes; and storing in the attribute system an association between the user-determined alias name and the first and second user-selected attribute names; and b) subsequently in a system usage phase: receiving query input during execution of a global attribute search in at least two attribute repositories of the distributed computing system, the query input comprising at least one target alias name; identifying, in response to the query input, at least two attribute names corresponding to the target alias name and at least one data object having an attribute value matching the query input, wherein the identification comprises determining which of the attribute repositories to access to retrieve the at least two attribute names corresponding to the target alias name, the determination made using (i) an attribute registry having a hash table of attributes mapped to the first and second attribute repositories, and (ii) an alias mapping table, wherein the alias mapping table contains associations of the first and second attribute repositories with each other and with the target alias name; and providing output in response to the query input, the output comprising the identified at least two attribute names and the at least one data object having an attribute value matching the query input. 4. The computer-implemented method of claim 1 , further comprising displaying a list of alias names during the system configuration phase. | 0.785714 |
7,752,198 | 6 | 8 | 6. A computer readable storage medium containing stored thereon instructions that when executed by a computing device cause the computing device to execute a link analysis method for determining a context-based relevance of a first electronic document of a plurality of electronic documents to remaining electronic documents of said plurality of electronic documents, the method comprising: populating a weighted symmetric similarity matrix S with link weights representing a measure of similarity between pairs of said plurality of electronic documents; determining entries S(D,X) in a row of said similarity matrix S corresponding to an electronic document D; summing said entries of at least a submatrix S′ of similarity matrix S to produce a first importance score regarding said electronic document D; and one of searching, navigating and ranking at least a subset of said plurality of electronic documents based on a total score including said first importance score. | 6. A computer readable storage medium containing stored thereon instructions that when executed by a computing device cause the computing device to execute a link analysis method for determining a context-based relevance of a first electronic document of a plurality of electronic documents to remaining electronic documents of said plurality of electronic documents, the method comprising: populating a weighted symmetric similarity matrix S with link weights representing a measure of similarity between pairs of said plurality of electronic documents; determining entries S(D,X) in a row of said similarity matrix S corresponding to an electronic document D; summing said entries of at least a submatrix S′ of similarity matrix S to produce a first importance score regarding said electronic document D; and one of searching, navigating and ranking at least a subset of said plurality of electronic documents based on a total score including said first importance score. 8. The computer readable storage medium of claim 6 , wherein said at least a submatrix S′ of similarity matrix S is an entire amount of said similarity matrix S. | 0.818284 |
8,336,027 | 5 | 7 | 5. The method of claim 4 , wherein the changes are changes to source level elements. | 5. The method of claim 4 , wherein the changes are changes to source level elements. 7. The method of claim 5 , wherein the changes comprise subtracting elements from the base version of the underlying source code. | 0.961584 |
9,405,834 | 1 | 2 | 1. A computer-implemented method for identifying related search queries, performed on a server having at least one processor and memory storing at least one program for execution by the at least one processor to perform the method, comprising: receiving a search query from a user; identifying a set of ranked search results satisfying the search query; identifying, using historical search query data, at least one last related search query in at least one chain of related search queries that is related to the search query and that includes at least one search result that was selected by users who issued the search query, wherein the identifying includes querying a query database to identify the at least one last related search query in the at least one chain of related search queries that are related to the search query, wherein a respective chain of related search queries is a sequence of consecutive search queries that are issued by a respective user and that include an initial search query that is successively refined; the query database includes a plurality of records, wherein each respective record includes: a respective search query; a number of times the respective search query was issued; a respective search result that was selected by users who issued the respective search query and that corresponds to at least one respective related search query in at least one respective chain of related search queries that are related to the respective search query; the at least one respective related search query; and a number of times the respective search query led to a selection of the respective search result; and returning the set of ranked search results and the at least one last related search query to the user. | 1. A computer-implemented method for identifying related search queries, performed on a server having at least one processor and memory storing at least one program for execution by the at least one processor to perform the method, comprising: receiving a search query from a user; identifying a set of ranked search results satisfying the search query; identifying, using historical search query data, at least one last related search query in at least one chain of related search queries that is related to the search query and that includes at least one search result that was selected by users who issued the search query, wherein the identifying includes querying a query database to identify the at least one last related search query in the at least one chain of related search queries that are related to the search query, wherein a respective chain of related search queries is a sequence of consecutive search queries that are issued by a respective user and that include an initial search query that is successively refined; the query database includes a plurality of records, wherein each respective record includes: a respective search query; a number of times the respective search query was issued; a respective search result that was selected by users who issued the respective search query and that corresponds to at least one respective related search query in at least one respective chain of related search queries that are related to the respective search query; the at least one respective related search query; and a number of times the respective search query led to a selection of the respective search result; and returning the set of ranked search results and the at least one last related search query to the user. 2. The computer-implemented method of claim 1 , wherein a first search query in the at least one chain of related search queries is the search query. | 0.83698 |
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