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1. A sign language recognition apparatus comprising an input assembly for detecting sign language, a computer connected to said input assembly and generating an output signal for producing a visual or audible output corresponding to said sign language, said input assembly comprising: a glove to be worn by a user, said glove having sensors for detecting dynamic hand movements of each finger and thumb; an elbow sensor for detecting and measuring flexing and positioning of the forearm about the elbow; and a shoulder sensor for detecting movement and position of the arm with respect to the shoulder, wherein said input assembly further comprises a frame having a first section for coupling to the upper arm of the user and a second section for coupling to the forearm of the user, said first sections being coupled together by a hinge, said elbow sensor being positioned on said frame for measuring flexing and positioning of the forearm, and second section.
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1. A sign language recognition apparatus comprising an input assembly for detecting sign language, a computer connected to said input assembly and generating an output signal for producing a visual or audible output corresponding to said sign language, said input assembly comprising: a glove to be worn by a user, said glove having sensors for detecting dynamic hand movements of each finger and thumb; an elbow sensor for detecting and measuring flexing and positioning of the forearm about the elbow; and a shoulder sensor for detecting movement and position of the arm with respect to the shoulder, wherein said input assembly further comprises a frame having a first section for coupling to the upper arm of the user and a second section for coupling to the forearm of the user, said first sections being coupled together by a hinge, said elbow sensor being positioned on said frame for measuring flexing and positioning of the forearm, and second section. 6. The apparatus of claim 1 , wherein said glove includes a first accelerometer on each finger and thumb, a second accelerometer on the back of said glove to detect vertical orientation and movement of said glove, and a third accelerometer on the back of said glove to detect axial orientation and movement of said glove with respect to the forearm.
| 0.714455 |
5. The method of claim 1 , wherein similarity across references and reference vectors is configurable.
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5. The method of claim 1 , wherein similarity across references and reference vectors is configurable. 6. The method of claim 5 , wherein characteristics of the at least one reference are taken into account, the characteristics comprising: font; font size; or style; or any combination thereof.
| 0.965015 |
1. An authoring component configured for generating components for use in mapping natural language inputs to slots and preterminals derived from a schema in a natural language understanding (NLU) system, the authoring component comprising: a model trainer implemented using a processor of a computer, wherein the model trainer obtains a schema indicative of a task to be completed, the schema including a plurality of slots and a plurality of preterminals configured to be filled with portions of a natural language input, the preterminals comprising at least one of a preamble and postamble associated with one or more of the slots, and wherein the model trainer is configured to train a rules based grammar, based on training data, for mapping terms from the natural language input to slots derived from the schema and to train a plurality of statistical models for mapping terms from the natural language input to the preterminals derived from the schema, wherein the model trainer is configured to train a statistical model corresponding to each of a plurality of different preterminals, wherein the model trainer receives the training data and enumerates segmentations of the training data to associate the slots and preterminals with the training data, wherein the model trainer is configured to train a statistical model for each preterminal derived from the schema using the text associated with each preterminal as training data for the statistical model for that preterminal.
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1. An authoring component configured for generating components for use in mapping natural language inputs to slots and preterminals derived from a schema in a natural language understanding (NLU) system, the authoring component comprising: a model trainer implemented using a processor of a computer, wherein the model trainer obtains a schema indicative of a task to be completed, the schema including a plurality of slots and a plurality of preterminals configured to be filled with portions of a natural language input, the preterminals comprising at least one of a preamble and postamble associated with one or more of the slots, and wherein the model trainer is configured to train a rules based grammar, based on training data, for mapping terms from the natural language input to slots derived from the schema and to train a plurality of statistical models for mapping terms from the natural language input to the preterminals derived from the schema, wherein the model trainer is configured to train a statistical model corresponding to each of a plurality of different preterminals, wherein the model trainer receives the training data and enumerates segmentations of the training data to associate the slots and preterminals with the training data, wherein the model trainer is configured to train a statistical model for each preterminal derived from the schema using the text associated with each preterminal as training data for the statistical model for that preterminal. 7. The authoring component of claim 1 and further comprising: a probabilistic library grammar accessible by the model trainer.
| 0.728931 |
1. A tangible computer-readable medium, storing instructions executed by a computer system to implement a method for indexing data, the instructions comprising: instructions for receiving input from a user defining a classification; instructions for receiving input from the user defining an analytic for the classification; instructions for determining a definition of relevance parameters that characterize the classification; instructions for populating a cortex of data in a tangible computer readable database, the cortex of data being populated based on the classification of the data to be indexed; instructions for determining, using a processor based machine learning engine, relevant data from the cortex of data based on the definition of relevance parameters, the relevant data being data which is determined to be relevant to the classification defined by the user; instructions for analyzing the relevant data from the cortex of data based on the relevance parameters to determine attributes in the relevant data; instructions for generating an index of the attributes from the relevant data based on the analyzing of the relevant data; instructions for storing the index in the cortex; and instructions for receiving a query from an analytics tool, the query specifying the classification and an analytics measure, wherein the index is used by the analytics tool to provide results for the query using the analytics measure as applied to the data in the relevant data indexed in the classification.
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1. A tangible computer-readable medium, storing instructions executed by a computer system to implement a method for indexing data, the instructions comprising: instructions for receiving input from a user defining a classification; instructions for receiving input from the user defining an analytic for the classification; instructions for determining a definition of relevance parameters that characterize the classification; instructions for populating a cortex of data in a tangible computer readable database, the cortex of data being populated based on the classification of the data to be indexed; instructions for determining, using a processor based machine learning engine, relevant data from the cortex of data based on the definition of relevance parameters, the relevant data being data which is determined to be relevant to the classification defined by the user; instructions for analyzing the relevant data from the cortex of data based on the relevance parameters to determine attributes in the relevant data; instructions for generating an index of the attributes from the relevant data based on the analyzing of the relevant data; instructions for storing the index in the cortex; and instructions for receiving a query from an analytics tool, the query specifying the classification and an analytics measure, wherein the index is used by the analytics tool to provide results for the query using the analytics measure as applied to the data in the relevant data indexed in the classification. 9. The tangible computer-readable medium of claim 1 , wherein the analytic measure comprises a subject area to be analyzed.
| 0.59207 |
1. A modular lexical system for searching or inputting Chinese-like characters and words, the system having a processor configured to perform operations comprising: receiving input from a user to link or unlink one or more of a plurality of lexical data sources, each lexical data source having an independent data structure; generating one or more data structures for storing data from one or more of the lexical data sources in a plurality of data storage sections; indicating a structure of the stored data in one of the data storage sections; integrating the stored data in each data storage section into hierarchical data structure; creating an aggregate collection of lexemes, said collection of lexemes comprising an aggregate of all search keys and corresponding data found in the lexical data sources, together with cross-references to the lexical data sources in which said keys are found; designating, in response to user input, a subset of lexical data to be used; creating an activated subset of lexical data, said activated subset comprising a subset of the lexeme collection corresponding to the lexical data tables designated for use by the user, wherein each record corresponds to a phonetic or phonological search key for which the retrieved values correspond to character or word objects having an orthographic realization and additional lexical data as provided via the originating lexicon; retrieving individual records of lexical data from said lexical data sources such that all said sources may contribute candidates for input to the input means when a search key has been provided; displaying said candidates for selection by the user during word search and text input; generating a summary table that includes a basic nature and characteristic of individual lexicons stored in the system; and displaying information contained in said summary table.
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1. A modular lexical system for searching or inputting Chinese-like characters and words, the system having a processor configured to perform operations comprising: receiving input from a user to link or unlink one or more of a plurality of lexical data sources, each lexical data source having an independent data structure; generating one or more data structures for storing data from one or more of the lexical data sources in a plurality of data storage sections; indicating a structure of the stored data in one of the data storage sections; integrating the stored data in each data storage section into hierarchical data structure; creating an aggregate collection of lexemes, said collection of lexemes comprising an aggregate of all search keys and corresponding data found in the lexical data sources, together with cross-references to the lexical data sources in which said keys are found; designating, in response to user input, a subset of lexical data to be used; creating an activated subset of lexical data, said activated subset comprising a subset of the lexeme collection corresponding to the lexical data tables designated for use by the user, wherein each record corresponds to a phonetic or phonological search key for which the retrieved values correspond to character or word objects having an orthographic realization and additional lexical data as provided via the originating lexicon; retrieving individual records of lexical data from said lexical data sources such that all said sources may contribute candidates for input to the input means when a search key has been provided; displaying said candidates for selection by the user during word search and text input; generating a summary table that includes a basic nature and characteristic of individual lexicons stored in the system; and displaying information contained in said summary table. 8. The modular lexical system of claim 1 , further comprising: filter means for filtering word searches so that candidate search results are filtered by some criterion selected by the user, said criterion including at least one of a word class, membership in proper noun class, membership in place name class, a frequency cutoff, and a technical field of origin, wherein the resulting filtered candidate list includes characters or words corresponding to the filter applied.
| 0.6536 |
11. The non-transitory computer-readable storage medium of claim 8 , wherein the layer that was launched by the client device includes a named entity layer, wherein identifying the layer information comprises: identifying one or more named entities referenced by the activated ebook content identified by the translated position range; and obtaining entity data for the one or more named entities referenced by the activated ebook content identified by the received position range, and wherein the identified layer information includes the obtained entity data for the one or more named entities.
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11. The non-transitory computer-readable storage medium of claim 8 , wherein the layer that was launched by the client device includes a named entity layer, wherein identifying the layer information comprises: identifying one or more named entities referenced by the activated ebook content identified by the translated position range; and obtaining entity data for the one or more named entities referenced by the activated ebook content identified by the received position range, and wherein the identified layer information includes the obtained entity data for the one or more named entities. 12. The non-transitory computer-readable storage medium of claim 11 , wherein obtaining the entity data for the one or more named entities referenced by the activated ebook content comprises: obtaining entity data for one or more types of the one or more named entities, the one or more types of the one or more named entities selected from a set of named entity types consisting of: date entities, person entities, and geographic location entities.
| 0.863305 |
14. A method comprising the steps of: performing one or more reasoning operations on metadata characterizing data sets associated with data processing elements of an information processing system in order to identify at least selected portions of one or more of the data sets as being suitable for use in achieving a designated purpose; and utilizing results of the one or more reasoning operations to assemble at least a subset of the selected portions so as to achieve the designated purpose; wherein the metadata characterizes the data sets in accordance with at least one specified semantic ontology comprising at least one process, at least one task associated with each process, and at least one role associated with each process, the task being subject to at least one of a rule and a constraint, and being associated with at least one agent, and the role being a role for a given one of the data sets; wherein identifying the selected portions of the one or more data sets as being suitable for use in achieving the designated purpose comprises analyzing at least one of what data sets are needed and what data sets are available for the at least one process; wherein the utilizing step comprises manipulating the selected portions for achieving the designated purpose; wherein the manipulating comprises at least one of: (i) substituting a data set for an unavailable data set; (ii) updating at least one of the data sets; and (iii) combining at least two of the data sets; and wherein the steps are performed by at least one processing device comprising a processor coupled to a memory.
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14. A method comprising the steps of: performing one or more reasoning operations on metadata characterizing data sets associated with data processing elements of an information processing system in order to identify at least selected portions of one or more of the data sets as being suitable for use in achieving a designated purpose; and utilizing results of the one or more reasoning operations to assemble at least a subset of the selected portions so as to achieve the designated purpose; wherein the metadata characterizes the data sets in accordance with at least one specified semantic ontology comprising at least one process, at least one task associated with each process, and at least one role associated with each process, the task being subject to at least one of a rule and a constraint, and being associated with at least one agent, and the role being a role for a given one of the data sets; wherein identifying the selected portions of the one or more data sets as being suitable for use in achieving the designated purpose comprises analyzing at least one of what data sets are needed and what data sets are available for the at least one process; wherein the utilizing step comprises manipulating the selected portions for achieving the designated purpose; wherein the manipulating comprises at least one of: (i) substituting a data set for an unavailable data set; (ii) updating at least one of the data sets; and (iii) combining at least two of the data sets; and wherein the steps are performed by at least one processing device comprising a processor coupled to a memory. 18. A computer program product comprising a non-transitory processor-readable storage medium having encoded therein executable code of one or more software programs, wherein the one or more software programs when executed by the processor of the processing device implement the steps of the method of claim 14 .
| 0.579128 |
7. A substantially purified and isolated protein fraction, obtained from a composition according to claim 2 , and having at least 50% of its maximal cellulase activity at a pH between about 6.0 and about 7.0.
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7. A substantially purified and isolated protein fraction, obtained from a composition according to claim 2 , and having at least 50% of its maximal cellulase activity at a pH between about 6.0 and about 7.0. 10. An endoglucanase obtained from a fraction according to claim 7 , having a molecular weight of about 60 kD and a pI of about 3.
| 0.833084 |
19. One or more computer-readable media storing computer-executable instructions that, when executed by at least one processor, configure the at least one processor to perform operations comprising: receiving, from one or more sensors of an asset, on-site monitoring (OSM) data, the OSM data comprising time-series data associated with one or more respective units of the asset; performing at least one of data validation, outlier analysis, data filtration, data imputation, or statistical distribution analysis on the time-series data, wherein the performing removes a first respective portion of the time-series data associated with noise, and wherein a second respective portion of the time-series data that is not removed comprises principal information for use in predicting a fault; extracting the principal information from the time-series data; combining the extracted principal information; establishing a prediction model based at least in part on the combined principal information; quantifying a probability of a fault of the asset occurring at each of the one or more respective units for which time-series data was received; and predicting the fault in the asset based at least in part on the quantified probability of the fault.
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19. One or more computer-readable media storing computer-executable instructions that, when executed by at least one processor, configure the at least one processor to perform operations comprising: receiving, from one or more sensors of an asset, on-site monitoring (OSM) data, the OSM data comprising time-series data associated with one or more respective units of the asset; performing at least one of data validation, outlier analysis, data filtration, data imputation, or statistical distribution analysis on the time-series data, wherein the performing removes a first respective portion of the time-series data associated with noise, and wherein a second respective portion of the time-series data that is not removed comprises principal information for use in predicting a fault; extracting the principal information from the time-series data; combining the extracted principal information; establishing a prediction model based at least in part on the combined principal information; quantifying a probability of a fault of the asset occurring at each of the one or more respective units for which time-series data was received; and predicting the fault in the asset based at least in part on the quantified probability of the fault. 20. The one or more computer-readable media of claim 19 , wherein the asset comprises a gas turbine compressor.
| 0.529321 |
28. The method of claim 1 , wherein the XSLT stylesheet is a first XSLT stylesheet, further comprising: at request compile time, computing a rewritten XSLT stylesheet by rewriting the first XSLT stylesheet; wherein computing the rewritten XSLT stylesheet includes said step of determining, based at least in part on the structural description that constrains the set of one or more XML documents to the hierarchy of nodes that may be present in the set of one or more XML documents, which particular one or more transformation templates to use to transform the set of one or more XML documents; and wherein the rewritten XSLT stylesheet includes fewer dynamic template matching calls than the first XSLT stylesheet.
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28. The method of claim 1 , wherein the XSLT stylesheet is a first XSLT stylesheet, further comprising: at request compile time, computing a rewritten XSLT stylesheet by rewriting the first XSLT stylesheet; wherein computing the rewritten XSLT stylesheet includes said step of determining, based at least in part on the structural description that constrains the set of one or more XML documents to the hierarchy of nodes that may be present in the set of one or more XML documents, which particular one or more transformation templates to use to transform the set of one or more XML documents; and wherein the rewritten XSLT stylesheet includes fewer dynamic template matching calls than the first XSLT stylesheet. 31. The method of claim 28 , wherein determining which one or more transformation templates to use to transform the set of one or more XML documents comprises: based at least in part on the structural description that constrains the set of one or more XML documents to the hierarchy of nodes that may be present in the set of one or more XML documents, constructing a corresponding sample document that represents possible structures of the XML documents in the set of one or more XML documents; submitting the sample document to an XSLT engine for transformation based at least in part on the XSLT stylesheet and for tracing execution paths associated with the transformation, wherein the execution paths indicate, for each node contained in the sample document, which particular transformation template to use to transform the corresponding node.
| 0.718856 |
1. A learning system, comprising: a plurality of teacher stations and a plurality of student stations for holding one or more interactive learning sessions on a subject between a teacher of a plurality of teachers and at least two students, wherein the teacher and the at least two of the students interact with each other using free-style handwriting via a shared electronic white board of at least one of the plurality of teacher stations and at least two of the plurality of student stations; a database that stores at least one teacher attribute and at least one student attribute that relate to a language ability and a subject proficiency for the subject; and a server in communication with the database that: (i) serves computer generated instructional material relating to the subject to the at least two students through the at least two student stations, the computer generated instructional material for creating an interactive learning environment during the one or more interactive learning sessions, and wherein the computer generated instructional material is customized for the at least two students based on the language ability of each of the at least two students as determined by the server through each of the at least two student's respective student attributes stored in the database; and (ii) after serving the computer generated instructional material to the at least two students, selects the teacher from the plurality of teachers for the at least two students based on the language ability and the subject proficiency of each of the respective plurality of teachers teacher attributes stored in the database, wherein the teacher teaches the subject to the at least two students during the one or more interactive learning sessions in a language determined based on the language ability.
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1. A learning system, comprising: a plurality of teacher stations and a plurality of student stations for holding one or more interactive learning sessions on a subject between a teacher of a plurality of teachers and at least two students, wherein the teacher and the at least two of the students interact with each other using free-style handwriting via a shared electronic white board of at least one of the plurality of teacher stations and at least two of the plurality of student stations; a database that stores at least one teacher attribute and at least one student attribute that relate to a language ability and a subject proficiency for the subject; and a server in communication with the database that: (i) serves computer generated instructional material relating to the subject to the at least two students through the at least two student stations, the computer generated instructional material for creating an interactive learning environment during the one or more interactive learning sessions, and wherein the computer generated instructional material is customized for the at least two students based on the language ability of each of the at least two students as determined by the server through each of the at least two student's respective student attributes stored in the database; and (ii) after serving the computer generated instructional material to the at least two students, selects the teacher from the plurality of teachers for the at least two students based on the language ability and the subject proficiency of each of the respective plurality of teachers teacher attributes stored in the database, wherein the teacher teaches the subject to the at least two students during the one or more interactive learning sessions in a language determined based on the language ability. 2. The learning system of claim 1 , wherein the computer generated instructional material comprises at least one of instructional software, an electronic text book, a work sheet, a practice sheet, and a problem set.
| 0.506294 |
1. A method comprising: receiving audio input into a hearing prosthesis that is operable to stimulate a physiological system of a recipient in accordance with the received audio input, the received audio input representing an audio environment of the recipient; determining by the hearing prosthesis, based on the received audio input, linguistic characteristics of the audio environment, wherein the linguistic characteristics comprise (i) a measure of quantity of speech by the recipient and (ii) a measure of quantity of speech by one or more people other than the recipient; generating by the hearing prosthesis data representing the determined linguistic characteristics; and outputting the data from the hearing prosthesis.
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1. A method comprising: receiving audio input into a hearing prosthesis that is operable to stimulate a physiological system of a recipient in accordance with the received audio input, the received audio input representing an audio environment of the recipient; determining by the hearing prosthesis, based on the received audio input, linguistic characteristics of the audio environment, wherein the linguistic characteristics comprise (i) a measure of quantity of speech by the recipient and (ii) a measure of quantity of speech by one or more people other than the recipient; generating by the hearing prosthesis data representing the determined linguistic characteristics; and outputting the data from the hearing prosthesis. 8. The method of claim 1 , wherein the hearing prosthesis has a stimulation mode that switches between a stimulation-on mode in which the hearing prosthesis is set to stimulate the physiological system of the recipient in accordance with the audio input and a stimulation-off mode in which the hearing prosthesis is set to not stimulate the physiological system of the recipient in accordance with the audio input, and wherein generating the data representing the determined linguistic characteristics comprises: basing the data at least in part on the stimulation mode of the hearing prosthesis.
| 0.603364 |
8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving an audio signal encoding a portion of an utterance; receiving context information associated with the utterance, wherein the context information is not derived from the audio signal or any other audio signal; generating, for input to a neural network of an automatic speech recognition system and based on characteristics of the context information that existed when the context information was received, characteristic data that corresponds to the context information; providing, as input to the neural network of the automatic speech recognition system, data corresponding to the audio signal and the characteristic data that corresponds to the context information; and generating a transcription for the utterance based on at least an output of the neural network.
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8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving an audio signal encoding a portion of an utterance; receiving context information associated with the utterance, wherein the context information is not derived from the audio signal or any other audio signal; generating, for input to a neural network of an automatic speech recognition system and based on characteristics of the context information that existed when the context information was received, characteristic data that corresponds to the context information; providing, as input to the neural network of the automatic speech recognition system, data corresponding to the audio signal and the characteristic data that corresponds to the context information; and generating a transcription for the utterance based on at least an output of the neural network. 10. The system of claim 8 , wherein receiving context information associated with the utterance comprises receiving an internet protocol (IP) address of a client device from which the audio signal originated.
| 0.689189 |
2. The system of claim 1 wherein the device set comprises a plurality of devices, and wherein the information agent service determines a selected device of the set to send the notification to based on the user criteria.
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2. The system of claim 1 wherein the device set comprises a plurality of devices, and wherein the information agent service determines a selected device of the set to send the notification to based on the user criteria. 3. The system of claim 2 , wherein the information agent service accesses device data corresponding to the selected device, and modifies data in the notification to match the device data of the selected device.
| 0.945619 |
1. A method preventing incorporation of data entries by a third party to a user's own user profile, including: maintaining at least one trust object linked to fields of a user profile on an online social network, wherein the trust object holds audit trail fields that identify how data became incorporated in at least some fields of the user profile including names of data sources, interface categories of the data sources, and origins that identify geographic locations of the data sources; and access control fields that specify field-by-field and party-by-party control over third party data incorporation to the user profile fields including identifying a user's engagement preferences, a connection type of the user with a third party, statuses of data streams from third parties and information identifying the third parties; providing a privacy controller, wherein the privacy controller provides user access to information in the audit trail fields for user's own user profile; and provides user control on a field-by-field and party-by-party basis over third party data incorporation to the user profile fields; receiving instructions that set user's preferences for field-by-field and party-by-party control over the third party data incorporation to the user's own user profile; and updating the trust object responsive to the received instructions and using the updated trust object to automatically prevent incorporation of data entries by a third party to the user's own user profile of the online social network according to one or more of a source, a type, and an origin of the third party identified from the information.
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1. A method preventing incorporation of data entries by a third party to a user's own user profile, including: maintaining at least one trust object linked to fields of a user profile on an online social network, wherein the trust object holds audit trail fields that identify how data became incorporated in at least some fields of the user profile including names of data sources, interface categories of the data sources, and origins that identify geographic locations of the data sources; and access control fields that specify field-by-field and party-by-party control over third party data incorporation to the user profile fields including identifying a user's engagement preferences, a connection type of the user with a third party, statuses of data streams from third parties and information identifying the third parties; providing a privacy controller, wherein the privacy controller provides user access to information in the audit trail fields for user's own user profile; and provides user control on a field-by-field and party-by-party basis over third party data incorporation to the user profile fields; receiving instructions that set user's preferences for field-by-field and party-by-party control over the third party data incorporation to the user's own user profile; and updating the trust object responsive to the received instructions and using the updated trust object to automatically prevent incorporation of data entries by a third party to the user's own user profile of the online social network according to one or more of a source, a type, and an origin of the third party identified from the information. 3. The method of claim 1 , wherein the interface categories of the data sources include access controlled APIs, public Internet and social networking sites.
| 0.781337 |
1. A method, comprising: establishing at least one substantially three dimensional learning model of at least one learning subject; establishing at least one substantially three dimensional gallery model for at least one gallery subject; establishing at least one substantially three dimensional query model of a query subject; determining a transform of at least one parent gallery model from among said at least one gallery model in combination with at least one active learning model from among said at least one learning model so as to yield at least one transformed gallery model, wherein said transformed gallery model approaches correspondence with at least one of said at least one query model in at least one model property as compared with said parent gallery model; applying said transform; and comparing at least one substantially two dimensional transformed gallery image at least substantially corresponding with said at least one transformed gallery model against at least one substantially two dimensional query image at least substantially corresponding with said at least one query model, so as to determine whether said at least one query subject is said at least one gallery subject.
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1. A method, comprising: establishing at least one substantially three dimensional learning model of at least one learning subject; establishing at least one substantially three dimensional gallery model for at least one gallery subject; establishing at least one substantially three dimensional query model of a query subject; determining a transform of at least one parent gallery model from among said at least one gallery model in combination with at least one active learning model from among said at least one learning model so as to yield at least one transformed gallery model, wherein said transformed gallery model approaches correspondence with at least one of said at least one query model in at least one model property as compared with said parent gallery model; applying said transform; and comparing at least one substantially two dimensional transformed gallery image at least substantially corresponding with said at least one transformed gallery model against at least one substantially two dimensional query image at least substantially corresponding with said at least one query model, so as to determine whether said at least one query subject is said at least one gallery subject. 9. The method of claim 1 , comprising: determining said at least one query image from said at least one query model.
| 0.641682 |
1. A method execute by a processor for performing software due diligence review, comprising: receiving software subject to due diligence review, wherein the received software includes at least one source file; exposing plain text information for the at least one source file; searching the plain text information for the at least one source file to identify one or more keywords relevant to the due diligence review, wherein searching the plain text information to identify the one or more keywords includes identifying one or more normal keywords that indicate language potentially relevant to the due diligence review, identifying one or more negative keywords that indicate language irrelevant to the due diligence review, wherein a threshold proximity is associated with each of the respective negative keywords, negating at least one of the normal keywords if the at least one normal keyword appears within the threshold proximity associated with one or more of the negative keywords, identifying a plurality of weak normal keywords that indicate language potentially relevant to the due diligence review, wherein a threshold value is associated with each of the respective weak normal keywords, incrementing a normal counter according to the threshold values associated with each of the respective weak normal keywords, and triggering a keyword match for the plurality of weak normal keywords if the normal counter exceeds a first threshold value; matching the identified keywords against a plurality of text patterns that contain excerpts of language relevant to the due diligence review; and constructing a report providing information relating to the due diligence review, wherein the report indicates whether the software has potential compliance problems regarding one or more of software licenses, export regulations, or internal security policies.
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1. A method execute by a processor for performing software due diligence review, comprising: receiving software subject to due diligence review, wherein the received software includes at least one source file; exposing plain text information for the at least one source file; searching the plain text information for the at least one source file to identify one or more keywords relevant to the due diligence review, wherein searching the plain text information to identify the one or more keywords includes identifying one or more normal keywords that indicate language potentially relevant to the due diligence review, identifying one or more negative keywords that indicate language irrelevant to the due diligence review, wherein a threshold proximity is associated with each of the respective negative keywords, negating at least one of the normal keywords if the at least one normal keyword appears within the threshold proximity associated with one or more of the negative keywords, identifying a plurality of weak normal keywords that indicate language potentially relevant to the due diligence review, wherein a threshold value is associated with each of the respective weak normal keywords, incrementing a normal counter according to the threshold values associated with each of the respective weak normal keywords, and triggering a keyword match for the plurality of weak normal keywords if the normal counter exceeds a first threshold value; matching the identified keywords against a plurality of text patterns that contain excerpts of language relevant to the due diligence review; and constructing a report providing information relating to the due diligence review, wherein the report indicates whether the software has potential compliance problems regarding one or more of software licenses, export regulations, or internal security policies. 9. The method of claim 1 , wherein the plain text information is searched to identify the one or more keywords in an over-inclusive manner to minimize false negatives, and wherein the identified keywords are matched against a local subset of the plurality of the text patterns.
| 0.672008 |
1. A method, comprising: communicating a plurality of parameters from a client device, wherein the plurality of parameters are based, at least in part, on metadata information obtained from data mining one or more databases, at least one database including tags associated with objects, wherein the data mining includes applying one or more filters to the tags of the at least one database to obtain at least a portion of the metadata information, wherein the one or more filters are applied to one or more elements, respectively, of the tags; creating a rule associated with at least some of the parameters; and incorporating the rule into a security policy to be used by the client device and one or more additional client devices, wherein the security policy controls network communications involving the client device and the one or more additional client devices.
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1. A method, comprising: communicating a plurality of parameters from a client device, wherein the plurality of parameters are based, at least in part, on metadata information obtained from data mining one or more databases, at least one database including tags associated with objects, wherein the data mining includes applying one or more filters to the tags of the at least one database to obtain at least a portion of the metadata information, wherein the one or more filters are applied to one or more elements, respectively, of the tags; creating a rule associated with at least some of the parameters; and incorporating the rule into a security policy to be used by the client device and one or more additional client devices, wherein the security policy controls network communications involving the client device and the one or more additional client devices. 9. The method of claim 1 , further comprising: running the rule against one or more databases to determine if the rule provides a targeted result.
| 0.817618 |
26. A computer implemented method for synthesizing media utilizing a semantic network, the method comprising: (a) generating, or facilitating the generation of, by one or more computer processors, a thought network including: an active concept translated from a text query received from a human user, selected data entities from an information domain, and relationships derived between the active concept and the selected data entities, the generating comprising: including the active concept as a node in the thought network, and populating the thought network at least in part with the selected data entities from the information domain and the derived relationships between the active concept and the selected data entities; and (b) transforming the thought network to generate and provide one or more forms of synthesized media to the human user.
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26. A computer implemented method for synthesizing media utilizing a semantic network, the method comprising: (a) generating, or facilitating the generation of, by one or more computer processors, a thought network including: an active concept translated from a text query received from a human user, selected data entities from an information domain, and relationships derived between the active concept and the selected data entities, the generating comprising: including the active concept as a node in the thought network, and populating the thought network at least in part with the selected data entities from the information domain and the derived relationships between the active concept and the selected data entities; and (b) transforming the thought network to generate and provide one or more forms of synthesized media to the human user. 37. The computer implemented method of claim 26 , further comprising making the generated media available for the consumer to display, export and edit.
| 0.635812 |
7. A computer program product for adding a hotspot definition to an imaged document to create a mixed media document, the computer program product comprising: a non-transitory computer-readable medium; and computer program code, coded on the medium, for: converting a source document into the imaged document from which a feature representation can be extracted; extracting features from the imaged document to create the feature representation; receiving a first user input for the hotspot definition that comprises a first coordinate location of a first bounding box for a hotspot in the imaged document and at least one of a media or an action that is associated with the first coordinate location, wherein the hotspot comprises a portion of the imaged document that is included in the first bounding box; determining whether the portion of the imaged document that is included in the first bounding box uniquely identifies the hotspot in a database based on an amount of information included in the first bounding box; in response to determining that the portion of the imaged document that is included in the first bounding box does not uniquely identify the hotspot in the database, receiving a second user input to change the hotspot definition to a second coordinate location of a second bounding box, the second bounding box comprising the first bounding box and containing a larger amount of information than the first bounding box, wherein the larger amount of information contained in the second bounding box uniquely identifies the hotspot in the database; and storing, as the mixed media document, the imaged document, the hotspot definition, and the feature representation.
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7. A computer program product for adding a hotspot definition to an imaged document to create a mixed media document, the computer program product comprising: a non-transitory computer-readable medium; and computer program code, coded on the medium, for: converting a source document into the imaged document from which a feature representation can be extracted; extracting features from the imaged document to create the feature representation; receiving a first user input for the hotspot definition that comprises a first coordinate location of a first bounding box for a hotspot in the imaged document and at least one of a media or an action that is associated with the first coordinate location, wherein the hotspot comprises a portion of the imaged document that is included in the first bounding box; determining whether the portion of the imaged document that is included in the first bounding box uniquely identifies the hotspot in a database based on an amount of information included in the first bounding box; in response to determining that the portion of the imaged document that is included in the first bounding box does not uniquely identify the hotspot in the database, receiving a second user input to change the hotspot definition to a second coordinate location of a second bounding box, the second bounding box comprising the first bounding box and containing a larger amount of information than the first bounding box, wherein the larger amount of information contained in the second bounding box uniquely identifies the hotspot in the database; and storing, as the mixed media document, the imaged document, the hotspot definition, and the feature representation. 8. The computer program product of claim 7 , wherein converting comprises scanning the source document.
| 0.611437 |
1. A computer-implemented method comprising: receiving, via a search box comprising a native part of a Web browser, a text string associated with a user's search query, the search box not provided by a separately-installed mechanism; communicating the text string to a search provider; receiving information communicated from the search provider, wherein said information includes at least non-textual information; rendering said information in a search box drop down menu associated with said search box, wherein rendering includes rendering in the search box drop down menu at least some locally acquired information, wherein the locally acquired information comprises links associated with the user's search query; receiving a text string that the user has entered in a third-party search provider search box; replicating the text string entered in the third-party search provider search box in the search box comprising the native part of the Web browser; and providing, via the search box comprising the native part of the Web browser, one or more suggestions associated with said replicated text string.
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1. A computer-implemented method comprising: receiving, via a search box comprising a native part of a Web browser, a text string associated with a user's search query, the search box not provided by a separately-installed mechanism; communicating the text string to a search provider; receiving information communicated from the search provider, wherein said information includes at least non-textual information; rendering said information in a search box drop down menu associated with said search box, wherein rendering includes rendering in the search box drop down menu at least some locally acquired information, wherein the locally acquired information comprises links associated with the user's search query; receiving a text string that the user has entered in a third-party search provider search box; replicating the text string entered in the third-party search provider search box in the search box comprising the native part of the Web browser; and providing, via the search box comprising the native part of the Web browser, one or more suggestions associated with said replicated text string. 8. The method of claim 1 , wherein said information includes textual information.
| 0.651883 |
1. A text entry system comprising: a user input device comprising a virtual keyboard including an auto-correcting region comprising a plurality of the characters of a character set, where the characters occupy different character locations with different known coordinates in the auto-correcting region, wherein an interaction location associated with a user interaction is determined when a user interacts with the user input device within the auto-correcting region, the interaction location including coordinates of a contact point on the auto-correcting region, and the determined interaction location is added to a current input sequence of interaction locations; a machine readable vocabulary containing a plurality of objects, wherein one or more of the objects comprise a string of one or a plurality of characters forming all or part of a word or phrase; an output device having an output text region and an object choice list region; and a processor coupled to the user input device, the vocabulary, and the output device, said processor programmed to perform operations comprising: responsive to each new user interaction, conducting object-level analysis of various candidate objects from the vocabulary, comprising operations of: associating each user interaction with a different character of the given object, and scoring the given object according to factors including distances from the interaction locations in the current input sequence and the known coordinates of the associated characters of the given object; additionally responsive to each new user interaction, causing the object choice list region to display multiple objects according to scores produced by the object-level analysis; operating the output text region to display text entered by the user and to serve as a buffer for text input and editing; responsive to the user selecting one of the objects displayed in the object choice list, entering the selected object in the output text region.
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1. A text entry system comprising: a user input device comprising a virtual keyboard including an auto-correcting region comprising a plurality of the characters of a character set, where the characters occupy different character locations with different known coordinates in the auto-correcting region, wherein an interaction location associated with a user interaction is determined when a user interacts with the user input device within the auto-correcting region, the interaction location including coordinates of a contact point on the auto-correcting region, and the determined interaction location is added to a current input sequence of interaction locations; a machine readable vocabulary containing a plurality of objects, wherein one or more of the objects comprise a string of one or a plurality of characters forming all or part of a word or phrase; an output device having an output text region and an object choice list region; and a processor coupled to the user input device, the vocabulary, and the output device, said processor programmed to perform operations comprising: responsive to each new user interaction, conducting object-level analysis of various candidate objects from the vocabulary, comprising operations of: associating each user interaction with a different character of the given object, and scoring the given object according to factors including distances from the interaction locations in the current input sequence and the known coordinates of the associated characters of the given object; additionally responsive to each new user interaction, causing the object choice list region to display multiple objects according to scores produced by the object-level analysis; operating the output text region to display text entered by the user and to serve as a buffer for text input and editing; responsive to the user selecting one of the objects displayed in the object choice list, entering the selected object in the output text region. 34. The system of claim 1 , where objects in the vocabulary are organized into groups of same length words and the processor is programmed such that the scoring operation comprises: identifying all objects from the vocabulary having a length equal to the current input sequence and scoring only the identified objects; determining whether there are more than a prescribed minimum number of scored and identified objects; if so, outputting the scored and identified objects for use in the object choice list; if not, iteratively identifying all objects from the vocabulary having a length equal to the current input sequence plus incrementally greater numbers starting with one, and only in response to occurrence of the prescribed minimum number of scored and identified objects, outputting the scored and found objects for use in the object choice list.
| 0.5 |
1. A computer-implemented method executed by a processing unit coupled to memory for determining an entity category for an entity, the entity comprising a subject of a web page, comprising: extracting a set of potential categories relating to an entity, wherein the set of potential categories is extracted from a first portion of a web page and the entity comprises a subject of the web page; extracting summary text relating to the entity from a second portion of the web page, wherein the first portion is disposed at a first region of the web page and the second portion is disposed at a second region of the webpage separate from the first region; comparing at least some of the set of potential categories to the summary text to determine a set of candidate categories for the entity, wherein the set of candidate categories is a subset of the set of potential categories, and wherein the comparing includes A) performing a morphological analysis upon one or more category words of a potential category of the set of potential categories to generate a set of variation category words of the potential category, and B) identifying a match between one or more variation category words of the set of variation category words and one or more summary words of the summary text; ranking a first candidate category of the set of candidate categories relative to a second candidate category of the set of candidate categories based upon one or more ranking features to generate a ranked set of candidate categories; determining an entity category for the entity from the ranked set of candidate categories, wherein the entity category has a first rank within the ranked set of candidate categories, wherein the first rank is above a threshold; and presenting the entity category having the first rank in a search result page.
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1. A computer-implemented method executed by a processing unit coupled to memory for determining an entity category for an entity, the entity comprising a subject of a web page, comprising: extracting a set of potential categories relating to an entity, wherein the set of potential categories is extracted from a first portion of a web page and the entity comprises a subject of the web page; extracting summary text relating to the entity from a second portion of the web page, wherein the first portion is disposed at a first region of the web page and the second portion is disposed at a second region of the webpage separate from the first region; comparing at least some of the set of potential categories to the summary text to determine a set of candidate categories for the entity, wherein the set of candidate categories is a subset of the set of potential categories, and wherein the comparing includes A) performing a morphological analysis upon one or more category words of a potential category of the set of potential categories to generate a set of variation category words of the potential category, and B) identifying a match between one or more variation category words of the set of variation category words and one or more summary words of the summary text; ranking a first candidate category of the set of candidate categories relative to a second candidate category of the set of candidate categories based upon one or more ranking features to generate a ranked set of candidate categories; determining an entity category for the entity from the ranked set of candidate categories, wherein the entity category has a first rank within the ranked set of candidate categories, wherein the first rank is above a threshold; and presenting the entity category having the first rank in a search result page. 8. The computer-implemented method of claim 1 , the comparing comprising: identifying a second match between one or more category words of a second potential category of the set of potential categories and one or more summary words of the summary text; and identifying the second potential category as the first candidate category responsive to the identifying a second match.
| 0.631836 |
2. A knowledge based user educational guidance system for accessing, storing, compiling and transferring mentor experience information directed to financial services comprising: a server communicatively linked to a plurality of personal computers or workstations; said server providing to said personal computers or workstations a graphical user interface for introducing and navigating throughout said knowledge based system; said system providing a set of non-linear alternative learning paths which require interactive user participation in accordance with said mentor experience information; means for the user to non-linearly and interactively select a desired learning path based on user interest and demonstrated performance; means for providing contextual case based explication and application of said mentor knowledge and experience directed to financial services; means for providing a set of interactive multi-tiered valid use simulations of application of said knowledge in accordance with said knowledge based system; interactive means for mentoring said user when, as, and if user learning guidance is required; and consequential feedback means for the user based on user responses to said mentoring.
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2. A knowledge based user educational guidance system for accessing, storing, compiling and transferring mentor experience information directed to financial services comprising: a server communicatively linked to a plurality of personal computers or workstations; said server providing to said personal computers or workstations a graphical user interface for introducing and navigating throughout said knowledge based system; said system providing a set of non-linear alternative learning paths which require interactive user participation in accordance with said mentor experience information; means for the user to non-linearly and interactively select a desired learning path based on user interest and demonstrated performance; means for providing contextual case based explication and application of said mentor knowledge and experience directed to financial services; means for providing a set of interactive multi-tiered valid use simulations of application of said knowledge in accordance with said knowledge based system; interactive means for mentoring said user when, as, and if user learning guidance is required; and consequential feedback means for the user based on user responses to said mentoring. 7. The knowledge based user educational guidance system for accessing, storing, compiling and transferring mentor experience information directed to financial services of claim 2 in which said system is cross-referenced and hypertext linked to an on-the-job training episode file.
| 0.593455 |
1. A method for generating, maintaining, updating, and augmenting a working database containing documents used as references for other documents in said working database, said method executed as a supplemental program operable within a word processor, said method comprising the steps of: searching a new document for symbols, retrieving said symbols and replacing said retrieved symbols with text representing said retrieved symbols; searching said new document for images, retrieving said images and replacing said retrieved images with text representing said retrieved images; parsing all text within said new document, including general text, said text representing retrieved symbols, and said text representing retrieved images into one or more discrete clusters, said one or more of said discrete clusters separated with markers, said markers positioned by a marker positioning algorithm; manually moving said markers within said new document, said movement of said markers accomplished by a user manually adjusting said markers to user specified positions within said new document; deleting said markers within said new document by said user manually deleting said markers; adding additional markers within said new document by said user manually inserting said additional markers to user specified positions within said new document; highlighting marked discrete clusters within said new document for verification by said user; assigning one or more identification codes corresponding one or more said marked discrete clusters within said new document; uploading said new document into said working database; verifying the upload of said new document into a file system of said working database by providing a file name and location of said new document within said file system; searching said working database for text, including general text, said text representing retrieved symbols, and said text representing retrieved images by querying said working database using a search string, said document file name, said document location, and or said identification code representing a discrete cluster; retrieving one or more relevant parent documents from said working database, said parent documents containing said text relevant to said search; generating a child document by said user selecting text from one or more discrete clusters within one or more of said relevant parent documents; inserting said selected text into said child document, said insertion allowing elective retention of parent document identification codes within said inserted text in said child document; searching said child document for symbols and images, replacing said symbols and said images with text representing said retrieved symbols and images; manually augmenting said inserted text and within said child document, said augmentation allowing addition to, removal, and/or alteration of said inserted text within said child document, said manual augmentation allowing paraphrasing of said inserted text, parsing all text within said child document, including general text, said text representing retrieved symbols, and said text representing retrieved images into one or more discrete clusters, said one or more of said discrete clusters separated with markers, said markers positioned by a marker positioning algorithm; manually adjusting said markers around said paraphrasing in said child document, while maintaining matches between the said discrete clusters in said parent documents and said discrete clusters in said child documents; assigning identification codes to said inserted text within said discrete clusters within said child document; automatically generating links between said inserted text within said child document to said selected text within one or more of said parent documents corresponding to said inserted text, said links containing said parent document identification codes retained within said inserted text and said child document identification codes; automatically generating links between said inserted text within said child document and said selected text within one or more of said parent documents corresponding to said inserted text by searching said working database for parent documents containing matches to said inserted text within said discrete clusters of said child documents, said links containing said parent document identification codes and said child document identification codes; manually generating links between said inserted text within said child document and said selected text within one or more said discrete clusters with said parent documents, said links containing said parent document identification codes and said child document identification codes; maintaining a registry of said links in said working database, said registry prompting child document authors when one or more of said parent documents are augmented, said prompting giving notice of said augmentation of said parent document; automatically generating citations for said inserted text within said child document using said links, said automatically generated citations referencing corresponding discrete clusters within said parent documents, said citations generated in a pre-set format, customizable by said user; inserting said citations into said child document, said citations being movable or augmentable by said user; uploading said child document into said working database while allowing said user to electively remove said parent document identification codes within said child document prior to uploading; verifying said upload of said child document into said file system of said working database by providing a file name and file location for said child document in said file system of said working database; searching said working database for exact matches between the text of said child document and text of all documents stored within said working database and searching said working database for exact matches to said parent document identification codes retained within said child document, if said exact matches are retrieved, said method includes updating positioning of said markers within said child document corresponding to said discrete clusters within said exact matches; prompting said user when said exact matches are not retrieved and providing a list of best matches between said text of said child document and said discrete clusters of documents stored within said working database, said user selecting a best match which reposition said markers in said child document corresponding to the text of said best match; uploading said child document containing said new markers; verifying said upload of said child document containing said new markers into said file system of said working database by providing a file name and file location for said child document in said file system of said working database; tracking modifications to text, symbols, format, and/or images of said documents within said working database; alerting said user when said modifications occur; comparing said documents within said working database by aligning one or more referenced documents with one or more referencing documents and tagging the differences between said documents.
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1. A method for generating, maintaining, updating, and augmenting a working database containing documents used as references for other documents in said working database, said method executed as a supplemental program operable within a word processor, said method comprising the steps of: searching a new document for symbols, retrieving said symbols and replacing said retrieved symbols with text representing said retrieved symbols; searching said new document for images, retrieving said images and replacing said retrieved images with text representing said retrieved images; parsing all text within said new document, including general text, said text representing retrieved symbols, and said text representing retrieved images into one or more discrete clusters, said one or more of said discrete clusters separated with markers, said markers positioned by a marker positioning algorithm; manually moving said markers within said new document, said movement of said markers accomplished by a user manually adjusting said markers to user specified positions within said new document; deleting said markers within said new document by said user manually deleting said markers; adding additional markers within said new document by said user manually inserting said additional markers to user specified positions within said new document; highlighting marked discrete clusters within said new document for verification by said user; assigning one or more identification codes corresponding one or more said marked discrete clusters within said new document; uploading said new document into said working database; verifying the upload of said new document into a file system of said working database by providing a file name and location of said new document within said file system; searching said working database for text, including general text, said text representing retrieved symbols, and said text representing retrieved images by querying said working database using a search string, said document file name, said document location, and or said identification code representing a discrete cluster; retrieving one or more relevant parent documents from said working database, said parent documents containing said text relevant to said search; generating a child document by said user selecting text from one or more discrete clusters within one or more of said relevant parent documents; inserting said selected text into said child document, said insertion allowing elective retention of parent document identification codes within said inserted text in said child document; searching said child document for symbols and images, replacing said symbols and said images with text representing said retrieved symbols and images; manually augmenting said inserted text and within said child document, said augmentation allowing addition to, removal, and/or alteration of said inserted text within said child document, said manual augmentation allowing paraphrasing of said inserted text, parsing all text within said child document, including general text, said text representing retrieved symbols, and said text representing retrieved images into one or more discrete clusters, said one or more of said discrete clusters separated with markers, said markers positioned by a marker positioning algorithm; manually adjusting said markers around said paraphrasing in said child document, while maintaining matches between the said discrete clusters in said parent documents and said discrete clusters in said child documents; assigning identification codes to said inserted text within said discrete clusters within said child document; automatically generating links between said inserted text within said child document to said selected text within one or more of said parent documents corresponding to said inserted text, said links containing said parent document identification codes retained within said inserted text and said child document identification codes; automatically generating links between said inserted text within said child document and said selected text within one or more of said parent documents corresponding to said inserted text by searching said working database for parent documents containing matches to said inserted text within said discrete clusters of said child documents, said links containing said parent document identification codes and said child document identification codes; manually generating links between said inserted text within said child document and said selected text within one or more said discrete clusters with said parent documents, said links containing said parent document identification codes and said child document identification codes; maintaining a registry of said links in said working database, said registry prompting child document authors when one or more of said parent documents are augmented, said prompting giving notice of said augmentation of said parent document; automatically generating citations for said inserted text within said child document using said links, said automatically generated citations referencing corresponding discrete clusters within said parent documents, said citations generated in a pre-set format, customizable by said user; inserting said citations into said child document, said citations being movable or augmentable by said user; uploading said child document into said working database while allowing said user to electively remove said parent document identification codes within said child document prior to uploading; verifying said upload of said child document into said file system of said working database by providing a file name and file location for said child document in said file system of said working database; searching said working database for exact matches between the text of said child document and text of all documents stored within said working database and searching said working database for exact matches to said parent document identification codes retained within said child document, if said exact matches are retrieved, said method includes updating positioning of said markers within said child document corresponding to said discrete clusters within said exact matches; prompting said user when said exact matches are not retrieved and providing a list of best matches between said text of said child document and said discrete clusters of documents stored within said working database, said user selecting a best match which reposition said markers in said child document corresponding to the text of said best match; uploading said child document containing said new markers; verifying said upload of said child document containing said new markers into said file system of said working database by providing a file name and file location for said child document in said file system of said working database; tracking modifications to text, symbols, format, and/or images of said documents within said working database; alerting said user when said modifications occur; comparing said documents within said working database by aligning one or more referenced documents with one or more referencing documents and tagging the differences between said documents. 3. The method of claim 1 , in which said marker positioning algorithm detects spaces between and inserts said markers between said text, said images, and said symbols, said marker positioning algorithm adjustable to user preferences.
| 0.852645 |
11. A set of one or more computer-readable non-transitory storage media that provides instructions that, when executed by a set of one or more processing devices, will cause said set of processing devices to perform operations comprising: maintaining one or more data stores storing a social graph of a social networking system comprising a plurality of nodes and a plurality of edges between the nodes, wherein the plurality of nodes includes user nodes corresponding to users of the social networking system and concept nodes corresponding to concepts, and wherein user attributes are associated with each user node; identifying an unknown, incomplete, or inaccurate user attribute to be inferred for a user of the social networking system; generating a plurality of probability lists using a corresponding plurality of probability algorithms that utilize a set of known user attributes of the user and the social graph, wherein each probability list of the plurality of probability lists includes a set of one or more probability entries that each include a prediction value and a confidence score corresponding to the prediction value, wherein the prediction value is a possible value of the unknown, incomplete, or inaccurate user attribute, and wherein the confidence score is a value indicating a predicted likelihood that the prediction value is a correct value of the unknown, incomplete, or inaccurate user attribute; generating an inferred user attribute value based upon the plurality of probability lists and a plurality of weights corresponding to the plurality of probability algorithms, wherein each weight of the plurality of weights indicates a relative confidence that the corresponding probability algorithm will generate a probability list including a prediction value that is the correct value of the unknown, incomplete, or inaccurate user attribute; and storing the inferred user attribute value in the one or more data stores.
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11. A set of one or more computer-readable non-transitory storage media that provides instructions that, when executed by a set of one or more processing devices, will cause said set of processing devices to perform operations comprising: maintaining one or more data stores storing a social graph of a social networking system comprising a plurality of nodes and a plurality of edges between the nodes, wherein the plurality of nodes includes user nodes corresponding to users of the social networking system and concept nodes corresponding to concepts, and wherein user attributes are associated with each user node; identifying an unknown, incomplete, or inaccurate user attribute to be inferred for a user of the social networking system; generating a plurality of probability lists using a corresponding plurality of probability algorithms that utilize a set of known user attributes of the user and the social graph, wherein each probability list of the plurality of probability lists includes a set of one or more probability entries that each include a prediction value and a confidence score corresponding to the prediction value, wherein the prediction value is a possible value of the unknown, incomplete, or inaccurate user attribute, and wherein the confidence score is a value indicating a predicted likelihood that the prediction value is a correct value of the unknown, incomplete, or inaccurate user attribute; generating an inferred user attribute value based upon the plurality of probability lists and a plurality of weights corresponding to the plurality of probability algorithms, wherein each weight of the plurality of weights indicates a relative confidence that the corresponding probability algorithm will generate a probability list including a prediction value that is the correct value of the unknown, incomplete, or inaccurate user attribute; and storing the inferred user attribute value in the one or more data stores. 12. The set of computer-readable non-transitory storage media of claim 11 , wherein a first probability list of the plurality of probability lists is generated using a set of one or more known user attributes of the user.
| 0.593788 |
7. The computer-implemented method of claim 1 , wherein the readable object comprises a document structure or a text document.
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7. The computer-implemented method of claim 1 , wherein the readable object comprises a document structure or a text document. 8. The computer-implemented method of claim 7 , wherein document attributes are associated to the document structure.
| 0.941925 |
1. A method for an improved News Meta-Search over a large number of Online news sources on the Internet or similar networks, comprising providing a meta-search system which includes at least one server, and displaying news items to a user through a browser on a computer, wherein the server performs, under software instruction from the meta-search system, at least one of the steps of: i. Switching between news items from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention; and ii. Switching between news images from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention, and wherein said images are at least one of still images and streaming data; wherein at least one of the following features exists: a. Recursive sub-clustering is performed and the recursive sub-clustering continues until there are sufficiently few items in the final sub-category or until the items are too different to group further; b. If the user searches for keywords in the News Meta Search, the results are displayed recursively in clusters and sub-cluster in a way similar to the automatically generated newspaper page; c. If the user searches for keywords in the News Meta Search, the results can have all the features that exist in the automatically generated newspaper page; d. The system enables the user to switch between a mode that displays also images and a mode without images; e. The same news item or same sub-cluster can belong to more than one cluster or sub-cluster, and thus it is shown and/or can be reached from all the sufficiently relevant clusters or sub-clusters to which it is related; f. The system enables the user to request to sort a list of related items by relevance and/or by time and date to create order between and/or within the sub-clusters, so that the system performs the sorting without interfering with the cluster structure itself; g. The system enables the user to request to sort the items by at least one of: 1. The country of the source, so that the system orders or clusters the news items in addition or instead also according to the country of the news source, 2. The level of reliability of the source, so that the system orders or clusters the news items in addition or instead also according to the reliability of the news source; h. The system enables the user to view a graphical or textual hierarchical representation which shows simultaneously the multi-level structure of clusters and sub-clusters, showing more than two levels of the hierarchy at the same time, or showing the structure down to the end-nodes; i. The Meta News system automatically chooses only images that are within a certain reasonable range of sizes; j. As additional new related news items come in, the headlines and/or the images can be automatically updated even if the user does not click on any refresh button; k. The user gets a different indication when the items or images themselves have changed or new items or images are brought in (compared to the normal swapping between items), and said indication is at least one of sound indication and visual indication of the item that has changed or the new item that has been inserted; l. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is either truncated automatically to fit in the allowed window, or is automatically downscaled in order to fit completely into the allowed space; m. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is truncated automatically to fit in the allowed window and for said truncation the improved html protocol allows the web programmer to specify for each image the x-y coordinates of its central point of interest, and/or various heuristics are used by the browser or by the server in order to find the central point of interest automatically; n. When switching images contain also streaming data, at least one of the following is done: 1. Automatic switching of images is disabled so that the user has to click on something in order to view related streaming data from a different source or other still images, and 2. Each streaming source remains in the position for a longer time than still images until switching to the next streaming source or to the next still image; o. The system determines which item to use as the main item of the general cluster by at least one of: 1. First picking the sub-cluster that has the largest number of items and/or the most recent cluster that is big enough relative to other sub-clusters, 2. Picking the item within the chosen first sub-cluster which has the highest average similarity to other items in that sub-cluster and/or belongs to the largest sub-cluster of that sub-cluster and/or is most relevant within the cluster or within the sub-cluster and/or is most recent within the cluster or within the sub-cluster; p. When requesting News alerts, instead of being able to request only by specific keywords, the system enables the user to also at least one of: 1. Mark a cluster or a specific sub-cluster, so that he/she is notified automatically on any new items that belong to that cluster or after sufficient changes have accumulated in the cluster, 2. Use semantic qualifiers, 3. Mark words in a way that indicates that synonyms should also be checked for these words, so that he/she will be notified also about items that contain synonyms of these marked words; and wherein at least one of the following features exists: q. In order to improve the clustering ability, the time the items were published is taken into account, with the assumption that the closer the time of publication between them, the higher the chance that two items are dealing with the same event; r. Temporal words or phrases used in the news item are used to decide when the event occurred, and this time is used to separate between news items that occurred before this time and items that occurred after this time and/or to help decide the similarity between items that might be referring to the same event; s. Temporal words or phrases used in the news item are used to decide when the event occurred, and in order to analyze the temporal phrases used in the item, the system is able to perform also at least some minimal type of semantic analysis and/or has at least knowledge of the relevant temporal nouns and relevant verbs; and t. When sorting automatically generated news clusters the number of items in each cluster is normalized by the time factor, since clusters that have exited for a longer time would normally have more items than a newer cluster even if the new cluster is more important.
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1. A method for an improved News Meta-Search over a large number of Online news sources on the Internet or similar networks, comprising providing a meta-search system which includes at least one server, and displaying news items to a user through a browser on a computer, wherein the server performs, under software instruction from the meta-search system, at least one of the steps of: i. Switching between news items from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention; and ii. Switching between news images from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention, and wherein said images are at least one of still images and streaming data; wherein at least one of the following features exists: a. Recursive sub-clustering is performed and the recursive sub-clustering continues until there are sufficiently few items in the final sub-category or until the items are too different to group further; b. If the user searches for keywords in the News Meta Search, the results are displayed recursively in clusters and sub-cluster in a way similar to the automatically generated newspaper page; c. If the user searches for keywords in the News Meta Search, the results can have all the features that exist in the automatically generated newspaper page; d. The system enables the user to switch between a mode that displays also images and a mode without images; e. The same news item or same sub-cluster can belong to more than one cluster or sub-cluster, and thus it is shown and/or can be reached from all the sufficiently relevant clusters or sub-clusters to which it is related; f. The system enables the user to request to sort a list of related items by relevance and/or by time and date to create order between and/or within the sub-clusters, so that the system performs the sorting without interfering with the cluster structure itself; g. The system enables the user to request to sort the items by at least one of: 1. The country of the source, so that the system orders or clusters the news items in addition or instead also according to the country of the news source, 2. The level of reliability of the source, so that the system orders or clusters the news items in addition or instead also according to the reliability of the news source; h. The system enables the user to view a graphical or textual hierarchical representation which shows simultaneously the multi-level structure of clusters and sub-clusters, showing more than two levels of the hierarchy at the same time, or showing the structure down to the end-nodes; i. The Meta News system automatically chooses only images that are within a certain reasonable range of sizes; j. As additional new related news items come in, the headlines and/or the images can be automatically updated even if the user does not click on any refresh button; k. The user gets a different indication when the items or images themselves have changed or new items or images are brought in (compared to the normal swapping between items), and said indication is at least one of sound indication and visual indication of the item that has changed or the new item that has been inserted; l. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is either truncated automatically to fit in the allowed window, or is automatically downscaled in order to fit completely into the allowed space; m. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is truncated automatically to fit in the allowed window and for said truncation the improved html protocol allows the web programmer to specify for each image the x-y coordinates of its central point of interest, and/or various heuristics are used by the browser or by the server in order to find the central point of interest automatically; n. When switching images contain also streaming data, at least one of the following is done: 1. Automatic switching of images is disabled so that the user has to click on something in order to view related streaming data from a different source or other still images, and 2. Each streaming source remains in the position for a longer time than still images until switching to the next streaming source or to the next still image; o. The system determines which item to use as the main item of the general cluster by at least one of: 1. First picking the sub-cluster that has the largest number of items and/or the most recent cluster that is big enough relative to other sub-clusters, 2. Picking the item within the chosen first sub-cluster which has the highest average similarity to other items in that sub-cluster and/or belongs to the largest sub-cluster of that sub-cluster and/or is most relevant within the cluster or within the sub-cluster and/or is most recent within the cluster or within the sub-cluster; p. When requesting News alerts, instead of being able to request only by specific keywords, the system enables the user to also at least one of: 1. Mark a cluster or a specific sub-cluster, so that he/she is notified automatically on any new items that belong to that cluster or after sufficient changes have accumulated in the cluster, 2. Use semantic qualifiers, 3. Mark words in a way that indicates that synonyms should also be checked for these words, so that he/she will be notified also about items that contain synonyms of these marked words; and wherein at least one of the following features exists: q. In order to improve the clustering ability, the time the items were published is taken into account, with the assumption that the closer the time of publication between them, the higher the chance that two items are dealing with the same event; r. Temporal words or phrases used in the news item are used to decide when the event occurred, and this time is used to separate between news items that occurred before this time and items that occurred after this time and/or to help decide the similarity between items that might be referring to the same event; s. Temporal words or phrases used in the news item are used to decide when the event occurred, and in order to analyze the temporal phrases used in the item, the system is able to perform also at least some minimal type of semantic analysis and/or has at least knowledge of the relevant temporal nouns and relevant verbs; and t. When sorting automatically generated news clusters the number of items in each cluster is normalized by the time factor, since clusters that have exited for a longer time would normally have more items than a newer cluster even if the new cluster is more important. 3. The method of claim 1 wherein as additional new related news items come in, the headlines and/or the images can be automatically updated even if the user does not click on any refresh button and wherein said automatic updating is done by partial refresh on a need basis by at least one of the following ways: a. The refresh command is initiated automatically by the site when there is any change in the page, so that the browser can get a refresh even if it didn't ask for it; b. The browser can ask for refresh, but if nothing has changed then the browser gets just a code that tells it to keep the current page or window as is; c. When the refresh is sent, it is a smart refresh, which tells the browser only what to change on the page instead of having to send the entire page again.
| 0.815075 |
1. A system for converting user-selected printed text to a synthesized image sequence, comprising: processing electronics configured to receive an image of text over a network, the text being a passage from a source text, to translate the text of the image of text into a machine readable format, and, in response to receiving the image: to determine the source text from the text; to search for and to receive, from a source other than the image of text, auxiliary information comprising another passage within the source text; and to generate model information based on the auxiliary information and the text translated into the machine readable format.
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1. A system for converting user-selected printed text to a synthesized image sequence, comprising: processing electronics configured to receive an image of text over a network, the text being a passage from a source text, to translate the text of the image of text into a machine readable format, and, in response to receiving the image: to determine the source text from the text; to search for and to receive, from a source other than the image of text, auxiliary information comprising another passage within the source text; and to generate model information based on the auxiliary information and the text translated into the machine readable format. 4. The system of claim 1 , wherein receiving the image comprises receiving a text selection information.
| 0.587421 |
1. A method of operating a gesture identification system to identify a user-performed gesture, the gesture identification system including at least one sensor responsive to user-performed gestures and a processor communicatively coupled to the at least one sensor, the method comprising: providing at least one signal from the at least one sensor to the processor; segmenting the at least one signal into data windows; for each i th data window in at least a subset of the data windows: determining a window class for the i th data window by the processor, the window class selected by the processor from a library of window classes, wherein each window class in the library of window classes exclusively characterizes at least one data window property; determining, by the processor, a respective probability that each gesture in a gesture library is the user-performed gesture based on a) the window class for the i th data window and, when i>1, b) the window class for at least one j th data window, where j<i; and identifying a highest-probability gesture for the i th data window by the processor, the highest-probability gesture corresponding to the gesture in the gesture library that has a highest probability of being the user-performed gesture for the i th data window; and identifying the user-performed gesture by the processor based on the respective highest-probability gestures for at least two data windows in the at least a subset of data windows.
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1. A method of operating a gesture identification system to identify a user-performed gesture, the gesture identification system including at least one sensor responsive to user-performed gestures and a processor communicatively coupled to the at least one sensor, the method comprising: providing at least one signal from the at least one sensor to the processor; segmenting the at least one signal into data windows; for each i th data window in at least a subset of the data windows: determining a window class for the i th data window by the processor, the window class selected by the processor from a library of window classes, wherein each window class in the library of window classes exclusively characterizes at least one data window property; determining, by the processor, a respective probability that each gesture in a gesture library is the user-performed gesture based on a) the window class for the i th data window and, when i>1, b) the window class for at least one j th data window, where j<i; and identifying a highest-probability gesture for the i th data window by the processor, the highest-probability gesture corresponding to the gesture in the gesture library that has a highest probability of being the user-performed gesture for the i th data window; and identifying the user-performed gesture by the processor based on the respective highest-probability gestures for at least two data windows in the at least a subset of data windows. 3. The method of claim 1 wherein each window class in the library of window classes exclusively characterizes a respective range of values for the same at least one data window property.
| 0.722011 |
8. A tangible machine-readable medium storing instructions which, when executed by one or more processors of a machine, cause the machine to perform operations comprising: for each of a plurality of publications, generating an author-name-mention data structure for each author name listed on the publication, the author-name-mention data structure comprising at least an identifier of the publication and the listed author name; associating, with each of the author-name-mention data structures, a feature set derived from the publication identified in the author-name-mention data structure; automatically clustering the author-name-mention data structures, at least in part based on comparison between the feature sets, to form a plurality of clusters each representing a disambiguated cluster author and containing one or more publications within the cluster; for a selected individual, searching one or more databases to identify social contacts of the selected individual; searching the one or more databases to automatically identify, among unassigned ones of the plurality of clusters and a plurality of author identities uniquely representing the selected individual's social contacts within the computing system, pairs of a cluster and an author identity name-compatible with the disambiguated cluster author of the cluster; and searching the one or more databases to detect, for at least one of the pairs of a cluster and a name-compatible author identity, at least one publication within the cluster that is at least one of co-authored by the selected individual or cited in a publication authored or co-authored by the selected individual, suggesting the at least one pair of a cluster and a name-compatible author identity representing one of the selected individual's social contacts as a candidate match to the selected individual with a request for confirmation that the social contact represented by the author identity is the disambiguated cluster author of the cluster and, following receipt of the requested confirmation, assigning the cluster to the name-compatible author identity based at least in part on the confirmation.
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8. A tangible machine-readable medium storing instructions which, when executed by one or more processors of a machine, cause the machine to perform operations comprising: for each of a plurality of publications, generating an author-name-mention data structure for each author name listed on the publication, the author-name-mention data structure comprising at least an identifier of the publication and the listed author name; associating, with each of the author-name-mention data structures, a feature set derived from the publication identified in the author-name-mention data structure; automatically clustering the author-name-mention data structures, at least in part based on comparison between the feature sets, to form a plurality of clusters each representing a disambiguated cluster author and containing one or more publications within the cluster; for a selected individual, searching one or more databases to identify social contacts of the selected individual; searching the one or more databases to automatically identify, among unassigned ones of the plurality of clusters and a plurality of author identities uniquely representing the selected individual's social contacts within the computing system, pairs of a cluster and an author identity name-compatible with the disambiguated cluster author of the cluster; and searching the one or more databases to detect, for at least one of the pairs of a cluster and a name-compatible author identity, at least one publication within the cluster that is at least one of co-authored by the selected individual or cited in a publication authored or co-authored by the selected individual, suggesting the at least one pair of a cluster and a name-compatible author identity representing one of the selected individual's social contacts as a candidate match to the selected individual with a request for confirmation that the social contact represented by the author identity is the disambiguated cluster author of the cluster and, following receipt of the requested confirmation, assigning the cluster to the name-compatible author identity based at least in part on the confirmation. 10. The machine-readable medium of claim 8 , wherein the operations further comprise, following the detecting, comparing a feature set associated with the cluster to one or more features sets of one or more other clusters previously assigned to the name-compatible author identity to compute one or more respective feature-similarity scores, wherein the cluster is assigned to the name-compatible author identity further based at least in part on the one or more feature-similarity scores.
| 0.561709 |
24. A method of performing XBRL extension taxonomy concept replacement comprising: analyzing, by a computer processor, an XBRL document having XBRL tags to identify an XBRL extension taxonomy concept of an XBRL extension taxonomy that is superfluous compared to an XBRL base taxonomy concept of an XBRL base taxonomy based on a figure of merit; and replacing, by a computer processor, the identified XBRL extension taxonomy concept in the XBRL document with the compared XBRL base taxonomy concept, wherein the figure of merit indicates a degree of similarity among at least three degrees of similarity along a continuum from a low degree to a high degree of similarity between the identified XBRL extension taxonomy concept and the compared XBRL base taxonomy concept.
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24. A method of performing XBRL extension taxonomy concept replacement comprising: analyzing, by a computer processor, an XBRL document having XBRL tags to identify an XBRL extension taxonomy concept of an XBRL extension taxonomy that is superfluous compared to an XBRL base taxonomy concept of an XBRL base taxonomy based on a figure of merit; and replacing, by a computer processor, the identified XBRL extension taxonomy concept in the XBRL document with the compared XBRL base taxonomy concept, wherein the figure of merit indicates a degree of similarity among at least three degrees of similarity along a continuum from a low degree to a high degree of similarity between the identified XBRL extension taxonomy concept and the compared XBRL base taxonomy concept. 26. The method of claim 24 , wherein the figure of merit includes a similarity of a name of the identified XBRL extension taxonomy concept and a corresponding name of the compared XBRL base taxonomy concept based at least in part on whether a word included in the name of the identified XBRL extension taxonomy concept is an antonym of a corresponding word included in the corresponding name of the compared XBRL base taxonomy concept and whether a balance type of the identified XBRL extension taxonomy concept is opposite of a balance type of the compared XBRL base taxonomy concept.
| 0.641919 |
8. A computer program product comprising a computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code configured to, when operating in a training mode, handle a subset of a plurality of string queries having a plurality of contextual metadata received from a client application in an instructional environment, wherein an effectiveness of the handling of the subset of the plurality of string queries is based upon feedback from the client application, and, wherein the subset of string queries represents a spectrum of string queries expected to be generated by the client application in an operational environment; computer usable program code configured to, upon completion of the handling of the subset of the plurality of string queries, synthesize a string analysis algorithm selection policy for the client application, wherein said string analysis algorithm selection policy is based upon the handling of the subset of string queries while in the training mode, wherein the string analysis algorithm selection policy correlates a context of a string query in the subset to a usage of a string analysis algorithm; and computer usable program code configured to, when operating in a production mode, dynamically handle the plurality of string queries having the plurality of contextual metadata received from the client application in the operational environment in accordance with the string analysis algorithm selection policy, wherein the string analysis algorithm to be used for a string query is dynamically and independently determined.
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8. A computer program product comprising a computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code configured to, when operating in a training mode, handle a subset of a plurality of string queries having a plurality of contextual metadata received from a client application in an instructional environment, wherein an effectiveness of the handling of the subset of the plurality of string queries is based upon feedback from the client application, and, wherein the subset of string queries represents a spectrum of string queries expected to be generated by the client application in an operational environment; computer usable program code configured to, upon completion of the handling of the subset of the plurality of string queries, synthesize a string analysis algorithm selection policy for the client application, wherein said string analysis algorithm selection policy is based upon the handling of the subset of string queries while in the training mode, wherein the string analysis algorithm selection policy correlates a context of a string query in the subset to a usage of a string analysis algorithm; and computer usable program code configured to, when operating in a production mode, dynamically handle the plurality of string queries having the plurality of contextual metadata received from the client application in the operational environment in accordance with the string analysis algorithm selection policy, wherein the string analysis algorithm to be used for a string query is dynamically and independently determined. 9. The computer program product of claim 8 , wherein handling of the subset of the plurality of string queries when operating in the training mode further comprises: computer usable program code configured to receive a query request from the client application, wherein said query request comprises the string query of the subset and the plurality of contextual metadata associated with the string query of the subset; computer usable program code configured to select a string analysis algorithm from a plurality of string analysis algorithms available for use by the string analysis module that best addresses the received query request, wherein said selection utilizes a heuristic strategy; computer usable program code configured to execute the selected string analysis algorithm upon the string query of the subset; computer usable program code configured to convey results of the execution of the selected string analysis algorithm to the client application; computer usable program code configured to receive selection feedback having a selection score from the client application for the results of the executed string analysis algorithm, wherein said selection score quantitatively expresses the effectiveness of the selected string analysis algorithm; and computer usable program code configured to, when the received selection feedback indicates an unsatisfactory selection of the string analysis algorithm, automatically modify the heuristic strategy with respect to at least one of the string query of the subset, the plurality of contextual metadata associated with the string query of the subset, and a plurality of selection rules that influence the heuristic strategy.
| 0.678252 |
1. A touch screen method for configuring and applying metadata tags on an electronic whiteboard, comprising: receiving as first touch screen input on the electronic whiteboard a tag class configuration instruction identifying a metadata tag class; displaying on the electronic whiteboard in response to the tag class configuration instruction a tag configuration list for the metadata tag class; receiving as second touch screen input on the electronic whiteboard a plurality of metadata tags and associated metadata tag priorities for inclusion in the metadata tag class, wherein the metadata tags and the associated metadata tag priorities are received as handwritten characters in empty metadata tag cells and counterpart empty metadata tag priority cells within the tag configuration list; associating in a memory on the electronic whiteboard the metadata tag class with the metadata tags and the associated metadata tag priorities; receiving as third touch screen input on the electronic whiteboard an object tagging instruction identifying an object on the electronic whiteboard to be tagged with metadata; displaying, on the electronic whiteboard in response to the object tagging instruction using the associated metadata tag class, metadata tags and metadata tag priorities a hierarchical selection menu including the metadata tag class as a selectable option on a first level and the metadata tags as selectable options on a second level, wherein the metadata tags are ordered on the second level in accordance with the metadata tag priorities; and receiving as fourth touch screen input on the electronic whiteboard a selection from the hierarchical selection menu of one of the metadata tags whereby the identified object is tagged with the metadata.
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1. A touch screen method for configuring and applying metadata tags on an electronic whiteboard, comprising: receiving as first touch screen input on the electronic whiteboard a tag class configuration instruction identifying a metadata tag class; displaying on the electronic whiteboard in response to the tag class configuration instruction a tag configuration list for the metadata tag class; receiving as second touch screen input on the electronic whiteboard a plurality of metadata tags and associated metadata tag priorities for inclusion in the metadata tag class, wherein the metadata tags and the associated metadata tag priorities are received as handwritten characters in empty metadata tag cells and counterpart empty metadata tag priority cells within the tag configuration list; associating in a memory on the electronic whiteboard the metadata tag class with the metadata tags and the associated metadata tag priorities; receiving as third touch screen input on the electronic whiteboard an object tagging instruction identifying an object on the electronic whiteboard to be tagged with metadata; displaying, on the electronic whiteboard in response to the object tagging instruction using the associated metadata tag class, metadata tags and metadata tag priorities a hierarchical selection menu including the metadata tag class as a selectable option on a first level and the metadata tags as selectable options on a second level, wherein the metadata tags are ordered on the second level in accordance with the metadata tag priorities; and receiving as fourth touch screen input on the electronic whiteboard a selection from the hierarchical selection menu of one of the metadata tags whereby the identified object is tagged with the metadata. 7. The method of claim 1 , wherein the hierarchical menu is a cascading menu.
| 0.628286 |
10. A method comprising: receiving, by one or more processors of a server, an initial search query from a user device over a communication network; identifying, by the one or more processors of the server, a reference to a first color in the initial search query; determining, by the one or more processors of the server, whether the reference to the first color is intended to identify any actual color; in response to determining that the reference to the first color is not intended to identify an actual color, the one or more processors of the server performing operations comprising: executing the initial search query to obtain a search result; ranking the search result without regard to the reference to the first color; and transmitting a first displayable result of the ranking of the search result to the user device over the communication network; and in response to determining that the reference to the first color is intended to identify the actual color, the one or more processors of the server performing operations comprising: creating a rewritten search query which is different from the initial search query by re-writing the initial search query; executing the rewritten search query to identify a plurality of products based on the rewritten search query; determining one or more products of the plurality of products as being associated with one or more colors identical or similar to the first color; transforming the ranking of the search result comprising: increasing a ranking score associated with each of the one or more products based on similarity between the first color and the one or more colors associated with the each of the one or more products; ranking the plurality of products in the ranking of the search result based on the initial search query and the ranking score associated with each of the one or more products; and transmitting a second displayable result of the ranking of the plurality of products to the user device over the communication network.
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10. A method comprising: receiving, by one or more processors of a server, an initial search query from a user device over a communication network; identifying, by the one or more processors of the server, a reference to a first color in the initial search query; determining, by the one or more processors of the server, whether the reference to the first color is intended to identify any actual color; in response to determining that the reference to the first color is not intended to identify an actual color, the one or more processors of the server performing operations comprising: executing the initial search query to obtain a search result; ranking the search result without regard to the reference to the first color; and transmitting a first displayable result of the ranking of the search result to the user device over the communication network; and in response to determining that the reference to the first color is intended to identify the actual color, the one or more processors of the server performing operations comprising: creating a rewritten search query which is different from the initial search query by re-writing the initial search query; executing the rewritten search query to identify a plurality of products based on the rewritten search query; determining one or more products of the plurality of products as being associated with one or more colors identical or similar to the first color; transforming the ranking of the search result comprising: increasing a ranking score associated with each of the one or more products based on similarity between the first color and the one or more colors associated with the each of the one or more products; ranking the plurality of products in the ranking of the search result based on the initial search query and the ranking score associated with each of the one or more products; and transmitting a second displayable result of the ranking of the plurality of products to the user device over the communication network. 12. The method of claim 10 wherein the determining one or more products of the plurality of products as being associated with one or more colors identical or similar to the first color is based at least in part on a color similarity score determined by a color difference formula, the color similarity score being based on a similarity between the first color and the one or more colors associated with the each of the one or more products.
| 0.649483 |
65. A method comprising: providing a computer-based service over a network to a set of users, wherein the set of users includes a first user and a plurality of second users; receiving, by the computer-based service, from a given user of the plurality of second users, a given expression of interest in being notified about interactions of the first user; receiving, by the computer-based service, an indication of a first interaction of the first user; after receiving the given expression of interest and receiving the indication, sending, by the computer-based service, first information about the first interaction to each user of the plurality of second users, to cause display of the first information in a respective view of each of the plurality of second users; wherein the step of sending the first information includes sending the first information to the given user based, at least in part, on the given expression of interest; wherein the first information includes one or more links that provide access to one or more views that are associated with the first interaction; receiving, by the computer-based service from a particular second user, of the plurality of second users, a comment entered in a particular text entry interface, wherein the particular text entry interface is related to the first information; and in response to receiving the comment, the computer-based service sending the comment, to each user of the plurality of second users other than the particular second user, to enable display of the comment, in relation to the first information, to the each user of the plurality of second users other than the particular second user.
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65. A method comprising: providing a computer-based service over a network to a set of users, wherein the set of users includes a first user and a plurality of second users; receiving, by the computer-based service, from a given user of the plurality of second users, a given expression of interest in being notified about interactions of the first user; receiving, by the computer-based service, an indication of a first interaction of the first user; after receiving the given expression of interest and receiving the indication, sending, by the computer-based service, first information about the first interaction to each user of the plurality of second users, to cause display of the first information in a respective view of each of the plurality of second users; wherein the step of sending the first information includes sending the first information to the given user based, at least in part, on the given expression of interest; wherein the first information includes one or more links that provide access to one or more views that are associated with the first interaction; receiving, by the computer-based service from a particular second user, of the plurality of second users, a comment entered in a particular text entry interface, wherein the particular text entry interface is related to the first information; and in response to receiving the comment, the computer-based service sending the comment, to each user of the plurality of second users other than the particular second user, to enable display of the comment, in relation to the first information, to the each user of the plurality of second users other than the particular second user. 75. The method of claim 65 wherein the first interaction includes interaction with a particular image and the first information includes at least a portion of the particular image.
| 0.719335 |
52. The system according to claim 51 wherein said forward state rule further comprises an antecedent rule part comprising rule nodes representing object states comprising a causes relationship to all object states represented by said rule nodes of a consequent rule part.
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52. The system according to claim 51 wherein said forward state rule further comprises an antecedent rule part comprising rule nodes representing object states comprising a causes relationship to all object states represented by said rule nodes of a consequent rule part. 54. The system according to claim 52 wherein said fact corresponding to said consequent rule part comprises a fact representation status truth value determined by: determining if a true condition exists for an object state corresponding to an antecedent node; returning a degree of probability assigned to said fact representation status of said fact.
| 0.804933 |
1. A navigation system comprising: a user interface configured to receive a location query for a retail location from a location requestor; a control unit, coupled to the user interface, configured to: determine candidate locations for the location query; determine a candidate associated location, specific to each of the candidate locations, based on the frequency the candidate associated location is selected on a device and subsequently traveled to; generate a list of the candidate locations matching the retail location, wherein the list includes the candidate associated location for each of the candidate locations; determine a waypoint destination from an instance of the candidate locations based on a selected instance of the candidate associated location specific to the instance of the candidate locations; and calculate a travel route including the waypoint destination and the selected instance of the candidate associated location for displaying on the device; and calculate a popularity weighing scheme for the selected instance of the candidate associated location based on travel of the location requestor along the travel route to the selected instance of the candidate associated location.
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1. A navigation system comprising: a user interface configured to receive a location query for a retail location from a location requestor; a control unit, coupled to the user interface, configured to: determine candidate locations for the location query; determine a candidate associated location, specific to each of the candidate locations, based on the frequency the candidate associated location is selected on a device and subsequently traveled to; generate a list of the candidate locations matching the retail location, wherein the list includes the candidate associated location for each of the candidate locations; determine a waypoint destination from an instance of the candidate locations based on a selected instance of the candidate associated location specific to the instance of the candidate locations; and calculate a travel route including the waypoint destination and the selected instance of the candidate associated location for displaying on the device; and calculate a popularity weighing scheme for the selected instance of the candidate associated location based on travel of the location requestor along the travel route to the selected instance of the candidate associated location. 2. The system as claimed in claim 1 wherein the control unit is configured calculate the popularity weighing scheme of the selected instance of the candidate associated location based on the frequency the candidate associated location is selected.
| 0.536415 |
1. A speech recognition system for recognizing, as a concatenation of selected ones of first through N-th reference words, an input pattern representing connected words and having a pattern time axis defining first through I-th pattern time instants, where N represents a predetermined natural number and I represents a positive integer dependent on said input pattern, said speech recognition system comprising: first through N-th neural networks representing said first through said N-th reference words and having first through N-th reference time axes, respectively; supply means for supplying said input pattern to said first through said N-th neural networks in compliance with a mapping function mapping each of said first through said N-th reference time axes and said pattern time axis onto each other to make said first through said N-th neural networks produce first through N-th output signals, respectively, said first through said N-th output signals depending on said mapping function and on a plurality of relation functions each of which relates each of said first through said N-th reference words to a portion defined in said input pattern by a plurality of consecutive ones of said first through said I-th pattern time instants; and determining means for determining said selected ones of first through N-th reference words based on optimum ones of said relation functions that maximize summations of said first through said N-th output signals.
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1. A speech recognition system for recognizing, as a concatenation of selected ones of first through N-th reference words, an input pattern representing connected words and having a pattern time axis defining first through I-th pattern time instants, where N represents a predetermined natural number and I represents a positive integer dependent on said input pattern, said speech recognition system comprising: first through N-th neural networks representing said first through said N-th reference words and having first through N-th reference time axes, respectively; supply means for supplying said input pattern to said first through said N-th neural networks in compliance with a mapping function mapping each of said first through said N-th reference time axes and said pattern time axis onto each other to make said first through said N-th neural networks produce first through N-th output signals, respectively, said first through said N-th output signals depending on said mapping function and on a plurality of relation functions each of which relates each of said first through said N-th reference words to a portion defined in said input pattern by a plurality of consecutive ones of said first through said I-th pattern time instants; and determining means for determining said selected ones of first through N-th reference words based on optimum ones of said relation functions that maximize summations of said first through said N-th output signals. 4. A speech recognition system as claimed in claim 1, wherein said mapping function is an inverse function which defines for said j-th signal time instant one of a predetermined number of consecutive ones of said first through said I-th pattern time instants.
| 0.721868 |
8. The address parsing system of claim 7 wherein the universal parsing engine is further arranged to assign penalties when disfavored matches occur in applying the input address to the one or more branches of the parsing tree.
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8. The address parsing system of claim 7 wherein the universal parsing engine is further arranged to assign penalties when disfavored matches occur in applying the input address to the one or more branches of the parsing tree. 9. The address parsing system of claim 8 wherein the universal parsing engine is further arranged to rank the one or more parsing tree branches that include matches based on the assigned penalties.
| 0.916493 |
1. A computer-implemented method comprising: receiving a list of keywords via a data network interface for processing by a processor of a computer system; ordering the list of keywords from high activity to low activity, the high activity corresponding to keywords with a statistically significant number of return on investment (ROI) events, the ROI events corresponding to revenue-generating events; partitioning the list into at least two sets, a head partition including keywords with an activity level above a predefined threshold, a tail partition including the remainder of the keywords in the list; modeling the keywords in the head partition based on a set of variables, the modeling including generating a revenue per click (RPC) value prediction for each of the keywords in the head partition, the RPC value prediction being based on the set of variables, past keyword revenue performance data, and historical bid density by category for each keyword; scoring the keywords in the head partition based on the modeling; and clustering head partition keywords with tail partition keywords having at least one common variable into at least one keyword cluster.
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1. A computer-implemented method comprising: receiving a list of keywords via a data network interface for processing by a processor of a computer system; ordering the list of keywords from high activity to low activity, the high activity corresponding to keywords with a statistically significant number of return on investment (ROI) events, the ROI events corresponding to revenue-generating events; partitioning the list into at least two sets, a head partition including keywords with an activity level above a predefined threshold, a tail partition including the remainder of the keywords in the list; modeling the keywords in the head partition based on a set of variables, the modeling including generating a revenue per click (RPC) value prediction for each of the keywords in the head partition, the RPC value prediction being based on the set of variables, past keyword revenue performance data, and historical bid density by category for each keyword; scoring the keywords in the head partition based on the modeling; and clustering head partition keywords with tail partition keywords having at least one common variable into at least one keyword cluster. 5. The method as claimed in claim 1 wherein the set of variables include pop culture variables.
| 0.568302 |
27. A system for responding to a query initiated at a user device, comprising: one or more data stores having a knowledge base stored therein that includes data representing first knowledge about a plurality of objects using a plurality of relationships among the objects, wherein selected ones of the objects are associated with class objects identifying corresponding classes for the selected objects using class member objects that define class member relationships between the selected objects and the corresponding classes; and one or more computing devices configured to generate a response to the query using second knowledge not statically stored or represented in the at least one knowledge base prior to receipt of the query, the second knowledge being generated by inference from the first knowledge in response to the query, the inference including retrieving one or more first facts included in the first knowledge, the first facts corresponding to first ones of the objects and first ones of the relationships, and generating one or more second facts from the first facts that express at least one new relationship for at least one of the one or more first objects.
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27. A system for responding to a query initiated at a user device, comprising: one or more data stores having a knowledge base stored therein that includes data representing first knowledge about a plurality of objects using a plurality of relationships among the objects, wherein selected ones of the objects are associated with class objects identifying corresponding classes for the selected objects using class member objects that define class member relationships between the selected objects and the corresponding classes; and one or more computing devices configured to generate a response to the query using second knowledge not statically stored or represented in the at least one knowledge base prior to receipt of the query, the second knowledge being generated by inference from the first knowledge in response to the query, the inference including retrieving one or more first facts included in the first knowledge, the first facts corresponding to first ones of the objects and first ones of the relationships, and generating one or more second facts from the first facts that express at least one new relationship for at least one of the one or more first objects. 29. The system of claim 27 wherein the one or more computing devices are further configured generate a plurality of query candidates for presentation at the user device in response to the query.
| 0.650576 |
23. A pen based computer system for interaction with pre-printed material comprising: a processor; a memory coupled to said processor and for storing audio content that is associated with positions of printed material; an optical detector coupled to said processor; said processor for receiving input from said optical detector to determine a position of said pen based computer system over printed material comprising a position code responsive to an interaction of said pen based computer system and said printed material; an audio transducer for producing audio output under control of said processor; wherein said pen based computer system is capable of producing audio output corresponding to said position contemporaneously with said interaction, and wherein said audio output further corresponds with other positions that were not previously determined by said pen based computer system.
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23. A pen based computer system for interaction with pre-printed material comprising: a processor; a memory coupled to said processor and for storing audio content that is associated with positions of printed material; an optical detector coupled to said processor; said processor for receiving input from said optical detector to determine a position of said pen based computer system over printed material comprising a position code responsive to an interaction of said pen based computer system and said printed material; an audio transducer for producing audio output under control of said processor; wherein said pen based computer system is capable of producing audio output corresponding to said position contemporaneously with said interaction, and wherein said audio output further corresponds with other positions that were not previously determined by said pen based computer system. 25. The pen based computer system of claim 23 wherein said audio output comprises non word sounds corresponding to graphic images printed at said position.
| 0.536103 |
13. The computer-readable medium of claim 12 , wherein the operations further comprise: selecting the negative keywords to increase a number of search criteria identified as being off-topic to the advertisement item.
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13. The computer-readable medium of claim 12 , wherein the operations further comprise: selecting the negative keywords to increase a number of search criteria identified as being off-topic to the advertisement item. 14. The computer-readable medium of claim 13 , wherein selecting the negative keywords to increase the number of search criteria identified as being off-topic to the advertisement item maximizes the number of search criteria identified as being off-topic to the advertisement item.
| 0.894029 |
12. The method of claim 11 , wherein the one or more hits are received in a search result list, and wherein the hit visibility score is derived based on a position of the one or more hits in the search result list.
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12. The method of claim 11 , wherein the one or more hits are received in a search result list, and wherein the hit visibility score is derived based on a position of the one or more hits in the search result list. 14. The method of claim 12 , wherein the hit visibility score is derived by inserting the position of the corresponding hit in a positional visibility function.
| 0.905926 |
1. A method for processing semi-conductor manufacturing data comprising: capturing files from a plurality of manufacturing data sites having semi-conductor manufacturing data; the semi-conductor manufacturing data including test data; the test data indicating electrical characteristics; converting the files into a standard format for storage in a database; building a query from a client device using a plurality of sets of selections, wherein when a first selection is made by the client device in a first set of the sets of selections, a second set of the sets of selections is dynamically changed to only display a displayed set of selections on the client device limited to selections associated with the first selection; checking limits of the test data of the semi-conductor manufacturing data by accessing the database and comparing the test data of the semi-conductor manufacturing data stored in the database with limits therefor; a portion of the limits being user defined limits including a parameter limit associated with the electrical characteristics, the parameter limit being for threshold voltage; alerting the client device, when any stored semi-conductor manufacturing data exceeds one or more limit of the portion of the limits; and generating a report for the client device based on the built query and the converted files stored in the database.
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1. A method for processing semi-conductor manufacturing data comprising: capturing files from a plurality of manufacturing data sites having semi-conductor manufacturing data; the semi-conductor manufacturing data including test data; the test data indicating electrical characteristics; converting the files into a standard format for storage in a database; building a query from a client device using a plurality of sets of selections, wherein when a first selection is made by the client device in a first set of the sets of selections, a second set of the sets of selections is dynamically changed to only display a displayed set of selections on the client device limited to selections associated with the first selection; checking limits of the test data of the semi-conductor manufacturing data by accessing the database and comparing the test data of the semi-conductor manufacturing data stored in the database with limits therefor; a portion of the limits being user defined limits including a parameter limit associated with the electrical characteristics, the parameter limit being for threshold voltage; alerting the client device, when any stored semi-conductor manufacturing data exceeds one or more limit of the portion of the limits; and generating a report for the client device based on the built query and the converted files stored in the database. 3. The method of claim 1 wherein the altering includes sending an email to an email client on the client device.
| 0.578558 |
3. The method of claim 1 , further comprising: sorting the one or more matched fields according to the determined aggregate weights; at least partially forming one or more search tables corresponding to the one or more search values; and at least partially forming one or more base tables corresponding to the one or more fields of the plurality of records of the linked hierarchical database; and wherein the merging, based at least in part on determining the aggregate weights, comprises combining at least a portion of the one or more search tables and the one or more base tables to form the merged table.
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3. The method of claim 1 , further comprising: sorting the one or more matched fields according to the determined aggregate weights; at least partially forming one or more search tables corresponding to the one or more search values; and at least partially forming one or more base tables corresponding to the one or more fields of the plurality of records of the linked hierarchical database; and wherein the merging, based at least in part on determining the aggregate weights, comprises combining at least a portion of the one or more search tables and the one or more base tables to form the merged table. 4. The method of claim 3 , wherein at least partially forming the one or more base tables comprises at least partially forming tables having multiple fields and wherein the base tables comprise record identifiers for each entity in the hierarchy and wherein the method further comprises sorting each entity in the hierarchy by an associated hierarchy level, wherein the sorting each entity in the hierarchy by the associated hierarchy level comprises progressively sorting each entity in the hierarchy by each hierarchy level from a highest level to a lowest level in the hierarchy.
| 0.871075 |
12. The method of claim 7 , wherein the classifying comprises: measuring a distance between the vector-space projection and a vector-space measurement at each node of the plurality of nodes for at least a portion of the plurality of levels; determining a placement of the transformed human-capital information into the family node based on the measured distance.
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12. The method of claim 7 , wherein the classifying comprises: measuring a distance between the vector-space projection and a vector-space measurement at each node of the plurality of nodes for at least a portion of the plurality of levels; determining a placement of the transformed human-capital information into the family node based on the measured distance. 14. The method of claim 12 , the method comprising: wherein, for each of the plurality of levels, each node of the plurality of nodes comprises a plurality of node attributes, each node attribute of the plurality of node attributes having associated therewith a bit flag; wherein the bit flag comprises performance-optimization information regarding one or more siblings of the node; and via the performance-optimization information, determining that the one or more siblings need not be measured in the measuring responsive to a condition for action being satisfied.
| 0.804326 |
13. A tangible computer readable storage device storing instructions, which, when executed by a processor, cause the processor to perform a process comprising: receiving, at a computer processor, an archive of video data from which a plurality of archive descriptor types are extracted; applying, using the computer processor, a query to the archive, the query comprising a number of N query descriptor types for a query object; determining, using the computer processor, a difference between each query descriptor type and corresponding descriptor types of track segments in the archive, and storing the differences in one or more vectors; storing each vector of differences in a computer storage medium as a point in an N dimensional space; and identifying, using the computer processor, an archive object that is similar to the query object as a function of proximities of the differences to an origin in one or more dimensions of the N dimensional space.
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13. A tangible computer readable storage device storing instructions, which, when executed by a processor, cause the processor to perform a process comprising: receiving, at a computer processor, an archive of video data from which a plurality of archive descriptor types are extracted; applying, using the computer processor, a query to the archive, the query comprising a number of N query descriptor types for a query object; determining, using the computer processor, a difference between each query descriptor type and corresponding descriptor types of track segments in the archive, and storing the differences in one or more vectors; storing each vector of differences in a computer storage medium as a point in an N dimensional space; and identifying, using the computer processor, an archive object that is similar to the query object as a function of proximities of the differences to an origin in one or more dimensions of the N dimensional space. 20. The tangible computer readable storage device of claim 13 , comprising instructions which when executed by a processor perform a process comprising: receiving feedback from a user; and re-weighting dimensions in the N-dimensional space based on the feedback from the user.
| 0.573962 |
2. The control system of claim 1 , wherein the display image includes an overhead space diagram of a room that includes a location of the autonomous robot and respective locations of the candidate target objects.
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2. The control system of claim 1 , wherein the display image includes an overhead space diagram of a room that includes a location of the autonomous robot and respective locations of the candidate target objects. 6. The control system of claim 2 , further comprising: the autonomous robot, wherein the autonomous robot includes in the recognition information space information regarding a space diagram of the room, and object images of the candidate target objects.
| 0.744849 |
13. A computer-implemented people matching system, comprising one or more processor-based devices configured to execute: an inference function that infers a mutual interest between a first person who is a first user of the computer-implemented system and a second person who is a second user of the computer-implemented system; a recommendation-generating function that generates a recommendation comprising a representation of the second person for delivery to the first person, wherein the recommendation is generated based on the inference of mutual interest; a first expression of interest function that delivers a first expression of interest that is in response to the recommendation from the first person to the second person, wherein the first expression of interest comprises the first person explicitly expressing an interest in establishing a computer-implemented relationship with the second person; and a second expression of interest function that delivers a second expression of interest that is in response to the first expression of interest, wherein the second expression of interest comprises the second person establishing the computer-implemented relationship between the first person and the second person, wherein the computer-implemented relationship comprises a subscribing relationship that delivers content authored by the second person to the first person.
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13. A computer-implemented people matching system, comprising one or more processor-based devices configured to execute: an inference function that infers a mutual interest between a first person who is a first user of the computer-implemented system and a second person who is a second user of the computer-implemented system; a recommendation-generating function that generates a recommendation comprising a representation of the second person for delivery to the first person, wherein the recommendation is generated based on the inference of mutual interest; a first expression of interest function that delivers a first expression of interest that is in response to the recommendation from the first person to the second person, wherein the first expression of interest comprises the first person explicitly expressing an interest in establishing a computer-implemented relationship with the second person; and a second expression of interest function that delivers a second expression of interest that is in response to the first expression of interest, wherein the second expression of interest comprises the second person establishing the computer-implemented relationship between the first person and the second person, wherein the computer-implemented relationship comprises a subscribing relationship that delivers content authored by the second person to the first person. 14. The system of claim 13 , further comprising: the inference function that infers the mutual interest, wherein the mutual interest is inferred by the inference function from a plurality of usage behaviors, wherein one of the plurality of usage behaviors is performed by the first person and one of the plurality of usage behaviors is performed by the second person.
| 0.645614 |
1. A computer-implemented method for searching for information on a network in response to an image query sent by a user, comprising: under control of one or more computer systems configured with executable instructions, receiving an image query sent from a mobile communications device, the image query including at least one image taken using a camera of the mobile communications device; processing the at least one image to detect any text present in the at least one image and to determine geometry information pertaining to the text, the geometry information including at least one of position and geometry information for the text in the at least one image; automatically recognizing the text from at least one portion of the at least one image corresponding to the geometry information of the image; determining matches for the detected text in at least one domain database on the network, the at least one domain database selected based at least in part upon the image query by; removing words in the text that are not present in a pre-identified dictionary; performing an N-gram match by counting a number of N-grams in common between the text and each field of every entry in the at least one domain database, the at least one domain database being selected from various domain databases; normalizing a count of the matching N-grams to return a score for each field of every entry in the at least one domain database; determining weighted combinations of the scores from multiple fields to compute a final score for every entry in the at least one domain database; ranking entries in the at least one domain database based on the final scores; and retrieving relevant information for one or more top-ranked entries in the at least one domain database; and sending one or more of the identified matches to the mobile device for display to the user.
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1. A computer-implemented method for searching for information on a network in response to an image query sent by a user, comprising: under control of one or more computer systems configured with executable instructions, receiving an image query sent from a mobile communications device, the image query including at least one image taken using a camera of the mobile communications device; processing the at least one image to detect any text present in the at least one image and to determine geometry information pertaining to the text, the geometry information including at least one of position and geometry information for the text in the at least one image; automatically recognizing the text from at least one portion of the at least one image corresponding to the geometry information of the image; determining matches for the detected text in at least one domain database on the network, the at least one domain database selected based at least in part upon the image query by; removing words in the text that are not present in a pre-identified dictionary; performing an N-gram match by counting a number of N-grams in common between the text and each field of every entry in the at least one domain database, the at least one domain database being selected from various domain databases; normalizing a count of the matching N-grams to return a score for each field of every entry in the at least one domain database; determining weighted combinations of the scores from multiple fields to compute a final score for every entry in the at least one domain database; ranking entries in the at least one domain database based on the final scores; and retrieving relevant information for one or more top-ranked entries in the at least one domain database; and sending one or more of the identified matches to the mobile device for display to the user. 2. The method of claim 1 , wherein the network includes a plurality of domain databases, and wherein the image query further comprises a text query portion along with the image, the text query portion including information corresponding to one of the plurality of domain databases.
| 0.508607 |
1. A method for obtaining representative text items from a plurality of text items in computer tasks, the method comprising: receiving first information indicative of a first computer task, the first information including a first plurality of text items; determining a genre associated with the first computer task; determining first representative location information of the genre based on a first frequency of occurrence of identical text associated with the first representative location information in the genre; for each of the first plurality of text items, assigning a first weight with a first magnitude, the first magnitude being determined based on the genre and the first representative location information; ranking the first plurality of text items based on the first weight assigned to each of the first plurality of text items to produce a first plurality of ranked text items; generating and storing first representative text items based on the first plurality of ranked text items; wherein the first computer task is a task other than entering search terms for the purpose of retrieving information; receiving second information indicative of a second computer task, the second computer task being different than the first computer task, the second information including a second plurality of text items, wherein the second plurality of text items is different than the first plurality of text items; determining second representative location information of the genre based on a second frequency of occurrence of identical text associated with the second representative location information; for each of the second plurality of text items, assigning a second weight with a second magnitude that is determined based on the genre and the second representative location information, the second magnitude being different than the first magnitude; ranking the second plurality of text items based on the second weight assigned to each of the second plurality of text items to produce a second plurality of ranked text items; and generating and storing second representative text items based on the second plurality of ranked text items; wherein the second computer task is a task other than entering search terms for the purpose of retrieving information.
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1. A method for obtaining representative text items from a plurality of text items in computer tasks, the method comprising: receiving first information indicative of a first computer task, the first information including a first plurality of text items; determining a genre associated with the first computer task; determining first representative location information of the genre based on a first frequency of occurrence of identical text associated with the first representative location information in the genre; for each of the first plurality of text items, assigning a first weight with a first magnitude, the first magnitude being determined based on the genre and the first representative location information; ranking the first plurality of text items based on the first weight assigned to each of the first plurality of text items to produce a first plurality of ranked text items; generating and storing first representative text items based on the first plurality of ranked text items; wherein the first computer task is a task other than entering search terms for the purpose of retrieving information; receiving second information indicative of a second computer task, the second computer task being different than the first computer task, the second information including a second plurality of text items, wherein the second plurality of text items is different than the first plurality of text items; determining second representative location information of the genre based on a second frequency of occurrence of identical text associated with the second representative location information; for each of the second plurality of text items, assigning a second weight with a second magnitude that is determined based on the genre and the second representative location information, the second magnitude being different than the first magnitude; ranking the second plurality of text items based on the second weight assigned to each of the second plurality of text items to produce a second plurality of ranked text items; and generating and storing second representative text items based on the second plurality of ranked text items; wherein the second computer task is a task other than entering search terms for the purpose of retrieving information. 16. The method of claim 1 , wherein assigning the first weight is based on a user's role in an organization.
| 0.560374 |
7. One or more computing devices comprising: one or more processors; and memory storing computer-readable instructions that, when executed by the one or more processors, cause the one or more processors to: receive a first audio signal representing first user speech; identify a first intent associated with a first activity of a first set of activities based at least in part on the first audio signal; identify a second intent associated with a second activity of the first set of activities based at least in part on the first audio signal; identifying a third intent associated with a third activity of a second set of activities based at least in part on the first audio signal; send a second audio signal representing a first question associated with the first set of activities and the second set of activities; receive a third audio signal representing second user speech; select the first set of activities based at least in part on the third audio signal; send, based at least in part on the first activity and the second activity, a fourth audio signal representing a second question for at least one additional piece of information; receive a fifth audio signal representing third user speech; and select the first activity from the first set of activities based at least in part on the fifth audio signal.
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7. One or more computing devices comprising: one or more processors; and memory storing computer-readable instructions that, when executed by the one or more processors, cause the one or more processors to: receive a first audio signal representing first user speech; identify a first intent associated with a first activity of a first set of activities based at least in part on the first audio signal; identify a second intent associated with a second activity of the first set of activities based at least in part on the first audio signal; identifying a third intent associated with a third activity of a second set of activities based at least in part on the first audio signal; send a second audio signal representing a first question associated with the first set of activities and the second set of activities; receive a third audio signal representing second user speech; select the first set of activities based at least in part on the third audio signal; send, based at least in part on the first activity and the second activity, a fourth audio signal representing a second question for at least one additional piece of information; receive a fifth audio signal representing third user speech; and select the first activity from the first set of activities based at least in part on the fifth audio signal. 10. One or more computing devices as recited in claim 7 , wherein sending the second audio signal is based at least in part on determining that the first intent does not include information sufficient for performing the first activity from the first set of activities.
| 0.663332 |
3. The method recited in claim 1 , further comprising associating metadata with the one or more objects.
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3. The method recited in claim 1 , further comprising associating metadata with the one or more objects. 4. The method recited in claim 3 , wherein the preliminary relevance is determined at least in part based on the metadata.
| 0.959619 |
18. The method of claim 1 , wherein non-linearity of said non-linear transformation is characterized by a parameter non-linearity having a single numerical value.
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18. The method of claim 1 , wherein non-linearity of said non-linear transformation is characterized by a parameter non-linearity having a single numerical value. 19. The method of claim 18 , wherein the step (a) comprises introducing two or more patent indices, and said non-linear transformation is characterized by a single parameter of non-linearity selected so that a variation of the parameter of non-linearity preserves relative contributions of said patent indices in said Patent Quality index.
| 0.925826 |
1. A document-based system for acquiring information pertaining to a document, comprising: a computer having a memory storing a meta-document including the document, the document including content information, and a set of one or more document service requests based on a personality associated with the document, wherein a personality comprises a theme or context, wherein each document service request in the set comprises a process for using a portion of the document's content information as a starting point to obtain other information from a service provider pertaining to the document's content information, wherein associating a set of one or more document service requests based on a different personality to the document's content information will provide different results; and a scheduler for autonomously activating and managing the document service requests without user intervention by periodically polling the meta-document for document service requests, for selecting a document service request from the set of one or more document service requests, for initiating and managing communication with a selected service provider to satisfy the selected document service request and for integrating any results from the selected document service request into the meta-document, wherein the meta-document includes the document, the set of one or more document service requests and integrated results; wherein the set of one or more document service requests follow a sequence of calls to service providers for extracting information from one or more of other documents, databases and data stores, and for searching for other information responsive to any extracted information from the one or more of other documents, databases and data stores.
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1. A document-based system for acquiring information pertaining to a document, comprising: a computer having a memory storing a meta-document including the document, the document including content information, and a set of one or more document service requests based on a personality associated with the document, wherein a personality comprises a theme or context, wherein each document service request in the set comprises a process for using a portion of the document's content information as a starting point to obtain other information from a service provider pertaining to the document's content information, wherein associating a set of one or more document service requests based on a different personality to the document's content information will provide different results; and a scheduler for autonomously activating and managing the document service requests without user intervention by periodically polling the meta-document for document service requests, for selecting a document service request from the set of one or more document service requests, for initiating and managing communication with a selected service provider to satisfy the selected document service request and for integrating any results from the selected document service request into the meta-document, wherein the meta-document includes the document, the set of one or more document service requests and integrated results; wherein the set of one or more document service requests follow a sequence of calls to service providers for extracting information from one or more of other documents, databases and data stores, and for searching for other information responsive to any extracted information from the one or more of other documents, databases and data stores. 9. The system of claim 1 , wherein the meta-document, the scheduler and the service providers reside at different locations.
| 0.529915 |
9. A method, comprising acts of: recognizing text in an image, the text of a first language written in a first direction; translating the text of the first language into text of a second language; aligning the text between the first language and the second language; visually overlaying the text of the second language on top of the text of the first language, the text of the second language is selectively presented vertically or horizontally according to a direction in which the second language is written; and configuring a processor to execute instructions related to at least one of the acts of recognizing, translating, aligning, or visually overlaying.
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9. A method, comprising acts of: recognizing text in an image, the text of a first language written in a first direction; translating the text of the first language into text of a second language; aligning the text between the first language and the second language; visually overlaying the text of the second language on top of the text of the first language, the text of the second language is selectively presented vertically or horizontally according to a direction in which the second language is written; and configuring a processor to execute instructions related to at least one of the acts of recognizing, translating, aligning, or visually overlaying. 16. The method of claim 9 , further comprising performing the acts of recognizing, translating, aligning, and visually overlaying, in realtime during a video mode of a camera.
| 0.785442 |
2. The computer implemented method of claim 1 , wherein, in the recognizing step, the operations occurring on the operating system are expressed as a context layer that expresses the contexts, and the operations are defined by an object layer, an object handle layer, and an operation layer, which are located under the context layer.
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2. The computer implemented method of claim 1 , wherein, in the recognizing step, the operations occurring on the operating system are expressed as a context layer that expresses the contexts, and the operations are defined by an object layer, an object handle layer, and an operation layer, which are located under the context layer. 3. The computer implemented method of claim 2 , wherein the associations between the contexts are defined in a context association layer.
| 0.92001 |
133. A system for selectable input based on motion of a pointing device in relation to an region, comprising: means for tracking the motion of the pointing device in relation to the region; a determined device path, comprising a plurality of positions and corresponding times, based upon the tracked motion; a comparison of subsequent positions and corresponding times to path data; means for detecting subsequent positions which meet at least one threshold of a selected position within the region; means for sequential entry of each of the selected positions which correspond to a selection; logic for determining a distance between a current location of the pointing device and selectable positions within the region; logic for determining a selectable position which is closest to the current location of the pointing device; and a highlight corresponding to the determined closest selectable position.
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133. A system for selectable input based on motion of a pointing device in relation to an region, comprising: means for tracking the motion of the pointing device in relation to the region; a determined device path, comprising a plurality of positions and corresponding times, based upon the tracked motion; a comparison of subsequent positions and corresponding times to path data; means for detecting subsequent positions which meet at least one threshold of a selected position within the region; means for sequential entry of each of the selected positions which correspond to a selection; logic for determining a distance between a current location of the pointing device and selectable positions within the region; logic for determining a selectable position which is closest to the current location of the pointing device; and a highlight corresponding to the determined closest selectable position. 134. The system of claim 133 , wherein the highlight comprises any of a display and a magnification of the determined closest selectable position.
| 0.714328 |
6. The apparatus as recited in claim 5, wherein the one application program comprises a plurality of application threads, each of the plurality of application threads running independently of other application threads and comprising means for instantiating a view object in the storage.
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6. The apparatus as recited in claim 5, wherein the one application program comprises a plurality of application threads, each of the plurality of application threads running independently of other application threads and comprising means for instantiating a view object in the storage. 7. The apparatus as recited in claim 6, further comprising a view system monitor object and means in each of the plurality of application threads for acquiring and releasing the view system monitor object to prevent the application threads from simultaneously accessing the view hierarchy structure of the one application program.
| 0.914603 |
21. A method, comprising: discovering one or more storage area network (SAN) components of a SAN; monitoring the discovered SAN components; providing the SAN discovery information and SAN monitoring information to a centralized SAN management user interface; and managing the SAN from the centralized SAN management user interface using the provided SAN discovery information and the provided SAN monitoring information, wherein said managing the SAN comprises performing one or more SAN management tasks in response to interactions of the user interface, and wherein said managing the SAN comprises managing the discovered one or more SAN components.
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21. A method, comprising: discovering one or more storage area network (SAN) components of a SAN; monitoring the discovered SAN components; providing the SAN discovery information and SAN monitoring information to a centralized SAN management user interface; and managing the SAN from the centralized SAN management user interface using the provided SAN discovery information and the provided SAN monitoring information, wherein said managing the SAN comprises performing one or more SAN management tasks in response to interactions of the user interface, and wherein said managing the SAN comprises managing the discovered one or more SAN components. 24. The method as recited in claim 21 , further comprising displaying representations of discovered SAN components on the centralized SAN management user interface.
| 0.834041 |
11. A non-transitory computer readable recording medium, storing a plurality of program codes, wherein when the program codes are loaded into a processor, the processor executes the program codes to accomplish following steps: transforming a first input voice from a voice receiver into an input sentence according to a grammar rule; determining whether the input sentence is the same as a learning sentence displayed on a display; and when the input sentence is different from the learning sentence, generating an ancillary information comprising at least one error word in the input sentence that is different from the learning sentence, wherein the step of transforming the first input voice from the voice receiver into the input sentence according to the grammar rule comprises: obtaining, based on the first input voice, a first phoneme sequence, wherein the first phoneme sequence represents a pronunciation of the entire first input voice; and obtaining, based on the entire first phoneme sequence, the input sentence according to the grammar rule, wherein the step of determining whether the input sentence is the same as the learning sentence displayed on the display comprises: obtaining, based on the input sentence, a second phoneme sequence, wherein the second phoneme sequence represents a pronunciation of the entire input sentence; determining whether the second phoneme sequence is the same as a standard phoneme sequence corresponding to the learning sentence; and determining whether the input sentence is different from the learning sentence when the second phoneme sequence is different from the standard phoneme sequence, wherein the step of generating the ancillary information comprising the at least one error word in the input sentence that is different from the learning sentence comprises: dividing the input sentence into at least one phrase according to a grammar format of the learning sentence; and generating the ancillary information in unit of the at least one phrase, wherein the ancillary information comprises the at least one error word and at least one phoneme of a standard phoneme sequence corresponding to the learning sentence, wherein the at least one phoneme is pronounced incorrectly and corresponded to the at least one error word, wherein the learning sentence comprises a plurality of words, and the standard phoneme sequence compliant with a grammatical structure of the learning sentence is determined according to positions of the plurality of words in the learning sentence, wherein the ancillary information further comprises a suggestion indicating to practice a pronunciation of at least two adjacent words of a specific phrase which conforms to a specific phrase structure recorded in a grammar database, wherein the at least two adjacent words comprises one of the at least one error word.
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11. A non-transitory computer readable recording medium, storing a plurality of program codes, wherein when the program codes are loaded into a processor, the processor executes the program codes to accomplish following steps: transforming a first input voice from a voice receiver into an input sentence according to a grammar rule; determining whether the input sentence is the same as a learning sentence displayed on a display; and when the input sentence is different from the learning sentence, generating an ancillary information comprising at least one error word in the input sentence that is different from the learning sentence, wherein the step of transforming the first input voice from the voice receiver into the input sentence according to the grammar rule comprises: obtaining, based on the first input voice, a first phoneme sequence, wherein the first phoneme sequence represents a pronunciation of the entire first input voice; and obtaining, based on the entire first phoneme sequence, the input sentence according to the grammar rule, wherein the step of determining whether the input sentence is the same as the learning sentence displayed on the display comprises: obtaining, based on the input sentence, a second phoneme sequence, wherein the second phoneme sequence represents a pronunciation of the entire input sentence; determining whether the second phoneme sequence is the same as a standard phoneme sequence corresponding to the learning sentence; and determining whether the input sentence is different from the learning sentence when the second phoneme sequence is different from the standard phoneme sequence, wherein the step of generating the ancillary information comprising the at least one error word in the input sentence that is different from the learning sentence comprises: dividing the input sentence into at least one phrase according to a grammar format of the learning sentence; and generating the ancillary information in unit of the at least one phrase, wherein the ancillary information comprises the at least one error word and at least one phoneme of a standard phoneme sequence corresponding to the learning sentence, wherein the at least one phoneme is pronounced incorrectly and corresponded to the at least one error word, wherein the learning sentence comprises a plurality of words, and the standard phoneme sequence compliant with a grammatical structure of the learning sentence is determined according to positions of the plurality of words in the learning sentence, wherein the ancillary information further comprises a suggestion indicating to practice a pronunciation of at least two adjacent words of a specific phrase which conforms to a specific phrase structure recorded in a grammar database, wherein the at least two adjacent words comprises one of the at least one error word. 12. The computer readable recording medium according to claim 11 , wherein the step of determining whether the second phoneme sequence is the same as the standard phoneme sequence corresponding to the learning sentence comprises: comparing the second phoneme sequence with the standard phoneme sequence by using a dynamic time warping (DTW) algorithm; and determining whether the second phoneme sequence is the same as the standard phoneme sequence according to a comparison result of the DTW algorithm.
| 0.549564 |
11. A user-interface system for incrementally providing fully qualified links to a set of relevant search engines, the system comprising: a catalog in computer readable format including a set of search engines identities, each of at least a plurality of search engines being associated with at least one descriptive category to which the subject matter of the corresponding search engine relates; computer memory comprising instructions in computer readable form that when executed cause a computer system to: receive a partial search query entered on a keypad by a user; infer, after at least one keypress received from the user, a set of potential full queries intended by the user, wherein the set of potential full queries is inferred by determining suggested query refinements based at least in part on the partial search query; select a subset of the identified search engines that are relevant to at least one of the set of inferred full queries based on comparing the inferred full queries with the descriptive categories associated with the search engines; and provide, for each of the selected search engines, a fully qualified link designed to directly launch a search for a relevant query using the search engine.
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11. A user-interface system for incrementally providing fully qualified links to a set of relevant search engines, the system comprising: a catalog in computer readable format including a set of search engines identities, each of at least a plurality of search engines being associated with at least one descriptive category to which the subject matter of the corresponding search engine relates; computer memory comprising instructions in computer readable form that when executed cause a computer system to: receive a partial search query entered on a keypad by a user; infer, after at least one keypress received from the user, a set of potential full queries intended by the user, wherein the set of potential full queries is inferred by determining suggested query refinements based at least in part on the partial search query; select a subset of the identified search engines that are relevant to at least one of the set of inferred full queries based on comparing the inferred full queries with the descriptive categories associated with the search engines; and provide, for each of the selected search engines, a fully qualified link designed to directly launch a search for a relevant query using the search engine. 14. The system of claim 11 , the computer memory further comprising instructions that cause the computer system to present at least one of the inferred potential full queries to the user.
| 0.632242 |
11. The system of claim 8 , wherein clustering module further comprises a clique module to identify a largest clique in the single product graph, the largest clique comprising a largest combined graph pattern obtainable from the merger input graph patterns of the selected pair of merger inputs; the clustering module configured to use a size of the largest clique to determine if the selected pair of merger inputs comprise sufficient structural similarities.
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11. The system of claim 8 , wherein clustering module further comprises a clique module to identify a largest clique in the single product graph, the largest clique comprising a largest combined graph pattern obtainable from the merger input graph patterns of the selected pair of merger inputs; the clustering module configured to use a size of the largest clique to determine if the selected pair of merger inputs comprise sufficient structural similarities. 12. The system of claim 11 , wherein clustering module is further configured to: identify a plurality of candidate combined graph patterns obtainable from the merger input graph patterns if the largest combined graph pattern exceeds a predetermined size, each candidate combined graph pattern smaller than the largest combined graph pattern and representing a unique overlapping of the merger input graph patterns; associate a search cost optimization realization level with each candidate combined graph pattern; select the candidate combined graph pattern representing a most cost effective balance of merger input graph pattern overlap and search cost optimization realization level; and use the selected candidate combined graph pattern to generate the optimized query set.
| 0.760216 |
1. A method comprising: establishing, via at least one host server, a video conference session between a plurality of meeting clients, each meeting client comprising a computing device that communicates via a network with the at least one host server and computing devices of other meeting clients; establishing a presenter for the video conference session, the presenter comprising at least one of the meeting clients; providing audio and video content generated from the presenter to other meeting clients within a base room of the video conference session, wherein the presenter provides audio content to the base room in a first language; assigning a sub-presenter to a private room associated with the video conference session; providing audio and video content generated from the presenter to the sub-presenter; facilitating control of audio and video content provided to the private room by the sub-presenter, wherein the sub-presenter generates and provides audio content along with video content generated from the presenter to the private room, the audio content generated by the sub-presenter comprising an audio broadcast of a translation of the audio content in the first language into a second language, wherein the facilitating control of the audio and video content provided to the private room by the sub-presenter comprises: facilitating control by the sub-presenter of a time lag for the video content provided in the private room by providing the sub-presenter with a graphical user interface that allows the sub-presenter to perform at least one of pausing, slowing down and speeding up of the video content generated from the presenter to allow the sub-presenter to sync the video content with the audio content translated into the second language and being provided to the private room; and in response to at least one meeting client selecting a translation of the audio content from the presenter and in the first language into the second language, assigning the at least one meeting client selecting the second language in which to receive audio content to the private room such that the at least one meeting client receives audio and video content from the sub-presenter.
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1. A method comprising: establishing, via at least one host server, a video conference session between a plurality of meeting clients, each meeting client comprising a computing device that communicates via a network with the at least one host server and computing devices of other meeting clients; establishing a presenter for the video conference session, the presenter comprising at least one of the meeting clients; providing audio and video content generated from the presenter to other meeting clients within a base room of the video conference session, wherein the presenter provides audio content to the base room in a first language; assigning a sub-presenter to a private room associated with the video conference session; providing audio and video content generated from the presenter to the sub-presenter; facilitating control of audio and video content provided to the private room by the sub-presenter, wherein the sub-presenter generates and provides audio content along with video content generated from the presenter to the private room, the audio content generated by the sub-presenter comprising an audio broadcast of a translation of the audio content in the first language into a second language, wherein the facilitating control of the audio and video content provided to the private room by the sub-presenter comprises: facilitating control by the sub-presenter of a time lag for the video content provided in the private room by providing the sub-presenter with a graphical user interface that allows the sub-presenter to perform at least one of pausing, slowing down and speeding up of the video content generated from the presenter to allow the sub-presenter to sync the video content with the audio content translated into the second language and being provided to the private room; and in response to at least one meeting client selecting a translation of the audio content from the presenter and in the first language into the second language, assigning the at least one meeting client selecting the second language in which to receive audio content to the private room such that the at least one meeting client receives audio and video content from the sub-presenter. 5. The method of claim 1 , further comprising: establishing a second presenter for the video conference session, the second presenter comprising at least one of the meeting clients; providing audio and video content generated from the second presenter to other meeting clients within the base room of the video conference session, wherein the second presenter provides audio content to the base room in a third language; and providing audio content to the at least one meeting client in the second language during the ongoing video conference session, wherein the audio content in the second language comprises a translation of the audio content in the third language.
| 0.665165 |
1. A system to generate a video comprising a plurality of scenes comprising: a database having a set of storage devices to hold a set of data records to form a plurality of search corpora, at least a portion of the search corpora accessible based on a user credential; one or more processors corresponding to a plurality of processing entities associated with respective portions of program memory; a memory segment being accessible by an address provided by one or more concurrently executing processing entities; a processor that executes a sequence of instructions which, when executed by the processor causes the processor to execute a process, the process comprising: analyzing information from the portion of the search corpora or from a second search corpus to determine at least one attribute pertaining to the information; executing a rule corresponding to a node of a decision graph, each node comprising one or more selected from a group consisting of: a scene name, a scene indication, an audience description, a template description, and any combination thereof; detecting a scene condition of a scene based on execution of the rule corresponding to the node of the decision graph; generating the scene, the scene comprising information included in the portion of the search corpora; evaluating the scene condition of the scene, the scene condition based at least in part on the attribute; determining a content of a next scene of the plurality of scenes based at least in part on a value obtained by evaluating the scene condition; determining an additional scene should not be generated based on the scene condition of the scene; accessing a second portion of the search corpora accessible based on the scene condition of another scene, the second portion of the search corpora comprising the content of the next scene; selecting a template for presenting the content of the next scene, the template selected based on information found in the second portion of the search corpora; generating the next scene of the plurality of scenes such that the next scene comprises the content; editing the next scene based on information specified in a user interface, the user interface comprising information specifying one or more of a name of the next scene and the template for presenting the next scene; assembling at least the scene and the next scene into the video; and adding narration to the video; wherein evaluating the scene condition of the scene comprises comparing the scene condition to a plurality of scene conditions associated with the node of the decision graph; wherein the portion of the search corpora is defined based on one or more selected from a group consisting of the user credential, a user role of a user associated with the user credential, a rule, and any combination thereof; wherein access to the plurality of search corpora is restricted to the portion of the search corpora based on the user credential; wherein the user credential comprises one or more of a login screen name and a username-password pair; wherein the scene condition evaluates to a quantified value or a Boolean value; wherein the information from the portion of the search corpora is analyzed periodically; wherein determining the content of the next scene comprises using statistical analysis to determine a scope and a relevance of the content of the next scene; wherein determining the content of the next scene of the plurality of scenes comprises traversing the decision graph, the content of the next scene determined based on a set of rules encoded into the decision graph, at least some of the set of rules associated with a determination of one or more statistical quantities; wherein the decision graph is traversed in a depth-first manner or a breadth-first manner; wherein the search corpora comprises structured data and unstructured data; wherein the template comprises a plurality of attribute fields, the attributes comprising one or more selected from a group consisting of: a title, a subtitle, a narration, a transition, and any combination thereof.
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1. A system to generate a video comprising a plurality of scenes comprising: a database having a set of storage devices to hold a set of data records to form a plurality of search corpora, at least a portion of the search corpora accessible based on a user credential; one or more processors corresponding to a plurality of processing entities associated with respective portions of program memory; a memory segment being accessible by an address provided by one or more concurrently executing processing entities; a processor that executes a sequence of instructions which, when executed by the processor causes the processor to execute a process, the process comprising: analyzing information from the portion of the search corpora or from a second search corpus to determine at least one attribute pertaining to the information; executing a rule corresponding to a node of a decision graph, each node comprising one or more selected from a group consisting of: a scene name, a scene indication, an audience description, a template description, and any combination thereof; detecting a scene condition of a scene based on execution of the rule corresponding to the node of the decision graph; generating the scene, the scene comprising information included in the portion of the search corpora; evaluating the scene condition of the scene, the scene condition based at least in part on the attribute; determining a content of a next scene of the plurality of scenes based at least in part on a value obtained by evaluating the scene condition; determining an additional scene should not be generated based on the scene condition of the scene; accessing a second portion of the search corpora accessible based on the scene condition of another scene, the second portion of the search corpora comprising the content of the next scene; selecting a template for presenting the content of the next scene, the template selected based on information found in the second portion of the search corpora; generating the next scene of the plurality of scenes such that the next scene comprises the content; editing the next scene based on information specified in a user interface, the user interface comprising information specifying one or more of a name of the next scene and the template for presenting the next scene; assembling at least the scene and the next scene into the video; and adding narration to the video; wherein evaluating the scene condition of the scene comprises comparing the scene condition to a plurality of scene conditions associated with the node of the decision graph; wherein the portion of the search corpora is defined based on one or more selected from a group consisting of the user credential, a user role of a user associated with the user credential, a rule, and any combination thereof; wherein access to the plurality of search corpora is restricted to the portion of the search corpora based on the user credential; wherein the user credential comprises one or more of a login screen name and a username-password pair; wherein the scene condition evaluates to a quantified value or a Boolean value; wherein the information from the portion of the search corpora is analyzed periodically; wherein determining the content of the next scene comprises using statistical analysis to determine a scope and a relevance of the content of the next scene; wherein determining the content of the next scene of the plurality of scenes comprises traversing the decision graph, the content of the next scene determined based on a set of rules encoded into the decision graph, at least some of the set of rules associated with a determination of one or more statistical quantities; wherein the decision graph is traversed in a depth-first manner or a breadth-first manner; wherein the search corpora comprises structured data and unstructured data; wherein the template comprises a plurality of attribute fields, the attributes comprising one or more selected from a group consisting of: a title, a subtitle, a narration, a transition, and any combination thereof. 7. The system of claim 1 , further comprising a template editor configured to read from a plurality of templates.
| 0.521004 |
29. A program storage device readable by a machine tangibly embodying a program of instructions executable by the machine to perform a method for accessing electronic records obtained from at least one electronic records database search, the method enabling users to select for retrieval at least one raw data set related to the electronic records, the device comprising: selecting one of a plurality of user input, stored electronic records search requests from a queued search database to execute next based upon one or more selection criteria; executing the selected electronic records search request and retrieving at least one electronic record from at least one storage location during the executing; determining which of two or more different types of communication medium can be used to access at least one of a plurality of electronic records databases associated with the selected one of the electronic records search request; retrieving instructions for accessing the at least one of a plurality of electronic records databases based on at least one of the determined types of communication medium which can be used to access the at least one of the plurality of electronic records databases; accessing the at least one of the plurality of electronic records databases with the retrieved instructions; retrieving at least one electronic record from at least one storage location, wherein the at least one electronic record comprises results of an executed electronic records search request, at least one criterion used in formulating the electronic records search request and data related to at least one electronic database associated with the electronic records search request; parsing the electronic records to convert one or more raw data sets into user-selectable objects; determining at least one data parsing algorithm that should be used for parsing the at least one retrieved electronic record based upon a content of the at least one retrieved electronic record; executing the parsing using the at least one determined data parsing algorithm; and causing the user-selectable objects to be displayed.
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29. A program storage device readable by a machine tangibly embodying a program of instructions executable by the machine to perform a method for accessing electronic records obtained from at least one electronic records database search, the method enabling users to select for retrieval at least one raw data set related to the electronic records, the device comprising: selecting one of a plurality of user input, stored electronic records search requests from a queued search database to execute next based upon one or more selection criteria; executing the selected electronic records search request and retrieving at least one electronic record from at least one storage location during the executing; determining which of two or more different types of communication medium can be used to access at least one of a plurality of electronic records databases associated with the selected one of the electronic records search request; retrieving instructions for accessing the at least one of a plurality of electronic records databases based on at least one of the determined types of communication medium which can be used to access the at least one of the plurality of electronic records databases; accessing the at least one of the plurality of electronic records databases with the retrieved instructions; retrieving at least one electronic record from at least one storage location, wherein the at least one electronic record comprises results of an executed electronic records search request, at least one criterion used in formulating the electronic records search request and data related to at least one electronic database associated with the electronic records search request; parsing the electronic records to convert one or more raw data sets into user-selectable objects; determining at least one data parsing algorithm that should be used for parsing the at least one retrieved electronic record based upon a content of the at least one retrieved electronic record; executing the parsing using the at least one determined data parsing algorithm; and causing the user-selectable objects to be displayed. 38. The device of claim 29 wherein the electronic records search requests comprise court case docket sheet search requests.
| 0.553781 |
1. A computer-implemented method of formatting content on a user network site, comprising: receiving format preference information for the user network site from a network site administrator, the format preference information defining a format preference of the user network site; identifying format performance information comprising performance metrics of advertisements, each of the performance metrics based upon a performance of a particular advertisement positioned at a particular advertisement location on network sites having a particular format; based upon the identified format performance information, determining advertisement locations on the user network site that optimize a performance metric of advertisements presented on the user network site; determining a document format for the user network site based on the format preference information and the determined advertisement locations; dynamically adjusting the document format based on changes to the format preference information or the format performance information; and formatting the user network site based on the adjusted document format.
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1. A computer-implemented method of formatting content on a user network site, comprising: receiving format preference information for the user network site from a network site administrator, the format preference information defining a format preference of the user network site; identifying format performance information comprising performance metrics of advertisements, each of the performance metrics based upon a performance of a particular advertisement positioned at a particular advertisement location on network sites having a particular format; based upon the identified format performance information, determining advertisement locations on the user network site that optimize a performance metric of advertisements presented on the user network site; determining a document format for the user network site based on the format preference information and the determined advertisement locations; dynamically adjusting the document format based on changes to the format preference information or the format performance information; and formatting the user network site based on the adjusted document format. 16. The method of claim 1 , wherein the format preference information comprises information about a network site administrator's preference regarding the location of a plurality of electronic document objects on a webpage.
| 0.5 |
15. A system for managing a conversation system, the system comprising: a computer coupled to a storage medium readable and storing instructions for execution by the system for performing presenting on a user system of a first party, each of at least one chatbot as part of at least one messaging window forming a chat window hosted by a third party, the chatbot adapted to act as a customer service agent for at least one of a good and a service; and a web page document hosted by a second party, the web page document including code to launch the chat window hosted by the third party, and the second party and the third party being independent business entities; displaying a message to the first party through the messaging window; reviewing a response from the first party using a combination of keyword/response pair scripting and artificial intelligence; and wherein the keyword/response pair scripting, the messaging window and the artificial intelligence are all managed via a web-based management console hosted by the third party, the web-based management console includes components selectable by the second party for managing the messaging window of the chatbot, separate from a window of the web page document hosted by the second party for display on the user system of the first party, the components including at least one event to launch the messaging window of the chatbot in response to code scripting at the web page document hosted by the second party.
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15. A system for managing a conversation system, the system comprising: a computer coupled to a storage medium readable and storing instructions for execution by the system for performing presenting on a user system of a first party, each of at least one chatbot as part of at least one messaging window forming a chat window hosted by a third party, the chatbot adapted to act as a customer service agent for at least one of a good and a service; and a web page document hosted by a second party, the web page document including code to launch the chat window hosted by the third party, and the second party and the third party being independent business entities; displaying a message to the first party through the messaging window; reviewing a response from the first party using a combination of keyword/response pair scripting and artificial intelligence; and wherein the keyword/response pair scripting, the messaging window and the artificial intelligence are all managed via a web-based management console hosted by the third party, the web-based management console includes components selectable by the second party for managing the messaging window of the chatbot, separate from a window of the web page document hosted by the second party for display on the user system of the first party, the components including at least one event to launch the messaging window of the chatbot in response to code scripting at the web page document hosted by the second party. 19. The system of claim 15 , wherein the web-based management console of the third party includes a management console for managing the messaging window of the chatbot, separate from the window of the web page document of the second party for display on the computer of the first party, the components selectable by the second party includes a period of time when messaging window of the chatbot is active.
| 0.568841 |
1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data.
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1. A system, comprising: an inference data acquisition module configured to acquire inference data that indicate an inferred mental state of an authoring user in connection with a particular item of an electronic message, the inference data derived based, at least in part, on at least one physical characteristic of the authoring user; one or more sensors configured to sense the at least one physical characteristic of the authoring user in connection with the particular item of the electronic message; a source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors; an inference data association module configured to associate the inference data with the particular item, the inference data association module including at least an inference data inclusion module configured to include the inference data into the electronic message; and a source identity association module configured to associate the source identity data with the particular item, the source identity association module including at least a source identity inclusion module configured to include into the electronic message one or more identities of the one or more sensors, the one or more sensors having been used to derive, at least in part, the inference data acquired by the inference data acquisition module; and wherein the electronic message thereby includes at least a data pair that includes at least the inference data that indicate the inferred mental state of the authoring user in connection with the particular item and the one or more identities of the one or more sensors used to derive, at least in part, the inference data. 18. The system of claim 1 , wherein said source identity acquisition module configured to acquire source identity data providing at least one identity of one or more sources that provide a basis, at least in part, for the inference data, the one or more sources including at least the one or more sensors comprises: an inference technique or model identity (ID) acquisition module configured to acquire an identity of an inference technique or model used to derive the inference data.
| 0.607174 |
1. A method for suggesting a search query based on terms, the method comprising: receiving, via a processor, a search query having at least a first term; identifying a plurality of related terms having a relationship to the first term, based on prior search queries; determining to ignore a first related term of the plurality of related terms, based on the first related term having not been observed with the first term over a specified time interval; and generating a plurality of predictive suggestions for completing the search query, wherein none of the plurality of predictive suggestions includes the ignored first related term, wherein a first of the plurality of predictive suggestions includes at least the first term, and wherein a second of the plurality of predictive suggestions includes an identified semantic equivalent of the first term and a second related term of the plurality of related terms, wherein the identified semantic equivalent is synonymous with the first term.
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1. A method for suggesting a search query based on terms, the method comprising: receiving, via a processor, a search query having at least a first term; identifying a plurality of related terms having a relationship to the first term, based on prior search queries; determining to ignore a first related term of the plurality of related terms, based on the first related term having not been observed with the first term over a specified time interval; and generating a plurality of predictive suggestions for completing the search query, wherein none of the plurality of predictive suggestions includes the ignored first related term, wherein a first of the plurality of predictive suggestions includes at least the first term, and wherein a second of the plurality of predictive suggestions includes an identified semantic equivalent of the first term and a second related term of the plurality of related terms, wherein the identified semantic equivalent is synonymous with the first term. 2. The method of claim 1 , further comprising: determining a score for each of the plurality of predictive suggestions based on a number of occasions that the first term has been observed with at least one of the plurality of related terms.
| 0.610807 |
12. A method as recited in claim 1 , wherein the step for using an interface and a graphical design technique to design an adaptive educational path comprises automatically snapping activity icons to a grid.
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12. A method as recited in claim 1 , wherein the step for using an interface and a graphical design technique to design an adaptive educational path comprises automatically snapping activity icons to a grid. 13. A method as recited in claim 12 , wherein the step for using an interface and a graphical design technique to design an adaptive educational path further comprises selectively organizing the activity icons to develop a flow of activities.
| 0.961951 |
1. A method in a computer system for, in a representation of one or more dictionaries comprising a plurality of text segments, characterizing the sense of an occurrence of a polysemous word, the method comprising the steps of: selecting a plurality of dictionary text segments each containing a first word; identifying among the selected dictionary text segments a first occurrence of a second word, the first occurrence of the second word having no word sense characterization; identifying among the selected dictionary text segments a second occurrence of the second word, the second occurrence of the second word having a word sense characterization; and attributing to the first occurrence of the second word the word sense characterization of the second occurrence of the second word.
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1. A method in a computer system for, in a representation of one or more dictionaries comprising a plurality of text segments, characterizing the sense of an occurrence of a polysemous word, the method comprising the steps of: selecting a plurality of dictionary text segments each containing a first word; identifying among the selected dictionary text segments a first occurrence of a second word, the first occurrence of the second word having no word sense characterization; identifying among the selected dictionary text segments a second occurrence of the second word, the second occurrence of the second word having a word sense characterization; and attributing to the first occurrence of the second word the word sense characterization of the second occurrence of the second word. 5. The method of claim 1 wherein the attributing step is only performed where a condition relating to the identified occurrences of the second word is satisfied.
| 0.741599 |
16. An apparatus, comprising: an event record creator, implemented at least partially in hardware, that creates two or more sets of field searchable, time stamped event records from raw data stored in at least one data store, wherein each set of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records comprises field searchable, time stamped event records having time stamps that fall within a time range, the time range different than time ranges associated with other sets of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records, wherein each field searchable, time stamped event record in the two or more sets of field searchable, time stamped event records includes a portion of the raw data and is associated with a time stamp derived from the raw data, wherein the raw data reflects activity in an information technology environment; a summarization table generator, implemented at least partially in hardware, that generates a summarization table for each set of field searchable, time stamped event records in the two or more sets of field searchable, time stamped event records that: identifies one or more field values, wherein a field value comprises a value that appears in an associated field in one or more field searchable, time stamped event records in the set of field searchable, time stamped event records; and for each field value, includes a posting value to the one or more field searchable, time stamped event records in the set of field searchable, time stamped event records that contain the field value for the associated field; a summarization table storage system, implemented at least partially in hardware, that stores the summarization table for each set of field searchable, time stamped event records among the two or more sets of time stamped field searchable event records; a summarization table selector, implemented at least partially in hardware, that selects a stored summarization table based on a received query that includes search criteria for evaluating field values for one or more fields; a subsystem, implemented at least partially in hardware, that uses the search criteria to evaluate field values for one or more fields in the selected summarization table to generate a query result; and wherein the query result reflects an aspect of activity in the information technology environment.
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16. An apparatus, comprising: an event record creator, implemented at least partially in hardware, that creates two or more sets of field searchable, time stamped event records from raw data stored in at least one data store, wherein each set of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records comprises field searchable, time stamped event records having time stamps that fall within a time range, the time range different than time ranges associated with other sets of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records, wherein each field searchable, time stamped event record in the two or more sets of field searchable, time stamped event records includes a portion of the raw data and is associated with a time stamp derived from the raw data, wherein the raw data reflects activity in an information technology environment; a summarization table generator, implemented at least partially in hardware, that generates a summarization table for each set of field searchable, time stamped event records in the two or more sets of field searchable, time stamped event records that: identifies one or more field values, wherein a field value comprises a value that appears in an associated field in one or more field searchable, time stamped event records in the set of field searchable, time stamped event records; and for each field value, includes a posting value to the one or more field searchable, time stamped event records in the set of field searchable, time stamped event records that contain the field value for the associated field; a summarization table storage system, implemented at least partially in hardware, that stores the summarization table for each set of field searchable, time stamped event records among the two or more sets of time stamped field searchable event records; a summarization table selector, implemented at least partially in hardware, that selects a stored summarization table based on a received query that includes search criteria for evaluating field values for one or more fields; a subsystem, implemented at least partially in hardware, that uses the search criteria to evaluate field values for one or more fields in the selected summarization table to generate a query result; and wherein the query result reflects an aspect of activity in the information technology environment. 26. The apparatus of claim 16 , wherein the raw data includes machine data.
| 0.719586 |
1. A method for generating queries for at least one of retrieving data that satisfy a conditional expression from a database and performing a calculation on at least part of the retrieved data, the method comprising: receiving, at one or more computer systems, a first query containing at least one first conditional expression; determining, with one or more processors associated with the one or more computer systems, a first replaceable token and a second replaceable token in the first query; retrieving, with the one or more processors associated with the one or more computer systems, a parameter definition for a first instance of a parameter corresponding to the first replaceable token in the first query from a pool of parameter definitions that exist outside of a report or query that includes the first query; verifying that the at least one first conditional expression in the query references the parameter having the persistent parameter definition; in response to the at least one first conditional expression referencing the parameter having the persistent parameter definition, obtaining user input for a first instance of the parameter and user input for a second instance of the parameter based on the persistent parameter definition, wherein obtaining user input comprises: generating, with the one or more processors associated with the one or more computer systems, a first graphical user interface in response to processing the first query based on the parameter definition for the first instance of the parameter corresponding to the first replaceable token identified in the first query, the parameter definition including information configured to prompt users for information indicative of a conditional expression and a calculation, wherein the first graphical user interface is sent and displayed to a user as a prompt for first information indicative of a second conditional expression and a first calculation; receiving first user input from a user, wherein the first user input comprises the second conditional expression and first calculation; generating, with the one or more processors associated with the one or more computer systems, a second graphical user interface in response to processing the first query based on reusing the parameter definition for the second instance of the parameter corresponding to the second replaceable token identified in the first query, wherein the second graphical user interface is sent and displayed to a user as a prompt for second information indicative of a third conditional expression and a second calculation; receiving second user input from a user, wherein the second user input comprises the third conditional expression and second calculation; replacing the first replaceable token with the second conditional expression and the first calculation and replacing the second token with the third conditional expression and the second calculation; in response to replacing the first replaceable token identified in the first query with the second conditional expression and the first calculation and the second replaceable token identified in the first query with the third conditional expression and the second calculation, performing generation of a second query for retrieving data that satisfy the at least one first conditional expression; retrieving data that satisfies the at least one first conditional expression, wherein retrieving data that satisfies the at least one first conditional expression comprises evaluating the second conditional expression and the third conditional expression; and performing the first calculation and the second calculation on the retrieved data.
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1. A method for generating queries for at least one of retrieving data that satisfy a conditional expression from a database and performing a calculation on at least part of the retrieved data, the method comprising: receiving, at one or more computer systems, a first query containing at least one first conditional expression; determining, with one or more processors associated with the one or more computer systems, a first replaceable token and a second replaceable token in the first query; retrieving, with the one or more processors associated with the one or more computer systems, a parameter definition for a first instance of a parameter corresponding to the first replaceable token in the first query from a pool of parameter definitions that exist outside of a report or query that includes the first query; verifying that the at least one first conditional expression in the query references the parameter having the persistent parameter definition; in response to the at least one first conditional expression referencing the parameter having the persistent parameter definition, obtaining user input for a first instance of the parameter and user input for a second instance of the parameter based on the persistent parameter definition, wherein obtaining user input comprises: generating, with the one or more processors associated with the one or more computer systems, a first graphical user interface in response to processing the first query based on the parameter definition for the first instance of the parameter corresponding to the first replaceable token identified in the first query, the parameter definition including information configured to prompt users for information indicative of a conditional expression and a calculation, wherein the first graphical user interface is sent and displayed to a user as a prompt for first information indicative of a second conditional expression and a first calculation; receiving first user input from a user, wherein the first user input comprises the second conditional expression and first calculation; generating, with the one or more processors associated with the one or more computer systems, a second graphical user interface in response to processing the first query based on reusing the parameter definition for the second instance of the parameter corresponding to the second replaceable token identified in the first query, wherein the second graphical user interface is sent and displayed to a user as a prompt for second information indicative of a third conditional expression and a second calculation; receiving second user input from a user, wherein the second user input comprises the third conditional expression and second calculation; replacing the first replaceable token with the second conditional expression and the first calculation and replacing the second token with the third conditional expression and the second calculation; in response to replacing the first replaceable token identified in the first query with the second conditional expression and the first calculation and the second replaceable token identified in the first query with the third conditional expression and the second calculation, performing generation of a second query for retrieving data that satisfy the at least one first conditional expression; retrieving data that satisfies the at least one first conditional expression, wherein retrieving data that satisfies the at least one first conditional expression comprises evaluating the second conditional expression and the third conditional expression; and performing the first calculation and the second calculation on the retrieved data. 7. The method of claim 1 wherein the parameter definition includes at least one of the following properties: a parameter name, a default value for a parameter, whether multiple values are allowed, whether a parameter is optional or mandatory, and a text prompt used to prompt the user for input.
| 0.531481 |
10. The method of claim 1 , wherein: the obtained corpus of text is associated with a first context; the input is associated with an input context; and ranking the plurality of candidate word strings is based on a degree of similarity between the input context and the first context.
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10. The method of claim 1 , wherein: the obtained corpus of text is associated with a first context; the input is associated with an input context; and ranking the plurality of candidate word strings is based on a degree of similarity between the input context and the first context. 12. The method of claim 10 , wherein the first context and input context are determined using a sensor of the electronic device.
| 0.941578 |
1. A computer implemented method for providing near real-time feedback to a first user of a social networking system when the first user is composing a social media message, the feedback indicating a predicted level of engagement with the social media message by a second one or more users of the social networking system, the method comprising: receiving, at a server, message information regarding the social media message being composed by the first user at a computing device; determining, using a prediction model, a predicted engagement score based on the message information, the predicted engagement score being an approximation of the predicted level of engagement with the social media message by the second one or more users of the social networking system; and sending data representing the predicted engagement score to the computing device to display a presentation in a user interface at which the social media message is being composed, the presentation including a graphical representation of the predicted engagement score and a graph presenting one or more previous predicted engagement scores for the social media message, the graphical representation including a graphical indicator proximate a region of the user interface at which the social media message is being composed, the graphical indicator configured to indicate at least a positive or a negative change to the predicted engagement score in response to a change to content of the social media message being composed.
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1. A computer implemented method for providing near real-time feedback to a first user of a social networking system when the first user is composing a social media message, the feedback indicating a predicted level of engagement with the social media message by a second one or more users of the social networking system, the method comprising: receiving, at a server, message information regarding the social media message being composed by the first user at a computing device; determining, using a prediction model, a predicted engagement score based on the message information, the predicted engagement score being an approximation of the predicted level of engagement with the social media message by the second one or more users of the social networking system; and sending data representing the predicted engagement score to the computing device to display a presentation in a user interface at which the social media message is being composed, the presentation including a graphical representation of the predicted engagement score and a graph presenting one or more previous predicted engagement scores for the social media message, the graphical representation including a graphical indicator proximate a region of the user interface at which the social media message is being composed, the graphical indicator configured to indicate at least a positive or a negative change to the predicted engagement score in response to a change to content of the social media message being composed. 6. The method of claim 1 , wherein the predicted engagement score is a numerical approximation.
| 0.715888 |
13. An apparatus, comprising: one or more processors; and one or more memory devices for storing program instructions used by the one or more processors, wherein the program instructions, when executed by the one or more processors, cause the one or more processors to: output, at a computing device and for display, a spreadsheet document that includes one or more data cells and a document tab; receive an indication of a user input selecting a document entry in the spreadsheet document for applying conditional formatting to a document tab based on the document entry, wherein the document entry is one or more of the one or more data cells of the spreadsheet document; output, for display in response to the user input selecting the document entry in the spreadsheet document, a conditional formatting user interface for associating one or more conditional formatting rules with the document entry and the document tab; receive an indication of a user input of one or more conditional formatting rules linking a property of the document tab with the document entry; and change the property of the document tab based on the one or more conditional formatting rules.
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13. An apparatus, comprising: one or more processors; and one or more memory devices for storing program instructions used by the one or more processors, wherein the program instructions, when executed by the one or more processors, cause the one or more processors to: output, at a computing device and for display, a spreadsheet document that includes one or more data cells and a document tab; receive an indication of a user input selecting a document entry in the spreadsheet document for applying conditional formatting to a document tab based on the document entry, wherein the document entry is one or more of the one or more data cells of the spreadsheet document; output, for display in response to the user input selecting the document entry in the spreadsheet document, a conditional formatting user interface for associating one or more conditional formatting rules with the document entry and the document tab; receive an indication of a user input of one or more conditional formatting rules linking a property of the document tab with the document entry; and change the property of the document tab based on the one or more conditional formatting rules. 14. The apparatus of claim 13 , wherein the property of the document tab is one of background color, font style, font size, and font color.
| 0.687339 |
1. A method for interacting with a user, the method performed by a computer having access to an electronic knowledge database, the method comprising: automatically with the computer (a) generating a structured representation of a received user input; (b) comparing the structured representation of the received user input with each of a plurality of expected user statement fields that are entries in the electronic knowledge database, and are associated with respective action fields specifying at least one action; and (c) when one of the plurality of expected user statements fields matches the structured representation of the received user inputs, causing the at least one action specified by the action field associated with the matching one of the plurality of expected user statement fields to be performed; the method further comprising: (i) when a match is identified in part (c), generating a second structural representation of a second received user input; and (ii) comparing the second structured representation of the second received user input with a second plurality of expected user statement fields that are entries in the electronic knowledge database and are associated with respective actions fields specifying at least one action: (A) wherein the entries of the knowledge database are arranged in a hierarchical structure; (B) wherein each entry in the electronic knowledge database also comprises an associated identification field indicative of a position in the hierarchical structure; and (C) wherein all the positions indicated by the identification fields associated with the second plurality of expected user statement fields substantially match; and (iii) when one of the second plurality of expected user statements fields matches the second structured representation of the second received user input, causing the at least one action specified by the action field associated with the matching one of the second plurality of expected user statement fields to be performed.
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1. A method for interacting with a user, the method performed by a computer having access to an electronic knowledge database, the method comprising: automatically with the computer (a) generating a structured representation of a received user input; (b) comparing the structured representation of the received user input with each of a plurality of expected user statement fields that are entries in the electronic knowledge database, and are associated with respective action fields specifying at least one action; and (c) when one of the plurality of expected user statements fields matches the structured representation of the received user inputs, causing the at least one action specified by the action field associated with the matching one of the plurality of expected user statement fields to be performed; the method further comprising: (i) when a match is identified in part (c), generating a second structural representation of a second received user input; and (ii) comparing the second structured representation of the second received user input with a second plurality of expected user statement fields that are entries in the electronic knowledge database and are associated with respective actions fields specifying at least one action: (A) wherein the entries of the knowledge database are arranged in a hierarchical structure; (B) wherein each entry in the electronic knowledge database also comprises an associated identification field indicative of a position in the hierarchical structure; and (C) wherein all the positions indicated by the identification fields associated with the second plurality of expected user statement fields substantially match; and (iii) when one of the second plurality of expected user statements fields matches the second structured representation of the second received user input, causing the at least one action specified by the action field associated with the matching one of the second plurality of expected user statement fields to be performed. 2. The method according to claim 1 wherein the at least one action in part (c) comprises a link to another of the plurality of knowledge database entries.
| 0.681544 |
1. A method for dynamically binding a user interface to information stored in a data source, comprising: displaying a user interface, wherein the user interface is operable to display information in a web page, wherein the information is stored in a first data source on a business object, collect additional information from a user, and store the additional information in the first data source on the business object; providing a data binding tag that defines a rendering boundary within the web page for rendering the information, and rules to be applied when the information is rendered, wherein the data binding tag includes a plurality of attributes; specifying, by the data binding tag, a first action which includes reading or updating the information stored in the first data source, wherein at least one of the attributes is associated with the first action; specifying the first data source associated with the first action using a script; and rendering each item in the first data source on the web page in the user interface with a markup language according to the boundary and the rules defined by the data binding tag and based on the first action, including evaluation of the script.
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1. A method for dynamically binding a user interface to information stored in a data source, comprising: displaying a user interface, wherein the user interface is operable to display information in a web page, wherein the information is stored in a first data source on a business object, collect additional information from a user, and store the additional information in the first data source on the business object; providing a data binding tag that defines a rendering boundary within the web page for rendering the information, and rules to be applied when the information is rendered, wherein the data binding tag includes a plurality of attributes; specifying, by the data binding tag, a first action which includes reading or updating the information stored in the first data source, wherein at least one of the attributes is associated with the first action; specifying the first data source associated with the first action using a script; and rendering each item in the first data source on the web page in the user interface with a markup language according to the boundary and the rules defined by the data binding tag and based on the first action, including evaluation of the script. 6. The method of claim 1 wherein: the first data source is one of: 1) an array; 2) a list; 3) a map.
| 0.582591 |
8. An article of manufacture comprising a tangible computer readable storage medium storing a program for building an index, wherein the program, when executed by a processor of a computer, causes operations to be performed, the operations comprising: storing a current version of a store having a tokenized version of each document in a corpus of documents, a delta store accumulating changes to the current version of the store, and previously generated global analysis computations, wherein the previously generated global analysis computations include an anchor text table, a rank table, and a duplicates table; building a new version of the index and outputting a raw anchor text table and a raw duplicates table by accessing the current version of the store store i , the delta store, and the previously generated global analysis computations; and generating new global analysis computations by accessing the raw anchor text table, the raw duplicates table, and the previously generated global analysis computations, wherein the new global analysis computations include a new anchor text table, a new rank table, and a new duplicates table.
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8. An article of manufacture comprising a tangible computer readable storage medium storing a program for building an index, wherein the program, when executed by a processor of a computer, causes operations to be performed, the operations comprising: storing a current version of a store having a tokenized version of each document in a corpus of documents, a delta store accumulating changes to the current version of the store, and previously generated global analysis computations, wherein the previously generated global analysis computations include an anchor text table, a rank table, and a duplicates table; building a new version of the index and outputting a raw anchor text table and a raw duplicates table by accessing the current version of the store store i , the delta store, and the previously generated global analysis computations; and generating new global analysis computations by accessing the raw anchor text table, the raw duplicates table, and the previously generated global analysis computations, wherein the new global analysis computations include a new anchor text table, a new rank table, and a new duplicates table. 14. The article of manufacture of claim 8 , wherein the new global analysis computations are generated using results of recent processing of documents existing at a certain point in time.
| 0.533666 |
7. The advertising targeting system of claim 6 , wherein the targeting server system is further configured to: assign a feature vector to each of the identified keywords; and estimate the performance of the feature vector in targeting the specific offer to the desired audience.
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7. The advertising targeting system of claim 6 , wherein the targeting server system is further configured to: assign a feature vector to each of the identified keywords; and estimate the performance of the feature vector in targeting the specific offer to the desired audience. 8. The advertising targeting system of claim 7 , wherein the feature vector of a keyword includes at least one value indicative of a relationship between the keyword and at least one of the offer keywords.
| 0.933299 |
11. A question and answer data editing method of editing the content of a dialogue to generate question and answer data, comprising: detecting a first question part or a first answer part from a history data of said dialogue content that is similar to a first question and answer data included in existing question and answer data; extracting an expression pattern including a context or a condition in which said dialogue was made from the proximity of said first question part or said first answer part; registering said extracted expression pattern as index information of said first question and answer data; extracting a) a second answer part from the history data, when the second question part in the history data is similar to the first question and answer data and the second answer part in the history data is not similar to the first question and answer data, and b) a third question part from the history data, when a third answer part in the history data is similar to the first question and answer data and the second question part is not similar to the first question and answer data; registering said extracted third question part or second answer part as a variation of said first question and answer data; and extracting a second question and answer data from the history data of said dialogue content as associated question and answer data to said first question and answer data in response to detecting that a third question part or a third answer part similar to the extracted second question and answer data is present in the vicinity of the first question part or the first answer part.
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11. A question and answer data editing method of editing the content of a dialogue to generate question and answer data, comprising: detecting a first question part or a first answer part from a history data of said dialogue content that is similar to a first question and answer data included in existing question and answer data; extracting an expression pattern including a context or a condition in which said dialogue was made from the proximity of said first question part or said first answer part; registering said extracted expression pattern as index information of said first question and answer data; extracting a) a second answer part from the history data, when the second question part in the history data is similar to the first question and answer data and the second answer part in the history data is not similar to the first question and answer data, and b) a third question part from the history data, when a third answer part in the history data is similar to the first question and answer data and the second question part is not similar to the first question and answer data; registering said extracted third question part or second answer part as a variation of said first question and answer data; and extracting a second question and answer data from the history data of said dialogue content as associated question and answer data to said first question and answer data in response to detecting that a third question part or a third answer part similar to the extracted second question and answer data is present in the vicinity of the first question part or the first answer part. 19. A dialogue supporting method of supporting a dialogue by using said generated question and answer data or said index information which is generated by the question and answer data editing method according to claim 11 .
| 0.622472 |
10. One or more computer storage media having computer executable instructions embodied thereon for performing a method in a computerized healthcare system for populating an electronic clinical document having a plurality of sections, the method comprising: providing an electronic clinical document for a particular patient having a plurality of sections, at least one of the plurality of sections being capable of receiving input of multiple data types; receiving dictation audio input into at least two of the plurality of sections, wherein the dictation audio input is audio data; embedding the dictation audio input directly into each of the at least two of the plurality of sections; presenting graphical representations indicative of the embedded dictation audio input in association with each of the at least two of the plurality of sections; and utilizing a dictation audio identifier to associate the dictation audio input with the particular patient, the electronic clinical document, and a location of the dictation audio input within the electronic clinical document.
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10. One or more computer storage media having computer executable instructions embodied thereon for performing a method in a computerized healthcare system for populating an electronic clinical document having a plurality of sections, the method comprising: providing an electronic clinical document for a particular patient having a plurality of sections, at least one of the plurality of sections being capable of receiving input of multiple data types; receiving dictation audio input into at least two of the plurality of sections, wherein the dictation audio input is audio data; embedding the dictation audio input directly into each of the at least two of the plurality of sections; presenting graphical representations indicative of the embedded dictation audio input in association with each of the at least two of the plurality of sections; and utilizing a dictation audio identifier to associate the dictation audio input with the particular patient, the electronic clinical document, and a location of the dictation audio input within the electronic clinical document. 16. The computer storage media of claim 10 , wherein the plurality of sections are provided in a common user interface.
| 0.56394 |
15. Apparatus for accessing electronic documents, the apparatus comprising: a server computer storing a plurality of electronic documents; a plurality of client computers that can view the plurality of electronic documents stored on the host server and can copy text from the plurality of electronic documents; and an annotation service, wherein the annotation service generates a first annotation from a selected portion of text within a first electronic document by: analyzing an unselected portion of text that precedes the selected portion of text within the first electronic document; and identifying a part of the unselected portion of text to replace a part of the selected portion of text; and wherein the annotation service makes the first annotation available to a first client computer in the plurality of client computers when the first client computer copies the selected portion of text, and wherein the first annotation is used to generate a modified selected portion of text that is pasted into a second electronic document different from the first electronic document.
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15. Apparatus for accessing electronic documents, the apparatus comprising: a server computer storing a plurality of electronic documents; a plurality of client computers that can view the plurality of electronic documents stored on the host server and can copy text from the plurality of electronic documents; and an annotation service, wherein the annotation service generates a first annotation from a selected portion of text within a first electronic document by: analyzing an unselected portion of text that precedes the selected portion of text within the first electronic document; and identifying a part of the unselected portion of text to replace a part of the selected portion of text; and wherein the annotation service makes the first annotation available to a first client computer in the plurality of client computers when the first client computer copies the selected portion of text, and wherein the first annotation is used to generate a modified selected portion of text that is pasted into a second electronic document different from the first electronic document. 21. The apparatus of claim 15 , wherein the annotation service allows a user to edit the first annotation.
| 0.654218 |
1. A method comprising: conducting a campaign experiment that reflects implementation of a campaign change in an experiment environment to generate experimental results that reflect a causal measurement of value of a campaign, wherein the campaign change includes a current change to one or more campaign parameters for providing content items over a computer network for presentation by user computing devices; determining, by one or more computing servers, a measure of effectiveness of the campaign change to within a predetermined confidence level, based at least in part on analyzing the experimental results; determining, by the one or more computing servers, an estimate of effectiveness of the campaign change, wherein determining the estimate of effectiveness comprises referencing campaign data related to the campaign change, referencing interaction data that indicates user interactions with one or more of the content items, correlating the campaign data with the interaction data over a predetermined time period, and applying rules of an identified attribution model that assigns credit to user interactions with one or more of the content items that lead to user conversions; comparing, by the one or more computing servers, the determined estimate of effectiveness of the campaign change to the determined measure of effectiveness of the campaign change; determining, based on the comparison, that the identified attribution model provides an estimate of the measure of effectiveness that is within a predetermined range of the measure of effectiveness of the campaign change; for one or more subsequent campaign changes that include a change to the one or more campaign parameters that matches the current change to the one or more campaign parameters, determining a subsequent estimate of effectiveness of the subsequent campaign change, based at least in part on applying the identified attribution model in lieu of conducting another campaign experiment to determine the subsequent estimate of effectiveness of the subsequent campaign change; and using subsequent determined estimates of effectiveness of the subsequent campaign changes obtained from application of the identified attribution model as a proxy for measures of effectiveness in lieu of conducting another campaign experiment to determine the measure of effectiveness.
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1. A method comprising: conducting a campaign experiment that reflects implementation of a campaign change in an experiment environment to generate experimental results that reflect a causal measurement of value of a campaign, wherein the campaign change includes a current change to one or more campaign parameters for providing content items over a computer network for presentation by user computing devices; determining, by one or more computing servers, a measure of effectiveness of the campaign change to within a predetermined confidence level, based at least in part on analyzing the experimental results; determining, by the one or more computing servers, an estimate of effectiveness of the campaign change, wherein determining the estimate of effectiveness comprises referencing campaign data related to the campaign change, referencing interaction data that indicates user interactions with one or more of the content items, correlating the campaign data with the interaction data over a predetermined time period, and applying rules of an identified attribution model that assigns credit to user interactions with one or more of the content items that lead to user conversions; comparing, by the one or more computing servers, the determined estimate of effectiveness of the campaign change to the determined measure of effectiveness of the campaign change; determining, based on the comparison, that the identified attribution model provides an estimate of the measure of effectiveness that is within a predetermined range of the measure of effectiveness of the campaign change; for one or more subsequent campaign changes that include a change to the one or more campaign parameters that matches the current change to the one or more campaign parameters, determining a subsequent estimate of effectiveness of the subsequent campaign change, based at least in part on applying the identified attribution model in lieu of conducting another campaign experiment to determine the subsequent estimate of effectiveness of the subsequent campaign change; and using subsequent determined estimates of effectiveness of the subsequent campaign changes obtained from application of the identified attribution model as a proxy for measures of effectiveness in lieu of conducting another campaign experiment to determine the measure of effectiveness. 6. The method of claim 1 , further comprising providing a user interface to a campaign sponsor, wherein the user interface visually presents a suggestion for a model change from a previously selected attribution model used for the campaign to a suggested attribution model including providing the suggested attribution model as the suggestion when an estimate of effectiveness of a campaign change based on an application of the previously selected attribution model is an unacceptable estimate of a measure of effectiveness of the campaign change.
| 0.574855 |
8. The computer-implemented method of claim 2 , wherein the one or more scripts are determined based on past computing activity by the user.
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8. The computer-implemented method of claim 2 , wherein the one or more scripts are determined based on past computing activity by the user. 9. The computer-implemented method of claim 8 , wherein the past computing activity includes at least one of (i) content of e-mails sent by the user, (ii) social network commentary generated by the user, and (iii) search queries generated by the user.
| 0.888397 |
1. A deep learning based method for three dimensional (3D) model triangular facet feature learning and classifying, comprising: constructing a deep convolutional neural network (CNN) feature learning model having a first convolution layer, a first downsampling layer, a second convolution layer and a second downsampling layer, wherein the first convolution layer has 16 convolution kernels, each of which has a dimension of 5×5, a scaling factor of the first downsampling layer is 2, the second convolution layer has 16×20 convolution kernels, each of which has a dimension of 3×3, and a scaling factor of the second downsampling layer is 2; extracting a feature from a 3D model triangular facet having a class label and constructing a feature vector for the 3D model triangular facet having the class label, and reconstructing a feature in the constructed feature vector using a bag-of-words algorithm to obtain an initial feature corresponding to the 3D model triangular facet having the class label; training the deep CNN feature learning model using the initial feature corresponding to the 3D model triangular facet having the class label to obtain a trained deep CNN feature learning model; extracting a feature from a 3D model triangular facet having no class label and constructing a feature vector for the 3D model triangular facet having no class label, and reconstructing a feature in the constructed feature vector using the bag-of-words algorithm to obtain an initial feature corresponding to the 3D model triangular facet having no class label; determining an output feature corresponding to the 3D model triangular facet having no class label according to the trained deep CNN feature learning model and the initial feature corresponding to the 3D model triangular facet having no class label; and classifying the 3D model triangular facet having no class label according to the output feature corresponding to the 3D model triangular facet having no class label.
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1. A deep learning based method for three dimensional (3D) model triangular facet feature learning and classifying, comprising: constructing a deep convolutional neural network (CNN) feature learning model having a first convolution layer, a first downsampling layer, a second convolution layer and a second downsampling layer, wherein the first convolution layer has 16 convolution kernels, each of which has a dimension of 5×5, a scaling factor of the first downsampling layer is 2, the second convolution layer has 16×20 convolution kernels, each of which has a dimension of 3×3, and a scaling factor of the second downsampling layer is 2; extracting a feature from a 3D model triangular facet having a class label and constructing a feature vector for the 3D model triangular facet having the class label, and reconstructing a feature in the constructed feature vector using a bag-of-words algorithm to obtain an initial feature corresponding to the 3D model triangular facet having the class label; training the deep CNN feature learning model using the initial feature corresponding to the 3D model triangular facet having the class label to obtain a trained deep CNN feature learning model; extracting a feature from a 3D model triangular facet having no class label and constructing a feature vector for the 3D model triangular facet having no class label, and reconstructing a feature in the constructed feature vector using the bag-of-words algorithm to obtain an initial feature corresponding to the 3D model triangular facet having no class label; determining an output feature corresponding to the 3D model triangular facet having no class label according to the trained deep CNN feature learning model and the initial feature corresponding to the 3D model triangular facet having no class label; and classifying the 3D model triangular facet having no class label according to the output feature corresponding to the 3D model triangular facet having no class label. 3. The method according to claim 1 , wherein the training the deep CNN feature learning model using the initial feature corresponding to the 3D model triangular facet having the class label to obtain a trained deep CNN feature learning model comprises: A, inputting the initial feature corresponding to the 3D model triangular facet having the class label into the deep CNN feature learning model, and obtaining a probability of each 3D model triangular facet having a class label belonging to each class by calculating layer-by-layer; B, obtaining a residual error by subtracting a class label data that each 3D model triangular facet having a class label has from the obtained probability of each 3D model triangular facet having a class label belonging to each class and performing a square operation; C, obtaining, according to the residual error, a partial derivative for a parameter of each layer by starting from a last layer of the deep CNN feature learning model and moving forward layer-by-layer, and updating the parameter of each layer by moving layer-by-layer; and D, looping from A to C until reaching a predefined number of loops.
| 0.700939 |
1. A computer-implemented method comprising: receiving, from a natural language interface system, a natural language task specification; converting said natural language task specification into a domain independent data flow graph, said domain independent data flow graph comprising one or more substeps; presenting said domain independent data flow graph via said natural language interface system as a natural language program; interactively refining, by said natural language interface system, said natural language program and correspondingly modifying said domain independent data flow graph; for each substep of said one or more substeps: selecting one or more candidate application programming interfaces from an application programming interface library, based on said substep; interactively narrowing, by said natural language interface system, said one or more candidate application programming interfaces to at least one selected application programming interface; implementing said substep by specifying one or more calls to said at least one selected application programming interface to yield a substep implementation; and appending said substep implementation to a result program.
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1. A computer-implemented method comprising: receiving, from a natural language interface system, a natural language task specification; converting said natural language task specification into a domain independent data flow graph, said domain independent data flow graph comprising one or more substeps; presenting said domain independent data flow graph via said natural language interface system as a natural language program; interactively refining, by said natural language interface system, said natural language program and correspondingly modifying said domain independent data flow graph; for each substep of said one or more substeps: selecting one or more candidate application programming interfaces from an application programming interface library, based on said substep; interactively narrowing, by said natural language interface system, said one or more candidate application programming interfaces to at least one selected application programming interface; implementing said substep by specifying one or more calls to said at least one selected application programming interface to yield a substep implementation; and appending said substep implementation to a result program. 4. The computer-implemented method of claim 1 , wherein said domain independent data flow graph specifies a mapping of inputs to outputs.
| 0.786728 |
1. A computer implemented method for processing database content, the method comprising the steps of: syndicating one or more data objects associated with a term database to one or more remote computers, wherein the one or more data objects contain data associated with one or more terms; parsing one or more documents to identify at least one term based on at least one rule; identifying content for the at least one term; and associating the at least one term with the identified content; wherein the one or more data objects associated with the term database provide a representation of at least a portion of the term database at the one or more remote computers and are used to link the identified content with the at least one term.
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1. A computer implemented method for processing database content, the method comprising the steps of: syndicating one or more data objects associated with a term database to one or more remote computers, wherein the one or more data objects contain data associated with one or more terms; parsing one or more documents to identify at least one term based on at least one rule; identifying content for the at least one term; and associating the at least one term with the identified content; wherein the one or more data objects associated with the term database provide a representation of at least a portion of the term database at the one or more remote computers and are used to link the identified content with the at least one term. 9. The method of claim 1 , wherein the one or more data objects are synchronized with at least the term database.
| 0.619512 |
12. A method of controlling a mobile terminal, comprising: displaying a first page of an e-book including at least one or more pages; searching for at least one or more candidate images with a search word determined using at least one portion of a content of the first page; displaying a selected one of the found at least one or more candidate images to be displayed as a background image of the first page; and changing a layout of paragraphs in the first page in response to displaying the selected image as the background image of the first page.
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12. A method of controlling a mobile terminal, comprising: displaying a first page of an e-book including at least one or more pages; searching for at least one or more candidate images with a search word determined using at least one portion of a content of the first page; displaying a selected one of the found at least one or more candidate images to be displayed as a background image of the first page; and changing a layout of paragraphs in the first page in response to displaying the selected image as the background image of the first page. 15. The method of claim 12 , wherein the search word comprises a portion of a text content in the content of the first page.
| 0.790152 |
1. A method of searching for information, comprising: receiving a query; providing the query to a first search engine that searches a set of data sources, the data sources having relationships to at least one ontology, the ontology modeling relationships between concepts in a domain and data source content containing information specific to the concepts; receiving search results from the search engine; analyzing the search results with one or more processors to determine at least one statistic corresponding to the search results and the query, wherein the statistic is based upon a relevance score for each of a plurality of concepts given the query, the relevance score expressed as r cq = w ( c ) ∑ i [ w ( i ) f ( h c , h q ) ] where w(c) is a weighing function related to a concept c, w(i) is a weighing function for a data source item i, h c is a set of items related to the concept c, h q is a set of items related to the query q, and ƒ(h c , h q ) is a normalized score function, wherein weighing function w (i) varies by data source; providing a subset of the concepts to a user based on the relevance score; and using a template to process domain specific rules and the subset of the concepts.
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1. A method of searching for information, comprising: receiving a query; providing the query to a first search engine that searches a set of data sources, the data sources having relationships to at least one ontology, the ontology modeling relationships between concepts in a domain and data source content containing information specific to the concepts; receiving search results from the search engine; analyzing the search results with one or more processors to determine at least one statistic corresponding to the search results and the query, wherein the statistic is based upon a relevance score for each of a plurality of concepts given the query, the relevance score expressed as r cq = w ( c ) ∑ i [ w ( i ) f ( h c , h q ) ] where w(c) is a weighing function related to a concept c, w(i) is a weighing function for a data source item i, h c is a set of items related to the concept c, h q is a set of items related to the query q, and ƒ(h c , h q ) is a normalized score function, wherein weighing function w (i) varies by data source; providing a subset of the concepts to a user based on the relevance score; and using a template to process domain specific rules and the subset of the concepts. 20. The method of claim 1 , wherein the query comprises a medical treatment.
| 0.583333 |
1. A method for using user provided tags for searching, comprising: collecting at an application server a plurality of user provided tags associated with each one of a plurality of entities, wherein the plurality of user provided tags comprises semantic descriptions entered by a plurality of different users: creating by the application server a tag topological network layer that is managed by a service provider, wherein the tag topological network layer predefines a next entity for each one of the plurality of entities based upon the plurality of user provided tags; receiving at the application server a user query that contains a search term from a user; generating at the application server a search result containing an entity of the plurality of entities in the tag topological network layer, wherein the entity is found based on a distance measure of a tag vector, t p , for the entity, p, wherein a function t p (i) represents a measure of a weight of a tag, i, that is used to tag the entity, p, based on a normalized count of times tag, i, is used to tag the entity, p, wherein the entity contains a link to another entity in accordance with the tag topological network layer, wherein the link is created in accordance with the tag vector of the entity; and outputting the search result to an internet protocol device of the user.
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1. A method for using user provided tags for searching, comprising: collecting at an application server a plurality of user provided tags associated with each one of a plurality of entities, wherein the plurality of user provided tags comprises semantic descriptions entered by a plurality of different users: creating by the application server a tag topological network layer that is managed by a service provider, wherein the tag topological network layer predefines a next entity for each one of the plurality of entities based upon the plurality of user provided tags; receiving at the application server a user query that contains a search term from a user; generating at the application server a search result containing an entity of the plurality of entities in the tag topological network layer, wherein the entity is found based on a distance measure of a tag vector, t p , for the entity, p, wherein a function t p (i) represents a measure of a weight of a tag, i, that is used to tag the entity, p, based on a normalized count of times tag, i, is used to tag the entity, p, wherein the entity contains a link to another entity in accordance with the tag topological network layer, wherein the link is created in accordance with the tag vector of the entity; and outputting the search result to an internet protocol device of the user. 7. The method of claim 1 , wherein the entity is accessible via an Internet.
| 0.601445 |
14. The method of claim 13 , wherein: the first set of formulas includes a first formula and the rewritten set of formulas does not include a first formula; and the step of rewriting includes pruning said first formula from said first set of formulas.
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14. The method of claim 13 , wherein: the first set of formulas includes a first formula and the rewritten set of formulas does not include a first formula; and the step of rewriting includes pruning said first formula from said first set of formulas. 16. The method of claim 14 , wherein: each formula of said first set of formulas: evaluates one or more cells in said array, and modifies as one or more cells in said array a measure column in said relation; the step of rewriting is based on a set of conditions for a given formula of said first set of formulas that include a first condition, a second condition, and a third condition, wherein: (1) the first condition is that one or more cells modified by the given formula of said first set of formulas are not evaluated by any other formula of said first set of formulas, (2) the second condition is that the one or more cells modified by the given formula are filtered out by said one or more predicates, and (3) the third condition is that the measure column is not referenced by said first query; the step of rewriting includes: (A) establishing a first subset of said first set of formulas that meet the first condition; (B) for each formula of said first subset, pruning said each formula from said first set of formulas if said each formula meets either the second condition or the third condition; (C) after performing step (B), establishing a second subset of the remaining formulas in said first set of formulas that meet the first condition.
| 0.659989 |
1. A computer-implemented method for providing a statistical initial topic classification model for use in a natural language call routing application to map a natural language user statement to at least one of a plurality of topics in the natural language call routing application, the computer-implemented method comprising acts of: accessing a voice user interface (VUI) specification that specifies a VUI for allowing users to interact with the natural language call routing application, the VUI specification comprising a plurality of expressions of possible user intentions composed by at least one VUI designer, the VUI specification further comprising, for each one of the plurality of expressions of possible user intentions, at least one system response or action defined by the at least one VUI designer as corresponding to the one of the plurality of expressions of possible user intentions; analyzing the VUI specification to determine a plurality of topic descriptions, each one of the plurality of topic descriptions describing a meaning of a corresponding one of the plurality of topics; and using, as training data, the plurality of topic descriptions determined by analyzing the VUI specification to build the statistical initial topic classification model, comprising; identifying keywords in the plurality of topic descriptions used as training data to build the statistical initial topic classification model; providing an optimal feature set comprising at least one combination of at least some of the keywords; and using at least one computer to build the statistical initial topic classification model based at least partially on the optimal feature set.
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1. A computer-implemented method for providing a statistical initial topic classification model for use in a natural language call routing application to map a natural language user statement to at least one of a plurality of topics in the natural language call routing application, the computer-implemented method comprising acts of: accessing a voice user interface (VUI) specification that specifies a VUI for allowing users to interact with the natural language call routing application, the VUI specification comprising a plurality of expressions of possible user intentions composed by at least one VUI designer, the VUI specification further comprising, for each one of the plurality of expressions of possible user intentions, at least one system response or action defined by the at least one VUI designer as corresponding to the one of the plurality of expressions of possible user intentions; analyzing the VUI specification to determine a plurality of topic descriptions, each one of the plurality of topic descriptions describing a meaning of a corresponding one of the plurality of topics; and using, as training data, the plurality of topic descriptions determined by analyzing the VUI specification to build the statistical initial topic classification model, comprising; identifying keywords in the plurality of topic descriptions used as training data to build the statistical initial topic classification model; providing an optimal feature set comprising at least one combination of at least some of the keywords; and using at least one computer to build the statistical initial topic classification model based at least partially on the optimal feature set. 7. The method of claim 1 , further comprising: filtering text data using the statistical initial topic classification model to produce filter output, the text data from a source other than the natural language call routing application; providing additional training data based at least in part on the filter output; and refining the statistical initial topic classification model using the additional training data.
| 0.540233 |
1. A method for optimizing sentiment classification, the method comprising: performing, by a sentiment management computing device, a classification analysis on a first post received for sentiment evaluation to determine a first sentiment classification; receiving, by the sentiment management computing device, a second sentiment classification related to the first post from at least one user; and updating, by the sentiment management computing device, the classification analysis when the first sentiment classification does not match the second sentiment classification, wherein the updating the sentiment classification analysis comprises: plotting the first post in a multidimensional feature space, wherein each dimension in the multidimensional feature space represents a unique feature corresponding to the first post; performing a neighborhood operation for the first post to identify a pattern space in the multidimensional feature space containing a plurality of posts associated with the first post; and applying the second sentiment classification to the plurality of posts in the pattern space, wherein the plurality of posts in the pattern space provide updated training data for the classification analysis.
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1. A method for optimizing sentiment classification, the method comprising: performing, by a sentiment management computing device, a classification analysis on a first post received for sentiment evaluation to determine a first sentiment classification; receiving, by the sentiment management computing device, a second sentiment classification related to the first post from at least one user; and updating, by the sentiment management computing device, the classification analysis when the first sentiment classification does not match the second sentiment classification, wherein the updating the sentiment classification analysis comprises: plotting the first post in a multidimensional feature space, wherein each dimension in the multidimensional feature space represents a unique feature corresponding to the first post; performing a neighborhood operation for the first post to identify a pattern space in the multidimensional feature space containing a plurality of posts associated with the first post; and applying the second sentiment classification to the plurality of posts in the pattern space, wherein the plurality of posts in the pattern space provide updated training data for the classification analysis. 4. The method as set forth in claim 1 , wherein performing the classification analysis further comprises: determining, by the sentiment management computing device, a complexity level of the first post; and performing, by the sentiment management computing device, the classification analysis based on the complexity level.
| 0.5 |
11. A method for searching for a satellite signal in a sieving mode in a satellite-based navigation receiver comprising: non-coherently integrating one or more coherent integrations of a correlation of the satellite signal with a plurality of first hypotheses to generate a plurality of non-coherent integrations; tracking the satellite signal to generate a plurality of tracked satellite signals; non-coherently integrating one or more coherent integrations of a correlation of the plurality of tracked satellite signals with a plurality of second hypotheses to generate a plurality of extended non-coherent integrations; comparing the plurality of non-coherent integrations and the plurality of extended non-coherent integrations to select a plurality of candidate hypotheses corresponding to a plurality of largest peaks from the plurality of non-coherent integrations and the plurality of extended non-coherent integrations; updating the plurality of second hypotheses with the plurality of candidate hypotheses to extend the non-coherent integrations or the extended non-coherent integrations corresponding to the plurality of candidate hypotheses; selecting a largest peak from the plurality of non-coherent integrations and the plurality of extended non-coherent integrations to compare with a detection threshold; and declaring a detection of the satellite signal when the largest peak exceeds the detection threshold.
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11. A method for searching for a satellite signal in a sieving mode in a satellite-based navigation receiver comprising: non-coherently integrating one or more coherent integrations of a correlation of the satellite signal with a plurality of first hypotheses to generate a plurality of non-coherent integrations; tracking the satellite signal to generate a plurality of tracked satellite signals; non-coherently integrating one or more coherent integrations of a correlation of the plurality of tracked satellite signals with a plurality of second hypotheses to generate a plurality of extended non-coherent integrations; comparing the plurality of non-coherent integrations and the plurality of extended non-coherent integrations to select a plurality of candidate hypotheses corresponding to a plurality of largest peaks from the plurality of non-coherent integrations and the plurality of extended non-coherent integrations; updating the plurality of second hypotheses with the plurality of candidate hypotheses to extend the non-coherent integrations or the extended non-coherent integrations corresponding to the plurality of candidate hypotheses; selecting a largest peak from the plurality of non-coherent integrations and the plurality of extended non-coherent integrations to compare with a detection threshold; and declaring a detection of the satellite signal when the largest peak exceeds the detection threshold. 14. The method of claim 11 , wherein the plurality of non-coherent integrations comprises a plurality of log likelihood ratios for the plurality of first hypotheses, wherein a log likelihood ratio for a first hypothesis comprises the natural logarithm of a ratio of a probability of a non-coherent integration conditioned on a presence of the satellite signal to a probability of the non-coherent integration conditioned on an absence of the satellite signal.
| 0.616604 |
15. A computing system, comprising: at least one processor; and at least one memory having computer-readable instructions that when executed by the at least one processor cause the computing system to perform a method, the method comprising: receiving a selection of textual content comprising at least a first line of text and a second line of text that are not included in a hierarchical graphic, wherein there is a hierarchical relationship between the first line of text and the second line of text; receiving a selection of a conversion command; generating the hierarchical graphic from the selected textual content, the hierarchical graphic comprising: at least a first graphical shape encapsulating the first line of text; and at least a second graphical shape encapsulating the second line of text, wherein there is a graphical hierarchical relationship between the first graphical shape and the second graphical shape that corresponds to the hierarchical relationship between the first line of text and the second line of text; and replacing the selected textual content with the hierarchical graphic.
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15. A computing system, comprising: at least one processor; and at least one memory having computer-readable instructions that when executed by the at least one processor cause the computing system to perform a method, the method comprising: receiving a selection of textual content comprising at least a first line of text and a second line of text that are not included in a hierarchical graphic, wherein there is a hierarchical relationship between the first line of text and the second line of text; receiving a selection of a conversion command; generating the hierarchical graphic from the selected textual content, the hierarchical graphic comprising: at least a first graphical shape encapsulating the first line of text; and at least a second graphical shape encapsulating the second line of text, wherein there is a graphical hierarchical relationship between the first graphical shape and the second graphical shape that corresponds to the hierarchical relationship between the first line of text and the second line of text; and replacing the selected textual content with the hierarchical graphic. 20. The computing system of claim 15 , further comprising: substantially simultaneously displaying the hierarchical graphic with the selected textual content; receiving edits to the selected textual content; and in response to receiving the edits, displaying edits to the hierarchical graphic that correspond to the edits to the selected textual content.
| 0.5 |
1. A speech recognition device comprising: a processor; and a memory which stores a plurality of instructions, which when executed by the processor, cause the processor to execute, conducting a search, by speech recognition, on audio data stored in a first memory to extract wordspoken portions where plural words transferred are each spoken and, of the word-spoken portions extracted, rejects the word-spoken portion for the word designated as a rejecting object; obtaining a derived word of a designated search target word, the derived word being generated in accordance with a derived word generation rule stored in a second memory or read out from the second memory where the derived word is stored in association with the search target word, and sets the derived word to an outputting object or the rejecting object according to setting designation information or a user's instruction, the setting designation information being stored in the second memory and indicating whether the derived word is the outputting object or the rejecting object; transferring the derived word and the search target word to the conducting, the derived word being obtained and set to the outputting object or the rejecting object by the obtaining; and outputting the word-spoken portion extracted and not rejected in the search of the conducting, wherein the derived word generation rule is generated based on a difference between the search target word and a derived word that is stored in the second memory.
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1. A speech recognition device comprising: a processor; and a memory which stores a plurality of instructions, which when executed by the processor, cause the processor to execute, conducting a search, by speech recognition, on audio data stored in a first memory to extract wordspoken portions where plural words transferred are each spoken and, of the word-spoken portions extracted, rejects the word-spoken portion for the word designated as a rejecting object; obtaining a derived word of a designated search target word, the derived word being generated in accordance with a derived word generation rule stored in a second memory or read out from the second memory where the derived word is stored in association with the search target word, and sets the derived word to an outputting object or the rejecting object according to setting designation information or a user's instruction, the setting designation information being stored in the second memory and indicating whether the derived word is the outputting object or the rejecting object; transferring the derived word and the search target word to the conducting, the derived word being obtained and set to the outputting object or the rejecting object by the obtaining; and outputting the word-spoken portion extracted and not rejected in the search of the conducting, wherein the derived word generation rule is generated based on a difference between the search target word and a derived word that is stored in the second memory. 4. The device according to claim 1 , wherein the processor presents the derived word, and sets the derived word presented to the outputting object or the rejecting object based on an instruction.
| 0.648588 |
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