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9,620,105 | 21 | 36 | 21. A non-transitory computer-readable storage medium comprising instructions for causing one or more processor to: receive audio input; determine whether the audio input includes music; determine whether the audio input includes speech; responsive to determining that the audio input includes music, generate an acoustic fingerprint representing a portion of the audio input that includes music; and responsive to determining that the audio input includes speech rather than music, identify an end-point of a speech utterance of the audio input. | 21. A non-transitory computer-readable storage medium comprising instructions for causing one or more processor to: receive audio input; determine whether the audio input includes music; determine whether the audio input includes speech; responsive to determining that the audio input includes music, generate an acoustic fingerprint representing a portion of the audio input that includes music; and responsive to determining that the audio input includes speech rather than music, identify an end-point of a speech utterance of the audio input. 36. The computer-readable storage medium according to claim 21 , further comprising instructions for causing one or more processor to: in response to determining that the audio input includes music: obtain an identity of the music in the audio input based on the acoustic fingerprint; and display the identity of the music. | 0.786658 |
9,348,329 | 15 | 20 | 15. A distributed automation control device, comprising: a memory circuit storing a multi-Boolean function block configured to receive a plurality of inputs, to perform multiple Boolean logical operations based on the inputs, and to output any one of a plurality of logical outputs based upon the Boolean logical operations, wherein the plurality of inputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of inputs and as the plurality of individual inputs, and the plurality of logical outputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of logical outputs and as the plurality of individual logical outputs; a processor configured to execute the multiple Boolean logical operations; and an interface configured to output any of the plurality of logical outputs based upon the operations executed by the processor. | 15. A distributed automation control device, comprising: a memory circuit storing a multi-Boolean function block configured to receive a plurality of inputs, to perform multiple Boolean logical operations based on the inputs, and to output any one of a plurality of logical outputs based upon the Boolean logical operations, wherein the plurality of inputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of inputs and as the plurality of individual inputs, and the plurality of logical outputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of logical outputs and as the plurality of individual logical outputs; a processor configured to execute the multiple Boolean logical operations; and an interface configured to output any of the plurality of logical outputs based upon the operations executed by the processor. 20. The distributed automation control device of claim 15 , wherein the distributed automation control device is an input/output terminal block. | 0.880399 |
8,396,733 | 8 | 13 | 8. A method, comprising: receiving, by a location decisioning system at a first computing device, a process criteria for a work function associated with an organization; receiving, by the location decisioning system, a provider attribute including a desired quality of a provider performing the work function; receiving, by the location decisioning system, a plurality of additional factors associated with the work function, the plurality of additional factors including whether information associated with the work function is non-public or privileged, whether intellectual property is involved with the work function, whether knowledge retention is desired for the work function, and whether management oversight is desired for the work function; determining, by the location decisioning system, whether the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization; and responsive to determining that the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization, determining, by the location decisioning system, a recommended location in which to perform the work function associated with the organization based on the received process criteria for the work function, the received provider attribute, including the desired quality of the provider performing the work function, the received plurality of additional factors associated with the work function, and the determination that the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization, wherein the recommended location in which to perform the work function associated with the organization is determined based at least in part on the plurality of additional factors, including whether information associated with the work function is non-public or privileged, whether intellectual property is involved with the work function, whether knowledge retention is desired for the work function, and whether management oversight is desired for the work function. | 8. A method, comprising: receiving, by a location decisioning system at a first computing device, a process criteria for a work function associated with an organization; receiving, by the location decisioning system, a provider attribute including a desired quality of a provider performing the work function; receiving, by the location decisioning system, a plurality of additional factors associated with the work function, the plurality of additional factors including whether information associated with the work function is non-public or privileged, whether intellectual property is involved with the work function, whether knowledge retention is desired for the work function, and whether management oversight is desired for the work function; determining, by the location decisioning system, whether the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization; and responsive to determining that the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization, determining, by the location decisioning system, a recommended location in which to perform the work function associated with the organization based on the received process criteria for the work function, the received provider attribute, including the desired quality of the provider performing the work function, the received plurality of additional factors associated with the work function, and the determination that the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization, wherein the recommended location in which to perform the work function associated with the organization is determined based at least in part on the plurality of additional factors, including whether information associated with the work function is non-public or privileged, whether intellectual property is involved with the work function, whether knowledge retention is desired for the work function, and whether management oversight is desired for the work function. 13. The method of claim 8 , wherein the received provider attribute includes at least one of: management oversight required for the work function, a time zone of a provider, a language of a provider, knowledge base of a provider related to the work function, a duration of the work function, whether the work function provides a provider access to intellectual property, flexibility of provider staffing, and specialized skills of a provider. | 0.692629 |
8,495,059 | 1 | 9 | 1. A method of searching on a handheld electronic device, comprising: receiving input of at least one search criteria; receiving input to select at least two of a plurality of components of the handheld electronic device to be searched; conducting a search of the at least two components based upon the at least one search criteria; determining at least one search result from the search; displaying the at least one search result; and displaying and providing, for the at least one search result, at least one user interaction available from a different application, and performing one of the at least one user interaction directly from the search results displayed, without opening the different application, the at least one user interaction being selected from a group including directly editing the item, directly forwarding a message, replying to a message, directly e-mailing an e-mail address and directly calling a phone number. | 1. A method of searching on a handheld electronic device, comprising: receiving input of at least one search criteria; receiving input to select at least two of a plurality of components of the handheld electronic device to be searched; conducting a search of the at least two components based upon the at least one search criteria; determining at least one search result from the search; displaying the at least one search result; and displaying and providing, for the at least one search result, at least one user interaction available from a different application, and performing one of the at least one user interaction directly from the search results displayed, without opening the different application, the at least one user interaction being selected from a group including directly editing the item, directly forwarding a message, replying to a message, directly e-mailing an e-mail address and directly calling a phone number. 9. The method of claim 1 further comprising: employing as a representation of the plurality of components a representation of at least a first different application and a second different application; displaying a first group of the search results associated with the first different application; and separately displaying a second group of the search results associated with the second different application. | 0.697932 |
9,208,236 | 14 | 15 | 14. The system of claim 13 , wherein the search server is in communication with the query store. | 14. The system of claim 13 , wherein the search server is in communication with the query store. 15. The system of claim 14 , wherein the subject-version is implicit in the search query. | 0.973622 |
6,049,806 | 1 | 2 | 1. A method for managing data on a computer system, said method comprising the steps of: (a) a first party creating a topic record representative of a topic, wherein the topic record includes a plurality of fields for storing instruction data representative of data from a presentation and retained search data representative of data obtained from a storage means accessible to the computer system, wherein each of the plurality of fields includes a plurality of time slots representative of a plurality of time periods; (b) prompting the first party to input instruction data for a plurality of consecutive time slots; (c) for the plurality of consecutive time slots, receiving from the first party the instruction data; (d) storing on the storage means the topic record and instruction data in its respective field and time slot; (e) receiving from the first party a request to search for additional data for a particular time slot; (f) prompting the first party to input a search criteria related to the additional data to be searched; (g) receiving from the first party criteria data representative of the search criteria; (h) searching one or more storage means of the computer system for search data associated with the criteria data; (i) displaying the search data to the first party; (j) prompting the first party to select the search data to be retained; (k) receiving from the first party retained search data representative of the search data to be retained; (l) storing on the storage means the retained search data in its respective time slot of the topic record; (m) making the topic record available to one or more predetermined second parties; and (n) providing the opportunity for the predetermined second parties to perform steps (e)-(l), above. | 1. A method for managing data on a computer system, said method comprising the steps of: (a) a first party creating a topic record representative of a topic, wherein the topic record includes a plurality of fields for storing instruction data representative of data from a presentation and retained search data representative of data obtained from a storage means accessible to the computer system, wherein each of the plurality of fields includes a plurality of time slots representative of a plurality of time periods; (b) prompting the first party to input instruction data for a plurality of consecutive time slots; (c) for the plurality of consecutive time slots, receiving from the first party the instruction data; (d) storing on the storage means the topic record and instruction data in its respective field and time slot; (e) receiving from the first party a request to search for additional data for a particular time slot; (f) prompting the first party to input a search criteria related to the additional data to be searched; (g) receiving from the first party criteria data representative of the search criteria; (h) searching one or more storage means of the computer system for search data associated with the criteria data; (i) displaying the search data to the first party; (j) prompting the first party to select the search data to be retained; (k) receiving from the first party retained search data representative of the search data to be retained; (l) storing on the storage means the retained search data in its respective time slot of the topic record; (m) making the topic record available to one or more predetermined second parties; and (n) providing the opportunity for the predetermined second parties to perform steps (e)-(l), above. 2. The method of claim 1, further comprising the step of: creating link data representative of links between the retained data. | 0.840852 |
8,321,414 | 1 | 5 | 1. A method of producing a set of tags for an input audiovisual file, the set of tags indicating values of attributes of an audiovisual work of defined type represented by said audiovisual file, the method comprising the steps of: issuing, to a user, a prompt for manual assignment of tags to said input audiovisual file; inputting, as an initial estimate of the values of the respective attributes of the audiovisual work represented by said audiovisual file, data representative of the tags assigned to said input audiovisual file by the user in response to said prompt; automatically applying a set of one or more correlation functions to the attribute-value estimates of said initial estimate, to produce a set of revised estimates; assigning a respective confidence measure to each attribute value of said revised estimates; and outputting the final result of the applying step as the set of tags for said input audiovisual file; wherein the correlation functions applied in said applying step are functions embodying the correlations holding between known attribute-values of a set of training examples, said training examples being audiovisual works of said defined type corresponding to manually-tagged audiovisual files, and wherein the correlation-function application step is applied iteratively, said correlation functions are applied only to attribute-values estimates associated with a confidence measure whose value exceeds a threshold, and said confidence measure is set to a maximum value for attribute values provided by the user as the initial estimate to ensure that said attribute values provided by the user as the initial estimate are not changed. | 1. A method of producing a set of tags for an input audiovisual file, the set of tags indicating values of attributes of an audiovisual work of defined type represented by said audiovisual file, the method comprising the steps of: issuing, to a user, a prompt for manual assignment of tags to said input audiovisual file; inputting, as an initial estimate of the values of the respective attributes of the audiovisual work represented by said audiovisual file, data representative of the tags assigned to said input audiovisual file by the user in response to said prompt; automatically applying a set of one or more correlation functions to the attribute-value estimates of said initial estimate, to produce a set of revised estimates; assigning a respective confidence measure to each attribute value of said revised estimates; and outputting the final result of the applying step as the set of tags for said input audiovisual file; wherein the correlation functions applied in said applying step are functions embodying the correlations holding between known attribute-values of a set of training examples, said training examples being audiovisual works of said defined type corresponding to manually-tagged audiovisual files, and wherein the correlation-function application step is applied iteratively, said correlation functions are applied only to attribute-values estimates associated with a confidence measure whose value exceeds a threshold, and said confidence measure is set to a maximum value for attribute values provided by the user as the initial estimate to ensure that said attribute values provided by the user as the initial estimate are not changed. 5. The audiovisual-file tag production method according to claim 1 , wherein said prompt-issuing step employs a user interface adapted to prompt said user to input tags for an audiovisual file and said user interface is adapted to indicate to the user which kind of tags should be input. | 0.851756 |
8,572,475 | 3 | 4 | 3. The information processing apparatus as claimed in claim 1 , wherein the at least one annotation object comprises a plurality of annotation objects, wherein each of the plurality of annotation objects added on the page through the annotation operation control unit is associated with group identifying information, and wherein the electronic document data holding unit stores the group identifying information associated with each of the plurality of annotation objects in page data corresponding to the group identifying information. | 3. The information processing apparatus as claimed in claim 1 , wherein the at least one annotation object comprises a plurality of annotation objects, wherein each of the plurality of annotation objects added on the page through the annotation operation control unit is associated with group identifying information, and wherein the electronic document data holding unit stores the group identifying information associated with each of the plurality of annotation objects in page data corresponding to the group identifying information. 4. The information processing apparatus as claimed in claim 3 , wherein the electronic document display control unit, in response to the operation input unit receiving an input of the user to select the plurality of annotation objects, divides the screen into a plurality of screens on each of which the page of the electronic document is displayed based on the magnification and the portion of the page stored in the electronic document data holding unit corresponding to each of the plurality of annotation objects having the same group identifying information as the selected plurality of annotation objects. | 0.780689 |
8,265,939 | 11 | 17 | 11. At least one computer readable storage device encoded with a plurality of instructions that, when executed, cause at least one processor to perform a method for determining an intended action of a user of a computing system environment, the computing system environment comprising a voice system, the intended action being specified via a spoken utterance input of the user, wherein the method comprises acts of: obtaining a decoding of the spoken input of the user, wherein the voice system has a precise machine-based grammar to allow the user to invoke the intended action by speaking one or more predetermined voice commands and wherein the spoken input is a free form voice instruction that is different than the precise machine-based grammar; and extracting the intended action from the decoding of the spoken input using an iterative hierarchical extraction process comprising analyzing the decoding of the spoken input in multiple hierarchically dependent semantic stages, comprising: determining a first level of classification of the intended action from the decoding of the spoken input during a first semantic stage of the iterative hierarchical extraction process, the first level of classification having a plurality of sub-classifications associated with the first level of classification; and determining, from among the plurality of sub-classifications associated with the first level of classification, a second level of classification of the intended action from the same decoding of the spoken input during a second semantic stage of the iterative hierarchical extraction process. | 11. At least one computer readable storage device encoded with a plurality of instructions that, when executed, cause at least one processor to perform a method for determining an intended action of a user of a computing system environment, the computing system environment comprising a voice system, the intended action being specified via a spoken utterance input of the user, wherein the method comprises acts of: obtaining a decoding of the spoken input of the user, wherein the voice system has a precise machine-based grammar to allow the user to invoke the intended action by speaking one or more predetermined voice commands and wherein the spoken input is a free form voice instruction that is different than the precise machine-based grammar; and extracting the intended action from the decoding of the spoken input using an iterative hierarchical extraction process comprising analyzing the decoding of the spoken input in multiple hierarchically dependent semantic stages, comprising: determining a first level of classification of the intended action from the decoding of the spoken input during a first semantic stage of the iterative hierarchical extraction process, the first level of classification having a plurality of sub-classifications associated with the first level of classification; and determining, from among the plurality of sub-classifications associated with the first level of classification, a second level of classification of the intended action from the same decoding of the spoken input during a second semantic stage of the iterative hierarchical extraction process. 17. The at least one computer readable storage device of claim 11 , wherein the precise machine-based grammar is hierarchically arranged, and wherein the first level of classification and the second level of classification correspond to different levels within the grammar. | 0.811724 |
8,452,795 | 14 | 16 | 14. A computer-implemented method, comprising: obtaining a plurality of class instance pairs derived from a plurality of documents by applying one or more extraction patterns to the plurality of documents, each class-instance pair comprising class text naming an entity class and entity text naming a particular instance of the entity class; calculating a weight for each class-instance pair according to a frequency score and a diversity score for the class-instance pair, wherein the frequency score of the class-instance pair is based on a number of times the class-instance pair was derived from the plurality of documents, and wherein the diversity score of the class-instance pair is based on a number of distinct extraction patterns used to extract the class-instance pair; receiving a plurality of candidate text queries; generating one or more query specializations from the plurality of candidate text queries and the plurality of class-instance pairs, wherein each query specialization is the text of one of the candidate text queries modified so that an n-gram in the text of the candidate text query is replaced by the entity text from a class-instance pair having class text matching the n-gram, wherein generating a query specialization from a candidate text query and the class instance pairs comprises: extracting a plurality of n-grams from the candidate text query and extracting a respective context for each extracted n-gram from the candidate text query, the respective context for an extracted n-gram including a prefix context and a suffix context; comparing the extracted n-grams to the class text of the class-instance pairs; identifying an n-gram that matches class text of a first class-instance pair; and generating the query specialization from the entity text of the first class-instance pair and the respective context for the identified n-gram; and storing specialization data, the specialization data associating each of one or more of the candidate text queries with one or more query specializations identified from the candidate text query. | 14. A computer-implemented method, comprising: obtaining a plurality of class instance pairs derived from a plurality of documents by applying one or more extraction patterns to the plurality of documents, each class-instance pair comprising class text naming an entity class and entity text naming a particular instance of the entity class; calculating a weight for each class-instance pair according to a frequency score and a diversity score for the class-instance pair, wherein the frequency score of the class-instance pair is based on a number of times the class-instance pair was derived from the plurality of documents, and wherein the diversity score of the class-instance pair is based on a number of distinct extraction patterns used to extract the class-instance pair; receiving a plurality of candidate text queries; generating one or more query specializations from the plurality of candidate text queries and the plurality of class-instance pairs, wherein each query specialization is the text of one of the candidate text queries modified so that an n-gram in the text of the candidate text query is replaced by the entity text from a class-instance pair having class text matching the n-gram, wherein generating a query specialization from a candidate text query and the class instance pairs comprises: extracting a plurality of n-grams from the candidate text query and extracting a respective context for each extracted n-gram from the candidate text query, the respective context for an extracted n-gram including a prefix context and a suffix context; comparing the extracted n-grams to the class text of the class-instance pairs; identifying an n-gram that matches class text of a first class-instance pair; and generating the query specialization from the entity text of the first class-instance pair and the respective context for the identified n-gram; and storing specialization data, the specialization data associating each of one or more of the candidate text queries with one or more query specializations identified from the candidate text query. 16. The method of claim 14 , wherein generating the query specialization from the entity text of the first class-instance pair and the respective context for the identified n-gram includes replacing the identified n-gram with the entity text of the first class-instance pair. | 0.890088 |
9,495,140 | 8 | 9 | 8. A computer-implemented method for optimizing conditional statements in a program, the method comprising: obtaining, for a conditional expression used in a conditional statement in the program, a set of conditional expressions having an inclusion relation; computing a first provisional cost corresponding to the conditional expression being positive, and a second provisional cost corresponding to the conditional expression being negative; and moving the conditional expression to a move destination, wherein the move destination is determined by performing a data-flow analysis using expressions of positive and negative conditions of the conditional expression, and wherein moving the conditional expression comprises: in response to a result of the conditional expression not being cached in a variable, generating an if statement for the conditional expression and caching the result of the conditional expression in a new variable, wherein the if statement is generated in increasing order of the first provisional cost and the second provisional cost; and in response to the result of the conditional expression being cached in a variable, replacing a conditional operator of the conditional expression with a logical operator, prior to caching the result in the new variable. | 8. A computer-implemented method for optimizing conditional statements in a program, the method comprising: obtaining, for a conditional expression used in a conditional statement in the program, a set of conditional expressions having an inclusion relation; computing a first provisional cost corresponding to the conditional expression being positive, and a second provisional cost corresponding to the conditional expression being negative; and moving the conditional expression to a move destination, wherein the move destination is determined by performing a data-flow analysis using expressions of positive and negative conditions of the conditional expression, and wherein moving the conditional expression comprises: in response to a result of the conditional expression not being cached in a variable, generating an if statement for the conditional expression and caching the result of the conditional expression in a new variable, wherein the if statement is generated in increasing order of the first provisional cost and the second provisional cost; and in response to the result of the conditional expression being cached in a variable, replacing a conditional operator of the conditional expression with a logical operator, prior to caching the result in the new variable. 9. The computer-implemented method of claim 8 , wherein obtaining the set of conditional expressions for the conditional expression comprises: setting a positive condition and a negative condition for the conditional expression; and identifying the conditional expressions for which corresponding results are determinable based on the result of the conditional expression. | 0.75718 |
9,299,348 | 10 | 12 | 10. The apparatus of claim 7 , wherein the speech to text block is configured to convert the recall topics to speech. | 10. The apparatus of claim 7 , wherein the speech to text block is configured to convert the recall topics to speech. 12. The apparatus of claim 10 , further comprising: an interface block configured to apply the speech of the recall topics to one of the two or more individuals. | 0.875772 |
8,370,390 | 1 | 3 | 1. A computer-implemented method for identifying duplicate and near-duplicate documents, the method comprising: a) obtaining the document and extracting from the document a set of shingles; b) creating for this document a summary vector with n coordinates, wherein the n is a nature number; c) sorting coordinates of a summary vector; d) creating a vector representing evaluated document from the serial numbers of sorted coordinates; e) creating a document fingerprint as a reduced dimension vector from the vector representing evaluated document; and f) comparing the vector representing evaluated document with fingerprints of other documents to identify a duplicate or a near-duplicate of evaluated document. | 1. A computer-implemented method for identifying duplicate and near-duplicate documents, the method comprising: a) obtaining the document and extracting from the document a set of shingles; b) creating for this document a summary vector with n coordinates, wherein the n is a nature number; c) sorting coordinates of a summary vector; d) creating a vector representing evaluated document from the serial numbers of sorted coordinates; e) creating a document fingerprint as a reduced dimension vector from the vector representing evaluated document; and f) comparing the vector representing evaluated document with fingerprints of other documents to identify a duplicate or a near-duplicate of evaluated document. 3. The computer-implemented method of claim 1 , wherein the coordinates of a summary vector are sorted according to the values in coordinates and the serial numbers of coordinates form a vector representing evaluated document. | 0.606272 |
8,458,164 | 35 | 36 | 35. The non-transitory computer storage medium of manufacture of claim 34 , further comprising program instructions for selecting one or more of grouped predicates for ungrouping. | 35. The non-transitory computer storage medium of manufacture of claim 34 , further comprising program instructions for selecting one or more of grouped predicates for ungrouping. 36. The non-transitory computer storage medium of manufacture of claim 35 , further comprising program instructions for removing the indications of grouping from the first display area in response to the step of selecting grouped predicates. | 0.913496 |
10,025,807 | 1 | 4 | 1. A dynamic data acquisition method, comprising: extracting a search term from a search request string that is received; looking up the search term in a threshold value dictionary to acquire a dynamic threshold score corresponding to the search term, wherein the dynamic threshold score varies based on characteristic factors, wherein the characteristic factors include a textual characteristic factor for the search term and a data analysis characteristic factor for the search term, the textual characteristic factor and the data analysis characteristic factor being stored in a log dictionary; and wherein the dynamic threshold score relates to a correlation of the search term and a product, wherein the dynamic threshold score is calculated by: performing a first fitting calculation based on the textual characteristic factor for the search term to obtain a first threshold score; performing a second fitting calculation based on the data analysis characteristic factor for the search term to obtain a second threshold score; and performing a third fitting calculation based on the first threshold score and the second threshold score to obtain the dynamic threshold score; detecting a change in the characteristic factors, comprising: updating the dynamic threshold score based on the changed characteristic factors; and storing the updated dynamic threshold score in the threshold value dictionary; using the search term as a query condition and the updated dynamic threshold score corresponding to the search term as a filter condition to acquire, in an index data table, one or more corresponding pieces of index information; acquiring data information corresponding to the search term based on the index information in the index data table; and sending the data information to be displayed in a page of a website. | 1. A dynamic data acquisition method, comprising: extracting a search term from a search request string that is received; looking up the search term in a threshold value dictionary to acquire a dynamic threshold score corresponding to the search term, wherein the dynamic threshold score varies based on characteristic factors, wherein the characteristic factors include a textual characteristic factor for the search term and a data analysis characteristic factor for the search term, the textual characteristic factor and the data analysis characteristic factor being stored in a log dictionary; and wherein the dynamic threshold score relates to a correlation of the search term and a product, wherein the dynamic threshold score is calculated by: performing a first fitting calculation based on the textual characteristic factor for the search term to obtain a first threshold score; performing a second fitting calculation based on the data analysis characteristic factor for the search term to obtain a second threshold score; and performing a third fitting calculation based on the first threshold score and the second threshold score to obtain the dynamic threshold score; detecting a change in the characteristic factors, comprising: updating the dynamic threshold score based on the changed characteristic factors; and storing the updated dynamic threshold score in the threshold value dictionary; using the search term as a query condition and the updated dynamic threshold score corresponding to the search term as a filter condition to acquire, in an index data table, one or more corresponding pieces of index information; acquiring data information corresponding to the search term based on the index information in the index data table; and sending the data information to be displayed in a page of a website. 4. The method as described in claim 1 , wherein the index data table comprises: a plurality of keywords and a corresponding plurality of threshold scores between the keywords and the data information. | 0.91431 |
8,521,510 | 16 | 20 | 16. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: verifying, via a processor, an identity of a first user; when the identity of the first user is verified: identifying a template for a domain associated with the first user; receiving input speech from the first user, the input speech comprising a substantive portion and an instructional portion, the instructional portion related to navigation between fields in the template; transcribing the substantive portion of the input speech to text based on the domain, to yield transcribed text; and storing the transcribed text in a database; upon receiving a first request via a web page-from a second user to display the transcribed text: retrieving the transcribed text from the database; and displaying the transcribed text to the second user; and upon receiving a second request from the second user to play a dictation for a particular word in the transcribed text, playing the dictation of the particular word. | 16. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: verifying, via a processor, an identity of a first user; when the identity of the first user is verified: identifying a template for a domain associated with the first user; receiving input speech from the first user, the input speech comprising a substantive portion and an instructional portion, the instructional portion related to navigation between fields in the template; transcribing the substantive portion of the input speech to text based on the domain, to yield transcribed text; and storing the transcribed text in a database; upon receiving a first request via a web page-from a second user to display the transcribed text: retrieving the transcribed text from the database; and displaying the transcribed text to the second user; and upon receiving a second request from the second user to play a dictation for a particular word in the transcribed text, playing the dictation of the particular word. 20. The system of claim 16 , wherein an automated web transcription service unit prompts the second user to select one of printing the transcribed text, sending the transcribed text to another party, and saving the transcribed text to a memory. | 0.661111 |
9,880,984 | 1 | 2 | 1. A system implemented in hardware, comprising: a computer operable to: receive, from a document owner via a social media network, a portion of a document and an identification of at least one social media network contact to be notified for reviewing the portion of the document; store the portion of the document and the identification of the at least one social media network contact, as a reviewer of the portion of the document, into a memory; assign, by the document owner, forwarding rights to the at least one reviewer with respect to the portion of the document, the forwarding rights configured to selectively enable and prevent the ability of the at least one reviewer to forward the portion of the document to other individuals through the social media network; generate a link referencing the portion of the document stored in the memory; publish the link to the reviewer for the reviewer to access the portion of the document for reviewing via the social media network; receive a proposed edit associated with the portion of the document from the reviewer, wherein the received proposed edit is accessible to the document owner; and receive, from the document owner, an indication of one of an acceptance of the proposed edit and a rejection of the proposed edit; determine reviewers whose proposed edits are more frequently accepted by the document owner; and indicate the determined reviewers to the document owner; wherein the acceptance causes the computer to automatically update the portion of the document to include the proposed edit, and the rejection causes the computer to maintain the portion of the document without the proposed edit; wherein receiving the identification of the at least one social media network contact includes receiving a user-selected, pre-defined category of social media network contacts, the computer further configured to: receive a level of confidentiality indicator from the document owner for assignment to the portion of the document; and apply a filter to the social media network contacts listed in the category based on the level of confidentiality indicator and a social media network profile for each of the social media network contacts in the category; wherein publishing the link to the reviewer comprises publishing the link for only those social media network contacts that meet criteria of the filter. | 1. A system implemented in hardware, comprising: a computer operable to: receive, from a document owner via a social media network, a portion of a document and an identification of at least one social media network contact to be notified for reviewing the portion of the document; store the portion of the document and the identification of the at least one social media network contact, as a reviewer of the portion of the document, into a memory; assign, by the document owner, forwarding rights to the at least one reviewer with respect to the portion of the document, the forwarding rights configured to selectively enable and prevent the ability of the at least one reviewer to forward the portion of the document to other individuals through the social media network; generate a link referencing the portion of the document stored in the memory; publish the link to the reviewer for the reviewer to access the portion of the document for reviewing via the social media network; receive a proposed edit associated with the portion of the document from the reviewer, wherein the received proposed edit is accessible to the document owner; and receive, from the document owner, an indication of one of an acceptance of the proposed edit and a rejection of the proposed edit; determine reviewers whose proposed edits are more frequently accepted by the document owner; and indicate the determined reviewers to the document owner; wherein the acceptance causes the computer to automatically update the portion of the document to include the proposed edit, and the rejection causes the computer to maintain the portion of the document without the proposed edit; wherein receiving the identification of the at least one social media network contact includes receiving a user-selected, pre-defined category of social media network contacts, the computer further configured to: receive a level of confidentiality indicator from the document owner for assignment to the portion of the document; and apply a filter to the social media network contacts listed in the category based on the level of confidentiality indicator and a social media network profile for each of the social media network contacts in the category; wherein publishing the link to the reviewer comprises publishing the link for only those social media network contacts that meet criteria of the filter. 2. The system of claim 1 , wherein the computer is further operable to store the proposed edit in the memory. | 0.86409 |
9,304,826 | 15 | 24 | 15. An interactive self-help application system, comprising: an application script for implementing the interactive self-help service; a deployment platform on a network having a plurality of application servers distributed over the network and application resources able to execute the application script; a specification for preferred application resources needed for executing the application script; a centralized list of application resources, said centralized list of resources being checked and updated from a first node on the network to maintain a list of application resources prioritized by performance and including resource preference and availability; a selected application server located at a second node on the network for executing the application script, said selected application server being selected from the plurality of application servers on the network; a local list of application resources maintained at the selected application server, said local list of application resources listing application resources previously servicing the selected application server including quality of service of the application resources from the second node; a central view list of application resources obtained by querying the centralized list by resource type to conform to a predefined specification and prioritized by performance; a local view list of resources generated by querying the local list to select a list of previously contacted resources prioritized by availability and indicating a degree of success of previous browser attempts for each previously contacted resource; and wherein the application script is executed by the selected application server with application resources located dynamically from a final prioritized list created based upon the central view list filtered by using the local view list. | 15. An interactive self-help application system, comprising: an application script for implementing the interactive self-help service; a deployment platform on a network having a plurality of application servers distributed over the network and application resources able to execute the application script; a specification for preferred application resources needed for executing the application script; a centralized list of application resources, said centralized list of resources being checked and updated from a first node on the network to maintain a list of application resources prioritized by performance and including resource preference and availability; a selected application server located at a second node on the network for executing the application script, said selected application server being selected from the plurality of application servers on the network; a local list of application resources maintained at the selected application server, said local list of application resources listing application resources previously servicing the selected application server including quality of service of the application resources from the second node; a central view list of application resources obtained by querying the centralized list by resource type to conform to a predefined specification and prioritized by performance; a local view list of resources generated by querying the local list to select a list of previously contacted resources prioritized by availability and indicating a degree of success of previous browser attempts for each previously contacted resource; and wherein the application script is executed by the selected application server with application resources located dynamically from a final prioritized list created based upon the central view list filtered by using the local view list. 24. The system as in claim 15 , wherein the specification for preferred application resources needed for executing the application script includes application resources having a tariff below a predefined limit. | 0.608209 |
9,563,693 | 16 | 19 | 16. A computerized system comprising: one or more processors; and one or more computer storage media storing computer-useable instructions that, when used by the one or more processors, cause the one or more processors to: receive user feedback for each of one or more social posts presented to a user, each social post presented in association with a sentiment assigned to the social post, the user feedback for each social post regarding the sentiment assigned to the social post; generate sentiment tuning data from the user feedback; generate a new set of sentiment indicators from user provided sentiment indicators of the sentiment tuning data; apply the new set of sentiment indicators, generated from the sentiment tuning data, to new social posts to determine sentiments for the new social posts, wherein the applying comprises: identify designated expressive symbols of the new set of sentiment indicators in the new social posts, the new set of sentiment indicators comprising assignments between the designated expressive symbols and designated sentiments; and determine assignments of the sentiments to the new social posts based on the assignments between the designated expressive symbols and the designated sentiments; and present the new social posts in association with the sentiments assigned to the new social posts. | 16. A computerized system comprising: one or more processors; and one or more computer storage media storing computer-useable instructions that, when used by the one or more processors, cause the one or more processors to: receive user feedback for each of one or more social posts presented to a user, each social post presented in association with a sentiment assigned to the social post, the user feedback for each social post regarding the sentiment assigned to the social post; generate sentiment tuning data from the user feedback; generate a new set of sentiment indicators from user provided sentiment indicators of the sentiment tuning data; apply the new set of sentiment indicators, generated from the sentiment tuning data, to new social posts to determine sentiments for the new social posts, wherein the applying comprises: identify designated expressive symbols of the new set of sentiment indicators in the new social posts, the new set of sentiment indicators comprising assignments between the designated expressive symbols and designated sentiments; and determine assignments of the sentiments to the new social posts based on the assignments between the designated expressive symbols and the designated sentiments; and present the new social posts in association with the sentiments assigned to the new social posts. 19. The computerized system of claim 16 , wherein the sentiment tuning data is further generated from a user supplied lexical dictionary comprising associations between designated expressive symbols and designated sentiments of a plurality of sentiments. | 0.724512 |
4,689,022 | 4 | 5 | 4. A circuit as set forth in claim 3 which further includes: a continuous fast forward bistable which can be set by one of said control lines and reset by said read command; a continuous fast forward relay having switch contacts and a coil; and wherein the switch contacts of said continuous fast forward relay are paralleled with the switch contacts of the relay driven by the fast forward signal, said continuous fast forward relay having its coil driven by the output of said continuous fast forward bistable. | 4. A circuit as set forth in claim 3 which further includes: a continuous fast forward bistable which can be set by one of said control lines and reset by said read command; a continuous fast forward relay having switch contacts and a coil; and wherein the switch contacts of said continuous fast forward relay are paralleled with the switch contacts of the relay driven by the fast forward signal, said continuous fast forward relay having its coil driven by the output of said continuous fast forward bistable. 5. A circuit as set forth in claim 4 wherein: said read bistable includes a reset terminal connected to said control lines for the stop, pause, continuous fast forward, and continuous rewind relavs such that said read bistable will be reset in response to operational signals causing the stop, pause, continuous fastforward, or continuous rewind relays to be operated. | 0.936857 |
8,024,372 | 17 | 18 | 17. The computer-readable storage medium of claim 15 , wherein training the model based on the documents further comprises: for a given link, producing a weight function for each document; and optimizing a product of all the weight functions for the given link. | 17. The computer-readable storage medium of claim 15 , wherein training the model based on the documents further comprises: for a given link, producing a weight function for each document; and optimizing a product of all the weight functions for the given link. 18. The computer-readable storage medium of claim 17 , wherein for the given link and a given document, the corresponding weight function is based on a probability of the document's terminal nodes firing when all other link weights remain constant. | 0.835544 |
10,043,511 | 1 | 5 | 1. A computer implemented method for expanding a language model corresponding to a domain, comprising: collecting, by one or more processor, at least one feature vector from one or more external domain distinctive from the domain, wherein the domain and the one or more external domain are interconnected via a cloud; expanding the language model, stored in a corpora coupled to the cloud, with a feature vector of the at least one feature vector from the collecting, wherein the feature vector is, based on a logistic regression threshold, more relevant to the domain than not, the expanding comprising: (i) calculating a logistic regression value for the feature vector by use of σ(t)=e t /(e t +1)=1/(1+e −t ), wherein σ(t) indicates a standard equation of logistic regression for sentence t that represents the feature vector, (ii) ascertaining that the logistic regression value for the feature vector indicating that the probability of the feature vector to be relevant to the domain is greater than or equal to the logistic regression threshold of zero point five (0.5); and (iii) updating the language model in the corpora by adding the feature vector from the ascertaining to the language model; enhancing the language model by machine learning live content from one or more subject website in which the domain is interested such that the language model includes the live content and one or more secondary term derived from the live content that are more relevant to the domain than not, such that the language model accurately and comprehensively facilitates an automatic speech recognition (ASR) system for the domain; and performing speech recognition on a received speech input utilizing at least the enhanced language model. | 1. A computer implemented method for expanding a language model corresponding to a domain, comprising: collecting, by one or more processor, at least one feature vector from one or more external domain distinctive from the domain, wherein the domain and the one or more external domain are interconnected via a cloud; expanding the language model, stored in a corpora coupled to the cloud, with a feature vector of the at least one feature vector from the collecting, wherein the feature vector is, based on a logistic regression threshold, more relevant to the domain than not, the expanding comprising: (i) calculating a logistic regression value for the feature vector by use of σ(t)=e t /(e t +1)=1/(1+e −t ), wherein σ(t) indicates a standard equation of logistic regression for sentence t that represents the feature vector, (ii) ascertaining that the logistic regression value for the feature vector indicating that the probability of the feature vector to be relevant to the domain is greater than or equal to the logistic regression threshold of zero point five (0.5); and (iii) updating the language model in the corpora by adding the feature vector from the ascertaining to the language model; enhancing the language model by machine learning live content from one or more subject website in which the domain is interested such that the language model includes the live content and one or more secondary term derived from the live content that are more relevant to the domain than not, such that the language model accurately and comprehensively facilitates an automatic speech recognition (ASR) system for the domain; and performing speech recognition on a received speech input utilizing at least the enhanced language model. 5. The computer implemented method of claim 1 , further comprising: evaluating the language model from the expanding and from the enhancing, by use of evaluation techniques selected from Word Error Rate (WER), a ground truth test, and combinations thereof. | 0.869919 |
8,082,145 | 1 | 6 | 1. A computer-implemented method comprising: identifying a word that includes modifiable characters; correlating a different numerical value of a first set of numerical values with each individual character of the modifiable characters; and causing a second set of numerical values to be displayed in response to a selection of one of the numerical values of the first set of numerical values, each numerical value of the second set of numerical values being associated with a different character modification and being selectable to cause one of the modifiable characters correlated with the one of the numerical values of the first set of numerical values to be modified such that each of the modifiable characters is individually modifiable. | 1. A computer-implemented method comprising: identifying a word that includes modifiable characters; correlating a different numerical value of a first set of numerical values with each individual character of the modifiable characters; and causing a second set of numerical values to be displayed in response to a selection of one of the numerical values of the first set of numerical values, each numerical value of the second set of numerical values being associated with a different character modification and being selectable to cause one of the modifiable characters correlated with the one of the numerical values of the first set of numerical values to be modified such that each of the modifiable characters is individually modifiable. 6. The computer-implemented method of claim 1 , further comprising: receiving an indication of a selection of one of the numerical values of the second set of numerical values; and modifying the one of the modifiable characters responsive to the selection. | 0.750973 |
9,323,829 | 6 | 8 | 6. An apparatus comprising: a server, including at least one processor, to: receive a first request from a user device in response to embedded instructions in a document, wherein the first request includes at least a text segment of the document, determine phrases of interest in the at least a text segment based on a reference and logged information specific to the user, wherein the reference includes a plurality of phrases and associations between the plurality of phrases, indicate the phrases of interest in a response to the user device, transmit a first response to the user device, wherein the first response enables the user device to display the document, visually distinguish the phrases of interest indicated in the response within the document from the remaining text of the document so that to convey to a user a capability of user input corresponding to the phrases of interest, and in response to user input corresponding to a phrase of interest within the document, send a second request to retrieve information associated with the phrase of interest, receive the second request; transmit a second response to the user device with the retrieved information, wherein the retrieved information includes search results for the phrase of interest from a plurality of data sources, wherein the searches were performed before the second request was received, wherein the phrase of interest and at least a portion of the retrieved information are displayed simultaneously. | 6. An apparatus comprising: a server, including at least one processor, to: receive a first request from a user device in response to embedded instructions in a document, wherein the first request includes at least a text segment of the document, determine phrases of interest in the at least a text segment based on a reference and logged information specific to the user, wherein the reference includes a plurality of phrases and associations between the plurality of phrases, indicate the phrases of interest in a response to the user device, transmit a first response to the user device, wherein the first response enables the user device to display the document, visually distinguish the phrases of interest indicated in the response within the document from the remaining text of the document so that to convey to a user a capability of user input corresponding to the phrases of interest, and in response to user input corresponding to a phrase of interest within the document, send a second request to retrieve information associated with the phrase of interest, receive the second request; transmit a second response to the user device with the retrieved information, wherein the retrieved information includes search results for the phrase of interest from a plurality of data sources, wherein the searches were performed before the second request was received, wherein the phrase of interest and at least a portion of the retrieved information are displayed simultaneously. 8. The apparatus of claim 6 , further comprising: a cache to cache an identifier of the document and the determined phrases of interest. | 0.772575 |
9,047,285 | 1 | 10 | 1. A method for frame-based search to identify content of interest, comprising the following steps: determining, as a result of computing hardware and programmable memory, a set of logical forms, each logical form representative of a unit of natural language discourse in a first source of computer-accessible content, wherein each logical form, of the set of logical forms, is arranged as a tree, at least some trees including a logical verb root, a logical subject, and a logical object; determining, for each logical form of the set of logical forms, as a result of computing hardware and programmable memory, whether a first frame extraction rule is satisfied by a logical form and, if a frame extraction rule is satisfied, producing a first instance of a first frame; determining, for each unit of natural language discourse that invokes the first frame, as a result of computing hardware and programmable memory, a locality that includes the unit of natural language discourse; including, as a result of computing hardware and programmable memory, each locality as a record of a first database; and searching, as a result of computing hardware and programmable memory, the first database, to identify a first set of records, by identifying those records that contain at least one match to a first keyword query. | 1. A method for frame-based search to identify content of interest, comprising the following steps: determining, as a result of computing hardware and programmable memory, a set of logical forms, each logical form representative of a unit of natural language discourse in a first source of computer-accessible content, wherein each logical form, of the set of logical forms, is arranged as a tree, at least some trees including a logical verb root, a logical subject, and a logical object; determining, for each logical form of the set of logical forms, as a result of computing hardware and programmable memory, whether a first frame extraction rule is satisfied by a logical form and, if a frame extraction rule is satisfied, producing a first instance of a first frame; determining, for each unit of natural language discourse that invokes the first frame, as a result of computing hardware and programmable memory, a locality that includes the unit of natural language discourse; including, as a result of computing hardware and programmable memory, each locality as a record of a first database; and searching, as a result of computing hardware and programmable memory, the first database, to identify a first set of records, by identifying those records that contain at least one match to a first keyword query. 10. The method of claim 1 , wherein the step of search further comprises: identifying records that match, within a first portion of each record representative of a first role of the first frame, the first keyword query. | 0.793006 |
7,487,448 | 11 | 29 | 11. The system of claim 1 , wherein at least some of said additional elements comprise one or more elements that describe how drawing is performed and at least a grouping element that groups other elements. | 11. The system of claim 1 , wherein at least some of said additional elements comprise one or more elements that describe how drawing is performed and at least a grouping element that groups other elements. 29. The system of claim 11 , wherein one of said additional elements that describes how drawing is performed comprises an element that represents text. | 0.955925 |
9,575,843 | 5 | 7 | 5. The method of claim 1 , wherein the backup set comprising a grouping of files aggregated together according to a pre-defined criteria. | 5. The method of claim 1 , wherein the backup set comprising a grouping of files aggregated together according to a pre-defined criteria. 7. The method of claim 5 , wherein the pre-defined criteria includes a file type. | 0.967127 |
9,690,991 | 1 | 21 | 1. A mobile device comprising: at least one sensor; at least one display; a tangible, non-transitory computer readable memory storing software instructions; and at least one hardware processor coupled with the memory and the sensor, and configurable, upon execution of the software instructions, to: capture, via the at least one sensor, a digital representation a scene; obtain access to contextually relevant key frame bundles based on a context derived from the digital representation, wherein the contextually relevant key frame bundles include recognition features associated with modeled features of at least one known object; recognize at least one scene object in the scene as the at least one known object according to at least one recognition algorithm and as a function of the recognition features and the digital representation; obtain access to augmented reality (AR) content associated with the at least one known object, wherein the AR content comprises an object mask generated from an object model of the at least one known object; anchor the AR content to an anchor point on the at least one scene object as a function of the modeled features corresponding to the recognition features used to recognize the at least one scene object; and render the AR content on the display in relation to the anchor point on the at least one scene object. | 1. A mobile device comprising: at least one sensor; at least one display; a tangible, non-transitory computer readable memory storing software instructions; and at least one hardware processor coupled with the memory and the sensor, and configurable, upon execution of the software instructions, to: capture, via the at least one sensor, a digital representation a scene; obtain access to contextually relevant key frame bundles based on a context derived from the digital representation, wherein the contextually relevant key frame bundles include recognition features associated with modeled features of at least one known object; recognize at least one scene object in the scene as the at least one known object according to at least one recognition algorithm and as a function of the recognition features and the digital representation; obtain access to augmented reality (AR) content associated with the at least one known object, wherein the AR content comprises an object mask generated from an object model of the at least one known object; anchor the AR content to an anchor point on the at least one scene object as a function of the modeled features corresponding to the recognition features used to recognize the at least one scene object; and render the AR content on the display in relation to the anchor point on the at least one scene object. 21. The mobile device of claim 1 , wherein the at least one known object comprises at least one of a building, an automobile, a person, a face, a game player, a game character, a lamp post, and a vehicle. | 0.642105 |
10,152,298 | 5 | 8 | 5. A computer-implemented method, the method comprising: receiving audio data corresponding to a first utterance; performing first automatic speech recognition (ASR) processing on the audio data using a language model to generate a hypothesis, the hypothesis including a first word, wherein: the language model was trained using a first prior probability for the first word, the first prior probability based on a group prior probability for a plurality of words, the group prior probability based on a total number of predictions of the plurality of words during ASR testing and a total number of correct predictions of the plurality of words during the ASR testing, at least one of the plurality of words is not included in the hypothesis, and performing the first ASR processing on the audio data comprises: identifying the first word, and determining a confidence score for the hypothesis using the language model; and generating output data using the hypothesis. | 5. A computer-implemented method, the method comprising: receiving audio data corresponding to a first utterance; performing first automatic speech recognition (ASR) processing on the audio data using a language model to generate a hypothesis, the hypothesis including a first word, wherein: the language model was trained using a first prior probability for the first word, the first prior probability based on a group prior probability for a plurality of words, the group prior probability based on a total number of predictions of the plurality of words during ASR testing and a total number of correct predictions of the plurality of words during the ASR testing, at least one of the plurality of words is not included in the hypothesis, and performing the first ASR processing on the audio data comprises: identifying the first word, and determining a confidence score for the hypothesis using the language model; and generating output data using the hypothesis. 8. The computer-implemented method of claim 5 , wherein the plurality of words are grouped based on a language frequency. | 0.966333 |
8,001,140 | 17 | 21 | 17. A computer readable storage medium having stored therein instructions, which when executed by a computer system cause the computer system to: receive a search keyword provided by a user, wherein the search keyword satisfies a predefined expression pattern; determine an archetype for the search keyword; identify a query operator for the archetype, wherein the query operator includes a generalized expression of the search keyword; apply the identified query operator to a document; identify a chunk within the document that satisfies the identified query operator, wherein the chunk does not include an instance of the search keyword; and return the chunk for display to the user. | 17. A computer readable storage medium having stored therein instructions, which when executed by a computer system cause the computer system to: receive a search keyword provided by a user, wherein the search keyword satisfies a predefined expression pattern; determine an archetype for the search keyword; identify a query operator for the archetype, wherein the query operator includes a generalized expression of the search keyword; apply the identified query operator to a document; identify a chunk within the document that satisfies the identified query operator, wherein the chunk does not include an instance of the search keyword; and return the chunk for display to the user. 21. The computer readable storage medium of claim 17 , wherein the identified query operator has a parameter defining an expression pattern. | 0.858012 |
8,095,632 | 14 | 18 | 14. A method for performing, by a manufacturing process utility distributed across multiple networked nodes and including a diagnostic tool, diagnostics on a data access server from a remote network location, the method comprising: discovering, by a server agent located on a remote processing node remote from the diagnostic tool, a remote data access server located on the remote processing node by querying the remote processing node and returning a response identifying the remote data access server on the remote processing node; establishing a connection between the diagnostic tool, residing on a node distinct from the remote processing node, and the remote data access server to provide diagnostic information regarding the remote data access server to the diagnostic tool; storing, by a diagnostic roots storage on the remote processing node, diagnostic information regarding the data access server, the diagnostic information including both status information and diagnostic data schema information to guide presentation, by the diagnostic tool, of the status information for the data access server; displaying, by the diagnostic tool, the status information in view of the diagnostic data schema information; and wherein the data access server provides diagnostic data associated with particular information contexts supported by the data access server. | 14. A method for performing, by a manufacturing process utility distributed across multiple networked nodes and including a diagnostic tool, diagnostics on a data access server from a remote network location, the method comprising: discovering, by a server agent located on a remote processing node remote from the diagnostic tool, a remote data access server located on the remote processing node by querying the remote processing node and returning a response identifying the remote data access server on the remote processing node; establishing a connection between the diagnostic tool, residing on a node distinct from the remote processing node, and the remote data access server to provide diagnostic information regarding the remote data access server to the diagnostic tool; storing, by a diagnostic roots storage on the remote processing node, diagnostic information regarding the data access server, the diagnostic information including both status information and diagnostic data schema information to guide presentation, by the diagnostic tool, of the status information for the data access server; displaying, by the diagnostic tool, the status information in view of the diagnostic data schema information; and wherein the data access server provides diagnostic data associated with particular information contexts supported by the data access server. 18. The method of claim 14 further comprising displaying, by the diagnostic tool, a set of data access servers discovered by the server agent. | 0.766447 |
8,954,458 | 1 | 2 | 1. A computer-implemented method of selecting a content item from a content item database, the method comprising: accessing an incoming query from a memory device; creating a first set of tokens from the incoming query; computing a first total as a number of tokens in the first set of tokens; accessing a second set of tokens corresponding to the content item stored in the content item database; determining, with at least one processor, a degree of similarity by: determining a minimum of a first count and a second count, the first count being a count of a unique token in the first set of tokens and the second count being a count of the unique token in the second set of tokens; computing a randomized easy signature by: selecting a set of most frequent tokens from the second set of tokens; computing a second total as a number of tokens in the selected set of most frequent tokens; randomly selecting a sub-set of tokens from the selected set of most frequent tokens; determining a number of common tokens based on a minimum of the first count and a third count, the third count being a count of the unique token in the randomly selected sub-set of tokens; and determining the randomized easy signature as a ratio of the number of common tokens and a sum of the first total and the second total; and selecting, with the at least one processor, the content item as matching the incoming query if the degree of similarity exceeds a predetermined threshold. | 1. A computer-implemented method of selecting a content item from a content item database, the method comprising: accessing an incoming query from a memory device; creating a first set of tokens from the incoming query; computing a first total as a number of tokens in the first set of tokens; accessing a second set of tokens corresponding to the content item stored in the content item database; determining, with at least one processor, a degree of similarity by: determining a minimum of a first count and a second count, the first count being a count of a unique token in the first set of tokens and the second count being a count of the unique token in the second set of tokens; computing a randomized easy signature by: selecting a set of most frequent tokens from the second set of tokens; computing a second total as a number of tokens in the selected set of most frequent tokens; randomly selecting a sub-set of tokens from the selected set of most frequent tokens; determining a number of common tokens based on a minimum of the first count and a third count, the third count being a count of the unique token in the randomly selected sub-set of tokens; and determining the randomized easy signature as a ratio of the number of common tokens and a sum of the first total and the second total; and selecting, with the at least one processor, the content item as matching the incoming query if the degree of similarity exceeds a predetermined threshold. 2. The computer-implemented method of claim 1 , wherein the incoming query comprises at least one of a search string and a user query. | 0.922543 |
10,083,688 | 21 | 22 | 21. The method of claim 15 , further comprising: in response to another spoken user input, ceasing to highlight the highlighted one or more displayed affordances; and highlighting an affordance other than the previously highlighted one or more displayed affordances. | 21. The method of claim 15 , further comprising: in response to another spoken user input, ceasing to highlight the highlighted one or more displayed affordances; and highlighting an affordance other than the previously highlighted one or more displayed affordances. 22. The method of claim 21 , wherein the another spoken user input includes at least one of a name or index of the affordance other than the previously highlighted one or more displayed affordances. | 0.953975 |
9,201,592 | 7 | 9 | 7. The method of claim 4 , further comprising: determining whether the second handwritten input comprises at least one of a strikethrough input or a leaping input; and identifying the candidate word associated with a maximum of the rankings as the selected candidate word, when the second handwritten input includes at least one of the strikethrough input or the leaping input. | 7. The method of claim 4 , further comprising: determining whether the second handwritten input comprises at least one of a strikethrough input or a leaping input; and identifying the candidate word associated with a maximum of the rankings as the selected candidate word, when the second handwritten input includes at least one of the strikethrough input or the leaping input. 9. The method of claim 7 , wherein: the second handwritten input comprises a handwritten line connecting the one or more handwritten characters with the information identifying a corresponding one of the candidate words; and the method further comprises identifying the corresponding candidate word as the selected candidate word. | 0.886364 |
9,881,146 | 1 | 9 | 1. An authentication method for verifying password input to an authentication device by a user, comprising the following steps: (a) defining a candidate character set including a plurality of characters, a subset of the candidate character set being a known character set contained in a predefined password; (b) randomly distributing all of the characters of the candidate character set into a plurality of candidate character subsets such that each candidate character subset includes two or more characters, and displaying all of the characters of the plurality of candidate character subsets in a plurality of interactive regions, respectively, all of the characters of each candidate character subset being randomly generated and distributed; and (c) receiving from the user a series of selections of specific ones of the plurality of interactive regions, checking whether each selected interactive region displayed a character of the known character set contained in the predefined password, and confirming successful authentication and outputting a signal indicating successful authentication when each of the interactive regions containing the characters of the known character set contained in the predefined password were directly selected by the user, wherein step (b) is repeated before each user selection of a specific one of the plurality of interactive regions, such that the characters in the plurality of candidate character subsets are randomly generated and distributed before each user selection. | 1. An authentication method for verifying password input to an authentication device by a user, comprising the following steps: (a) defining a candidate character set including a plurality of characters, a subset of the candidate character set being a known character set contained in a predefined password; (b) randomly distributing all of the characters of the candidate character set into a plurality of candidate character subsets such that each candidate character subset includes two or more characters, and displaying all of the characters of the plurality of candidate character subsets in a plurality of interactive regions, respectively, all of the characters of each candidate character subset being randomly generated and distributed; and (c) receiving from the user a series of selections of specific ones of the plurality of interactive regions, checking whether each selected interactive region displayed a character of the known character set contained in the predefined password, and confirming successful authentication and outputting a signal indicating successful authentication when each of the interactive regions containing the characters of the known character set contained in the predefined password were directly selected by the user, wherein step (b) is repeated before each user selection of a specific one of the plurality of interactive regions, such that the characters in the plurality of candidate character subsets are randomly generated and distributed before each user selection. 9. The authentication device for performing the method as recited in claim 1 , comprising a control unit, a memory unit, and a touch screen, said memory unit configured to store the predefined password containing the known character set therein, wherein the control unit is configured to execute a program implemented by said method, the memory unit is configured to store candidate intermediate data generated by the program implemented by said method, and the touch screen is configured to receive the selections of the interactive regions and to transform said selections into instructions indicating the selections of the specific interactive regions. | 0.571335 |
9,471,559 | 2 | 3 | 2. The method of claim 1 , wherein the training a classifier based on the generated training instances comprises computing a plurality of features associated with the training instances and assigning a score to each of the features. | 2. The method of claim 1 , wherein the training a classifier based on the generated training instances comprises computing a plurality of features associated with the training instances and assigning a score to each of the features. 3. The method of claim 2 , wherein the plurality of features comprises one or more of lexical features, syntactic features, semantic features or corpus-based features, or combinations thereof. | 0.923506 |
7,895,174 | 1 | 5 | 1. A method of utilizing a schema for defining a join relationship, the schema being utilized for merging a database part table with a database table by a database application executing on a computer system, comprising: receiving, in the database application, target table metadata associated with a database part in a plurality of relationship elements in the schema, the database part comprising a target table, wherein an element in the plurality of relationship elements functions as a container for a set of relationships, the set of relationships defining a plurality of merges for the database part table and the database table, wherein the database application provides a user option to at least one of accept and reject one or more of the plurality of merges defined by the set of relationships; receiving, in the database application, source table metadata associated with a database comprising a source table to be joined with the target table in the plurality of relationship elements in the schema, the source table metadata describing a relationship to a class of tables existing outside of the target table; receiving, in the database application, join type metadata in the plurality of relationship elements in the schema, the join type metadata defining how data in the target table is to be merged with data in the source table; and in response to receiving the target table metadata and the source table metadata, merging the target and source tables utilizing the join type metadata. | 1. A method of utilizing a schema for defining a join relationship, the schema being utilized for merging a database part table with a database table by a database application executing on a computer system, comprising: receiving, in the database application, target table metadata associated with a database part in a plurality of relationship elements in the schema, the database part comprising a target table, wherein an element in the plurality of relationship elements functions as a container for a set of relationships, the set of relationships defining a plurality of merges for the database part table and the database table, wherein the database application provides a user option to at least one of accept and reject one or more of the plurality of merges defined by the set of relationships; receiving, in the database application, source table metadata associated with a database comprising a source table to be joined with the target table in the plurality of relationship elements in the schema, the source table metadata describing a relationship to a class of tables existing outside of the target table; receiving, in the database application, join type metadata in the plurality of relationship elements in the schema, the join type metadata defining how data in the target table is to be merged with data in the source table; and in response to receiving the target table metadata and the source table metadata, merging the target and source tables utilizing the join type metadata. 5. The method of claim 1 , wherein receiving source table metadata associated with the database in the source table to be joined with the target table in the plurality of relationship elements in the schema comprises receiving source table metadata in at least one of a source table identification element, a source table name element, a source field identification key element, and a source field identification lookup element in the schema. | 0.524731 |
9,424,008 | 1 | 2 | 1. A system comprising: one or more processors; and one or more memory devices comprising program instructions that when executed by the one or more processors cause the system to enable: a parsing module configured to parse a statically-typed code to locate one or more application programming interfaces (APIs); a projection module configured to project the application programming interfaces into one or more application programming interface projections; and a consumption module configured to locate call sites of a dynamically-typed code and verify that the call sites map to the application programming interface projections from the statically-typed code. | 1. A system comprising: one or more processors; and one or more memory devices comprising program instructions that when executed by the one or more processors cause the system to enable: a parsing module configured to parse a statically-typed code to locate one or more application programming interfaces (APIs); a projection module configured to project the application programming interfaces into one or more application programming interface projections; and a consumption module configured to locate call sites of a dynamically-typed code and verify that the call sites map to the application programming interface projections from the statically-typed code. 2. A system as described in claim 1 , wherein the consumption module is further configured to check for: syntax of the dynamically-typed code using the application programming interface projections; semantic use of the dynamically-typed code; or satisfaction of one or more contracts that is defined by an external code; or checking a callback into an implementation of another external code including existence of signatures involved for the callback. | 0.780795 |
9,262,528 | 9 | 10 | 9. The non-transitory storage medium according to claim 8 , wherein the operations further comprise using ontology elements associated with the enterprise information system as features for a clustering engine and then using at least some of the cluster names generated by the clustering engine to create the intent categories. | 9. The non-transitory storage medium according to claim 8 , wherein the operations further comprise using ontology elements associated with the enterprise information system as features for a clustering engine and then using at least some of the cluster names generated by the clustering engine to create the intent categories. 10. The non-transitory storage medium according to claim 9 , wherein the operations further comprise: identifying queries that do not match any of the created intent categories; submitting the identified queries to the clustering engine; generating new cluster names for the clusters of non-matching queries; and using the new cluster names to generate additional intent categories. | 0.918166 |
9,152,714 | 22 | 24 | 22. The computer-readable medium of claim 21 , wherein the operations further comprise: selecting one or more score improvement lists associated with high point values; breeding the one or more score improvement lists associated with high point values with each other using genetic operators to create children score improvement lists; and adding the children score improvement lists to the pool of score improvement lists; and adding the children score improvement lists to the pool of score improvement lists during the iterative selecting. | 22. The computer-readable medium of claim 21 , wherein the operations further comprise: selecting one or more score improvement lists associated with high point values; breeding the one or more score improvement lists associated with high point values with each other using genetic operators to create children score improvement lists; and adding the children score improvement lists to the pool of score improvement lists; and adding the children score improvement lists to the pool of score improvement lists during the iterative selecting. 24. The computer-readable medium of claim 22 , wherein selecting a score improvement list associated with a high point value comprises selecting a score improvement list with an associated point value that exceeds a threshold value or selecting a score improvement list with an associated point value that is within a top percentile of the point values associated with the pool of score improvement lists. | 0.909193 |
9,208,134 | 1 | 5 | 1. A method implemented in a computer infrastructure, comprising: determining an attribute of a current character in input text, the attribute of the current character indicating one or more classes of characters the current character is assigned thereto; determining one or more attributes of one or more next characters in the input text, the one or more attributes of the one or more next characters indicating the one or more classes the one or more next characters are assigned thereto; and constructing a token of the input text that comprises the current character and the one or more next characters, the attribute of the current character and the one or more attributes of the one or more next characters intersecting with each other, wherein the attribute of the current character and the one or more attributes of the one or more next characters comprises an attribute data structure which comprises a one-byte array, and wherein the one-byte array comprises a plurality of binary bits and each bit of the binary bits indicates a different class from remaining bits of the binary bits. | 1. A method implemented in a computer infrastructure, comprising: determining an attribute of a current character in input text, the attribute of the current character indicating one or more classes of characters the current character is assigned thereto; determining one or more attributes of one or more next characters in the input text, the one or more attributes of the one or more next characters indicating the one or more classes the one or more next characters are assigned thereto; and constructing a token of the input text that comprises the current character and the one or more next characters, the attribute of the current character and the one or more attributes of the one or more next characters intersecting with each other, wherein the attribute of the current character and the one or more attributes of the one or more next characters comprises an attribute data structure which comprises a one-byte array, and wherein the one-byte array comprises a plurality of binary bits and each bit of the binary bits indicates a different class from remaining bits of the binary bits. 5. The method of claim 1 , wherein the one or more classes comprise: a first alphabet class corresponding to a first language alphabet; a second alphabet class corresponding to a second language alphabet different from the first language alphabet; a punctuations, white spaces and controls class; and a numerals class. | 0.837589 |
8,380,502 | 19 | 23 | 19. A non-transitory computer-readable medium comprising: one or more instructions that, when executed by at least one processor, cause the at least one processor to receive a voice search query from a user; one or more instructions that, when executed by at least one processor, cause the at least one processor to derive a plurality of recognition hypotheses from the voice search query; one or more instructions that, when executed by at least one processor, cause the at least one processor to determine a plurality of scores associated with the plurality of recognition hypotheses, the plurality of scores being based on a comparison of the plurality of recognition hypotheses to previously received search queries; one or more instructions that, when executed by at least one processor, cause the at least one processor to discard at least one of the plurality of recognition hypotheses, that is associated with at least one first score, of the plurality of scores, that is less than a threshold value; one or more instructions that, when executed by at least one processor, cause the at least one processor to construct a first query using at least one first non-discarded recognition hypothesis, of the plurality of recognition hypotheses, where the at least one first non-discarded recognition hypothesis is associated with at least one second score, of the plurality of scores, that at least meets the threshold value, the one or more instructions to construct the first query, being further including: one or more instructions form an initial query based on the at least one first non-discarded recognition hypothesis, one or more instructions identify a plurality of stop words in the initial query, and one or more instructions prune, from the initial query, one or more of the plurality of stop words to form the first query, the first query satisfying a length threshold; one or more instructions that, when executed by at least one processor, cause the at least one processor to forward the first query to a search system; one or more instructions that, when executed by at least one processor, cause the at least one processor to receive, from the search system, results associated with the first query; and one or more instructions that, when executed by at least one processor, cause the at least one processor to provide, to the user, the first results. | 19. A non-transitory computer-readable medium comprising: one or more instructions that, when executed by at least one processor, cause the at least one processor to receive a voice search query from a user; one or more instructions that, when executed by at least one processor, cause the at least one processor to derive a plurality of recognition hypotheses from the voice search query; one or more instructions that, when executed by at least one processor, cause the at least one processor to determine a plurality of scores associated with the plurality of recognition hypotheses, the plurality of scores being based on a comparison of the plurality of recognition hypotheses to previously received search queries; one or more instructions that, when executed by at least one processor, cause the at least one processor to discard at least one of the plurality of recognition hypotheses, that is associated with at least one first score, of the plurality of scores, that is less than a threshold value; one or more instructions that, when executed by at least one processor, cause the at least one processor to construct a first query using at least one first non-discarded recognition hypothesis, of the plurality of recognition hypotheses, where the at least one first non-discarded recognition hypothesis is associated with at least one second score, of the plurality of scores, that at least meets the threshold value, the one or more instructions to construct the first query, being further including: one or more instructions form an initial query based on the at least one first non-discarded recognition hypothesis, one or more instructions identify a plurality of stop words in the initial query, and one or more instructions prune, from the initial query, one or more of the plurality of stop words to form the first query, the first query satisfying a length threshold; one or more instructions that, when executed by at least one processor, cause the at least one processor to forward the first query to a search system; one or more instructions that, when executed by at least one processor, cause the at least one processor to receive, from the search system, results associated with the first query; and one or more instructions that, when executed by at least one processor, cause the at least one processor to provide, to the user, the first results. 23. The non-transitory computer-readable medium of claim 19 , further comprising one or more instructions to identify a language model, of a plurality of language models, based on at least one characteristic associated with the user, and where the plurality of recognition hypotheses are derived using the identified language model. | 0.719595 |
8,122,043 | 9 | 13 | 9. A system for ranking the relevance of each of a plurality of documents in a corpus to a search query comprising: a) a processing unit capable of performing calculations; b) a storage device on which is stored a corpus of documents; c) an input device for receiving the search query; d) an output device for displaying the results of the ranking; wherein the processing unit groups words in the search query by synonym into one or more word groups; wherein the processing unit, for each word group, counts the number of instances (the “FQ” value) that a word from the word group appears in the search query; wherein the processing unit determines the maximum FQ value among all the word groups; wherein the processing unit calculates a scaling factor K; wherein the processing unit, for each word group, calculates a term frequency (“TF”) value by dividing the FQ value for the word group by the maximum FQ value and applying scaling factor K to the resulting quotient; wherein the processing unit, for each word group, counts the number of documents (“FC”) in the corpus that contain at least one word from the word group; wherein the processing unit counts the number of documents (“N”) in the corpus; wherein the processing unit, for each word group, calculates an inverse document frequency (“IDF”) value by dividing N by FC, adding one to the resulting quotient, and taking the natural logarithm of the resulting sum; wherein the processing unit, for each word group, calculates a TF-IDF value by multiplying said TF value by said IDF value; and wherein the processing unit ranks the relevance of each document in the corpus utilizing the TF-IDF values for the word groups in the search query. | 9. A system for ranking the relevance of each of a plurality of documents in a corpus to a search query comprising: a) a processing unit capable of performing calculations; b) a storage device on which is stored a corpus of documents; c) an input device for receiving the search query; d) an output device for displaying the results of the ranking; wherein the processing unit groups words in the search query by synonym into one or more word groups; wherein the processing unit, for each word group, counts the number of instances (the “FQ” value) that a word from the word group appears in the search query; wherein the processing unit determines the maximum FQ value among all the word groups; wherein the processing unit calculates a scaling factor K; wherein the processing unit, for each word group, calculates a term frequency (“TF”) value by dividing the FQ value for the word group by the maximum FQ value and applying scaling factor K to the resulting quotient; wherein the processing unit, for each word group, counts the number of documents (“FC”) in the corpus that contain at least one word from the word group; wherein the processing unit counts the number of documents (“N”) in the corpus; wherein the processing unit, for each word group, calculates an inverse document frequency (“IDF”) value by dividing N by FC, adding one to the resulting quotient, and taking the natural logarithm of the resulting sum; wherein the processing unit, for each word group, calculates a TF-IDF value by multiplying said TF value by said IDF value; and wherein the processing unit ranks the relevance of each document in the corpus utilizing the TF-IDF values for the word groups in the search query. 13. The system of claim 9 wherein said scaling factor K is a strictly decreasing function over the domain of positive integers whose range does not exceed 1 or fall below 0 where the domain represents the number of unique words (“C”) in the search query. | 0.703271 |
9,772,902 | 1 | 2 | 1. A method of generating coherent check words for programming memory cells to an intermediate state and to a final state without an intervening erase operation, the method comprising: receiving a first data; computing a first check code for the first data; programming the first data and the first check code to a plurality of memory cells to change contents of the plurality of memory cells from an initial state to the intermediate state; receiving a second data; computing a second check code for the second data; and programming the second data and the second check code to the plurality of memory cells without erasing the plurality of memory cells provided that contents of the second data and the second check code would be at the final state after programming. | 1. A method of generating coherent check words for programming memory cells to an intermediate state and to a final state without an intervening erase operation, the method comprising: receiving a first data; computing a first check code for the first data; programming the first data and the first check code to a plurality of memory cells to change contents of the plurality of memory cells from an initial state to the intermediate state; receiving a second data; computing a second check code for the second data; and programming the second data and the second check code to the plurality of memory cells without erasing the plurality of memory cells provided that contents of the second data and the second check code would be at the final state after programming. 2. The method of claim 1 , further comprising: receiving user data; and transforming the user data to the first data according to a transformation function, the first data being a same size as the user data. | 0.891282 |
9,785,658 | 13 | 16 | 13. A system comprising: a memory that stores instructions; and one or more processors configured by the instructions to perform operations comprising: accessing a first schema comprising a first plurality of business entities including a first business entity, the first business entity having a first name in the first schema; accessing a second schema comprising a second plurality of business entities including the first business entity, the first business entity having a second name in the second schema; generating from the first schema and the second schema, a merged schema comprising a third plurality of business entities, including a single instance of the first business entity; storing the merged schema in a database; extracting a first sequence of words from the first name of the first business entity; generating candidate phrases for the business entity from the first and second sequences of words; and ranking the candidate phrases for the first business entity; analyzing candidate sets of labels for the third plurality of business entities, each candidate set of labels including a label for each business entity of the third plurality of business entities, no two business entities having the same label in the candidate set of labels, the label for the first business entity being selected from the candidate phrases for the first business entity; and assigning labels to each business entity of the third plurality of business entities based on the analysis of the candidate sets of labels; and receiving data stored using the first schema; converting the received data to the merged schema; and causing a presentation of the converted data using the assigned labels. | 13. A system comprising: a memory that stores instructions; and one or more processors configured by the instructions to perform operations comprising: accessing a first schema comprising a first plurality of business entities including a first business entity, the first business entity having a first name in the first schema; accessing a second schema comprising a second plurality of business entities including the first business entity, the first business entity having a second name in the second schema; generating from the first schema and the second schema, a merged schema comprising a third plurality of business entities, including a single instance of the first business entity; storing the merged schema in a database; extracting a first sequence of words from the first name of the first business entity; generating candidate phrases for the business entity from the first and second sequences of words; and ranking the candidate phrases for the first business entity; analyzing candidate sets of labels for the third plurality of business entities, each candidate set of labels including a label for each business entity of the third plurality of business entities, no two business entities having the same label in the candidate set of labels, the label for the first business entity being selected from the candidate phrases for the first business entity; and assigning labels to each business entity of the third plurality of business entities based on the analysis of the candidate sets of labels; and receiving data stored using the first schema; converting the received data to the merged schema; and causing a presentation of the converted data using the assigned labels. 16. The system of claim 13 , wherein the ranking of the candidate phrases for the first business entity includes ranking the candidate phrases for the business entity based on a frequency of words in each candidate phrase in a description of the first business entity. | 0.802651 |
8,752,183 | 1 | 13 | 1. A method for testing a vulnerability of a web site, comprising: receiving a first set of addresses; identifying a second set of addresses by analyzing a first set of web pages located at the first set of addresses; identifying a third set of addresses by analyzing a first set of document object models (DOMs) associated with the first set of web pages and associated with a second set of web pages located at the second set of addresses; probing a third set of web pages for presence of a set of vulnerabilities using a document object model (DOM) analysis script to analyze a second set of document object models (DOMs) associated with the third set of web pages as a set of attack vectors is applied to the third set of web pages, wherein the third set of web pages is located at the first, second, and third sets of addresses, and the DOM analysis script is inserted into the third set of web pages; and determining presence of the set of vulnerabilities for the third set of web pages based on a set of results from the probing, wherein the attack vectors are designed to exploit a vulnerability of a web page. | 1. A method for testing a vulnerability of a web site, comprising: receiving a first set of addresses; identifying a second set of addresses by analyzing a first set of web pages located at the first set of addresses; identifying a third set of addresses by analyzing a first set of document object models (DOMs) associated with the first set of web pages and associated with a second set of web pages located at the second set of addresses; probing a third set of web pages for presence of a set of vulnerabilities using a document object model (DOM) analysis script to analyze a second set of document object models (DOMs) associated with the third set of web pages as a set of attack vectors is applied to the third set of web pages, wherein the third set of web pages is located at the first, second, and third sets of addresses, and the DOM analysis script is inserted into the third set of web pages; and determining presence of the set of vulnerabilities for the third set of web pages based on a set of results from the probing, wherein the attack vectors are designed to exploit a vulnerability of a web page. 13. The method of claim 1 , wherein determining the presence of the set of vulnerabilities based on the set of results comprises matching a result in the set of results with a vulnerability result signature associated with a vulnerability in the set of vulnerabilities. | 0.800741 |
8,615,421 | 1 | 12 | 1. A method of providing environmental transparency for entities, comprising: displaying via a website, a plurality of environmental categories, the plurality of environmental categories comprising recycling practices, use of public transportation, and energy saving practices; creating a nonpublic database of a plurality of the entities directly employing the actions within one or more of the plurality of environmental categories, wherein the non-public database allows a certified entity to measure the change in population of entities that are choosing to employ environmental actions; via the web site, receiving input from a first entity, the input comprising an indication of the first entity's performance of actions within one or more of the plurality of environmental categories; via the web site, storing on a computer readable storage medium; via the web site, publicly displaying: the plurality of environmental categories and showing, based on the input, that the first entity performs actions within selected categories; and a visual entity identifier adjacent to the plurality of environmental categories, wherein the visual entity identifier comprises one of a logo and a name of the first entity; and via the website, publicly displaying inspirational information regarding the first entity, wherein: the inspirational information is associated with the first entity and is collected by the website from at least one second entity, the inspirational information identifying the first entity as having inspired the at least one second entity; and the inspirational information includes a numerical exhibit reflecting a number of entities that the first entity has inspired, the numerical exhibit including a tally of the entities inspired by the first entity, wherein the method allows consumers or other relationship partners to have access to the input from the first entity, which provides transparency regarding the first entity's environmental conduct and inspirational effect. | 1. A method of providing environmental transparency for entities, comprising: displaying via a website, a plurality of environmental categories, the plurality of environmental categories comprising recycling practices, use of public transportation, and energy saving practices; creating a nonpublic database of a plurality of the entities directly employing the actions within one or more of the plurality of environmental categories, wherein the non-public database allows a certified entity to measure the change in population of entities that are choosing to employ environmental actions; via the web site, receiving input from a first entity, the input comprising an indication of the first entity's performance of actions within one or more of the plurality of environmental categories; via the web site, storing on a computer readable storage medium; via the web site, publicly displaying: the plurality of environmental categories and showing, based on the input, that the first entity performs actions within selected categories; and a visual entity identifier adjacent to the plurality of environmental categories, wherein the visual entity identifier comprises one of a logo and a name of the first entity; and via the website, publicly displaying inspirational information regarding the first entity, wherein: the inspirational information is associated with the first entity and is collected by the website from at least one second entity, the inspirational information identifying the first entity as having inspired the at least one second entity; and the inspirational information includes a numerical exhibit reflecting a number of entities that the first entity has inspired, the numerical exhibit including a tally of the entities inspired by the first entity, wherein the method allows consumers or other relationship partners to have access to the input from the first entity, which provides transparency regarding the first entity's environmental conduct and inspirational effect. 12. The method of claim 1 , further comprising receiving input regarding performance of the actions within one or more of the plurality of environmental categories via the website from a third entity of the entities. | 0.548117 |
8,880,445 | 3 | 4 | 3. The method of claim 2 , wherein the continuous feedback data includes supervised training information and feature resolution data. | 3. The method of claim 2 , wherein the continuous feedback data includes supervised training information and feature resolution data. 4. The method of claim 3 , wherein the supervised training information is generated from a supervised training session. | 0.947392 |
8,078,960 | 1 | 19 | 1. A method comprising: receiving an instruction to open a document in a first markup language; searching the document to locate a processing instruction (PI) including a solution identifier; discovering a solution using the solution identifier; opening the document with the solution, wherein: the solution includes a presentation application in the first markup language and a schema in the first markup language; the document can be inferred from the schema; and portions of the document are logically coupled with fragments of the schema; executing the presentation application to render an electronic form in a second markup language, different from the first markup language, the electronic form containing user input fields associated with the coupled portions; receiving, through one or more of the user input fields, data input by a user; validating the data input by the user with one or more of a plurality of validation rules, each of the one or more plurality of validation rules corresponding to one of said user input fields through which data is input by the user, each said validation rule: mapping to each said validation rule's corresponding said user input field by use of a first entity selected from the group consisting essentially of: a first path expression in the first markup language; a declarative syntax; and an entity that is script-based; and mapping to said coupled portion to which each said validation rule's corresponding said user input field is associated, the mapping with a second entity selected from the group consisting essentially of: a second path expression in the first markup language; an event handler; an event handler that determines when a real-time validation tool uses said validation rule; an event handler that determines when a real-time validation tool uses said validation rule before data received for said coupled portion is held by the document; and an event handler that determines when a real-time validation tool uses said validation rule after data received for said coupled portion is held by the document, and if the act of validating determines that the data input by the user is invalid, outputting indicia informing the user that the data input is invalid. | 1. A method comprising: receiving an instruction to open a document in a first markup language; searching the document to locate a processing instruction (PI) including a solution identifier; discovering a solution using the solution identifier; opening the document with the solution, wherein: the solution includes a presentation application in the first markup language and a schema in the first markup language; the document can be inferred from the schema; and portions of the document are logically coupled with fragments of the schema; executing the presentation application to render an electronic form in a second markup language, different from the first markup language, the electronic form containing user input fields associated with the coupled portions; receiving, through one or more of the user input fields, data input by a user; validating the data input by the user with one or more of a plurality of validation rules, each of the one or more plurality of validation rules corresponding to one of said user input fields through which data is input by the user, each said validation rule: mapping to each said validation rule's corresponding said user input field by use of a first entity selected from the group consisting essentially of: a first path expression in the first markup language; a declarative syntax; and an entity that is script-based; and mapping to said coupled portion to which each said validation rule's corresponding said user input field is associated, the mapping with a second entity selected from the group consisting essentially of: a second path expression in the first markup language; an event handler; an event handler that determines when a real-time validation tool uses said validation rule; an event handler that determines when a real-time validation tool uses said validation rule before data received for said coupled portion is held by the document; and an event handler that determines when a real-time validation tool uses said validation rule after data received for said coupled portion is held by the document, and if the act of validating determines that the data input by the user is invalid, outputting indicia informing the user that the data input is invalid. 19. The method as defined in claim 1 , wherein: the solution identifier includes at least one of a PI version and a product version; and discovering the solution comprises discovering the solution using a name associated with the PI version or the product version. | 0.745665 |
9,986,394 | 4 | 8 | 4. A system comprising: at least one processor; and at least one memory including instructions that, when executed by the at least one processor, configure the system to: receive, from a first device configured to capture spoken commands, input audio data corresponding to an utterance including message content; perform automatic speech recognition (ASR) on the input audio data to generate text data; determine, based on the text data, an intended recipient of the message content; determine a second device associated with the intended recipient; determine the second device is not configured to communicate using a direct audio messaging functionality; determine a first portion of the input audio data corresponding to the message content; store the first portion of the input audio data; generate a link associated with the first portion of the input audio data; generate message payload data including text corresponding to the message and the link; identify a third device associated with a sender of the message content, the third device capable of operating a first application to send a text-based message; and send, to a second application operable by the third device, the message payload data and an application programming interface (API) instruction causing the third device to send the message payload data from the second application to the first application for delivery to the second device. | 4. A system comprising: at least one processor; and at least one memory including instructions that, when executed by the at least one processor, configure the system to: receive, from a first device configured to capture spoken commands, input audio data corresponding to an utterance including message content; perform automatic speech recognition (ASR) on the input audio data to generate text data; determine, based on the text data, an intended recipient of the message content; determine a second device associated with the intended recipient; determine the second device is not configured to communicate using a direct audio messaging functionality; determine a first portion of the input audio data corresponding to the message content; store the first portion of the input audio data; generate a link associated with the first portion of the input audio data; generate message payload data including text corresponding to the message and the link; identify a third device associated with a sender of the message content, the third device capable of operating a first application to send a text-based message; and send, to a second application operable by the third device, the message payload data and an application programming interface (API) instruction causing the third device to send the message payload data from the second application to the first application for delivery to the second device. 8. The system of claim 4 , wherein the input audio data includes a second portion indicating a message corresponding to the message content should include a link. | 0.879104 |
9,860,262 | 18 | 21 | 18. The method of claim 17 , further comprising the steps of: selecting one or more of the zeta words to be anchor words; encoding in a vector a ζ , the probabilities of the anchor words, given that the process snippet contains one or more zeta words; creating a sparse vector a μ , that estimates the probabilities for the non-zeta words in the process snippet; and combining by direct weighted sum the vector a ζ and the sparse vector a μ into the sparse vector a of the process dot:
a=b ζ a ζ ⊕b μ a μ with weights b ζ and b μ . | 18. The method of claim 17 , further comprising the steps of: selecting one or more of the zeta words to be anchor words; encoding in a vector a ζ , the probabilities of the anchor words, given that the process snippet contains one or more zeta words; creating a sparse vector a μ , that estimates the probabilities for the non-zeta words in the process snippet; and combining by direct weighted sum the vector a ζ and the sparse vector a μ into the sparse vector a of the process dot:
a=b ζ a ζ ⊕b μ a μ with weights b ζ and b μ . 21. The method of claim 18 , wherein each entry in the sparse vector a of the compact representation is proportional to a probability that a feature is observed given an execution environment. | 0.913122 |
8,276,101 | 1 | 2 | 1. A method comprising: receiving, using a presence-sensitive display coupled to a computing device, a first user input comprising a first drawing gesture associated with a first area for user input defined at the presence-sensitive display, wherein the first user input specifies one or more characters to be displayed at the presence-sensitive display, and wherein the first drawing gesture includes a drawn representation of the one or more characters; receiving, using the presence-sensitive display, a second user input comprising a second drawing gesture, wherein the second drawing gesture spans only the first area and a second area for user input defined at the presence-sensitive display, and wherein the second user input specifies a first editing operation associated with the one or more characters; applying, by the computing device, the first editing operation to the one or more characters in response to receiving the second user input; receiving, using the presence-sensitive display, a third user input comprising a third drawing gesture, wherein the third drawing gesture spans the first area, the second area, and a third area for user input defined at the presence-sensitive display, and wherein the third user input specifies a second editing operation associated with the one or more characters; and applying, by the computing device, the second editing operation to the one or more characters in response to receiving the third user input. | 1. A method comprising: receiving, using a presence-sensitive display coupled to a computing device, a first user input comprising a first drawing gesture associated with a first area for user input defined at the presence-sensitive display, wherein the first user input specifies one or more characters to be displayed at the presence-sensitive display, and wherein the first drawing gesture includes a drawn representation of the one or more characters; receiving, using the presence-sensitive display, a second user input comprising a second drawing gesture, wherein the second drawing gesture spans only the first area and a second area for user input defined at the presence-sensitive display, and wherein the second user input specifies a first editing operation associated with the one or more characters; applying, by the computing device, the first editing operation to the one or more characters in response to receiving the second user input; receiving, using the presence-sensitive display, a third user input comprising a third drawing gesture, wherein the third drawing gesture spans the first area, the second area, and a third area for user input defined at the presence-sensitive display, and wherein the third user input specifies a second editing operation associated with the one or more characters; and applying, by the computing device, the second editing operation to the one or more characters in response to receiving the third user input. 2. The method of claim 1 , wherein the first editing operation is based on a direction of the second drawing gesture that spans the first area and the second area. | 0.795739 |
8,788,340 | 11 | 12 | 11. The method of claim 1 , wherein one or more of the concept nodes comprises a multimedia object created by the application. | 11. The method of claim 1 , wherein one or more of the concept nodes comprises a multimedia object created by the application. 12. The method of claim 11 , wherein the multimedia object comprises an audio file, a video file, a picture, text, or any combination thereof. | 0.97038 |
7,580,839 | 1 | 4 | 1. A speech processing apparatus comprising: a speech storage configured to store a plurality of speech units of a conversion-source speaker and source-speaker attribute information corresponding to the speech units; a speech-unit extractor configured to divide the speech of a conversion-target speaker into a predetermined type of a speech unit to form target-speaker speech units; an attribute-information generator configured to generate target-speaker attribute information corresponding to the target-speaker speech units from the speech of the conversion-target speaker or linguistic information of the speech; a speech-unit selector configured to calculate costs on the target-speaker attribute information and the source-speaker attribute information using cost functions, and selects one or a plurality of speech units with the same phoneme from the speech storage according to the costs to form a source-speaker speech unit; and a voice-conversion-rule generator configured to generate speech conversion functions for converting the one or the plurality of source-speaker speech units to the target-speaker speech units based on the target-speaker speech units and the one or the plurality of source-speakerspeech units. | 1. A speech processing apparatus comprising: a speech storage configured to store a plurality of speech units of a conversion-source speaker and source-speaker attribute information corresponding to the speech units; a speech-unit extractor configured to divide the speech of a conversion-target speaker into a predetermined type of a speech unit to form target-speaker speech units; an attribute-information generator configured to generate target-speaker attribute information corresponding to the target-speaker speech units from the speech of the conversion-target speaker or linguistic information of the speech; a speech-unit selector configured to calculate costs on the target-speaker attribute information and the source-speaker attribute information using cost functions, and selects one or a plurality of speech units with the same phoneme from the speech storage according to the costs to form a source-speaker speech unit; and a voice-conversion-rule generator configured to generate speech conversion functions for converting the one or the plurality of source-speaker speech units to the target-speaker speech units based on the target-speaker speech units and the one or the plurality of source-speakerspeech units. 4. The apparatus according to claim 1 , wherein the attribute-information generator comprises: an attribute-conversion-rule generator configured to generate an attribute conversion function for converting the attribute information of the conversion-target speaker to the attribute information of the conversion-source speaker; an attribute-information extractor configured to extract attribute information corresponding to the target-speaker speech units from the speech of the conversion-target speaker or the linguistic information of the speech of the conversion-target speaker; and an attribute-information converter configured to convert the attribute information corresponding to the target-speaker speech units using the attribute conversion function to use the converted attribute information as target-speaker attribute information corresponding to the target-speaker speech units. | 0.500561 |
7,499,908 | 7 | 11 | 7. A method to identify a workload type concentration for a given workload, the method comprising: producing a plurality of performance snapshots of a training set, the training set comprising a plurality of training workloads, each training workload predetermined to elicit a particular database behavior associated with a known workload type, the workload type comprising one of an Online Transactional Processing (OLTP) type and a Decision Support System (DSS) type, an OLTP type characterized by short simple database queries with many concurrent users, a DSS type characterized by long complex database queries with few concurrent users, each performance snapshot comprising database behavior across a predetermined time interval and classified as one of OLTP and DSS; extracting a set of attributes from the training set; constructing a set of rules based on the classification of the plurality of performance snapshots and the set of attributes, the set of rules organized into a decision tree having a rule per tree node, each node of the decision tree for testing an attribute related to the workload type; selecting a sample of the given workload; producing a plurality of performance snapshots for the selected sample; comparing the plurality of performance snapshots from the selected sample and the set of rules; classifying each performance snapshot from the selected sample as one of OLTP and DSS; and identifying the workload type concentration of the selected sample based on an OLTP to DSS ratio, the workload type concentration comprising a combination of OLTP and DSS, wherein a database may be more accurately tuned based on the workload type concentration, thereby enhancing database performance. | 7. A method to identify a workload type concentration for a given workload, the method comprising: producing a plurality of performance snapshots of a training set, the training set comprising a plurality of training workloads, each training workload predetermined to elicit a particular database behavior associated with a known workload type, the workload type comprising one of an Online Transactional Processing (OLTP) type and a Decision Support System (DSS) type, an OLTP type characterized by short simple database queries with many concurrent users, a DSS type characterized by long complex database queries with few concurrent users, each performance snapshot comprising database behavior across a predetermined time interval and classified as one of OLTP and DSS; extracting a set of attributes from the training set; constructing a set of rules based on the classification of the plurality of performance snapshots and the set of attributes, the set of rules organized into a decision tree having a rule per tree node, each node of the decision tree for testing an attribute related to the workload type; selecting a sample of the given workload; producing a plurality of performance snapshots for the selected sample; comparing the plurality of performance snapshots from the selected sample and the set of rules; classifying each performance snapshot from the selected sample as one of OLTP and DSS; and identifying the workload type concentration of the selected sample based on an OLTP to DSS ratio, the workload type concentration comprising a combination of OLTP and DSS, wherein a database may be more accurately tuned based on the workload type concentration, thereby enhancing database performance. 11. The method of claim 7 further comprising validating the set of rules when drastic changes occur to the given workload. | 0.551471 |
7,787,907 | 1 | 2 | 1. A control system for use in a vehicle and for accessing data files from a portable electronic device over a wireless communication link, the vehicle including a microphone for receiving an oral command from a vehicle occupant and an output display, the system comprising: a communication device for establishing the wireless communication link with the portable electronic device, the communication device being configured to receive a plurality of data files from the portable electronic device, wherein each of the data files includes text data; a data processing device coupled to the communication device, the data processing device being configured to generate a phonemic representation of the text data of the data files, wherein the phonemic representation of the text data of each data file is configured to facilitate speech recognition relating to the files; a speech recognition device configured to receive the oral command from the microphone, the speech recognition device being further configured to compare the received oral command to the phonemic representation of the data file generated by the data processing device; and a display driver for coupling to the output display, the display driver being configured to provide an electronic signal to the output display, wherein the electronic signal comprises a representation of the text data. | 1. A control system for use in a vehicle and for accessing data files from a portable electronic device over a wireless communication link, the vehicle including a microphone for receiving an oral command from a vehicle occupant and an output display, the system comprising: a communication device for establishing the wireless communication link with the portable electronic device, the communication device being configured to receive a plurality of data files from the portable electronic device, wherein each of the data files includes text data; a data processing device coupled to the communication device, the data processing device being configured to generate a phonemic representation of the text data of the data files, wherein the phonemic representation of the text data of each data file is configured to facilitate speech recognition relating to the files; a speech recognition device configured to receive the oral command from the microphone, the speech recognition device being further configured to compare the received oral command to the phonemic representation of the data file generated by the data processing device; and a display driver for coupling to the output display, the display driver being configured to provide an electronic signal to the output display, wherein the electronic signal comprises a representation of the text data. 2. A control system according to claim 1 , further including a user interface configured to receive input commands from a user to facilitate accessing and manipulating the data files accessed from the portable electronic device. | 0.502183 |
8,086,997 | 3 | 4 | 3. The computer implemented method of claim 1 , wherein creating a set of bit representations further comprises: reserving a bit for each method invocation of each class in the production rules to create a class-method pairing for each class; joining the class-method pairing for each class in the production rules together to form a message sequence; and reserving a bit for the message sequence. | 3. The computer implemented method of claim 1 , wherein creating a set of bit representations further comprises: reserving a bit for each method invocation of each class in the production rules to create a class-method pairing for each class; joining the class-method pairing for each class in the production rules together to form a message sequence; and reserving a bit for the message sequence. 4. The computer implemented method of claim 3 , wherein detecting common sub-sequences further comprises: performing a bitwise “OR” over a pattern defined by the message sequence; and performing a bitwise “AND” over a pattern defined by the each method invocation. | 0.880218 |
10,083,685 | 12 | 16 | 12. A method of changing vehicle features of an existing automatic speech recognition (ASR) system that includes a processor, comprising the steps of: (a) receiving, at a vehicle, a vehicle feature to add to or remove from the existing ASR system; (b) establishing, at the vehicle, a database of keywords that identify the vehicle feature; (c) applying a secondary speech recognition module to the existing ASR system, wherein the secondary speech recognition module is configured to monitor speech received from a vehicle occupant via a microphone for one or more of the keywords; (d) detecting one or more keywords in the monitored speech using the secondary speech recognition module executed by the processor; and (e) adding or removing the vehicle feature from the existing ASR system at a pre-processor software module or a post-processor software module based on step (d) so that the existing ASR system provides a defined number of vehicle features that conform to or match the features available at a vehicle, wherein adding or removing the vehicle feature modifies the configuration of the existing ASR system. | 12. A method of changing vehicle features of an existing automatic speech recognition (ASR) system that includes a processor, comprising the steps of: (a) receiving, at a vehicle, a vehicle feature to add to or remove from the existing ASR system; (b) establishing, at the vehicle, a database of keywords that identify the vehicle feature; (c) applying a secondary speech recognition module to the existing ASR system, wherein the secondary speech recognition module is configured to monitor speech received from a vehicle occupant via a microphone for one or more of the keywords; (d) detecting one or more keywords in the monitored speech using the secondary speech recognition module executed by the processor; and (e) adding or removing the vehicle feature from the existing ASR system at a pre-processor software module or a post-processor software module based on step (d) so that the existing ASR system provides a defined number of vehicle features that conform to or match the features available at a vehicle, wherein adding or removing the vehicle feature modifies the configuration of the existing ASR system. 16. The method of claim 12 , wherein the vehicle feature comprises a navigation feature, a radio feature, a telephone feature, or a multimedia feature. | 0.805913 |
8,918,713 | 50 | 51 | 50. A system to generate module data for use with a personalized container document, comprising: a computer memory; at least one hardware processor interoperably coupled with the computer memory and configured to: identify particular code that corresponds to a first module, the first module selectively designated for inclusion in a personalized container document, wherein the particular code provides first module data and parameters associated with the first module, wherein the first module data is adapted for use in the personalized container document, the parameters of the particular code including a first content element and one or more preference elements; identify additional code that corresponds to a second module selectively designated for inclusion in the personalized container document, wherein the additional code provides second module data and parameters associated with the second module, wherein the second module data is adapted for use in the personalized container document, the parameters of the additional code including a second content element; receive, into memory, the first module data and the second module data; serve the first module data and the second module data with the personalized container document to a remote browser client; wherein the personalized container document defines an organization for a presentation of content associated with the first module and the second module in a container document display, wherein for each module a portion of the container document display is allocated for the presentation of content corresponding to the module; wherein the first module data and the second module data includes computer-executable instructions adapted for execution by the remote browser client to render content for the corresponding module for presentation in the container document display; and wherein the first content element is different than the second content element and the one or more preference elements include at least one module preference element adapted to specify at least two alternative presentation states of content for the first module, the at least one module preference element defining conditions that change independent of user input in the container document display for dynamically presenting content in one of the at least two presentation states, with content rendered, using the computer-executable instructions executed by the remote browser client, in a first of the at least two presentation states in response to a first condition and rendered, using the computer-executable instructions executed by the remote browser client, in a second of the at least two presentation states in response to a second condition. | 50. A system to generate module data for use with a personalized container document, comprising: a computer memory; at least one hardware processor interoperably coupled with the computer memory and configured to: identify particular code that corresponds to a first module, the first module selectively designated for inclusion in a personalized container document, wherein the particular code provides first module data and parameters associated with the first module, wherein the first module data is adapted for use in the personalized container document, the parameters of the particular code including a first content element and one or more preference elements; identify additional code that corresponds to a second module selectively designated for inclusion in the personalized container document, wherein the additional code provides second module data and parameters associated with the second module, wherein the second module data is adapted for use in the personalized container document, the parameters of the additional code including a second content element; receive, into memory, the first module data and the second module data; serve the first module data and the second module data with the personalized container document to a remote browser client; wherein the personalized container document defines an organization for a presentation of content associated with the first module and the second module in a container document display, wherein for each module a portion of the container document display is allocated for the presentation of content corresponding to the module; wherein the first module data and the second module data includes computer-executable instructions adapted for execution by the remote browser client to render content for the corresponding module for presentation in the container document display; and wherein the first content element is different than the second content element and the one or more preference elements include at least one module preference element adapted to specify at least two alternative presentation states of content for the first module, the at least one module preference element defining conditions that change independent of user input in the container document display for dynamically presenting content in one of the at least two presentation states, with content rendered, using the computer-executable instructions executed by the remote browser client, in a first of the at least two presentation states in response to a first condition and rendered, using the computer-executable instructions executed by the remote browser client, in a second of the at least two presentation states in response to a second condition. 51. The system of claim 50 wherein one or more preferences comprise user preferences. | 0.77027 |
9,912,775 | 1 | 3 | 1. A non-transitory machine-readable medium including instructions for transmitting a message to a secondary computing device, which when executed by a machine, cause the machine to perform operations comprising: receiving a communication message at a primary computing device of a user; transmitting a default response option, from the primary computing device to the secondary computing device, to respond to the communication message based on a context of the user, the context of the user determined by using a sensor included in the primary computing device; identifying a message mode for communicating with a secondary computing device of the user based on a context of the user determined by using a sensor included in the primary computing device; and determining that the communication message is to be transmitted to the secondary computing device of the user based on the message mode, and based on the determining: translating the communication message into a translated message according to the message mode, the translating comprising truncating content of the communication message; and transmitting the translated message to the secondary computing device from the primary computing device. | 1. A non-transitory machine-readable medium including instructions for transmitting a message to a secondary computing device, which when executed by a machine, cause the machine to perform operations comprising: receiving a communication message at a primary computing device of a user; transmitting a default response option, from the primary computing device to the secondary computing device, to respond to the communication message based on a context of the user, the context of the user determined by using a sensor included in the primary computing device; identifying a message mode for communicating with a secondary computing device of the user based on a context of the user determined by using a sensor included in the primary computing device; and determining that the communication message is to be transmitted to the secondary computing device of the user based on the message mode, and based on the determining: translating the communication message into a translated message according to the message mode, the translating comprising truncating content of the communication message; and transmitting the translated message to the secondary computing device from the primary computing device. 3. The machine-readable medium of claim 1 , wherein translating the communication message into the translated message comprises: reducing content of the communication message into at least one keyword. | 0.765187 |
7,496,560 | 28 | 38 | 28. A computer system that provides electronic searching of a user-personalized library of content, comprising a processor, a search server in communication with a database server, in which the database server is configured with a general library of content that is accessible to multiple users, the general library including (1) a page image database containing images of pages of content, (2) an access rights database containing access rules that define the scope of content to be displayed to each user, and (3) a text searchable database containing text and identifying information indicating the page images in the page image database that contain the text, the search server being configured with a search engine comprised of computer-implemented instructions that enable the search server to: (a) receive one or more search terms from a user having established a personalized library within the general library of content, (b) search the full text of the user's personalized library for pages of content that match the search terms, (c) provide the results of the full text search to the user for selection by the user, (d) prepare a substitute image of a page image in the page image database corresponding to the search result selection from the user, wherein a portion of the content in the page image is suppressed in the substitute image in accordance with one or more access rules to limit the amount of content in the substitute image, (e) provide location information to the user that identifies the location of the search terms in the substitute image, and (f) provide to the user the substitute image responsive to the user's search result selection with an instruction to highlight the search terms in the substitute image, wherein the instruction to highlight the search terms in the substitute image comprises an instruction to apply a layer of color on or near the search terms. | 28. A computer system that provides electronic searching of a user-personalized library of content, comprising a processor, a search server in communication with a database server, in which the database server is configured with a general library of content that is accessible to multiple users, the general library including (1) a page image database containing images of pages of content, (2) an access rights database containing access rules that define the scope of content to be displayed to each user, and (3) a text searchable database containing text and identifying information indicating the page images in the page image database that contain the text, the search server being configured with a search engine comprised of computer-implemented instructions that enable the search server to: (a) receive one or more search terms from a user having established a personalized library within the general library of content, (b) search the full text of the user's personalized library for pages of content that match the search terms, (c) provide the results of the full text search to the user for selection by the user, (d) prepare a substitute image of a page image in the page image database corresponding to the search result selection from the user, wherein a portion of the content in the page image is suppressed in the substitute image in accordance with one or more access rules to limit the amount of content in the substitute image, (e) provide location information to the user that identifies the location of the search terms in the substitute image, and (f) provide to the user the substitute image responsive to the user's search result selection with an instruction to highlight the search terms in the substitute image, wherein the instruction to highlight the search terms in the substitute image comprises an instruction to apply a layer of color on or near the search terms. 38. The computer system of claim 28 , in which the search server provides the search results in the form of a list of content having pages with text that matches the search terms, which content in the list of content is ranked according to a predetermined criterion. | 0.514599 |
9,811,938 | 1 | 5 | 1. A method for generating an animated data visualization, the method comprising submitting a data query on a data structure; obtaining a time measurement for performing the data query, the time measurement being an amount of time between the submission of the query and obtaining a query result; adjusting, using one or more hardware processors, a sample size of the data query based on the time measurement and a frame refresh rate, wherein the sample size is a size of a subset of data obtained in a sample, wherein the adjusting increases the sample size if the obtained time measurement multiplied by a multiplication factor is smaller than an inverse of the frame refresh rate, and wherein the multiplication factor is not equal to zero or one; and generating the animated data visualization based on one or more results of the data query. | 1. A method for generating an animated data visualization, the method comprising submitting a data query on a data structure; obtaining a time measurement for performing the data query, the time measurement being an amount of time between the submission of the query and obtaining a query result; adjusting, using one or more hardware processors, a sample size of the data query based on the time measurement and a frame refresh rate, wherein the sample size is a size of a subset of data obtained in a sample, wherein the adjusting increases the sample size if the obtained time measurement multiplied by a multiplication factor is smaller than an inverse of the frame refresh rate, and wherein the multiplication factor is not equal to zero or one; and generating the animated data visualization based on one or more results of the data query. 5. The method of claim 1 , wherein the time measurement is obtained by determining an average amount of time to obtain a query result for each of a plurality of queries. | 0.781654 |
5,379,366 | 19 | 20 | 19. The method for representing information in a computer system according to claim 18, wherein the step of deriving a specific document includes the steps of: selecting a view, class, and type of display for said active concept record; automatically deriving the selected type of display by reading a subset of the records in said knowledge representation database relative to said active concept record, based on stored relationships therein, which subset defines the concepts constituting said selected type of display; assigning icons to said subset of the records according to said selected type of display; organizing and locating said icons in a display space of said computer system according to said selected class; and creating connection icons for interconnections between concept icons located in said display space according to said selected view. | 19. The method for representing information in a computer system according to claim 18, wherein the step of deriving a specific document includes the steps of: selecting a view, class, and type of display for said active concept record; automatically deriving the selected type of display by reading a subset of the records in said knowledge representation database relative to said active concept record, based on stored relationships therein, which subset defines the concepts constituting said selected type of display; assigning icons to said subset of the records according to said selected type of display; organizing and locating said icons in a display space of said computer system according to said selected class; and creating connection icons for interconnections between concept icons located in said display space according to said selected view. 20. The method for representing information in a computer system according to claim 19, wherein the type specifies particular procedures for selecting a subset of the information in said knowledge representation database, reading the descriptive networks for the concepts in said subset, and assigning icons to the concepts in said subset. | 0.977239 |
8,489,538 | 19 | 26 | 19. A method for analyzing a plurality of documents, comprising: receiving the plurality of documents via a computing device; filtering the plurality of documents to produce a subset of the plurality of documents; executing instructions stored in memory, wherein execution of the instructions by a processor generates an initial control set based on random sampling of the subset of the plurality of documents on a rolling load basis; receiving user input from the computing device, the user input based on an identified subject or category; and executing instructions stored in memory, wherein execution of the instructions by a processor: reviews the initial control set to determine at least one seed set parameter associated with the identified subject or category, automatically codes a first portion of the plurality of documents, based on the initial control set and the at least one seed set parameter associated with the identified subject or category, automatically codes a second portion of the plurality of documents resulting from an application of user analysis and an adaptive identification cycle, and adds the coded second portion of the plurality of documents to the initial control set. | 19. A method for analyzing a plurality of documents, comprising: receiving the plurality of documents via a computing device; filtering the plurality of documents to produce a subset of the plurality of documents; executing instructions stored in memory, wherein execution of the instructions by a processor generates an initial control set based on random sampling of the subset of the plurality of documents on a rolling load basis; receiving user input from the computing device, the user input based on an identified subject or category; and executing instructions stored in memory, wherein execution of the instructions by a processor: reviews the initial control set to determine at least one seed set parameter associated with the identified subject or category, automatically codes a first portion of the plurality of documents, based on the initial control set and the at least one seed set parameter associated with the identified subject or category, automatically codes a second portion of the plurality of documents resulting from an application of user analysis and an adaptive identification cycle, and adds the coded second portion of the plurality of documents to the initial control set. 26. The method of claim 19 , further comprising applying targeted document identification on the plurality of documents. | 0.871245 |
7,653,545 | 2 | 3 | 2. A method as claimed in claim 1 , wherein said prompts and grammar are generated on the basis of a predetermined pattern or structure for said prompts and grammar. | 2. A method as claimed in claim 1 , wherein said prompts and grammar are generated on the basis of a predetermined pattern or structure for said prompts and grammar. 3. A method as claimed in claim 2 wherein said grammar includes predefined grammar. | 0.971788 |
8,407,216 | 11 | 14 | 11. A method for automatically generating tag terms for objects in databases of a web site that is automatically created based on a subject, comprising: receiving a plurality of search terms related to the subject to create the web site; searching Internet web sites to identify information associated with the plurality of search terms on the Internet web sites to automatically create the web site; storing an identified information associated with the plurality of search terms as an object to a database of the web site; processing the identified information to determine which one of the plurality of search terms the identified information is associated with; wherein the identified information associated with the plurality of search terms to be used as content of the web site includes one or more of photos, music, videos, and articles; automatically generating a tag term for the identified information in the database using the one of the plurality of search terms determined to be associated with the identified information; processing and parsing any additional metadata of the identified information stored as an object to determine keywords to be used as additional tag terms for the identified information, the processing and parsing removing symbols and words without functionality as tag terms for the identified information; and automatically storing the additional tag terms as automatically generated tag terms for the identified information in the database; wherein the automatically generated tag terms for the identified information enable the identified information to be searched and to be associated with other objects in the databases on the web site without user involvement; generating a web page of the web site, the web page defining a content area related to the subject of the web site; populating the content area of the web page based on a search of the automatically generated tag terms. | 11. A method for automatically generating tag terms for objects in databases of a web site that is automatically created based on a subject, comprising: receiving a plurality of search terms related to the subject to create the web site; searching Internet web sites to identify information associated with the plurality of search terms on the Internet web sites to automatically create the web site; storing an identified information associated with the plurality of search terms as an object to a database of the web site; processing the identified information to determine which one of the plurality of search terms the identified information is associated with; wherein the identified information associated with the plurality of search terms to be used as content of the web site includes one or more of photos, music, videos, and articles; automatically generating a tag term for the identified information in the database using the one of the plurality of search terms determined to be associated with the identified information; processing and parsing any additional metadata of the identified information stored as an object to determine keywords to be used as additional tag terms for the identified information, the processing and parsing removing symbols and words without functionality as tag terms for the identified information; and automatically storing the additional tag terms as automatically generated tag terms for the identified information in the database; wherein the automatically generated tag terms for the identified information enable the identified information to be searched and to be associated with other objects in the databases on the web site without user involvement; generating a web page of the web site, the web page defining a content area related to the subject of the web site; populating the content area of the web page based on a search of the automatically generated tag terms. 14. The method of claim 11 , wherein the processing of the any additional metadata involves identifying a common term in the any additional metadata that exists in metadata of other objects in the database of the web site, the common term determined as a keyword for the identified information. | 0.720532 |
8,090,157 | 1 | 8 | 1. A computer implemented eye detection system for detecting eyes in a digital image, the system comprising: a digital image capture device; and a processor, the processor including: a filter; a first eye candidate selector connected to the filter; a first profile validator connected to the eye candidate selector, the first profile validator including measurements of eye candidate pupil contours; a first eye candidate eliminator connected to the first profile validator and the first eye candidate selector; a second eye candidate selector connected to the first profile validator; a pair validator connected to the second eye candidate selector, the pair validator including a space measurer that determines if the first and second eye candidates are at an appropriate distance from each other; a second profile validator connected to the pair validator; and a second eye candidate eliminator connected to the second profile validator and the second eye candidate selector; wherein the first profile validator comprising a first profiler connected to the first eye candidate selector, and a first profile evaluator connected to the first profiler, the first eye candidate eliminator and the second eye candidate selector; wherein the second profile validator comprises a second profiler connected to the pair validator, and a second profile evaluator connected to the second profiler and the second eye candidate eliminator; wherein the first profiler comprises: a pupil region extractor connected to the first eye candidate selector; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the first profile evaluator; and wherein the second profiler comprises: a pupil region extractor connected to the pair validator; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the second profile evaluator. | 1. A computer implemented eye detection system for detecting eyes in a digital image, the system comprising: a digital image capture device; and a processor, the processor including: a filter; a first eye candidate selector connected to the filter; a first profile validator connected to the eye candidate selector, the first profile validator including measurements of eye candidate pupil contours; a first eye candidate eliminator connected to the first profile validator and the first eye candidate selector; a second eye candidate selector connected to the first profile validator; a pair validator connected to the second eye candidate selector, the pair validator including a space measurer that determines if the first and second eye candidates are at an appropriate distance from each other; a second profile validator connected to the pair validator; and a second eye candidate eliminator connected to the second profile validator and the second eye candidate selector; wherein the first profile validator comprising a first profiler connected to the first eye candidate selector, and a first profile evaluator connected to the first profiler, the first eye candidate eliminator and the second eye candidate selector; wherein the second profile validator comprises a second profiler connected to the pair validator, and a second profile evaluator connected to the second profiler and the second eye candidate eliminator; wherein the first profiler comprises: a pupil region extractor connected to the first eye candidate selector; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the first profile evaluator; and wherein the second profiler comprises: a pupil region extractor connected to the pair validator; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the second profile evaluator. 8. The system of claim 1 , wherein the pair validator comprises: a range indicator connected to the space measurer and the second profile validator. | 0.881789 |
7,802,183 | 4 | 6 | 4. The record management system of claim 1 further comprising means for creating dictation insertion points within said electronic document. | 4. The record management system of claim 1 further comprising means for creating dictation insertion points within said electronic document. 6. The record management system of claim 4 further comprising means for displaying said electronic document in a workspace having a plurality of window panes, wherein said workspace displays original content of said electronic document in one of said plurality of window panes with the dictation insertion points highlighted. | 0.90881 |
7,583,647 | 1 | 15 | 1. An apparatus, comprising: a processor configured to receive tokens and to provide the tokens to a plurality of different pools, wherein each of the plurality of different pools is associated with a different server, and wherein one pool of the plurality of different pools is configured to hold M tokens, and remove tokens from said plurality of different pools, wherein said processor is configured such that, when it is determined that a server request is of a type that requires at least one token to be removed from said one pool for said server request to be handled, and that said server request requires a determined number of tokens to be removed from said one pool for said server request to be handled, then said server request is handled when said one pool contains said determined number of tokens for said request and said determined number of tokens is removed when said server request is handled by the server with which said one pool is associated. | 1. An apparatus, comprising: a processor configured to receive tokens and to provide the tokens to a plurality of different pools, wherein each of the plurality of different pools is associated with a different server, and wherein one pool of the plurality of different pools is configured to hold M tokens, and remove tokens from said plurality of different pools, wherein said processor is configured such that, when it is determined that a server request is of a type that requires at least one token to be removed from said one pool for said server request to be handled, and that said server request requires a determined number of tokens to be removed from said one pool for said server request to be handled, then said server request is handled when said one pool contains said determined number of tokens for said request and said determined number of tokens is removed when said server request is handled by the server with which said one pool is associated. 15. An apparatus as claimed in claim 1 , wherein the apparatus comprises or is part of a server. | 0.774648 |
10,152,535 | 1 | 10 | 1. A method comprising: decomposing a search query that includes three or more words into a plurality of candidate phrasifications, each candidate phrasification having a different grouping of component phrases, a component phrase including a non-zero quantity of the words and each candidate phrasification including all of the words of the search query; scoring one or more candidate phrasifications, a candidate phrasification being scored by applying a scoring model, the scoring model based on a number of component phrases in the phrasification, a probability of occurrence of each of the component phrases in the candidate phrasification from a valid phrase table, and parameters for adjusting precision and recall of the candidate phrasification, the parameters including a first parameter to adjust precision of candidate phrasifications and a second parameter to adjust bias against obtaining too many phrases; selecting at least one highest scoring candidate phrasification; and executing the at least one highest scoring candidate phrasification against an index that includes posting lists for phrases, the executing identifying documents associated with each of the component phrases of the highest scoring candidate phrasification. | 1. A method comprising: decomposing a search query that includes three or more words into a plurality of candidate phrasifications, each candidate phrasification having a different grouping of component phrases, a component phrase including a non-zero quantity of the words and each candidate phrasification including all of the words of the search query; scoring one or more candidate phrasifications, a candidate phrasification being scored by applying a scoring model, the scoring model based on a number of component phrases in the phrasification, a probability of occurrence of each of the component phrases in the candidate phrasification from a valid phrase table, and parameters for adjusting precision and recall of the candidate phrasification, the parameters including a first parameter to adjust precision of candidate phrasifications and a second parameter to adjust bias against obtaining too many phrases; selecting at least one highest scoring candidate phrasification; and executing the at least one highest scoring candidate phrasification against an index that includes posting lists for phrases, the executing identifying documents associated with each of the component phrases of the highest scoring candidate phrasification. 10. The method of claim 1 , wherein the probability of occurrence of each component phrase in a candidate phrasification is based on the incidence of the component phrase in an indexed document collection. | 0.57113 |
8,886,540 | 13 | 23 | 13. A speech processing system comprising: a device-resident capture facility for recording speech presented by a user; a wireless communication facility for transmitting the recording and contextual information relating to a software application to a speech recognition configured to generate results using an unstructured language model based at least in part on the contextual information relating to the software application and the recording, wherein the contextual information includes an identity of the mobile communication facility, an identity of a non-speech recognition application resident on the mobile communication facility and a usage history of the non-speech recognition application resident on the mobile communication facility, and wherein user feedback is used to adapt the unstructured language model; the wireless communication facility, further for transmitting the results to the device; the software application for receiving the results; and a device display for simultaneously displaying the results as a set of words and as a set of application results based on those words. | 13. A speech processing system comprising: a device-resident capture facility for recording speech presented by a user; a wireless communication facility for transmitting the recording and contextual information relating to a software application to a speech recognition configured to generate results using an unstructured language model based at least in part on the contextual information relating to the software application and the recording, wherein the contextual information includes an identity of the mobile communication facility, an identity of a non-speech recognition application resident on the mobile communication facility and a usage history of the non-speech recognition application resident on the mobile communication facility, and wherein user feedback is used to adapt the unstructured language model; the wireless communication facility, further for transmitting the results to the device; the software application for receiving the results; and a device display for simultaneously displaying the results as a set of words and as a set of application results based on those words. 23. The system of claim 13 , wherein contextual information includes at least one of, information from a user's favorites list, information about the user's address book or contact list, content of the user's inbox, content of the user's outbox, the user's location, information currently displayed in an application. | 0.732715 |
9,405,841 | 28 | 29 | 28. A computer-implemented method for providing sentence-structured searching, the method comprising: receiving one or more characters associated with at least a partial search term to be executed against a set of data, the characters being received using a user-modifiable search element; determining a plurality of search terms, and a plurality of search categories for each of the plurality of search terms, relevant to the one or more characters; selecting a subset of the plurality of search categories based at least in part a relevance value for each category meeting a threshold relevance value, the relevance value indicating a strength of an association of each category in the subset of the plurality of search categories to each search term of the plurality of search terms; providing for display at least the subset of the plurality of search categories and the plurality of search terms relating to the plurality of search categories, the plurality of search terms including the one or more characters of the at least a partial search term; determining an ordered set of some of the plurality of search terms and an ordered set of some of the subset of the plurality of search categories based at least in part on the relevance value of each category; and providing for display, within an allowable deviation from being simultaneous to receiving the one or more characters, the ordered set of some of the plurality of search terms associated with completing the partial search term and the ordered set of some of the subset of plurality of search categories, wherein the ordered set of the some of the plurality of search terms and the ordered set of the some of the subset of the plurality of search categories are displayed concurrently, the some of the plurality of search terms or the some of the subset of the plurality of search categories selectable to be executed against the set of data, a selected search term and a selected search category in the user-modifiable search element being separated by a preposition associated with at least one of the selected search term and the selected search category, the preposition specifying a context by which to search for the selected search term in the selected search category. | 28. A computer-implemented method for providing sentence-structured searching, the method comprising: receiving one or more characters associated with at least a partial search term to be executed against a set of data, the characters being received using a user-modifiable search element; determining a plurality of search terms, and a plurality of search categories for each of the plurality of search terms, relevant to the one or more characters; selecting a subset of the plurality of search categories based at least in part a relevance value for each category meeting a threshold relevance value, the relevance value indicating a strength of an association of each category in the subset of the plurality of search categories to each search term of the plurality of search terms; providing for display at least the subset of the plurality of search categories and the plurality of search terms relating to the plurality of search categories, the plurality of search terms including the one or more characters of the at least a partial search term; determining an ordered set of some of the plurality of search terms and an ordered set of some of the subset of the plurality of search categories based at least in part on the relevance value of each category; and providing for display, within an allowable deviation from being simultaneous to receiving the one or more characters, the ordered set of some of the plurality of search terms associated with completing the partial search term and the ordered set of some of the subset of plurality of search categories, wherein the ordered set of the some of the plurality of search terms and the ordered set of the some of the subset of the plurality of search categories are displayed concurrently, the some of the plurality of search terms or the some of the subset of the plurality of search categories selectable to be executed against the set of data, a selected search term and a selected search category in the user-modifiable search element being separated by a preposition associated with at least one of the selected search term and the selected search category, the preposition specifying a context by which to search for the selected search term in the selected search category. 29. The computer-implemented method of claim 28 , wherein the set of relevant search terms is displayed separately from the set of relevant search categories. | 0.834034 |
8,554,759 | 18 | 20 | 18. The method of claim 15 , further comprising: determining document features associated with each document of the plurality of documents, where generating the rules includes: generating the rules, for the model, further based on the document features associated with each document of the plurality of documents. | 18. The method of claim 15 , further comprising: determining document features associated with each document of the plurality of documents, where generating the rules includes: generating the rules, for the model, further based on the document features associated with each document of the plurality of documents. 20. The method of claim 18 , where the document features associated with at least one document, of the plurality of documents, include one or more of: a language of the at least one document, an encoding type associated with the at least one document, or a link-based score associated with the at least one document, where generating the rules includes: generating the rules, for the model, further based on the one or more of the language of the at least one document, the encoding type associated with the at least one document, or the link-based score associated with the at least one document. | 0.877864 |
10,033,671 | 1 | 4 | 1. A computer program product comprising code stored therein for dynamic message routing between publishing nodes and subscribing nodes sent throughout a network without regard to how a topology of the network changes, wherein the code when executed by a processor of a computer system causes the computer system to perform operations comprising: receiving a plurality of subscription requests at a plurality of brokers; consolidating the received plurality of subscription requests; determining whether to propagate the consolidated subscriptions requests; receiving the message and a topic at a broker via a network; identifying one or more subscribers for the topic received; obtaining up-to-date network path configuration information; reconfiguring broker network path information based on revisions to the network path configuration information to determine a path for sending the message via the network, including performing real-time adjustment of the path; and sending the message to the identified subscribers; wherein performing real-time adjustment of the path comprises: monitoring changes to the topology of the network; determining in real-time whether any connections within the network are unavailable to dynamically maintain subscriptions; and automatically calculating a path for any subscribers affected by any unavailable connections. | 1. A computer program product comprising code stored therein for dynamic message routing between publishing nodes and subscribing nodes sent throughout a network without regard to how a topology of the network changes, wherein the code when executed by a processor of a computer system causes the computer system to perform operations comprising: receiving a plurality of subscription requests at a plurality of brokers; consolidating the received plurality of subscription requests; determining whether to propagate the consolidated subscriptions requests; receiving the message and a topic at a broker via a network; identifying one or more subscribers for the topic received; obtaining up-to-date network path configuration information; reconfiguring broker network path information based on revisions to the network path configuration information to determine a path for sending the message via the network, including performing real-time adjustment of the path; and sending the message to the identified subscribers; wherein performing real-time adjustment of the path comprises: monitoring changes to the topology of the network; determining in real-time whether any connections within the network are unavailable to dynamically maintain subscriptions; and automatically calculating a path for any subscribers affected by any unavailable connections. 4. The computer program product of claim 1 , wherein the code is further executable by the processor to examine the message for delivery controls. | 0.836689 |
9,607,277 | 1 | 7 | 1. A method for crowd sourcing tasks, comprising: identifying, by a computer system, a group of potential candidates for crowd sourcing, wherein each candidate of the group of potential candidates is identified based on the candidate being expected to accept an offer for performance of a certain type of task, the certain type of task being at least performable within a predetermined range of time; receiving, by the computer system, a request to perform a particular task from a requester; determining, by the computer system, if the particular task corresponds to the certain type of task; and transmitting, by the computer system, an offer for performance of the particular task to a subgroup of the group of potential candidates in response to the particular task corresponding to the certain type of task for a target candidate, wherein transmitting the offer for performance of the particular task to the subgroup of the group of potential candidates comprises: determining when any candidates are currently performing the same task or similar task to the particular task, and transmitting the offer for performance of the particular task to the candidates that are currently performing the same task or the similar task; determining when any candidates have a history of completing the same task or the similar task to the particular task faster than other candidates, and transmitting the offer for performance of the particular task to the candidates that have the history of completing the same task or the similar task faster than the other candidates; determining when a particular candidate has completed a specific task, and transmitting the offer for performance of the particular task to the particular candidate in response to the particular candidate having completed the specific task, wherein the specific task is related to the particular task being offered; and determining when any candidates have reached a predefined quota of one of a total time in performing a group of tasks during a set time period or a number of tasks performed during the set time period, and not transmitting an offer for performance of another task to any candidates that have reached the predefined quota until a next set time period, wherein the next set time period is configurable by a user based on a policy. | 1. A method for crowd sourcing tasks, comprising: identifying, by a computer system, a group of potential candidates for crowd sourcing, wherein each candidate of the group of potential candidates is identified based on the candidate being expected to accept an offer for performance of a certain type of task, the certain type of task being at least performable within a predetermined range of time; receiving, by the computer system, a request to perform a particular task from a requester; determining, by the computer system, if the particular task corresponds to the certain type of task; and transmitting, by the computer system, an offer for performance of the particular task to a subgroup of the group of potential candidates in response to the particular task corresponding to the certain type of task for a target candidate, wherein transmitting the offer for performance of the particular task to the subgroup of the group of potential candidates comprises: determining when any candidates are currently performing the same task or similar task to the particular task, and transmitting the offer for performance of the particular task to the candidates that are currently performing the same task or the similar task; determining when any candidates have a history of completing the same task or the similar task to the particular task faster than other candidates, and transmitting the offer for performance of the particular task to the candidates that have the history of completing the same task or the similar task faster than the other candidates; determining when a particular candidate has completed a specific task, and transmitting the offer for performance of the particular task to the particular candidate in response to the particular candidate having completed the specific task, wherein the specific task is related to the particular task being offered; and determining when any candidates have reached a predefined quota of one of a total time in performing a group of tasks during a set time period or a number of tasks performed during the set time period, and not transmitting an offer for performance of another task to any candidates that have reached the predefined quota until a next set time period, wherein the next set time period is configurable by a user based on a policy. 7. The method of claim 1 , further comprising sending a message in response to the offer for performance of the particular task being accepted by one of the potential candidates of the subgroup, the message being sent to potential candidates of the subgroup that did not accept the offer for performance of the particular task. | 0.718589 |
9,754,022 | 15 | 17 | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a user query in a first language; identifying a local language associated with a current location of a user device; and when the first language is distinct from the local language: querying a database based on the user query, to yield search results, wherein the search results comprise (1) a first result having a first word in the first language and a second word in the local language and (2) a second result predominantly in the first language; prioritizing the search results by first presenting the first result followed by the second result, to yield prioritized search results; and presenting the prioritized search results with an indication associated with the second result identifying that the second result is predominantly in the first language. | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a user query in a first language; identifying a local language associated with a current location of a user device; and when the first language is distinct from the local language: querying a database based on the user query, to yield search results, wherein the search results comprise (1) a first result having a first word in the first language and a second word in the local language and (2) a second result predominantly in the first language; prioritizing the search results by first presenting the first result followed by the second result, to yield prioritized search results; and presenting the prioritized search results with an indication associated with the second result identifying that the second result is predominantly in the first language. 17. The computer-readable storage device of claim 15 , wherein the local geographic linguistic context comprises one of a sentence and a phrase in the local language comprising a translation of the user query into the local language. | 0.735828 |
9,805,718 | 1 | 4 | 1. A computer-implemented method, comprising: receiving, by a computing device, input, wherein the input is associated with an interaction with the computing device, and wherein the input includes dialog input, application input, or sensor input; determining an interaction history, wherein determining includes adding the input to the interaction history, wherein adding includes using an artificial intelligence-based model to combine the input with prior interaction history; determining a current context, wherein the current context is associated with an interaction with the computing device, and wherein the interaction includes dialog input, application input, or sensor input; receiving verbal input, wherein the verbal input includes natural language, and wherein the verbal input includes a plurality of words; interpreting the verbal input, wherein interpreting the verbal input includes assigning one or more attributes to the plurality of words; identifying an attribute from the one or more attributes, wherein the identified attribute is associated with one or more words from the plurality of words, wherein the identified attribute indicates that the one or more words are unclear, and wherein a word is unclear when the computing system cannot recognize the word; determining that the current context and the interaction history do not clarify the one or more words; determining a type of information needed to recognize the one or more words, wherein determining includes using the one or more attributes assigned to the one or more words to identify missing information; determining a clarification question for the one or more words, wherein determining includes using the type of information, the current context, and the interaction history, wherein the clarification question is formatted to request the missing information, and wherein the format is customized using the current context and the interaction history; and outputting the clarification question. | 1. A computer-implemented method, comprising: receiving, by a computing device, input, wherein the input is associated with an interaction with the computing device, and wherein the input includes dialog input, application input, or sensor input; determining an interaction history, wherein determining includes adding the input to the interaction history, wherein adding includes using an artificial intelligence-based model to combine the input with prior interaction history; determining a current context, wherein the current context is associated with an interaction with the computing device, and wherein the interaction includes dialog input, application input, or sensor input; receiving verbal input, wherein the verbal input includes natural language, and wherein the verbal input includes a plurality of words; interpreting the verbal input, wherein interpreting the verbal input includes assigning one or more attributes to the plurality of words; identifying an attribute from the one or more attributes, wherein the identified attribute is associated with one or more words from the plurality of words, wherein the identified attribute indicates that the one or more words are unclear, and wherein a word is unclear when the computing system cannot recognize the word; determining that the current context and the interaction history do not clarify the one or more words; determining a type of information needed to recognize the one or more words, wherein determining includes using the one or more attributes assigned to the one or more words to identify missing information; determining a clarification question for the one or more words, wherein determining includes using the type of information, the current context, and the interaction history, wherein the clarification question is formatted to request the missing information, and wherein the format is customized using the current context and the interaction history; and outputting the clarification question. 4. The computer-implemented method of claim 1 , further comprising: receiving non-verbal input, wherein the non-verbal input includes a physical motion interpreted from a sensor associated with the computing device, and wherein the current context includes the non-verbal input. | 0.830694 |
8,190,988 | 11 | 16 | 11. A computer-readable storage medium encoding a computer program for executing a computer process on a computer system, the computer process comprising: receiving a selection of electronic form instances to be merged into a bundled electronic form instance, each electronic form instance including at least one named form field and at least one script referencing the at least one named form field; renaming at least one named form field in at least one of the electronic form instances of the selection to be unique across the selection of electronic form instances; renaming one or more references to the named form field in the at least one script in the at least one of the electronic form instances of the selection to match the renamed form field; merging the selection of electronic form instances into the bundled electronic form instance, responsive to the renaming operations. | 11. A computer-readable storage medium encoding a computer program for executing a computer process on a computer system, the computer process comprising: receiving a selection of electronic form instances to be merged into a bundled electronic form instance, each electronic form instance including at least one named form field and at least one script referencing the at least one named form field; renaming at least one named form field in at least one of the electronic form instances of the selection to be unique across the selection of electronic form instances; renaming one or more references to the named form field in the at least one script in the at least one of the electronic form instances of the selection to match the renamed form field; merging the selection of electronic form instances into the bundled electronic form instance, responsive to the renaming operations. 16. The computer-readable storage medium of claim 11 wherein the operation of renaming at least one named form field comprises: identifying one or more named form fields that are not unique across the selection of electronic form instances; renaming the identified non-unique named form fields resident in any of the selected electronic form instances to be unique across the selection of electronic form instances. | 0.501202 |
8,135,730 | 9 | 10 | 9. An information processing system adapted to retrieving data from a database, the information processing system comprises: a memory; a processor communicatively coupled to the memory; and a database manager communicatively coupled to the memory and the processor, wherein the database manager is configured to: receive, from a user, a search request for a set of data in at least one database; perform, in response to receiving the search request from the user, an ontology query over at least one ontology associated with at least one database resulting in an ontological dataset associated with the search request, wherein the ontological dataset comprises at least one of a set of synonyms, a set of hypernyms, and a set of hyponyms, associated with the search request; perform, in response to performing the ontology query, a data query over data in the at least one database using a union of the ontological dataset with the search keywords in the search request; provide to the user at least a portion of the set of data based on the data query that has been performed; and dynamically adding a column to a table comprising the set of data in the at least one database, wherein each row in the column that has been added comprises a grouping annotation associated with a corresponding data entry in the set of data. | 9. An information processing system adapted to retrieving data from a database, the information processing system comprises: a memory; a processor communicatively coupled to the memory; and a database manager communicatively coupled to the memory and the processor, wherein the database manager is configured to: receive, from a user, a search request for a set of data in at least one database; perform, in response to receiving the search request from the user, an ontology query over at least one ontology associated with at least one database resulting in an ontological dataset associated with the search request, wherein the ontological dataset comprises at least one of a set of synonyms, a set of hypernyms, and a set of hyponyms, associated with the search request; perform, in response to performing the ontology query, a data query over data in the at least one database using a union of the ontological dataset with the search keywords in the search request; provide to the user at least a portion of the set of data based on the data query that has been performed; and dynamically adding a column to a table comprising the set of data in the at least one database, wherein each row in the column that has been added comprises a grouping annotation associated with a corresponding data entry in the set of data. 10. The information processing system of claim 9 , wherein the search request received from the user comprises at least one of: a set of search keywords; a set of dimension specifications for at least one search keyword in the set of search keywords indicating whether the ontology query is to consider at least one of synonyms, hypernyms, and hyponyms in the at least one ontology associated with the at least one search keyword; and an aggregation specification indicating at least one aggregation type for aggregating the at least one of synonyms, hypernyms, and hyponyms, in the at least one ontology for the at least one search keyword. | 0.624267 |
9,081,977 | 5 | 7 | 5. The method of claim 2 , wherein the at least one privilege supported by the document data object is a privilege supported by a node object corresponding to the document data object; the step of selecting a set of privilege from the at least one privilege supported by the document data object and granting the set of privilege selected to the role as the set of privilege of the role on the document data object comprises: selecting a set of privilege from the at least one privilege supported by the node object corresponding to the document data object, and granting the privilege selected to the role as the privilege of the role on the document data object. | 5. The method of claim 2 , wherein the at least one privilege supported by the document data object is a privilege supported by a node object corresponding to the document data object; the step of selecting a set of privilege from the at least one privilege supported by the document data object and granting the set of privilege selected to the role as the set of privilege of the role on the document data object comprises: selecting a set of privilege from the at least one privilege supported by the node object corresponding to the document data object, and granting the privilege selected to the role as the privilege of the role on the document data object. 7. The method of claim 5 , wherein the tree structure comprises anyone or any combination of following levels of node objects in sequence: a docbase, a document set, a document, a page, a layer, an object stream and a layout object. | 0.911518 |
8,577,668 | 13 | 15 | 13. A system comprising: one or more computing devices configured to perform operations including: sending, using one or more processors, a request to translate a source web document from a first language text to a second language text; receiving a translated web document for display containing a translation of the source web document into the second language text; displaying the translated web document; and in response to interacting with a portion of the translated web document, displaying the first language text that corresponds to a portion of the translated web document in a graphical element overlaying the translated web document. | 13. A system comprising: one or more computing devices configured to perform operations including: sending, using one or more processors, a request to translate a source web document from a first language text to a second language text; receiving a translated web document for display containing a translation of the source web document into the second language text; displaying the translated web document; and in response to interacting with a portion of the translated web document, displaying the first language text that corresponds to a portion of the translated web document in a graphical element overlaying the translated web document. 15. The system of claim 13 , further configured to perform operations comprising displaying the first language text in the graphical element according to span tags delimiting the portion of the translated text. | 0.875592 |
9,696,877 | 7 | 8 | 7. One or more non-transitory computer-readable storage media having instructions stored thereon that, responsive to execution by one or more processors, causes the one or more processors to perform operations comprising: receiving an indication indicating selection of a character, the selection of the character through a gesture-sensitive character-entry interface; presenting or causing presentation of, responsive to the selection of the character, based on the character, and through a completion interface, multiple characters adjacent a location at which the character was selected or superimposed over at least a portion of the gesture-sensitive character-entry interface, at least one of the multiple characters being a multi-string having or completing a long word and a short word, the short word being shorter than the long word and being a constituent part of the long word, the short word and the long word being presented at a same time and in the completion interface; enabling selection, through the completion interface, to select the short word or the long word, wherein selecting the short word would be selecting a portion of the multiple characters for the long word; receiving selection, through the completion interface, of the short word or the long word; and providing or presenting the selected short word or long word. | 7. One or more non-transitory computer-readable storage media having instructions stored thereon that, responsive to execution by one or more processors, causes the one or more processors to perform operations comprising: receiving an indication indicating selection of a character, the selection of the character through a gesture-sensitive character-entry interface; presenting or causing presentation of, responsive to the selection of the character, based on the character, and through a completion interface, multiple characters adjacent a location at which the character was selected or superimposed over at least a portion of the gesture-sensitive character-entry interface, at least one of the multiple characters being a multi-string having or completing a long word and a short word, the short word being shorter than the long word and being a constituent part of the long word, the short word and the long word being presented at a same time and in the completion interface; enabling selection, through the completion interface, to select the short word or the long word, wherein selecting the short word would be selecting a portion of the multiple characters for the long word; receiving selection, through the completion interface, of the short word or the long word; and providing or presenting the selected short word or long word. 8. The media of claim 7 , wherein presenting or causing presentation is responsive to determining that a gesture selecting the character through the gesture-sensitive character-entry interface has not ended or indicates selection of the completion interface. | 0.750484 |
10,073,898 | 1 | 9 | 1. A method of extracting content from a file and storing the content in a database, the file including content instances associated with file fields having a respective file field type, the method being performed using a processing system having a processor coupled to a memory, the method including: a) receiving a file, the file being a mark-up language file, each content instance being stored as a respective node in a corresponding file field; b) determining an indication of a document type definition of the file from the file by examining the elements and attributes contained in the file and then comparing the elements and attributes to a list of elements and attributes contained within each different document definition; c) retrieving a mapping in the form of a node map, the node map including a node rule for each node in the mark-up language file, the mapping being determined by selecting the node map from a list of node maps using the indication of the document type definition of the file, wherein the node rules specifying how the content of each type of the element or attribute of each node should be stored in the database; d) after retrieving the mapping, creating a data store in the memory of the processing system, the data store including store fields specified in the mapping, in accordance with the file fields of the file; e) after creating the data store, retrieving a content instance for a parent node from a file field of the file; f) storing the content instance in a store field of the store in accordance with the file field type of the file field and the mapping; g) retrieving a content instance for a child node of the parent node from a file field of the file; and, h) storing the content instance in a store field in the store in accordance with the file field type of the associated file field and the mapping; and, i) repeating steps e) to h) for each parent node; and, j) after storing the content instances in the store, transferring each content instance from the store to the database in accordance with the store field type of the respective store field and the mapping, wherein the transferring comprises creating one or more vacant locations in the query in accordance with the field type; transferring each content instance into a respective vacant location; and, applying the query to the database to thereby transfer the content instances to the database. | 1. A method of extracting content from a file and storing the content in a database, the file including content instances associated with file fields having a respective file field type, the method being performed using a processing system having a processor coupled to a memory, the method including: a) receiving a file, the file being a mark-up language file, each content instance being stored as a respective node in a corresponding file field; b) determining an indication of a document type definition of the file from the file by examining the elements and attributes contained in the file and then comparing the elements and attributes to a list of elements and attributes contained within each different document definition; c) retrieving a mapping in the form of a node map, the node map including a node rule for each node in the mark-up language file, the mapping being determined by selecting the node map from a list of node maps using the indication of the document type definition of the file, wherein the node rules specifying how the content of each type of the element or attribute of each node should be stored in the database; d) after retrieving the mapping, creating a data store in the memory of the processing system, the data store including store fields specified in the mapping, in accordance with the file fields of the file; e) after creating the data store, retrieving a content instance for a parent node from a file field of the file; f) storing the content instance in a store field of the store in accordance with the file field type of the file field and the mapping; g) retrieving a content instance for a child node of the parent node from a file field of the file; and, h) storing the content instance in a store field in the store in accordance with the file field type of the associated file field and the mapping; and, i) repeating steps e) to h) for each parent node; and, j) after storing the content instances in the store, transferring each content instance from the store to the database in accordance with the store field type of the respective store field and the mapping, wherein the transferring comprises creating one or more vacant locations in the query in accordance with the field type; transferring each content instance into a respective vacant location; and, applying the query to the database to thereby transfer the content instances to the database. 9. A method according to claim 1 , the query being an SQL query. | 0.919598 |
7,778,830 | 10 | 13 | 10. The machine-readable recording medium of claim 9 , wherein the feedback includes at least part of an n-best list of ASR matched entries associated with individual utterances processed during the communication session, each ASR matched entry having an associated likelihood score. | 10. The machine-readable recording medium of claim 9 , wherein the feedback includes at least part of an n-best list of ASR matched entries associated with individual utterances processed during the communication session, each ASR matched entry having an associated likelihood score. 13. The machine-readable recording medium of claim 10 , further causing the machine to perform the steps of: identifying when one of the individual utterances has been correctly matched based upon the feedback; and responsive to said identifying step, adjusting a parameter within the identified phrase-based grammar so that the likelihood score associated with the topmost entry in the n-best list is increased when the ASR computer program next processes an utterance similar to the correctly identified phrase in a session involving the identified phrase-based grammar. | 0.842598 |
7,801,917 | 1 | 4 | 1. A computer-implemented method of constructing a profile of an entity, wherein a computer executing instructions performs the method comprising: intercepting, by the computer, an electronic document while the electronic document is being transmitted on a network by the entity; the computer automatically identifying content, within the electronic document, as being potentially descriptive of an information focus of the entity, wherein the identifying the content comprises assigning a figure of merit to the content, and wherein the assigning the figure of merit to the content comprises determining a frequency with which the content occurs in collection of information associated with the entity; in response to said automatically identifying the content as being potentially descriptive of an information focus of the entity, enabling the entity to provide an authorization, the authorization indicating whether the identified content is to be included in at least a particular portion of the profile associated with the entity; and including the identified content within said at least a particular portion of the profile only if the entity provides the authorization, wherein the profile comprises a first portion and a second portion, wherein the first portion is a private portion of the profile and the second portion is a public portion of the profile, and wherein said including the identified content within said at least a particular portion of the profile only if the entity provides the authorization comprises including the identified content within the public portion of the profile. | 1. A computer-implemented method of constructing a profile of an entity, wherein a computer executing instructions performs the method comprising: intercepting, by the computer, an electronic document while the electronic document is being transmitted on a network by the entity; the computer automatically identifying content, within the electronic document, as being potentially descriptive of an information focus of the entity, wherein the identifying the content comprises assigning a figure of merit to the content, and wherein the assigning the figure of merit to the content comprises determining a frequency with which the content occurs in collection of information associated with the entity; in response to said automatically identifying the content as being potentially descriptive of an information focus of the entity, enabling the entity to provide an authorization, the authorization indicating whether the identified content is to be included in at least a particular portion of the profile associated with the entity; and including the identified content within said at least a particular portion of the profile only if the entity provides the authorization, wherein the profile comprises a first portion and a second portion, wherein the first portion is a private portion of the profile and the second portion is a public portion of the profile, and wherein said including the identified content within said at least a particular portion of the profile only if the entity provides the authorization comprises including the identified content within the public portion of the profile. 4. The method of claim 1 wherein the entity is a group of people. | 0.85426 |
9,086,735 | 1 | 8 | 1. A computer-implemented method, comprising: receiving a user input into a user interface of an input method editor (IME); determining, based on the user input, whether to process the user input with a script engine; when the user input indicates that the user input is to be processed with the script engine: providing the user input to the script engine, selecting a script from a plurality of scripts electronically stored in a script repository, processing the user input through the script using the script engine to generate one or more candidates, and providing the one or more candidates to an IME engine; when the user input indicates that the user input is not to be processed with the script engine: providing the user input to the IME engine, and processing the user input with the IME engine to generate the one or more candidates; and receiving an extension mode input indicating operation of the IME in an extension mode, operating the IME in the extension mode in response to receiving the extension mode input, and providing all user input to the script engine when operating in the extension mode. | 1. A computer-implemented method, comprising: receiving a user input into a user interface of an input method editor (IME); determining, based on the user input, whether to process the user input with a script engine; when the user input indicates that the user input is to be processed with the script engine: providing the user input to the script engine, selecting a script from a plurality of scripts electronically stored in a script repository, processing the user input through the script using the script engine to generate one or more candidates, and providing the one or more candidates to an IME engine; when the user input indicates that the user input is not to be processed with the script engine: providing the user input to the IME engine, and processing the user input with the IME engine to generate the one or more candidates; and receiving an extension mode input indicating operation of the IME in an extension mode, operating the IME in the extension mode in response to receiving the extension mode input, and providing all user input to the script engine when operating in the extension mode. 8. The computer-implemented method of claim 1 , wherein the user input comprises the extension mode input. | 0.921248 |
8,887,301 | 1 | 7 | 1. A computerized method for classifying and redacting an email message for distributing to multiple recipients having different security levels, the method comprising: using a processor for: selecting a segment of the email message; automatically analyzing contents of the selected segment in real time by using an artificial intelligence (AI) system; automatically classifying the segment, based on results of the analysis performed by the artificial intelligence system, and in accordance with a set of classification options characterizing a type of information contained in the segment; automatically marking the segment in accordance with a respective classification option, producing a marked segment; automatically classifying the email message based on classifications of segments of the email message; and automatically redacting the email message in real time in accordance with a respective clearance level of a recipient of the email message, producing a redacted email message, comprising: (i) arranging recipients of the email message in a hierarchy in accordance with respective clearance levels such that a recipient with a higher clearance level occupies a higher level in the hierarchy in comparison to a recipient with a lower clearance level; and (ii) automatically distributing the redacted email message to the recipients of a particular level in the hierarchy concurrently with the redacting marked segments for the recipients at the immediate lower level in the hierarchy. | 1. A computerized method for classifying and redacting an email message for distributing to multiple recipients having different security levels, the method comprising: using a processor for: selecting a segment of the email message; automatically analyzing contents of the selected segment in real time by using an artificial intelligence (AI) system; automatically classifying the segment, based on results of the analysis performed by the artificial intelligence system, and in accordance with a set of classification options characterizing a type of information contained in the segment; automatically marking the segment in accordance with a respective classification option, producing a marked segment; automatically classifying the email message based on classifications of segments of the email message; and automatically redacting the email message in real time in accordance with a respective clearance level of a recipient of the email message, producing a redacted email message, comprising: (i) arranging recipients of the email message in a hierarchy in accordance with respective clearance levels such that a recipient with a higher clearance level occupies a higher level in the hierarchy in comparison to a recipient with a lower clearance level; and (ii) automatically distributing the redacted email message to the recipients of a particular level in the hierarchy concurrently with the redacting marked segments for the recipients at the immediate lower level in the hierarchy. 7. The method of claim 1 , wherein the email message is formatted in Extensible Markup Language (XML) format. | 0.889228 |
9,246,708 | 12 | 18 | 12. A mobile device for accessing a social networking website managed by a social networking website system, the mobile device comprising: a memory; a location determination circuitry that facilitates determination of a current location; a processing circuitry coupled to the memory and the location determination circuitry; a client that is executed by the processing circuitry, wherein the client, when operable, interacts with the social networking website, without conducting any upfront registration, without sharing any user profile and without need for invitations; the client determining the current location of the mobile device employing the location determination circuitry and processing circuitry; the client automatically registering the current location of the mobile device with the social networking website system, without employing invitations and explicit user acceptance to join them, whereby the social networking website system, in response, automatically assigns the user as a member of at least one social network selected by the social networking website system from a plurality of social networks based on the current location of the mobile device; and the client facilitating the submission of new postings to the at least one of the a plurality of social network groups from the mobile device by the user; wherein each of the social networks facilitate creation and sharing of new postings by each of the plurality of users, the new postings each comprising audio inputs recorded by the user, a digital photo recorded, a video recorded, and textual inputs provided by the user on a corresponding one the plurality of mobile devices; and wherein the social networking website system also provides each user the ability to create their own social groups to share common interests or affiliations. | 12. A mobile device for accessing a social networking website managed by a social networking website system, the mobile device comprising: a memory; a location determination circuitry that facilitates determination of a current location; a processing circuitry coupled to the memory and the location determination circuitry; a client that is executed by the processing circuitry, wherein the client, when operable, interacts with the social networking website, without conducting any upfront registration, without sharing any user profile and without need for invitations; the client determining the current location of the mobile device employing the location determination circuitry and processing circuitry; the client automatically registering the current location of the mobile device with the social networking website system, without employing invitations and explicit user acceptance to join them, whereby the social networking website system, in response, automatically assigns the user as a member of at least one social network selected by the social networking website system from a plurality of social networks based on the current location of the mobile device; and the client facilitating the submission of new postings to the at least one of the a plurality of social network groups from the mobile device by the user; wherein each of the social networks facilitate creation and sharing of new postings by each of the plurality of users, the new postings each comprising audio inputs recorded by the user, a digital photo recorded, a video recorded, and textual inputs provided by the user on a corresponding one the plurality of mobile devices; and wherein the social networking website system also provides each user the ability to create their own social groups to share common interests or affiliations. 18. The mobile device of claim 12 further comprising: the client automatically providing information on local businesses, banks, local services and local experts based on the current location. | 0.724138 |
8,448,242 | 5 | 7 | 5. A method for outputting data based on anomaly detection, comprising: receiving known anomaly signatures; generating, using a hardware processor, n-grams of different sizes using the known anomaly signatures; storing, using the hardware processor, abnormal n-grams in the n-grams of different sizes in a binary anomaly detection model; using the binary anomaly detection model to determine whether an input dataset contains an anomaly, wherein the binary anomaly detection model is used to determine whether the input dataset contains an anomaly by checking the binary anomaly detection model for an n-gram in the input dataset; and outputting, using the hardware processor, the input dataset based on whether the input dataset contains an anomaly. | 5. A method for outputting data based on anomaly detection, comprising: receiving known anomaly signatures; generating, using a hardware processor, n-grams of different sizes using the known anomaly signatures; storing, using the hardware processor, abnormal n-grams in the n-grams of different sizes in a binary anomaly detection model; using the binary anomaly detection model to determine whether an input dataset contains an anomaly, wherein the binary anomaly detection model is used to determine whether the input dataset contains an anomaly by checking the binary anomaly detection model for an n-gram in the input dataset; and outputting, using the hardware processor, the input dataset based on whether the input dataset contains an anomaly. 7. The method of claim 5 , wherein the binary anomaly detection model is represented using a Bloom filter. | 0.8675 |
9,256,680 | 1 | 5 | 1. A system, comprising: a relevance component associated with each result of a results page, the relevance component having an interactive positive relevance as a “more” link configured to enable positive feedback as to each result and an interactive negative relevance as a “none” link configured to enable negative feedback as to each result, the results page related to an original query; an analysis component configured to automatically analyze metadata associated with each result and automatically select a topical term from each result; a query formulation component configured to automatically reformulate for each result of the relevance component a new query associated with the “more” link and a new query associated with the “none” link; a query processing component configured to automatically process the new query associated with selection of the “more” link or the new query associated with selection of the “none” link for each result of the results page, and return new results for the new query, such that selection of the “more” link includes the topical term in the processing of the new search results, or selection of the “none” link indicates negation of the topical term from the processing of the new search results to ensure the new search results do not contain the topical term; and a microprocessor configured to execute computer-executable instructions in a memory, the execution of the instructions enables at least one of the relevance component, analysis component, query formulation component, or query processing component. | 1. A system, comprising: a relevance component associated with each result of a results page, the relevance component having an interactive positive relevance as a “more” link configured to enable positive feedback as to each result and an interactive negative relevance as a “none” link configured to enable negative feedback as to each result, the results page related to an original query; an analysis component configured to automatically analyze metadata associated with each result and automatically select a topical term from each result; a query formulation component configured to automatically reformulate for each result of the relevance component a new query associated with the “more” link and a new query associated with the “none” link; a query processing component configured to automatically process the new query associated with selection of the “more” link or the new query associated with selection of the “none” link for each result of the results page, and return new results for the new query, such that selection of the “more” link includes the topical term in the processing of the new search results, or selection of the “none” link indicates negation of the topical term from the processing of the new search results to ensure the new search results do not contain the topical term; and a microprocessor configured to execute computer-executable instructions in a memory, the execution of the instructions enables at least one of the relevance component, analysis component, query formulation component, or query processing component. 5. The system of claim 1 , wherein the analysis component is configured to create and maintain a list of terms, which terms are not to be considered as part of the new query associated with the “more” link or the new query associated with the “none” link. | 0.501953 |
8,527,260 | 1 | 3 | 1. A method for selectively modifying an electronic document, the method comprising: receiving a request from a user to view a user selection of text of an electronic document in an original language instead of a second translated language, the electronic document having substantially all of its text in the second translated language; analyzing the request to determine an expanded selection to be changed into original replacement language, with the analyzing step including the substep of deciding the amount of text to modify, the expanded selection including at least the user selection; determining original replacement language associated with the determined expanded selection; selectively modifying the electronic document by choosing text that best communicates the meaning of the associated original replacement language, and by permanently replacing text of the electronic document in the second translated language with chosen text that communicates the meaning of the associated original replacement language; and storing the modified electronic document. | 1. A method for selectively modifying an electronic document, the method comprising: receiving a request from a user to view a user selection of text of an electronic document in an original language instead of a second translated language, the electronic document having substantially all of its text in the second translated language; analyzing the request to determine an expanded selection to be changed into original replacement language, with the analyzing step including the substep of deciding the amount of text to modify, the expanded selection including at least the user selection; determining original replacement language associated with the determined expanded selection; selectively modifying the electronic document by choosing text that best communicates the meaning of the associated original replacement language, and by permanently replacing text of the electronic document in the second translated language with chosen text that communicates the meaning of the associated original replacement language; and storing the modified electronic document. 3. The method of claim 1 , further comprising: wherein the original replacement language comprises one or more alternative translations; receiving an indication from the user of a preference for a particular alternative translation; and wherein selectively modifying the electronic document comprises permanently replacing text of the electronic document in the second translated language with text from the particular alternative translation. | 0.891951 |
9,953,274 | 14 | 15 | 14. The method for dynamically selecting attributes indicative of human users, evaluating users and selectively presenting offers to estimated human users as recited in claim 10 , the method further comprising: receiving data pertaining to a purchase by a purchaser of a ticket; and estimating whether the purchaser possessed the user characteristic, wherein the initial set of attributes is modified based on the estimation. | 14. The method for dynamically selecting attributes indicative of human users, evaluating users and selectively presenting offers to estimated human users as recited in claim 10 , the method further comprising: receiving data pertaining to a purchase by a purchaser of a ticket; and estimating whether the purchaser possessed the user characteristic, wherein the initial set of attributes is modified based on the estimation. 15. The method for dynamically selecting attributes indicative of human users, evaluating users and selectively presenting offers to estimated human users as recited in claim 14 , the method further comprising: biasing ticket offerings to favor users in the first group over users in the second group, wherein the purchasing data indicated whether a user in the first group attended an event. | 0.956551 |
9,116,955 | 26 | 30 | 26. A non-transitory computer-readable medium including computer-executable instructions for operating on data from a data source, the data stored in a tangible, non-transitory computer-readable medium of the data source, the operating based on a query that is expressed in accordance with a query language applicable to a relational database, the operating including executing the query on an executing system other than a system managing a relational database, the executable instructions causing a computer to carry out steps including: receiving a query; identifying a data source based on the query, the data source being associated with a system managing the data source; identifying an executing system other than a system managing a relational database; generating a request to a query planner based on the query; providing the request to the query planner; receiving a query plan generated by the query planner based on the request, the query plan including a description of one or more steps to be performed by a system managing a relational database; generating, based on the query plan, a data structure instantiating a dataflow graph that includes: a first node that represents at least one operation to be executed, the first node associated with information usable by an executing system to invoke executable program code to perform the operation, the first node associated with information usable by an executing system to make data available to the program code, and the operation being chosen based on a first step described by the query plan, and a second node associated with information usable by an executing system to invoke executable program code that causes a request to perform at least one operation chosen based on a second step described by the query plan to be transmitted to the system managing the data source; receiving data from the data source; and executing, on the identified executing system, program code based on the dataflow graph. | 26. A non-transitory computer-readable medium including computer-executable instructions for operating on data from a data source, the data stored in a tangible, non-transitory computer-readable medium of the data source, the operating based on a query that is expressed in accordance with a query language applicable to a relational database, the operating including executing the query on an executing system other than a system managing a relational database, the executable instructions causing a computer to carry out steps including: receiving a query; identifying a data source based on the query, the data source being associated with a system managing the data source; identifying an executing system other than a system managing a relational database; generating a request to a query planner based on the query; providing the request to the query planner; receiving a query plan generated by the query planner based on the request, the query plan including a description of one or more steps to be performed by a system managing a relational database; generating, based on the query plan, a data structure instantiating a dataflow graph that includes: a first node that represents at least one operation to be executed, the first node associated with information usable by an executing system to invoke executable program code to perform the operation, the first node associated with information usable by an executing system to make data available to the program code, and the operation being chosen based on a first step described by the query plan, and a second node associated with information usable by an executing system to invoke executable program code that causes a request to perform at least one operation chosen based on a second step described by the query plan to be transmitted to the system managing the data source; receiving data from the data source; and executing, on the identified executing system, program code based on the dataflow graph. 30. The computer-readable medium of claim 26 in which the data source includes a relational database table. | 0.807554 |
9,092,459 | 1 | 5 | 1. A method comprising: receiving, from a user device of a first user, an image and a text query related to the image, wherein the text query requests information identifying content presented in the image; providing for presentation the image and the text query to a plurality of second users different from the first user; and receiving a suggested answer to the text query from each of a group of second users of the plurality of second users, and wherein a suggested answer from a particular second user is either a new suggested answer submitted by the particular second user in response to the text query or a previous suggested answer to the text query, the previous suggested answer being a suggested answer previously submitted by a different second user of the plurality of second users in response to the text query. | 1. A method comprising: receiving, from a user device of a first user, an image and a text query related to the image, wherein the text query requests information identifying content presented in the image; providing for presentation the image and the text query to a plurality of second users different from the first user; and receiving a suggested answer to the text query from each of a group of second users of the plurality of second users, and wherein a suggested answer from a particular second user is either a new suggested answer submitted by the particular second user in response to the text query or a previous suggested answer to the text query, the previous suggested answer being a suggested answer previously submitted by a different second user of the plurality of second users in response to the text query. 5. The method of claim 1 , wherein providing the image and the text query to the plurality of second users further comprises: including the image and the text query pair in a list of additional image and query pairs, the image and text query pair having a position in the list; and selecting the image and text query pair from the list for presentation to the plurality of second users, the selection based on the position of the image and text query pair in the list. | 0.659884 |
7,912,715 | 8 | 12 | 8. A method according to claim 1 , wherein, for templates not included in said selected templates, specific components of distortion measures computed with respect to a different feature vector are used for determining said set of distortion measures. | 8. A method according to claim 1 , wherein, for templates not included in said selected templates, specific components of distortion measures computed with respect to a different feature vector are used for determining said set of distortion measures. 12. A method according to claim 8 , wherein said different feature vector is a feature vector compared to the first number of templates from the template set being closest to the current feature vector according to a predefined distance measure. | 0.861738 |
8,793,583 | 1 | 6 | 1. A method for annotation of video content in a device communicatively coupled to a network, the method comprising: receiving, in the device, a captured speech segment comprising speech from a user of a second device, wherein the captured speech segment annotates a portion of the video content streamed to the second device for being played to the user contemporaneously with the speech from the user; converting the captured speech segment to a text-segment; associating the text-segment with the portion of the video content contemporaneously played to the user; and storing in a selectively retrievable manner the text-segment so that the text-segment is associated with the portion of the video content. | 1. A method for annotation of video content in a device communicatively coupled to a network, the method comprising: receiving, in the device, a captured speech segment comprising speech from a user of a second device, wherein the captured speech segment annotates a portion of the video content streamed to the second device for being played to the user contemporaneously with the speech from the user; converting the captured speech segment to a text-segment; associating the text-segment with the portion of the video content contemporaneously played to the user; and storing in a selectively retrievable manner the text-segment so that the text-segment is associated with the portion of the video content. 6. The method of claim 1 further comprising: generating metadata based on an identified speaker associated with the speech segment. | 0.781667 |
9,485,211 | 1 | 8 | 1. A social networking website system that supports user interactions in a plurality of social networks, the social networking website system comprising: a server enabling a user to participate in a plurality of social networks based on a current location information; the server monitoring the current location information of the user, and, based on changes to the current location, adjusting the user's membership to, or participation in, the social networks and social groups; the server automatically enabling communication among a plurality of mobile devices used by a corresponding plurality of users via the plurality of social networks, each of the plurality of mobile devices identifies a corresponding current location information based on GPS coordinates; and the server automatically, without employing invitations and explicit user acceptance, automatically registering and including a first user among the plurality of users in a new social network based on GPS coordinates of the current location of the first user's mobile device among the plurality of mobile devices; wherein a current location to social networks mapping is employed to determine appropriate social networks and associated social groups for the first user based on the current location. | 1. A social networking website system that supports user interactions in a plurality of social networks, the social networking website system comprising: a server enabling a user to participate in a plurality of social networks based on a current location information; the server monitoring the current location information of the user, and, based on changes to the current location, adjusting the user's membership to, or participation in, the social networks and social groups; the server automatically enabling communication among a plurality of mobile devices used by a corresponding plurality of users via the plurality of social networks, each of the plurality of mobile devices identifies a corresponding current location information based on GPS coordinates; and the server automatically, without employing invitations and explicit user acceptance, automatically registering and including a first user among the plurality of users in a new social network based on GPS coordinates of the current location of the first user's mobile device among the plurality of mobile devices; wherein a current location to social networks mapping is employed to determine appropriate social networks and associated social groups for the first user based on the current location. 8. The social networking website system of claim 1 wherein the server assigns a primary and a secondary language to each of the plurality of users for content and for user interaction screens presented; wherein the server generates reports regarding popularity of various types of content that is pushed or delivered to the plurality of users participating in the plurality of social networks. | 0.501269 |
10,109,276 | 15 | 17 | 15. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving a first speech utterance beginning with a hotword followed by a particular phrase, the particular phrase not currently designated as a hotword; in response to receiving the first speech utterance beginning with the hotword, triggering semantic interpretation on the particular phrase following the hotword; designating the particular phrase as a new hotword based on the sematic interpretation determining that the particular phrase satisfies one or more predetermined criteria associated with designating voice commands as hotwords; and after designating the particular phrase as a new hotword and while the computing device is in a sleep state, receiving a second speech utterance beginning with the particular phrase, the particular phrase when designated as the new hotword causing the computing device to transition out of the sleep state and process the second speech utterance as a voice command. | 15. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving a first speech utterance beginning with a hotword followed by a particular phrase, the particular phrase not currently designated as a hotword; in response to receiving the first speech utterance beginning with the hotword, triggering semantic interpretation on the particular phrase following the hotword; designating the particular phrase as a new hotword based on the sematic interpretation determining that the particular phrase satisfies one or more predetermined criteria associated with designating voice commands as hotwords; and after designating the particular phrase as a new hotword and while the computing device is in a sleep state, receiving a second speech utterance beginning with the particular phrase, the particular phrase when designated as the new hotword causing the computing device to transition out of the sleep state and process the second speech utterance as a voice command. 17. The computer readable-medium of claim 15 , wherein a hotword comprises a sequence of one or more words that causes the computing device to process an utterance beginning with the hotword as a voice command. | 0.804833 |
9,419,926 | 18 | 19 | 18. A system comprising: a sending entity configured to transmit a multimedia message addressed to one or more recipients, wherein the multimedia message comprises media content; and a network entity configured to receive the transmitted multimedia message, determine whether a recipient rule specified by at least one recipient of the one or more recipients exists, and responsive to a determination that the recipient rule exists, deliver the media content to the at least one recipient of the one or more recipients based upon the recipient rule. | 18. A system comprising: a sending entity configured to transmit a multimedia message addressed to one or more recipients, wherein the multimedia message comprises media content; and a network entity configured to receive the transmitted multimedia message, determine whether a recipient rule specified by at least one recipient of the one or more recipients exists, and responsive to a determination that the recipient rule exists, deliver the media content to the at least one recipient of the one or more recipients based upon the recipient rule. 19. The system of claim 18 , wherein the network entity is further configured to process the media content based upon the recipient rule before delivering the media content. | 0.720065 |
9,589,399 | 13 | 14 | 13. The method of claim 12 further comprising providing a risk profile score, using a risk profile engine, based on one of the natural identification authentication score and a combination of one or more of the computed authentication score and a received device profile score. | 13. The method of claim 12 further comprising providing a risk profile score, using a risk profile engine, based on one of the natural identification authentication score and a combination of one or more of the computed authentication score and a received device profile score. 14. The method of claim 13 further comprising: communicating through the risk profile engine with an on-network third party risk assessment engine. | 0.932815 |
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