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1. A computerized method for automatically sectioning an audio signal of an interaction held in a call center, into sections representing the flow of the interaction, the method comprising the steps of: receiving at least a part of the audio signal from a logging and capturing unit comprising a computing platform and associated with the call center, the at least a part of the audio signal comprises a non-training production run-time interaction; performing audio analysis on the at least a part of the audio signal for obtaining run-time data; segmenting the at least a part of the audio signal into at least one context unit; extracting a feature vector as a multi-valued construct comprising at least one run-time feature of the at least one context unit, using the run-time data; classifying the at least one context unit using a sectioning model and the feature vector, to obtain at least one section label to be associated with the at least one context unit; and subsequently grouping context units assigned identical labels into one section, wherein the method is carried out by an at least one processing apparatus.
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1. A computerized method for automatically sectioning an audio signal of an interaction held in a call center, into sections representing the flow of the interaction, the method comprising the steps of: receiving at least a part of the audio signal from a logging and capturing unit comprising a computing platform and associated with the call center, the at least a part of the audio signal comprises a non-training production run-time interaction; performing audio analysis on the at least a part of the audio signal for obtaining run-time data; segmenting the at least a part of the audio signal into at least one context unit; extracting a feature vector as a multi-valued construct comprising at least one run-time feature of the at least one context unit, using the run-time data; classifying the at least one context unit using a sectioning model and the feature vector, to obtain at least one section label to be associated with the at least one context unit; and subsequently grouping context units assigned identical labels into one section, wherein the method is carried out by an at least one processing apparatus. 8. The method of claim 1 further comprising a sectioning training step for generating the sectioning model.
| 0.745368 |
13. A computer program product comprising a computer recordable medium having a computer readable program recorded thereon, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive a hierarchical query; separate the hierarchical query into a plurality of query legs; perform an index scan for evaluating the hierarchical query against at least one index of at least one hierarchically structured electronic document by processing a query leg on the at least one index of the at least one hierarchically structured electronic document to determine if a condition of the query leg is met by at least one node in the at least one index of the at least one hierarchically structured electronic document, wherein if at least one node in the at least one index of the at least one hierarchically structured electronic document satisfies the condition of the query leg, an entry in at least one hash table is populated with information regarding the at least one node; generate results of the hierarchical query based on content of the at least one hash table; and return the results of the hierarchical query to an originator of the hierarchical query, wherein the at least one hash table comprises a BUILD hash table and a PROBE hash table, wherein the BUILD hash table is used to store document nodes matching a predicate of the query leg and to buffer document nodes satisfying extraction nodes of the query leg, and wherein the PROBE hash table stores document nodes satisfying predicates from query legs evaluated prior to a current query leg being evaluated.
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13. A computer program product comprising a computer recordable medium having a computer readable program recorded thereon, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive a hierarchical query; separate the hierarchical query into a plurality of query legs; perform an index scan for evaluating the hierarchical query against at least one index of at least one hierarchically structured electronic document by processing a query leg on the at least one index of the at least one hierarchically structured electronic document to determine if a condition of the query leg is met by at least one node in the at least one index of the at least one hierarchically structured electronic document, wherein if at least one node in the at least one index of the at least one hierarchically structured electronic document satisfies the condition of the query leg, an entry in at least one hash table is populated with information regarding the at least one node; generate results of the hierarchical query based on content of the at least one hash table; and return the results of the hierarchical query to an originator of the hierarchical query, wherein the at least one hash table comprises a BUILD hash table and a PROBE hash table, wherein the BUILD hash table is used to store document nodes matching a predicate of the query leg and to buffer document nodes satisfying extraction nodes of the query leg, and wherein the PROBE hash table stores document nodes satisfying predicates from query legs evaluated prior to a current query leg being evaluated. 19. The computer program product of claim 13 , wherein each query leg is a linear hierarchy.
| 0.589464 |
7. A system for managing data, comprising: a network computer, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: employing a source data server to provide a principal data set of principal objects and another data set of other data objects; instantiating a first engine to perform actions including: associating one or more principal objects with one or more other objects that are selected as potential matches to the one or more of the principal objects; and identifying each match and non-match of the one or more of the selected other objects with their associated principal object; and instantiating a second engine to train and employ a ranker to identify a matched other object that is top-ranked in similarity by its association with the one or more principal objects; and instantiating a third engine to selectively filter the other objects to rank each matched other object higher than other objects associated with a same principal object; and employing geolocation information from a Global Positioning System (GPS) device at a client computer to determine one or more features that are included in a display of the ranked other objects to a user to improve the user's understanding of the ranked other objects, wherein the features include one or more of time zones, languages, currencies, or calendar formatting that is displayed to the user of the client computer when the client computer is located at a particular geo-location; and the client computer, comprising: a GPS device; a client computer transceiver that communicates over the network; a client computer memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: providing the display of the ranked other objects to the user.
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7. A system for managing data, comprising: a network computer, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: employing a source data server to provide a principal data set of principal objects and another data set of other data objects; instantiating a first engine to perform actions including: associating one or more principal objects with one or more other objects that are selected as potential matches to the one or more of the principal objects; and identifying each match and non-match of the one or more of the selected other objects with their associated principal object; and instantiating a second engine to train and employ a ranker to identify a matched other object that is top-ranked in similarity by its association with the one or more principal objects; and instantiating a third engine to selectively filter the other objects to rank each matched other object higher than other objects associated with a same principal object; and employing geolocation information from a Global Positioning System (GPS) device at a client computer to determine one or more features that are included in a display of the ranked other objects to a user to improve the user's understanding of the ranked other objects, wherein the features include one or more of time zones, languages, currencies, or calendar formatting that is displayed to the user of the client computer when the client computer is located at a particular geo-location; and the client computer, comprising: a GPS device; a client computer transceiver that communicates over the network; a client computer memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: providing the display of the ranked other objects to the user. 9. The system of claim 7 , further comprising employing a hardware security module to provide tamper resistant safeguarding of cryptographic information.
| 0.642424 |
7. A computer based system for predicting a data value, said system comprising: a processor capable of executing machine instructions; the machine instructions including a means for predicting a predicted data value of a first data set at a predicted dimension value utilizing a focus topic profile; and the means for predicting the predicted data value further comprises a modeling package capable of: receiving a base dimension value having a base focus topic value; receiving a predicted dimension value having a difference dimension value from the base dimension value; analyzing the focus topic profile over at least one dimension value to identify a most similar focus topic value to the base focus topic value; the dimension value at the most similar focus topic value being a selected dimension value; and selecting at least one data value from the first data set at the difference dimension value from the selected dimension value as the predicted data value at the predicted dimension value.
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7. A computer based system for predicting a data value, said system comprising: a processor capable of executing machine instructions; the machine instructions including a means for predicting a predicted data value of a first data set at a predicted dimension value utilizing a focus topic profile; and the means for predicting the predicted data value further comprises a modeling package capable of: receiving a base dimension value having a base focus topic value; receiving a predicted dimension value having a difference dimension value from the base dimension value; analyzing the focus topic profile over at least one dimension value to identify a most similar focus topic value to the base focus topic value; the dimension value at the most similar focus topic value being a selected dimension value; and selecting at least one data value from the first data set at the difference dimension value from the selected dimension value as the predicted data value at the predicted dimension value. 10. The computer based system of claim 7 wherein the wherein the focus topic profile comprises a focus topic profile of news data related to the first data set over a dimension including at least the selected dimension value.
| 0.618673 |
5. A system according to claim 1 , further comprising: a cluster mapping module to map one such document to one of the clusters based on a similarity of the document to the documents in the cluster, wherein the distance is quantified by a distance.
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5. A system according to claim 1 , further comprising: a cluster mapping module to map one such document to one of the clusters based on a similarity of the document to the documents in the cluster, wherein the distance is quantified by a distance. 6. A system according to claim 5 , further comprising: a distance determination module to calculate the distance using the following equation: d cluster = ∑ i -> n doc term i · cluster term i where doc term represents a frequency of occurrence for a given term i in the one such document and cluster term represents the weight of a given cluster for a given term i.
| 0.844099 |
41. The machine-implemented method of claim 40 wherein the matrix W is an M×N matrix where M is the number of instances, N is the maximum number of segment samples corresponding to an instance, wherein constructing the matrix W comprises inputting the numbers of segment samples corresponding to the instances.
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41. The machine-implemented method of claim 40 wherein the matrix W is an M×N matrix where M is the number of instances, N is the maximum number of segment samples corresponding to an instance, wherein constructing the matrix W comprises inputting the numbers of segment samples corresponding to the instances. 42. The machine-implemented method of claim 41 wherein the matrix W is zero padded to N samples.
| 0.937589 |
3. The computer-implemented method of claim 1 , further comprising: for each of a plurality of categories in the taxonomy, receiving, feature set-feature set correlation scores between the contributing feature sets and a feature set obtained from a person; and combining the feature set-feature set correlation scores to obtain a category-feature set score indicating the relevance of the category under consideration to the feature set obtained from the person; and determining whether the person is likely to have the disease or the phenotype by comparing the category-feature set score to a criterion.
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3. The computer-implemented method of claim 1 , further comprising: for each of a plurality of categories in the taxonomy, receiving, feature set-feature set correlation scores between the contributing feature sets and a feature set obtained from a person; and combining the feature set-feature set correlation scores to obtain a category-feature set score indicating the relevance of the category under consideration to the feature set obtained from the person; and determining whether the person is likely to have the disease or the phenotype by comparing the category-feature set score to a criterion. 9. The computer-implemented method of claim 3 , further comprising generating the feature set obtained from the person from raw data from a biological sample of the person, wherein the raw data includes information on one or more features with indications of one or more of: differential expression, abundance of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems.
| 0.887306 |
15. The system of claim 8 wherein the controlled vocabulary contains terms of metadata and an electronic thesaurus relates one metadata term to search terms, specific values or other user-specified indicators, wherein the electronic thesaurus comprises equivalent terms.
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15. The system of claim 8 wherein the controlled vocabulary contains terms of metadata and an electronic thesaurus relates one metadata term to search terms, specific values or other user-specified indicators, wherein the electronic thesaurus comprises equivalent terms. 16. The system of claim 15 wherein the request for environmental information further comprises a keyword, specific value or other user-specified indicator which is related by the electronic thesaurus to a metadata.
| 0.953342 |
2. The method of claim 1 , wherein generating a second search query that includes (i) one or more query terms that refer to a category including the object, and (ii) one or query terms that identify the viewpoint in which the object is to appear in images that are identified in response to the first search query, comprises: determining the category associated with the object based at least on the first search query; and determining one or more query terms that are not included in the first search query and that refer to the category.
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2. The method of claim 1 , wherein generating a second search query that includes (i) one or more query terms that refer to a category including the object, and (ii) one or query terms that identify the viewpoint in which the object is to appear in images that are identified in response to the first search query, comprises: determining the category associated with the object based at least on the first search query; and determining one or more query terms that are not included in the first search query and that refer to the category. 3. The method of claim 2 , wherein determining the category associated with the object based at least on the first search query, comprises: identifying the category associated with one or more query terms associated with the object in the first search query based at least on one or more terms in the first search query that refer to the object and that are different than the one or more query terms that identify the viewpoint in which the object is to appear in images.
| 0.826231 |
8. A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving an input comprising a plurality of features of a resource, wherein each of the features is of a different feature type; generating an alternative representation of the features of the resource, comprising: generating a respective numeric representation of each the features by processing each of the features using a respective embedding function, wherein each of the embedding functions is specific to features of a respective feature type, and processing the respective numeric representations through one or more neural network layers to generate the alternative representation; and providing the alternative representation of the features of the resource as input to a neural network classifier for classification of a relevance of a plurality of concept terms to the resource.
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8. A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving an input comprising a plurality of features of a resource, wherein each of the features is of a different feature type; generating an alternative representation of the features of the resource, comprising: generating a respective numeric representation of each the features by processing each of the features using a respective embedding function, wherein each of the embedding functions is specific to features of a respective feature type, and processing the respective numeric representations through one or more neural network layers to generate the alternative representation; and providing the alternative representation of the features of the resource as input to a neural network classifier for classification of a relevance of a plurality of concept terms to the resource. 10. The system of claim 8 , wherein the numeric representations are vectors of floating point values.
| 0.638741 |
11. A system comprising: a memory; and a processing device coupled with the memory to: cause display of a user interface having a threshold portion associated with a key performance indicator (KPI), the KPI defined by a search query that derives a value from machine data associated with one or more entities that provide a service, the threshold portion enabling a user to indicate one or more thresholds for the KPI and to indicate a per-entity application of the thresholds, each threshold corresponding to a different one of a plurality of KPI states; receive an indication of the thresholds and of the per-entity application of the thresholds in response to user interaction with the user interface; and store the thresholds in association with a definition of the KPI in accordance with the received indication such that a determining of a KPI state from among a plurality of KPI states is made, for an execution of the search query, on a per-entity basis for at least one of the entities in accordance with the thresholds.
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11. A system comprising: a memory; and a processing device coupled with the memory to: cause display of a user interface having a threshold portion associated with a key performance indicator (KPI), the KPI defined by a search query that derives a value from machine data associated with one or more entities that provide a service, the threshold portion enabling a user to indicate one or more thresholds for the KPI and to indicate a per-entity application of the thresholds, each threshold corresponding to a different one of a plurality of KPI states; receive an indication of the thresholds and of the per-entity application of the thresholds in response to user interaction with the user interface; and store the thresholds in association with a definition of the KPI in accordance with the received indication such that a determining of a KPI state from among a plurality of KPI states is made, for an execution of the search query, on a per-entity basis for at least one of the entities in accordance with the thresholds. 20. The system of claim 11 wherein the machine data are represented as stored event instances each having a segment of raw machine data.
| 0.921445 |
1. A computer-implemented method of synthesizing speech from text, the method comprising: inputting text to be synthesized to a computerized system; electronically marking the text with electronic versions of one or more prosodic graphical symbols, the electronically marked text being displayable or printable as human-readable text marked with the prosodic graphical symbols, to indicate to a speaker desired speech characteristics to be employed in speaking the text, wherein the prosodic graphical symbols indicate a desired prosody and include intelligibility pronunciation notations in sequence with the text and pitch change notations in sequence with the text; and generating a synthesized speech output comprising phonetic data corresponding with the marked up text and having the prosody indicated by the prosodic graphical symbols.
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1. A computer-implemented method of synthesizing speech from text, the method comprising: inputting text to be synthesized to a computerized system; electronically marking the text with electronic versions of one or more prosodic graphical symbols, the electronically marked text being displayable or printable as human-readable text marked with the prosodic graphical symbols, to indicate to a speaker desired speech characteristics to be employed in speaking the text, wherein the prosodic graphical symbols indicate a desired prosody and include intelligibility pronunciation notations in sequence with the text and pitch change notations in sequence with the text; and generating a synthesized speech output comprising phonetic data corresponding with the marked up text and having the prosody indicated by the prosodic graphical symbols. 9. A method according to claim 1 comprising marking up the text to be spoken by rendering the text in lines, marking the intelligibility pronunciation notations above the text, marking the prosodic graphical symbols beneath the text, marking a pitch reference line above the intelligibility pronunciation notation line and marking further prosodic symbols above the pitch reference line to indicate desired pitch changes and emphasis.
| 0.793217 |
8. A system comprising: one or more processor-implemented modules comprising: a plurality of format converters specific to a plurality of respective external document formats and configured to convert a human-readable publication document received in one of the external document formats into a common intermediate mark-up-language format, the document comprising a plurality of visually perceptible document parts and the converting being based on the visually perceptible document parts as reflected in visual clues of the document in the external format; a content parser configured to convert the document from the intermediate mark-up-language format to an internal format by parsing the document in the intermediate mark-up-language format to dissect the document, based on a plurality of document-element types associated with the internal format, into a plurality of document elements collectively constituting the contents of the document, and representing the document in the internal format, in multiple views of the document that differ in at least one of a selection of document elements or an ordering of document elements, by causing a document-element entry for each of the document elements and multiple document-view data structures for respective ones of the multiple views of the document to be stored in one or more databases, each document-element entry comprising a unique document-element identifier and one or more document-element attributes characterizing a content of the respective document element and each document-view data structure comprising an ordered list of document-element identifiers of at least a non-null subset of the document elements.
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8. A system comprising: one or more processor-implemented modules comprising: a plurality of format converters specific to a plurality of respective external document formats and configured to convert a human-readable publication document received in one of the external document formats into a common intermediate mark-up-language format, the document comprising a plurality of visually perceptible document parts and the converting being based on the visually perceptible document parts as reflected in visual clues of the document in the external format; a content parser configured to convert the document from the intermediate mark-up-language format to an internal format by parsing the document in the intermediate mark-up-language format to dissect the document, based on a plurality of document-element types associated with the internal format, into a plurality of document elements collectively constituting the contents of the document, and representing the document in the internal format, in multiple views of the document that differ in at least one of a selection of document elements or an ordering of document elements, by causing a document-element entry for each of the document elements and multiple document-view data structures for respective ones of the multiple views of the document to be stored in one or more databases, each document-element entry comprising a unique document-element identifier and one or more document-element attributes characterizing a content of the respective document element and each document-view data structure comprising an ordered list of document-element identifiers of at least a non-null subset of the document elements. 10. The system of claim 8 , wherein the content parser is further configured to extract metadata from the document when parsing the document, and to cause the extracted metadata to be stored in a database of metadata.
| 0.709932 |
8. The method as recited in claim 6 , further comprising determining a popularity ranking of a media item in the media domain based at least in part on the updated topic space.
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8. The method as recited in claim 6 , further comprising determining a popularity ranking of a media item in the media domain based at least in part on the updated topic space. 9. The method as recited in claim 8 , wherein the popularity ranking of the media item is further determined based on a view count of the media item.
| 0.931818 |
1. An automated method for facilitating a compliance audit, the method comprising: accessing a database, the database including a rule set formulated from at least one requirement, wherein the database includes a knowledge base; at a data processing system, accepting input regarding circumstance data, the circumstance data regarding a subject of the at least one requirement; automatically applying the rule set to the input regarding circumstance data, by the data processing system; and automatically generating a compliance audit report by the data processing system, the compliance audit report based on applying the rule set to the input regarding circumstance data; wherein the circumstance data comprises: product class data to identify a general class of products for an item of manufacture; and at least one item from the group consisting of: product type data to identify a more specific type of product, within the general class of products, for the item of manufacture; product attribute data to identify a property of the item of manufacture; and customer data to identify a type of customer for the item of manufacture.
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1. An automated method for facilitating a compliance audit, the method comprising: accessing a database, the database including a rule set formulated from at least one requirement, wherein the database includes a knowledge base; at a data processing system, accepting input regarding circumstance data, the circumstance data regarding a subject of the at least one requirement; automatically applying the rule set to the input regarding circumstance data, by the data processing system; and automatically generating a compliance audit report by the data processing system, the compliance audit report based on applying the rule set to the input regarding circumstance data; wherein the circumstance data comprises: product class data to identify a general class of products for an item of manufacture; and at least one item from the group consisting of: product type data to identify a more specific type of product, within the general class of products, for the item of manufacture; product attribute data to identify a property of the item of manufacture; and customer data to identify a type of customer for the item of manufacture. 8. The method of claim 1 , wherein the operation of accepting input regarding circumstance data comprises: accepting the input regarding circumstance data according to a data-driven approach.
| 0.770121 |
10. A computer-implemented method, comprising: providing a pipelined algorithm to train deep neural networks (DNNs) for performing data analysis based on training data, the DNNs being one of context-dependent DNNs or context-independent DNNs and including multiple layers; determining that a ratio between a size of a top layer and a size of one or more of the multiple layers exceeds a predetermined threshold; based at least in part on the determining, distributing the top layer of the DNNs across multiple processors through model striping for parallelized processing by the pipelined algorithm; and pipelining an execution of the pipelined algorithm on the DNNs through the multiple processors to train the DNNs using sample batches of the training data.
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10. A computer-implemented method, comprising: providing a pipelined algorithm to train deep neural networks (DNNs) for performing data analysis based on training data, the DNNs being one of context-dependent DNNs or context-independent DNNs and including multiple layers; determining that a ratio between a size of a top layer and a size of one or more of the multiple layers exceeds a predetermined threshold; based at least in part on the determining, distributing the top layer of the DNNs across multiple processors through model striping for parallelized processing by the pipelined algorithm; and pipelining an execution of the pipelined algorithm on the DNNs through the multiple processors to train the DNNs using sample batches of the training data. 11. The computer-implemented method of claim 10 , further comprising partitioning the training data into the sample batches having a specific batch size based on rates of data transfers between the multiple processors for executing the pipelined algorithm and an execution speed of each of the multiple processors.
| 0.785944 |
18. The method of claim 1 wherein publishing the remaining content items includes using an auction that determines the order of the remaining content items based at least in part on social quality scores.
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18. The method of claim 1 wherein publishing the remaining content items includes using an auction that determines the order of the remaining content items based at least in part on social quality scores. 19. The method of claim 18 wherein the auction further includes using the display sizes of content items to rank a first content item with a smaller display size over a second content item with a larger display size.
| 0.901605 |
6. The system as recited in claim 1 , further comprising: providing a set of images representing conjunction of the first word and the second word, the set of images comprising a third plurality of images, wherein estimating the correlation between the first word and second word is further based on visual features of the set of images representing conjunction of the first word and the second word.
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6. The system as recited in claim 1 , further comprising: providing a set of images representing conjunction of the first word and the second word, the set of images comprising a third plurality of images, wherein estimating the correlation between the first word and second word is further based on visual features of the set of images representing conjunction of the first word and the second word. 8. The system as recited in claim 6 , wherein providing the set of images representing conjunction of the first word and the second word comprises: performing an image search using the first word and the second word as a conjunctive query word; and selecting a fourth plurality of images from search results.
| 0.888952 |
9. The apparatus of claim 8 , wherein the property has a linear temporal logic form pv 1 U pv 2 , where pv represents a proportional variable.
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9. The apparatus of claim 8 , wherein the property has a linear temporal logic form pv 1 U pv 2 , where pv represents a proportional variable. 10. The apparatus of claim 9 , wherein the auxiliary property has a linear temporal logic form pv 3 U pv 2 , where pv 3 represents the condition.
| 0.943985 |
3. The system of claim 1 , the relevance component employs a product summation based on selection of an á priori probabilistic relationship.
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3. The system of claim 1 , the relevance component employs a product summation based on selection of an á priori probabilistic relationship. 4. The system of claim 3 , the product summation based on naïve Bayesian modeling and/or N-gram feature modeling.
| 0.956455 |
6. The method of claim 1 wherein said electronic database provides for download of at least one music clip associated with said food product.
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6. The method of claim 1 wherein said electronic database provides for download of at least one music clip associated with said food product. 7. The method of claim 6 wherein said music clip of claim 6 is the auditory phrase played concurrently with tasting the food product.
| 0.934888 |
3. The method of claim 1 , further comprising: accessing the plurality of expertise levels that are associated with each of the plurality of computer-implemented objects, wherein the computer-implemented objects comprise text-based information.
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3. The method of claim 1 , further comprising: accessing the plurality of expertise levels that are associated with each of the plurality of computer-implemented objects, wherein the computer-implemented objects comprise text-based information. 4. The method of claim 3 , further comprising: accessing the plurality of expertise levels that are associated with each of the plurality of computer-implemented objects, wherein the plurality of expertise values are automatically inferred from the text-based information.
| 0.903123 |
4. A method comprising: engaging in a speech dialog with a user to determine an intent of the user, wherein engaging in the speech dialog comprises engaging in a first dialog turn and, a second dialog turn, and a third dialog turn with the user; wherein engaging in the first dialog turn comprises: receiving a first audio signal produced by a first device, the first audio signal representing first user speech; and determining, based at least in part on providing the first audio signal to a speech service, a first meaning of the first user speech; wherein engaging in the second dialog turn comprises: receiving a second audio signal that is produced using a microphone of a second device, the second audio signal representing second user speech; and determining, based at least in part on providing the second audio signal to the speech service, a second meaning of the second user speech based; and wherein engaging in the third dialog turn comprises: receiving, based at least in part on an actuation of a talk control of the first device within a predefined time period after engaging in the second dialog turn, a third audio signal from the first device, the third audio signal representing third user speech; and determining a third meaning of the third user speech.
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4. A method comprising: engaging in a speech dialog with a user to determine an intent of the user, wherein engaging in the speech dialog comprises engaging in a first dialog turn and, a second dialog turn, and a third dialog turn with the user; wherein engaging in the first dialog turn comprises: receiving a first audio signal produced by a first device, the first audio signal representing first user speech; and determining, based at least in part on providing the first audio signal to a speech service, a first meaning of the first user speech; wherein engaging in the second dialog turn comprises: receiving a second audio signal that is produced using a microphone of a second device, the second audio signal representing second user speech; and determining, based at least in part on providing the second audio signal to the speech service, a second meaning of the second user speech based; and wherein engaging in the third dialog turn comprises: receiving, based at least in part on an actuation of a talk control of the first device within a predefined time period after engaging in the second dialog turn, a third audio signal from the first device, the third audio signal representing third user speech; and determining a third meaning of the third user speech. 16. The method of claim 4 , wherein, based at least in part on the first dialogue turn and the second dialogue turn, the speech service is configured to cause an action to be performed to fulfill the intent of the user.
| 0.763178 |
35. A method of processing a search query comprising: processing a number of sample web pages to generate network data indicative of the interconnections between the sample web pages as identified by hyperlinks included in the sample web pages; processing the generated network data to determine for each web page a value indicative of the number of hyperlinks in the shortest path between the web page and the other web pages in the sample; generating a ranked index of web pages ranked utilizing the determined values; receiving a search query; and outputting a results list in response to receipt of the search query identifying a number of web pages wherein the results list is ordered on the basis of the ranked index.
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35. A method of processing a search query comprising: processing a number of sample web pages to generate network data indicative of the interconnections between the sample web pages as identified by hyperlinks included in the sample web pages; processing the generated network data to determine for each web page a value indicative of the number of hyperlinks in the shortest path between the web page and the other web pages in the sample; generating a ranked index of web pages ranked utilizing the determined values; receiving a search query; and outputting a results list in response to receipt of the search query identifying a number of web pages wherein the results list is ordered on the basis of the ranked index. 36. The method of claim 35 wherein the value indicative of the shortest path between the web page and the other web pages in the sample comprises determining the number of hyperlinks in the shortest path from the current web page to another web in the sample of web pages which has the greatest number of links.
| 0.771925 |
9. One or more non-transitory computer-readable media storing instructions, which when executed by one or more hardware processors cause: receiving a first set of data comprising a plurality of unstructured data records; receiving a schema that describes characteristics of the plurality of unstructured data records and relationships between one or more data records of the plurality of unstructured data records; storing a first set of data using a first system, wherein the first system comprises a schema that describes objects and properties in the first set of data; generating, based on the first set of data and the schema, a first plurality of structured data records, wherein the first plurality of structured data records organizes the plurality of unstructured data records based on the schema; causing to be displayed, at a client computing device, the first plurality of structured data records; receiving schema modification instructions; in response to receiving the schema modification instructions, modifying the schema based on the schema modification instructions; generating, based on the modified schema and the first set of data, a second plurality of structured data records, wherein the second plurality of structured data records organizes the plurality of unstructured data records based on modified schema; in response to receiving the schema modification instructions, causing to be displayed, at the client computing device, the second plurality of structured data records.
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9. One or more non-transitory computer-readable media storing instructions, which when executed by one or more hardware processors cause: receiving a first set of data comprising a plurality of unstructured data records; receiving a schema that describes characteristics of the plurality of unstructured data records and relationships between one or more data records of the plurality of unstructured data records; storing a first set of data using a first system, wherein the first system comprises a schema that describes objects and properties in the first set of data; generating, based on the first set of data and the schema, a first plurality of structured data records, wherein the first plurality of structured data records organizes the plurality of unstructured data records based on the schema; causing to be displayed, at a client computing device, the first plurality of structured data records; receiving schema modification instructions; in response to receiving the schema modification instructions, modifying the schema based on the schema modification instructions; generating, based on the modified schema and the first set of data, a second plurality of structured data records, wherein the second plurality of structured data records organizes the plurality of unstructured data records based on modified schema; in response to receiving the schema modification instructions, causing to be displayed, at the client computing device, the second plurality of structured data records. 10. The one or more non-transitory computer-readable media of claim 9 , the instructions further comprising instructions, which when executed by one or more hardware processors cause: extracting a second set of data from one or more data sources; and applying a data modification rule to the second set of data to generate, at least in part, the first set of data.
| 0.5 |
15. An apparatus comprising: a processor, and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive, by a natural language processing pipeline configured to execute in the data processing system, an input document to be ingested into a corpus; divide, by the natural language processing pipeline, the input document into a plurality of input passages; identify, by a filter component of the natural language processing pipeline, whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts, wherein identifying whether a given input passage is a nonsense passage comprises: annotating, by an annotator in the natural language processing pipeline, the given input passage within the plurality of input passages with linguistic features to form an annotated passage; counting, by metric counters component in the natural language processing pipeline, a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts; determining, by the metric counters component of the natural language processing pipeline, a value for a metric based on the set of feature counts; and comparing, by a comparator component of the natural language processing pipeline, the value for the metric to a predetermined model threshold; filter, by the natural language processing pipeline, each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages; and add, by the natural language processing pipeline, the filtered plurality of input passages into the corpus.
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15. An apparatus comprising: a processor, and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive, by a natural language processing pipeline configured to execute in the data processing system, an input document to be ingested into a corpus; divide, by the natural language processing pipeline, the input document into a plurality of input passages; identify, by a filter component of the natural language processing pipeline, whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts, wherein identifying whether a given input passage is a nonsense passage comprises: annotating, by an annotator in the natural language processing pipeline, the given input passage within the plurality of input passages with linguistic features to form an annotated passage; counting, by metric counters component in the natural language processing pipeline, a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts; determining, by the metric counters component of the natural language processing pipeline, a value for a metric based on the set of feature counts; and comparing, by a comparator component of the natural language processing pipeline, the value for the metric to a predetermined model threshold; filter, by the natural language processing pipeline, each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages; and add, by the natural language processing pipeline, the filtered plurality of input passages into the corpus. 16. The apparatus of claim 15 , wherein filtering each input passage comprises removing a given input passage responsive to the given input passage being identified as a nonsense passage.
| 0.647059 |
11. The system as in claim 10 wherein said query engine means include means for providing a conditions window to permit a user to specify a list of conditions on any of the available objects.
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11. The system as in claim 10 wherein said query engine means include means for providing a conditions window to permit a user to specify a list of conditions on any of the available objects. 12. The system as in claim 11 wherein said query engine means includes means for providing a sorts window to permit a user to introduce a sort on a list of objects.
| 0.962316 |
1. A method for constructing and utilizing an ontological graph, the method comprising: receiving, by one or more processors, a seed term from a user; receiving, by one or more processors, a first expansion signal from the user; in response to receiving the first expansion signal, automatically generating, by one or more processors, an ontological graph that includes nodes representing the seed term plus other terms that are located in accordance with instructions derived from the first expansion signal, wherein the seed term and the other terms share a common trait; displaying, by one or more processors, terms from the ontological graph as string literals in a dictionary, wherein the dictionary contains related other terms at a resolution level that is controlled by the first expansion signal from the user and the seed term, wherein the first expansion signal causes additional nodes to be identified for the ontological graph, wherein the dictionary is an original dictionary that contains the seed term, wherein the first expansion signal further causes terms represented by the additional nodes to populate an expanded dictionary, and wherein the expanded dictionary is expanded from the original dictionary in which the seed term was located; receiving, by one or more processors, a second expansion signal from the user; and in response to receiving the second expansion signal, expanding, by one or more processors, the ontological graph to display additional terms that are related to the nodes that are represented in the ontological graph that was generated by the first expansion signal.
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1. A method for constructing and utilizing an ontological graph, the method comprising: receiving, by one or more processors, a seed term from a user; receiving, by one or more processors, a first expansion signal from the user; in response to receiving the first expansion signal, automatically generating, by one or more processors, an ontological graph that includes nodes representing the seed term plus other terms that are located in accordance with instructions derived from the first expansion signal, wherein the seed term and the other terms share a common trait; displaying, by one or more processors, terms from the ontological graph as string literals in a dictionary, wherein the dictionary contains related other terms at a resolution level that is controlled by the first expansion signal from the user and the seed term, wherein the first expansion signal causes additional nodes to be identified for the ontological graph, wherein the dictionary is an original dictionary that contains the seed term, wherein the first expansion signal further causes terms represented by the additional nodes to populate an expanded dictionary, and wherein the expanded dictionary is expanded from the original dictionary in which the seed term was located; receiving, by one or more processors, a second expansion signal from the user; and in response to receiving the second expansion signal, expanding, by one or more processors, the ontological graph to display additional terms that are related to the nodes that are represented in the ontological graph that was generated by the first expansion signal. 2. The method of claim 1 , further comprising: in response to receiving the second expansion signal, expanding, by one or more processors, the dictionary to include related terms for at least one of said terms from the ontological graph, wherein the related terms describe said at least one of said terms from the ontological graph, and wherein the dictionary is expanded to include the related terms in accordance with instructions derived from the second expansion signal.
| 0.536297 |
1. A system for executing search queries on a database comprising a plurality of documents, each search query having a search query operator and at least one search data element, the system comprising: a search query manager that receives a search query including at least one search query operator and at least one search data element associated therewith to be operated on by the search query operator; a storage structure that stores associations between search query operators and query node creators, each query node creator for creating a query node that executes a search query for a search query operator upon at least one search data element associated therewith, to identify a next document therein as a function of the search query operator and the at least one search data element of the search query, and returning an identifier of the document, and a score for the document; a parser, coupled to the storage structure and further coupled to the search query manager for receiving therefrom the search query, the parser identifying each search query operator and search data element in the search query, and for each search query operator in the search query, identifying the query node creator associated with the search query operator and calling the associated query node creator to create a query node for the search query operator and the search data element associated therewith; and a processor, coupled to the parser, and receiving therefrom a first query node, and executing the first query node.
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1. A system for executing search queries on a database comprising a plurality of documents, each search query having a search query operator and at least one search data element, the system comprising: a search query manager that receives a search query including at least one search query operator and at least one search data element associated therewith to be operated on by the search query operator; a storage structure that stores associations between search query operators and query node creators, each query node creator for creating a query node that executes a search query for a search query operator upon at least one search data element associated therewith, to identify a next document therein as a function of the search query operator and the at least one search data element of the search query, and returning an identifier of the document, and a score for the document; a parser, coupled to the storage structure and further coupled to the search query manager for receiving therefrom the search query, the parser identifying each search query operator and search data element in the search query, and for each search query operator in the search query, identifying the query node creator associated with the search query operator and calling the associated query node creator to create a query node for the search query operator and the search data element associated therewith; and a processor, coupled to the parser, and receiving therefrom a first query node, and executing the first query node. 4. The computer system of claim 1, further comprising: a) a query node base class, including: i) a search data element member for storing at least one search data element; and, ii) a search function member accepting an input including a first document number, the search function member for searching the database to retrieve a document having a second document number greater than the first document number, and a non-zero document score, and to return the non-zero document score and the second document number; b) at least one query node class derived from the query node base class; c) a query node creator base class including: a query data element member that stores at least one query data element including either a search data element or a subordinate query node; the query node creator base class returning a query node having as a search data element the query data element in response to an invocation of a constructor function of the query node creator base class by the parser; and d) at least one query node creator class derived from the query node creator base class.
| 0.5 |
1. A method of accessing content at a speech-enabled automated system, the method comprising: receiving a verbal input at an interactive voice response system; and accessing an information store to retrieve content based on the verbal input, wherein the information store determines whether to suspend retrieval of the content until the content is available when information store content of the information store is being modified and modifications to the information store content could influence retrieval of the content, and wherein the information store is logically external to the interactive voice response system.
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1. A method of accessing content at a speech-enabled automated system, the method comprising: receiving a verbal input at an interactive voice response system; and accessing an information store to retrieve content based on the verbal input, wherein the information store determines whether to suspend retrieval of the content until the content is available when information store content of the information store is being modified and modifications to the information store content could influence retrieval of the content, and wherein the information store is logically external to the interactive voice response system. 2. The method of claim 1 , further comprising communicating a prompt to a caller prior to receiving the verbal input.
| 0.759938 |
1. A method comprising: recognizing an activity performed at a first place based on sensor data of an electronic device, wherein the first place comprises an unlabeled semantic place without an assigned semantic place label; determining a location for the first place by performing localization for the electronic device; determining an observed mapping between the activity and the location for the first place; determining a typical mapping between the activity and a second place, wherein the second place comprises a labeled semantic place with an assigned semantic place label; based on the observed mapping and the typical mapping, assigning the same sematic place label assigned to the labeled semantic place to the location for the first place; and updating a semantic place map to include the semantic place label assigned to the location for the first place.
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1. A method comprising: recognizing an activity performed at a first place based on sensor data of an electronic device, wherein the first place comprises an unlabeled semantic place without an assigned semantic place label; determining a location for the first place by performing localization for the electronic device; determining an observed mapping between the activity and the location for the first place; determining a typical mapping between the activity and a second place, wherein the second place comprises a labeled semantic place with an assigned semantic place label; based on the observed mapping and the typical mapping, assigning the same sematic place label assigned to the labeled semantic place to the location for the first place; and updating a semantic place map to include the semantic place label assigned to the location for the first place. 2. The method of claim 1 , further comprising targeting at least one advertisement or incentive based message based on the location for the first place and the labeled semantic place.
| 0.843803 |
11. A navigation system comprising: a geographic database configured to store a preferred name for a feature, and a processor configured to obtain data from the geographic database identifying the preferred name for the feature, wherein the preferred name is in a native language, the processor configured to identify parts-of-speech of a plurality of components of the preferred name, translate the parts-of-speech of the preferred language into a target language and create a target language text representing the preferred name in the target language according to the parts-of-speech of the plurality of components of the preferred name and at least one grammatical rule of the target language.
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11. A navigation system comprising: a geographic database configured to store a preferred name for a feature, and a processor configured to obtain data from the geographic database identifying the preferred name for the feature, wherein the preferred name is in a native language, the processor configured to identify parts-of-speech of a plurality of components of the preferred name, translate the parts-of-speech of the preferred language into a target language and create a target language text representing the preferred name in the target language according to the parts-of-speech of the plurality of components of the preferred name and at least one grammatical rule of the target language. 15. The navigation system of claim 11 wherein the parts-of-speech include a noun and an adjective.
| 0.910163 |
6. The method of claim 1 , wherein Z is equal to three, and said semantic relationship values comprise: a factual semantic relationship value; a co-occurrence semantic relationship value; and an associative semantic relationship value.
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6. The method of claim 1 , wherein Z is equal to three, and said semantic relationship values comprise: a factual semantic relationship value; a co-occurrence semantic relationship value; and an associative semantic relationship value. 7. The method of claim 6 , further comprising: (i) calculating a semantic distance (SD) value between said one of said N concepts and one of the remaining N−1 concepts utilizing the formula:
SD=w 1 F+w 2 C+w 3 A; wherein: F represents said factual semantic relationship value; C represents said co-occurrence semantic relationship value; A represents said associative semantic relationship value; and w 1 , w 2 , w 3 are weights assigned to the F, C, and A semantic relationship values, respectively; whereby said SD value is indicative of how strongly associated said one of N concepts is to said one of the remaining N−1 concepts.
| 0.829111 |
15. The method of claim 11 , wherein the popularity metric of a candidate search result is determined by: determining a model predicting a likelihood of a user selection of a search result using multiple users' search histories; and applying the model to the user's search history to generate the popularity metric of the candidate search result.
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15. The method of claim 11 , wherein the popularity metric of a candidate search result is determined by: determining a model predicting a likelihood of a user selection of a search result using multiple users' search histories; and applying the model to the user's search history to generate the popularity metric of the candidate search result. 16. The method of claim 15 , wherein the model is determined by: generating a profile that characterizes the multiple users' behaviors over multiple search results in the multiple users' search histories; and determining as the model a set of coefficients from the profile, wherein the set of coefficients, when applied to a set of search results associated from a specific user's search history, is configured to predict the likelihood of the specific user's selection of each of the search results in the future.
| 0.838558 |
20. A device comprising: a processor device; memory in communication with the processor device; a display device operatively coupled to the processor and memory; and a storage medium storing a computer program product to configure the processor to: render text of an electronic representation of a document on the display device, with the text of the document having a first appearance that includes a first color and first style, and with at least first and second sentences of the document displayed on the display device in the first appearance; apply a first visual feedback indicium over all text of the first sentence displayed on the display device to indicate a current first sentence to be read, while having the second sentence displayed in the first appearance; receive audio from a user reading the first sentence aloud; determine, using speech recognition processing that converts the received audio for the first sentence a text file, when the user has reached a last word of the sentence; concurrently remove the first visual feedback indicium from the first sentence, return all of the displayed text of the first sentence to the first appearance and apply the first visual feedback indicium over all words in the second sentence after the user completes the last word of the first sentence; apply the first visual feedback indicium on the second sentence displayed on the display device, while the first sentence is displayed on the display device without the first visual feedback indicium; and generate in the presence of an intervention a visual intervention indicium for the word that required the intervention in the second sentence, by rendering the words in the second sentence that are prior to the word that required the intervention in a second color, the word that required the intervention rendered in a different color from the second color and with a highlight on the word that required the intervention, and with words in the second sentence subsequent to the word rendered in the different color.
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20. A device comprising: a processor device; memory in communication with the processor device; a display device operatively coupled to the processor and memory; and a storage medium storing a computer program product to configure the processor to: render text of an electronic representation of a document on the display device, with the text of the document having a first appearance that includes a first color and first style, and with at least first and second sentences of the document displayed on the display device in the first appearance; apply a first visual feedback indicium over all text of the first sentence displayed on the display device to indicate a current first sentence to be read, while having the second sentence displayed in the first appearance; receive audio from a user reading the first sentence aloud; determine, using speech recognition processing that converts the received audio for the first sentence a text file, when the user has reached a last word of the sentence; concurrently remove the first visual feedback indicium from the first sentence, return all of the displayed text of the first sentence to the first appearance and apply the first visual feedback indicium over all words in the second sentence after the user completes the last word of the first sentence; apply the first visual feedback indicium on the second sentence displayed on the display device, while the first sentence is displayed on the display device without the first visual feedback indicium; and generate in the presence of an intervention a visual intervention indicium for the word that required the intervention in the second sentence, by rendering the words in the second sentence that are prior to the word that required the intervention in a second color, the word that required the intervention rendered in a different color from the second color and with a highlight on the word that required the intervention, and with words in the second sentence subsequent to the word rendered in the different color. 22. The device of claim 20 further configured to assess the quality of the user's reading on a word-by-word basis.
| 0.597494 |
7. A method for user-extensible rule-based source code modification, the method comprising: loading, in a rule definition interface, multiple different end-user established source code modification rules for modifying source code to run on a source platform to be ported to a target platform so that the software application can run on the target platform, wherein the rule definition interface provides different templates to match different language constructs for different languages supported for the source code, the rules identifying a relative location of each of the different lines of source code to be modified based upon a position of each of the different lines relative to other lines of source code; loading a source code file of source code into a memory of a computer; parsing, by a processor, source code of the source code file into different sets of tokens; matching, by the processor, the rules to the different sets of tokens based upon the relative location of the rules; generating, by the processor, suggested modifications to the source code according to selected matched ones of the rules; and, providing a user interface for end users to specify the relative location as one of a line before, a same line, and a same file and to select modifications from the suggested modifications and apply the selected modifications to the source code.
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7. A method for user-extensible rule-based source code modification, the method comprising: loading, in a rule definition interface, multiple different end-user established source code modification rules for modifying source code to run on a source platform to be ported to a target platform so that the software application can run on the target platform, wherein the rule definition interface provides different templates to match different language constructs for different languages supported for the source code, the rules identifying a relative location of each of the different lines of source code to be modified based upon a position of each of the different lines relative to other lines of source code; loading a source code file of source code into a memory of a computer; parsing, by a processor, source code of the source code file into different sets of tokens; matching, by the processor, the rules to the different sets of tokens based upon the relative location of the rules; generating, by the processor, suggested modifications to the source code according to selected matched ones of the rules; and, providing a user interface for end users to specify the relative location as one of a line before, a same line, and a same file and to select modifications from the suggested modifications and apply the selected modifications to the source code. 10. The method of claim 7 , wherein to apply the selected modifications to the source code comprises: evaluating a regular expression to produce source code modifying text for inclusion in the source code; and inserting the produced source code modifying text into source code corresponding to a matched one of the rules.
| 0.706349 |
14. A system for identifying keywords, the system comprising: a processor; a memory coupled to the processor; computer code loaded into the memory for executing on the processor, for implementing the following functionality: a plurality of neurons arranged into a bidirectional neural network comprising a plurality of layers, the layers including words and documents, the neurons associated with words forming a first layer, and the neurons associated with documents forming a second layer, each neuron having multiple inputs from other neurons, a single output connecting the neuron to other neurons, and a threshold function at the single output, wherein at least some of the neurons of the first layer have connections between them and represent keywords in the documents; a plurality of connections between the neurons, wherein each neuron is connected to only some of the other neurons, such that at least some of the word neurons have connections between them; wherein, in response to an input query, the neural network outputs a plurality of keywords associated with documents that are contextually relevant to the input query.
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14. A system for identifying keywords, the system comprising: a processor; a memory coupled to the processor; computer code loaded into the memory for executing on the processor, for implementing the following functionality: a plurality of neurons arranged into a bidirectional neural network comprising a plurality of layers, the layers including words and documents, the neurons associated with words forming a first layer, and the neurons associated with documents forming a second layer, each neuron having multiple inputs from other neurons, a single output connecting the neuron to other neurons, and a threshold function at the single output, wherein at least some of the neurons of the first layer have connections between them and represent keywords in the documents; a plurality of connections between the neurons, wherein each neuron is connected to only some of the other neurons, such that at least some of the word neurons have connections between them; wherein, in response to an input query, the neural network outputs a plurality of keywords associated with documents that are contextually relevant to the input query. 22. The system of claim 14 , wherein the neural network also includes neurons having a group of words associated with a single neuron.
| 0.554291 |
9. A system for speech to speech translation, comprising: a processing element; an interface coupled to the processing element, wherein the interface is configured to receive at least one audio signal; and a memory communicatively connected to the processing element, wherein the memory contains instructions that, when executed by the processing element, configure the processing element to: identify a first concept in the received at least audio input; identify a first language based on the first concept identified for the received audio signal; identify a first plurality of concepts in the first language, wherein the first plurality of concepts is statistically proximate to the first concept and previously matched to a second plurality of concepts, wherein the second plurality of concepts is in the target language; and identify a second concept statistically proximate to the second plurality of concepts, wherein the statistical proximity is determined by use of a threshold in order to determine a match respective of the first concept and the second concept, wherein the second concept is respective of a target language.
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9. A system for speech to speech translation, comprising: a processing element; an interface coupled to the processing element, wherein the interface is configured to receive at least one audio signal; and a memory communicatively connected to the processing element, wherein the memory contains instructions that, when executed by the processing element, configure the processing element to: identify a first concept in the received at least audio input; identify a first language based on the first concept identified for the received audio signal; identify a first plurality of concepts in the first language, wherein the first plurality of concepts is statistically proximate to the first concept and previously matched to a second plurality of concepts, wherein the second plurality of concepts is in the target language; and identify a second concept statistically proximate to the second plurality of concepts, wherein the statistical proximity is determined by use of a threshold in order to determine a match respective of the first concept and the second concept, wherein the second concept is respective of a target language. 12. The system of claim 9 , wherein the received audio signal is at least one of: a digital representation of an audio signal, and a direct feed from at least one microphone device.
| 0.526213 |
1. A computer-implemented method comprising: receiving a first search query; obtaining search results referencing a plurality of documents that a search engine has identified as being responsive to the first search query; computing a respective count of occurrences of each of a plurality of search queries for which a first document, of the plurality of documents, was identified as being responsive; designating, as entity text strings for the first document, one or more search queries having a respective count that satisfies a threshold; generating a refined search query having one or more terms from the one or more entity text strings for the first document, including combining (i) one or more terms of the one or more entity text strings for the first document with (ii) one or more terms of the first search query; and providing the refined search query having the one or more terms from the one or more entity text strings for the first document in response to receiving the first search query.
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1. A computer-implemented method comprising: receiving a first search query; obtaining search results referencing a plurality of documents that a search engine has identified as being responsive to the first search query; computing a respective count of occurrences of each of a plurality of search queries for which a first document, of the plurality of documents, was identified as being responsive; designating, as entity text strings for the first document, one or more search queries having a respective count that satisfies a threshold; generating a refined search query having one or more terms from the one or more entity text strings for the first document, including combining (i) one or more terms of the one or more entity text strings for the first document with (ii) one or more terms of the first search query; and providing the refined search query having the one or more terms from the one or more entity text strings for the first document in response to receiving the first search query. 10. The method of claim 1 , wherein computing the respective count of occurrences of each of a plurality of search queries comprises: identifying search queries occurring a search log; determining for which of the search queries in the search log the first document was identified as being responsive; and computing a count of the search queries in the search log for which the first document was identified as being responsive.
| 0.57555 |
9. A computer-implemented method for tagging content, the method comprising: receiving a first identifier of a first natural language, of a session of a computer with a user; automatically displaying in the first natural language, at least a description of a piece of content accessible to the computer; at least one processor using the first identifier to retrieve from a memory, a first set of tags comprising strings of text expressed in the first natural language; wherein each tag in the first set comprises a string of text expressed in the first natural language and an identifier of said piece of content; and automatically checking if a number of the tags in the first set is greater than zero and if not then automatically using a second identifier to retrieve and display adjacent to the description in the first natural language, a second set tags comprising strings of text expressed in a second natural language different from the first natural language.
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9. A computer-implemented method for tagging content, the method comprising: receiving a first identifier of a first natural language, of a session of a computer with a user; automatically displaying in the first natural language, at least a description of a piece of content accessible to the computer; at least one processor using the first identifier to retrieve from a memory, a first set of tags comprising strings of text expressed in the first natural language; wherein each tag in the first set comprises a string of text expressed in the first natural language and an identifier of said piece of content; and automatically checking if a number of the tags in the first set is greater than zero and if not then automatically using a second identifier to retrieve and display adjacent to the description in the first natural language, a second set tags comprising strings of text expressed in a second natural language different from the first natural language. 11. The computer-implemented method of claim 9 further comprising: automatically displaying a link indicating availability of tags in the second natural language; wherein the second set of tags are displayed only in response to user clicking on said link.
| 0.772887 |
4. One or more server devices comprising: one or more processors operable to cause a server device to: receive, from a client device in communication with the server device via a network, an image including text; perform optical character recognition on the image to produce recognized text; determine one or more topics corresponding to the recognized text; select a word or a phrase from the recognized text for providing additional information; determine one or more potential meanings of the selected word or phrase; select a meaning of the one or more potential meanings using the one or more topics; select a source of additional information corresponding to the selected meaning; provide an indication to the client device that additional information is available for the selected word or phrase; receive a request from the client device for the additional information corresponding to the selected word or phrase; and send the additional information to the client device.
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4. One or more server devices comprising: one or more processors operable to cause a server device to: receive, from a client device in communication with the server device via a network, an image including text; perform optical character recognition on the image to produce recognized text; determine one or more topics corresponding to the recognized text; select a word or a phrase from the recognized text for providing additional information; determine one or more potential meanings of the selected word or phrase; select a meaning of the one or more potential meanings using the one or more topics; select a source of additional information corresponding to the selected meaning; provide an indication to the client device that additional information is available for the selected word or phrase; receive a request from the client device for the additional information corresponding to the selected word or phrase; and send the additional information to the client device. 11. The one or more server devices of claim 4 , wherein the selected source of information is: a products database including product information records each identifying a product and including product information characterizing the identified product, or a publications database including publication records each identifying a publication and including publication information characterizing the identified publication.
| 0.592905 |
3. The method of claim 2 wherein a representative bit location is a bit location such that its bit location count has a value equal to half the number of all of the generated n-bit binary addresses.
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3. The method of claim 2 wherein a representative bit location is a bit location such that its bit location count has a value equal to half the number of all of the generated n-bit binary addresses. 4. The method of claim 3 wherein the hierarchical data structure provides a perfect hash function.
| 0.949483 |
21. A computer system comprising: a computer processor; a memory, operatively coupled to the computer processor and including a history apparatus which in turn comprises: a user interface which converts signals generated by a user to user data which is stored in the memory and which has a user data description, the user data description comprising one or more instances of one or more selected elements of a collection of two or more elements; a history database, operatively coupled to the user interface, the history database comprising two or more categories, each of which is associated with a respective one of two or more elements of the collection; and a user data classifier, operatively coupled between the user interface and the history database, for storing the user data in the history database in a selected one of the categories which is associated with one of the selected elements; and a user data retriever, operatively coupled to the history database, for retrieving user data from the history database, the user data retriever comprising: a category selector, which is operatively coupled to the user interface and which specifies, in response to signals generated by a category selection gesture of the user, a selected one of the two or more categories; and a user data selector, which is operatively coupled to the user interface and which specifies, in response to signals generated by a user data selection gesture of the user, selected user data of the select category.
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21. A computer system comprising: a computer processor; a memory, operatively coupled to the computer processor and including a history apparatus which in turn comprises: a user interface which converts signals generated by a user to user data which is stored in the memory and which has a user data description, the user data description comprising one or more instances of one or more selected elements of a collection of two or more elements; a history database, operatively coupled to the user interface, the history database comprising two or more categories, each of which is associated with a respective one of two or more elements of the collection; and a user data classifier, operatively coupled between the user interface and the history database, for storing the user data in the history database in a selected one of the categories which is associated with one of the selected elements; and a user data retriever, operatively coupled to the history database, for retrieving user data from the history database, the user data retriever comprising: a category selector, which is operatively coupled to the user interface and which specifies, in response to signals generated by a category selection gesture of the user, a selected one of the two or more categories; and a user data selector, which is operatively coupled to the user interface and which specifies, in response to signals generated by a user data selection gesture of the user, selected user data of the select category. 25. The computer system of claim 21 wherein the two or more elements with which the categories are associated are letters of an alphabet.
| 0.657074 |
43. A computer-implemented method for identifying similarly formed paragraphs according to an analysis of paragraph metrics, the computer-implemented method comprising: as implemented by one or more computing devices configured with specific executable instructions, obtaining at least one page image, each page image comprising reflowable textual content; identifying paragraphs of reflowable textual content in the obtained at least one page image; for each identified paragraph, determining a plurality of metrics regarding the identified paragraph; and performing a clustering analysis of the identified paragraphs based on at least one of the plurality of metrics of each paragraph, thereby resulting in at least one cluster of similarly formed paragraphs found on the at least one page image.
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43. A computer-implemented method for identifying similarly formed paragraphs according to an analysis of paragraph metrics, the computer-implemented method comprising: as implemented by one or more computing devices configured with specific executable instructions, obtaining at least one page image, each page image comprising reflowable textual content; identifying paragraphs of reflowable textual content in the obtained at least one page image; for each identified paragraph, determining a plurality of metrics regarding the identified paragraph; and performing a clustering analysis of the identified paragraphs based on at least one of the plurality of metrics of each paragraph, thereby resulting in at least one cluster of similarly formed paragraphs found on the at least one page image. 44. The computer-implemented method of claim 43 , wherein determining metrics for each identified paragraph comprises determining a bounding region for each of the identified paragraphs.
| 0.681319 |
15. A non-transitory machine-readable medium containing a program that when executed by a computer causes the computer to: receive a transaction document having plural document lines, wherein the transaction document is associated with a transaction, and wherein the document lines correspond to sub-transactions of the transactions; and produce transaction-tax-related information according to a data schema for representing transaction-tax-related information for different jurisdictions, including jurisdictions with different kinds and numbers of taxation levels; the data schema providing a taxation-line entity for each of the document lines; the data schema providing a taxation-line-item entity, related to the taxation-line entity, for each taxation level of a corresponding document line, wherein plural transaction-line-item entities are provided for the corresponding document line associated with plural taxation levels; wherein an attribute of each taxation-line-item entity indicates the taxation level represented by the taxation-line-item entity.
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15. A non-transitory machine-readable medium containing a program that when executed by a computer causes the computer to: receive a transaction document having plural document lines, wherein the transaction document is associated with a transaction, and wherein the document lines correspond to sub-transactions of the transactions; and produce transaction-tax-related information according to a data schema for representing transaction-tax-related information for different jurisdictions, including jurisdictions with different kinds and numbers of taxation levels; the data schema providing a taxation-line entity for each of the document lines; the data schema providing a taxation-line-item entity, related to the taxation-line entity, for each taxation level of a corresponding document line, wherein plural transaction-line-item entities are provided for the corresponding document line associated with plural taxation levels; wherein an attribute of each taxation-line-item entity indicates the taxation level represented by the taxation-line-item entity. 17. The medium of claim 15 , wherein the data schema includes one or more jurisdiction-dependent constraints on the taxation-line-item entities associated with a taxation-line entity.
| 0.687356 |
1. A method for creating an in-browser visual HTML editor by setting “contentEditable” attribute to “true” for a top level HTML element to be edited or body element of an html page if whole web page is to be edited, the method comprising: detecting a lowest level of HTML element at a caret, a caret is a point of text insertion, a web browser provides one single caret referred to as the caret, an HTML element is a lowest level element if it does not contain child HTML elements, a lowest level HTML element is referred to as a base-element, a base-element at the caret is referred to as the base-element; creating a list to show a text representation of the base-element and a text representation of each level of parent elements of the base-element; detecting item selection change of the said list to get an HTML element selection which is referred to as the selected HTML element or the selected element; creating areas to hold command-buttons specific to said selected HTML element, referred to as element-command-area; creating a table for displaying and editing all attributes of said selected HTML element, said table has one column for displaying attribute names and one column for displaying and editing attribute values; said table is referred to as “a Property Grid”; in said table there is one row displaying a virtual property for grouping CSS styles, it is referred to as a “virtual” property because it is not a property specified by standard HTML specifications and it works like a command by following definition: when a user sets a value to said virtual property the value is used as a class name by said selected HTML element, the class name indicated by original value of said virtual property value is removed from class names of said selected HTML element; said virtual property is referred to as “style name”.
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1. A method for creating an in-browser visual HTML editor by setting “contentEditable” attribute to “true” for a top level HTML element to be edited or body element of an html page if whole web page is to be edited, the method comprising: detecting a lowest level of HTML element at a caret, a caret is a point of text insertion, a web browser provides one single caret referred to as the caret, an HTML element is a lowest level element if it does not contain child HTML elements, a lowest level HTML element is referred to as a base-element, a base-element at the caret is referred to as the base-element; creating a list to show a text representation of the base-element and a text representation of each level of parent elements of the base-element; detecting item selection change of the said list to get an HTML element selection which is referred to as the selected HTML element or the selected element; creating areas to hold command-buttons specific to said selected HTML element, referred to as element-command-area; creating a table for displaying and editing all attributes of said selected HTML element, said table has one column for displaying attribute names and one column for displaying and editing attribute values; said table is referred to as “a Property Grid”; in said table there is one row displaying a virtual property for grouping CSS styles, it is referred to as a “virtual” property because it is not a property specified by standard HTML specifications and it works like a command by following definition: when a user sets a value to said virtual property the value is used as a class name by said selected HTML element, the class name indicated by original value of said virtual property value is removed from class names of said selected HTML element; said virtual property is referred to as “style name”. 2. The method of claim 1 , further comprising of a process of creating CSS virtual properties for the selected element defined in claim 1 for CSS styles supported by the selected element defined in claim 1 , their values are shared between some elements in a way as defined below in this claim; each CSS virtual property is for a CSS style of the selected element defined in claim 1 ; each CSS virtual property is created for a CSS style with selector of said CSS style defined below: selector for said CSS styles is determined by tag name of the selected HTML element and value of “style name” of claim 1 ; if “style name” of the selected element defined in claim 1 is empty then the selector is the tag name of the selected element defined in claim 1 ; if “style name” of the selected element defined in claim 1 is not empty then the selector is the tag name of the selected element defined in claim 1 followed by a dot and followed by “style name” of the selected element defined in claim 1 ; value of a CSS virtual property is computed value of said CSS style; when a user sets a value to a CSS virtual property, the value is used as style value of said CSS style, if the value is empty or equals to default value according to standard HTML specifications for said CSS style then the style is removed from Cascade Style Sheet.
| 0.5 |
11. A non-transitory computer readable storage medium storing an image data structure produced by a method of generating a visualization of a plurality of words inside a predefined shape, the method comprising: storing, in a computer readable medium, a plurality of values, each corresponding to one of the plurality of words; selecting, one or more processors, a maximum word size; computing, the one or more processors, a word size for each of the plurality of words based on the value corresponding to the word and the maximum word size; obtaining, the one or more processors, a word color for each of the plurality of words; and generating, the one or more processors, the image data structure for displaying on a display, the image data structure including an image having the plurality of words, each word having the corresponding word size and the corresponding word color; wherein selecting the maximum word size includes: generating, the one or more processors, a first set of maximum word sizes; for each maximum word size in the first set, arranging, using the one or more processors, the plurality of words such that a first word of the plurality of words has the maximum word size and remaining words of the plurality of words are not larger than the maximum word size, and determining, using the one or more processors, whether the arrangement of the plurality of words satisfies a first criterion, the first criterion being that none of the words in the arrangement are outside the predefined shape; selecting, the one or more processors, the largest maximum word size in the first set having an arrangement of the plurality of words that satisfies the first criterion.
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11. A non-transitory computer readable storage medium storing an image data structure produced by a method of generating a visualization of a plurality of words inside a predefined shape, the method comprising: storing, in a computer readable medium, a plurality of values, each corresponding to one of the plurality of words; selecting, one or more processors, a maximum word size; computing, the one or more processors, a word size for each of the plurality of words based on the value corresponding to the word and the maximum word size; obtaining, the one or more processors, a word color for each of the plurality of words; and generating, the one or more processors, the image data structure for displaying on a display, the image data structure including an image having the plurality of words, each word having the corresponding word size and the corresponding word color; wherein selecting the maximum word size includes: generating, the one or more processors, a first set of maximum word sizes; for each maximum word size in the first set, arranging, using the one or more processors, the plurality of words such that a first word of the plurality of words has the maximum word size and remaining words of the plurality of words are not larger than the maximum word size, and determining, using the one or more processors, whether the arrangement of the plurality of words satisfies a first criterion, the first criterion being that none of the words in the arrangement are outside the predefined shape; selecting, the one or more processors, the largest maximum word size in the first set having an arrangement of the plurality of words that satisfies the first criterion. 15. The non-transitory computer readable storage medium of claim 11 , wherein obtaining the word color for each of the plurality of words includes determining the word color based on a psycho construct score associated with the word.
| 0.876452 |
8. A system for correcting words in transcribed text, the system comprising: an automated speech recognizer operable to receive speech audio data and in response transcribe the speech audio data in a word lattice; and a computing device comprising: a microphone operable to receive speech audio and generate the speech audio data, a network interface operable to send the speech audio data to the automated speech recognizer and in response receive the word lattice from the automated speech recognizer, a display screen operable to present one or more transcribed words from the word lattice, a user interface operable to receive a user selection of at least one of the transcribed words, and one or more processors and a memory storing instructions that when executed by the processors cause the computing device to perform operations to: provide a first transcription of an utterance, wherein the first transcription of the utterance includes one or more words; receive data indicating a selection of a word from among the one or more words included in the first transcription of the utterance; in response to receiving the data indicating the selection of the word, provide one or more alternate words for the selected word; receive data indicating a selection of a particular alternate word from among the one or more alternate words for the selected word; select a second transcription of the utterance that includes the particular alternate word and that is identified as having a speech recognition confidence measure value that satisfies one or more criteria; and replace the first transcription of the utterance with the second transcription of the utterance.
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8. A system for correcting words in transcribed text, the system comprising: an automated speech recognizer operable to receive speech audio data and in response transcribe the speech audio data in a word lattice; and a computing device comprising: a microphone operable to receive speech audio and generate the speech audio data, a network interface operable to send the speech audio data to the automated speech recognizer and in response receive the word lattice from the automated speech recognizer, a display screen operable to present one or more transcribed words from the word lattice, a user interface operable to receive a user selection of at least one of the transcribed words, and one or more processors and a memory storing instructions that when executed by the processors cause the computing device to perform operations to: provide a first transcription of an utterance, wherein the first transcription of the utterance includes one or more words; receive data indicating a selection of a word from among the one or more words included in the first transcription of the utterance; in response to receiving the data indicating the selection of the word, provide one or more alternate words for the selected word; receive data indicating a selection of a particular alternate word from among the one or more alternate words for the selected word; select a second transcription of the utterance that includes the particular alternate word and that is identified as having a speech recognition confidence measure value that satisfies one or more criteria; and replace the first transcription of the utterance with the second transcription of the utterance. 14. The system of claim 8 , wherein: the first transcription of the utterance and the second transcription of the utterance are provided for output at a touchscreen display of a computing device; and the data indicating the selection of the word from among the one or more words included in the first transcription and the data indicating the selection of the particular alternate word from among the one or more alternate words for the selected word are received in response to user input at the touchscreen display of the computing device.
| 0.5 |
1. A method for automated ontology building, comprising: creating, from text, contextual tokens representing at least one of date and time; calculating a dependency graph across the contextual tokens using at least one parse tree obtained by parsing the text; generating concept instance candidates and parent-child relationships based on pattern matching and transformation of the at least one parse tree; grouping concept instance candidates into concept candidates using concept candidate keys, the concept candidate keys being a sequence of triplets; arranging the concept candidates into a tree having tree nodes and creating predicate-based relationships between the tree nodes based on patterns and predicates identified in the text; scoring and sorting the tree nodes; performing an analysis of the tree nodes and rebalancing the tree based on the analysis to provide an ontology based on the text and formed as an output graph comprising a plurality of nodes; and providing a user interface for editing the ontology by selectively choosing from a plurality of options including adding a new node to the output graph, removing an existing node from the output graph, moving one of the plurality of nodes or a sub-graph across a parent-child hierarchy in the output graph, creating a new relation across the plurality of nodes, and removing an existing relation edges from the output graph.
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1. A method for automated ontology building, comprising: creating, from text, contextual tokens representing at least one of date and time; calculating a dependency graph across the contextual tokens using at least one parse tree obtained by parsing the text; generating concept instance candidates and parent-child relationships based on pattern matching and transformation of the at least one parse tree; grouping concept instance candidates into concept candidates using concept candidate keys, the concept candidate keys being a sequence of triplets; arranging the concept candidates into a tree having tree nodes and creating predicate-based relationships between the tree nodes based on patterns and predicates identified in the text; scoring and sorting the tree nodes; performing an analysis of the tree nodes and rebalancing the tree based on the analysis to provide an ontology based on the text and formed as an output graph comprising a plurality of nodes; and providing a user interface for editing the ontology by selectively choosing from a plurality of options including adding a new node to the output graph, removing an existing node from the output graph, moving one of the plurality of nodes or a sub-graph across a parent-child hierarchy in the output graph, creating a new relation across the plurality of nodes, and removing an existing relation edges from the output graph. 11. The method of claim 1 , wherein the predicates in the text identified by said identifying step consist of predicates having at least two mandatory arguments.
| 0.586995 |
24. A network computer for managing operations for organizations over a network, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and one or more processors that execute instructions that perform actions, including: when a plurality of Operations events are provided, performing further actions, including: providing one or more event clusters that are associated with one or more Operations events of the plurality of Operations events, wherein the one or more Operations events are associated with the one or more event clusters based on one or more characteristics of the one or more Operations events; associating one or more resolution metrics with the one or more event clusters, wherein the association is based on one or more of human-validated interface applications or generalized models; employing a modeling engine to train one or more models based on the one or more Operations events, the one or more event clusters, and the one or more resolution metrics, wherein the trained model is configured to correlate and predict the one or more resolution metrics from one or more real-time Operations events; configuring and arranging the memory for storing the one or more trained models; storing the one or more trained models in the memory; when the one or more real-time Operations events are provided, performing actions including: retrieving the one or more trained models from the memory; and employing the one or more trained models to identify the one or more resolution metrics that are associated with the one or more real-time Operations events.
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24. A network computer for managing operations for organizations over a network, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and one or more processors that execute instructions that perform actions, including: when a plurality of Operations events are provided, performing further actions, including: providing one or more event clusters that are associated with one or more Operations events of the plurality of Operations events, wherein the one or more Operations events are associated with the one or more event clusters based on one or more characteristics of the one or more Operations events; associating one or more resolution metrics with the one or more event clusters, wherein the association is based on one or more of human-validated interface applications or generalized models; employing a modeling engine to train one or more models based on the one or more Operations events, the one or more event clusters, and the one or more resolution metrics, wherein the trained model is configured to correlate and predict the one or more resolution metrics from one or more real-time Operations events; configuring and arranging the memory for storing the one or more trained models; storing the one or more trained models in the memory; when the one or more real-time Operations events are provided, performing actions including: retrieving the one or more trained models from the memory; and employing the one or more trained models to identify the one or more resolution metrics that are associated with the one or more real-time Operations events. 25. The network computer of claim 24 , further comprising, transforming, by the one or more processors, each Operations event in the plurality of Operations events into a common event format.
| 0.893923 |
2. The system of claim 1 , wherein the plurality of non-domain specific dialog motivators further comprises a previously encoded assumption dialog motivator.
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2. The system of claim 1 , wherein the plurality of non-domain specific dialog motivators further comprises a previously encoded assumption dialog motivator. 4. The system of claim 2 , wherein the previously encoded assumption dialog motivator is governed by predefined rules governing call flow.
| 0.943571 |
1. A method of correcting transcribed text utilizing a computer-processing system, the computer-processing system having a browser-based user interface, the method comprising: receiving a first plurality of audio data sets from one or more audio data sources, wherein at least two of the first plurality of audio data sets are associated with different speakers; transcribing the first plurality of audio data sets based on a voice-independent model to generate a plurality of text data sets, wherein at least two of the plurality of text data sets are associated with different speakers; storing the plurality of text data sets; making the plurality of text data sets available to a plurality of users over at least one computer network through the browser-based user interface; receiving a plurality of corrected text data sets over the at least one computer network from at least one of the plurality of users through the browser-based user interface, wherein the plurality of corrected text data sets are associated with the plurality of text data sets and at least two of the plurality of corrected text data sets are associated with different speakers; updating the voice-independent model based on the plurality of corrected text data sets received through the browser-based interface; and transcribing a second plurality of audio data sets based on the voice-independent model as updated, wherein at least two of the second plurality of audio data sets are associated with different speakers.
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1. A method of correcting transcribed text utilizing a computer-processing system, the computer-processing system having a browser-based user interface, the method comprising: receiving a first plurality of audio data sets from one or more audio data sources, wherein at least two of the first plurality of audio data sets are associated with different speakers; transcribing the first plurality of audio data sets based on a voice-independent model to generate a plurality of text data sets, wherein at least two of the plurality of text data sets are associated with different speakers; storing the plurality of text data sets; making the plurality of text data sets available to a plurality of users over at least one computer network through the browser-based user interface; receiving a plurality of corrected text data sets over the at least one computer network from at least one of the plurality of users through the browser-based user interface, wherein the plurality of corrected text data sets are associated with the plurality of text data sets and at least two of the plurality of corrected text data sets are associated with different speakers; updating the voice-independent model based on the plurality of corrected text data sets received through the browser-based interface; and transcribing a second plurality of audio data sets based on the voice-independent model as updated, wherein at least two of the second plurality of audio data sets are associated with different speakers. 12. The method of claim 1 , further comprising delivering at least one of the plurality of corrected text data sets to at least one destination.
| 0.535714 |
16. A method of creating a macro for a natural language (NL) query answering system by the one or more computing devices having one or more memories, comprising: obtaining, by the one or more computing devices and via at least one of i) a communication network or ii) a user interface device, a first term or phrase in imprecise syntax, wherein the first term or phrase is to serve as a macro for use with the NL query answering system such that, when the first term or phrase is provided as input to the NL query answering system, which is implemented by the one or more computing devices, the NL query answering system will interpret the first term or phrase as representing another term or phrase; obtaining, by the one or more computing devices, a second term or phrase in imprecise syntax by performing macro assistance, including: analyzing, by the one or more computing devices implementing NL processing techniques, the first term or phrase, including recognizing that the first term or phrase refers to a location, making an assumption, by the one or more computing devices implementing NL processing techniques, that the first term or phrase refers to a current location, determining, by the one or more computing devices, the current location based on at least one of: an IP address, a cell tower, GPS information, or other information corresponding to a device from which the first term or phrase or second term or phrase is obtained, and including, by the one or more computing devices, the current location in the second term or phrase, and suggesting, by the one or more computing devices, the second term or phrase based on at least the analyzing of the first term or phrase; generating, by the one or more computing devices, an association between the first term or phrase and the second term or phrase so that the first term or phrase represents the second term or phrase; and storing, by the one or more computing devices, the association as a natural language (NL) macro in the one or more memories so that the NL query answering system can recognize, when the NL query answering system subsequently receives the first term or phrase in an NL input, that the first term or phrase represents the second term or phrase.
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16. A method of creating a macro for a natural language (NL) query answering system by the one or more computing devices having one or more memories, comprising: obtaining, by the one or more computing devices and via at least one of i) a communication network or ii) a user interface device, a first term or phrase in imprecise syntax, wherein the first term or phrase is to serve as a macro for use with the NL query answering system such that, when the first term or phrase is provided as input to the NL query answering system, which is implemented by the one or more computing devices, the NL query answering system will interpret the first term or phrase as representing another term or phrase; obtaining, by the one or more computing devices, a second term or phrase in imprecise syntax by performing macro assistance, including: analyzing, by the one or more computing devices implementing NL processing techniques, the first term or phrase, including recognizing that the first term or phrase refers to a location, making an assumption, by the one or more computing devices implementing NL processing techniques, that the first term or phrase refers to a current location, determining, by the one or more computing devices, the current location based on at least one of: an IP address, a cell tower, GPS information, or other information corresponding to a device from which the first term or phrase or second term or phrase is obtained, and including, by the one or more computing devices, the current location in the second term or phrase, and suggesting, by the one or more computing devices, the second term or phrase based on at least the analyzing of the first term or phrase; generating, by the one or more computing devices, an association between the first term or phrase and the second term or phrase so that the first term or phrase represents the second term or phrase; and storing, by the one or more computing devices, the association as a natural language (NL) macro in the one or more memories so that the NL query answering system can recognize, when the NL query answering system subsequently receives the first term or phrase in an NL input, that the first term or phrase represents the second term or phrase. 18. The method of claim 16 , wherein the suggesting the second term or phrase is further based on at least one of: a context, determined by the NL query answering system, of the obtained first term or phrase, a previously received first term or phrase, a previously received second term or phrase, a particular stored NL macro, a user preference, a user activity, or data correspondence to a user of the natural language query answering system.
| 0.517123 |
17. The computer-implemented method of claim 15 , further comprising: receiving a second indication to incorporate the replacement narration audio data into the initial narration audio data at each instance corresponding to said single word.
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17. The computer-implemented method of claim 15 , further comprising: receiving a second indication to incorporate the replacement narration audio data into the initial narration audio data at each instance corresponding to said single word. 18. The computer-implemented method of claim 17 , wherein incorporating the replacement narration audio data comprises incorporating the single word replacement narration audio data into the initial narration audio data replacing each instance of previously recorded audio data corresponding to the single word in the initial narration audio data.
| 0.854308 |
4. The method of claim 2 , further comprising: displaying, on the input and display device, at least one search result corresponding to the machine text value of the handwriting ink strokes; and accepting, at the input and display device, user input selecting one of the at least one search results.
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4. The method of claim 2 , further comprising: displaying, on the input and display device, at least one search result corresponding to the machine text value of the handwriting ink strokes; and accepting, at the input and display device, user input selecting one of the at least one search results. 5. The method of claim 4 , wherein the at least one search result is not an exact match to the handwriting ink strokes.
| 0.855159 |
13. One or more non-transitory computer-readable media storing instructions for performing a method of generating a composite abstract for a document, wherein method comprises: receiving a query that includes one or more search query terms; generating a first version of a contextual abstract of the document, at least in part, by selecting, based on the one or more search query terms, first portions of the document for inclusion within the contextual abstract of the document; generating a static abstract of the document, at least in part, by selecting, without regard to the one or more search query terms, second portions of the document for inclusion within the static abstract of the document; generating a second version of the contextual abstract by removing one or more text strings from the first version of the contextual abstract; wherein removing the one or more text strings includes removing a particular text string from the first version of the contextual abstract based, at least in part, on similarities between the contextual abstract and the static abstract; combining text strings from the second version of the contextual abstract with text strings from the static abstract to form the composite abstract for the document; responding to the query with search results that include the composite abstract.
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13. One or more non-transitory computer-readable media storing instructions for performing a method of generating a composite abstract for a document, wherein method comprises: receiving a query that includes one or more search query terms; generating a first version of a contextual abstract of the document, at least in part, by selecting, based on the one or more search query terms, first portions of the document for inclusion within the contextual abstract of the document; generating a static abstract of the document, at least in part, by selecting, without regard to the one or more search query terms, second portions of the document for inclusion within the static abstract of the document; generating a second version of the contextual abstract by removing one or more text strings from the first version of the contextual abstract; wherein removing the one or more text strings includes removing a particular text string from the first version of the contextual abstract based, at least in part, on similarities between the contextual abstract and the static abstract; combining text strings from the second version of the contextual abstract with text strings from the static abstract to form the composite abstract for the document; responding to the query with search results that include the composite abstract. 18. The one or more non-transitory computer-readable media of claim 13 , wherein the method further comprises removing a part of the contextual abstract, wherein the part is contained in the static abstract.
| 0.651383 |
1. A system to improve authored text by mitigating problems related to passive voice, the system comprising: a database of rules, comprising at least one rule having detection logic for detecting whether a particular writing problem exists in authored text, the detection logic comprising a sign that indicates the possible occurrence or absence of the writing problem relating to passive voice, and correction logic for correcting the problem, the correction logic capable of identifying a proposed edit; a computer processor configured to apply the rules to the authored text; and a user interface configured to suggest the proposed edit to the user, according to the rules; wherein the sign comprises a past participle followed by the word “by” and one or more of the following: a time noun, and a transport noun, said sign not being a predetermined phrase.
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1. A system to improve authored text by mitigating problems related to passive voice, the system comprising: a database of rules, comprising at least one rule having detection logic for detecting whether a particular writing problem exists in authored text, the detection logic comprising a sign that indicates the possible occurrence or absence of the writing problem relating to passive voice, and correction logic for correcting the problem, the correction logic capable of identifying a proposed edit; a computer processor configured to apply the rules to the authored text; and a user interface configured to suggest the proposed edit to the user, according to the rules; wherein the sign comprises a past participle followed by the word “by” and one or more of the following: a time noun, and a transport noun, said sign not being a predetermined phrase. 8. The system of claim 1 , wherein the sign comprises a past participle followed by the word “by” and a time noun.
| 0.651591 |
16. A processor readable non-transitory medium storing instructions that, when executed by a processor, cause the processor to: receive a package specification unit (PU) representative of a design of a converged infrastructure (CI) including compute, storage, network, and virtualization components, the package specification unit including compiled component readable tasks that perform operations on the CI components, the package specification unit further including: an inventory task model associated with tasks to read inventory information from the CI components; an assessment task model associated with tasks to assess the CI components; a configuration task model associated with tasks to configure the CI components; and a user input model to generate prompts to solicit and receive CI component information from a user, and provide the received information to the other package specification unit models; display a package specification unit model menu from which the package specification unit models may be selected; receive a selection of one of the package specification unit models through the package specification unit model menu; and execute one or more tasks associated with the selected package specification unit model to perform corresponding operations on the CI components.
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16. A processor readable non-transitory medium storing instructions that, when executed by a processor, cause the processor to: receive a package specification unit (PU) representative of a design of a converged infrastructure (CI) including compute, storage, network, and virtualization components, the package specification unit including compiled component readable tasks that perform operations on the CI components, the package specification unit further including: an inventory task model associated with tasks to read inventory information from the CI components; an assessment task model associated with tasks to assess the CI components; a configuration task model associated with tasks to configure the CI components; and a user input model to generate prompts to solicit and receive CI component information from a user, and provide the received information to the other package specification unit models; display a package specification unit model menu from which the package specification unit models may be selected; receive a selection of one of the package specification unit models through the package specification unit model menu; and execute one or more tasks associated with the selected package specification unit model to perform corresponding operations on the CI components. 21. The processor readable medium of claim 16 , wherein the selected task model is the configuration task model, and the processor to cause the processor to execute includes further instructions to cause the processor to execute tasks associated with the configure task model to configure respective ones of compute, storage, network, and virtualization components.
| 0.640187 |
1. A computer implemented method for performing a component product integration synchronization, comprising: generating a component product extensible markup language (XML) schema; identifying a number of component products to be integrated together in a software system; generating a component product XML file for each identified component product according to the generated component product XML schema, wherein the component product XML file for a given component product is generated by searching an install unit of the given component product, extracting data pertinent to installation of the given component product from the install unit of the given component product, and storing this extracted data in the component product XML file for the given component product, wherein the install unit of the given component product includes instructions and data for installing the given component product in a stand-alone manner; using the data stored in the generated component product XML files to identify and resolve component product interface problems associated with component product specifications and dependencies prior to integrating the number of component products together in the software system; and integrating the number of component products into the software system using only data stored in the generated component product XML files, wherein the integrating is performed without running the install units respectively associated with the number of component products to direct installation of the number of component products.
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1. A computer implemented method for performing a component product integration synchronization, comprising: generating a component product extensible markup language (XML) schema; identifying a number of component products to be integrated together in a software system; generating a component product XML file for each identified component product according to the generated component product XML schema, wherein the component product XML file for a given component product is generated by searching an install unit of the given component product, extracting data pertinent to installation of the given component product from the install unit of the given component product, and storing this extracted data in the component product XML file for the given component product, wherein the install unit of the given component product includes instructions and data for installing the given component product in a stand-alone manner; using the data stored in the generated component product XML files to identify and resolve component product interface problems associated with component product specifications and dependencies prior to integrating the number of component products together in the software system; and integrating the number of component products into the software system using only data stored in the generated component product XML files, wherein the integrating is performed without running the install units respectively associated with the number of component products to direct installation of the number of component products. 5. A computer implemented method for performing a component product integration synchronization as recited in claim 1 , wherein generating the component product XML file for a particular component product includes parsing the generated component product XML schema to identify tags defined to direct retrieval of data associated with installation of the particular component product.
| 0.714966 |
8. A system comprising: a processor; and a memory containing instructions that, when executed, cause the processor to: present, alongside a computer-generated puzzle: primary information describing a primary subject related to a selected clue or solution of the computer-generated puzzle; secondary information describing a secondary subject related to the primary subject; and wherein the primary information and secondary information have been received over a communications network from a first computing device; receive, from a second computing device, input indicating selection of the secondary information; replace the primary information with the secondary information; and designate the secondary subject matter as the primary subject.
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8. A system comprising: a processor; and a memory containing instructions that, when executed, cause the processor to: present, alongside a computer-generated puzzle: primary information describing a primary subject related to a selected clue or solution of the computer-generated puzzle; secondary information describing a secondary subject related to the primary subject; and wherein the primary information and secondary information have been received over a communications network from a first computing device; receive, from a second computing device, input indicating selection of the secondary information; replace the primary information with the secondary information; and designate the secondary subject matter as the primary subject. 11. The system of claim 8 , wherein the primary information is an image describing the primary subject and the secondary information is an image describing the secondary subject.
| 0.625878 |
4. The method of claim 1 , the method further comprising: receiving, by the computer system, a request to provide the e-captcha challenge, wherein the executable instructions are provided responsive to the request, and wherein the request comprises one or more parameters that specify an e-captcha challenge to be provided; and identifying, by the computer system, the e-captcha challenge based on the one or more parameters.
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4. The method of claim 1 , the method further comprising: receiving, by the computer system, a request to provide the e-captcha challenge, wherein the executable instructions are provided responsive to the request, and wherein the request comprises one or more parameters that specify an e-captcha challenge to be provided; and identifying, by the computer system, the e-captcha challenge based on the one or more parameters. 6. The method of claim 4 , wherein the one or more parameters further specify a level of difficulty of the e-captcha challenge.
| 0.959776 |
1. A computer-implemented method comprising: receiving speech data that encodes a candidate hotword spoken by a user; evaluating the speech data, or a transcription of the candidate hotword, using one or more predetermined criteria; generating, by one or more computers, a hotword suitability score for the candidate hotword based on evaluating the speech data, or a transcription of the candidate hotword, using the one or more predetermined criteria, wherein the hotword suitability score reflects a suitability of the candidate hotword for future use as a hotword; and providing a representation of the hotword suitability score for output to the user.
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1. A computer-implemented method comprising: receiving speech data that encodes a candidate hotword spoken by a user; evaluating the speech data, or a transcription of the candidate hotword, using one or more predetermined criteria; generating, by one or more computers, a hotword suitability score for the candidate hotword based on evaluating the speech data, or a transcription of the candidate hotword, using the one or more predetermined criteria, wherein the hotword suitability score reflects a suitability of the candidate hotword for future use as a hotword; and providing a representation of the hotword suitability score for output to the user. 6. The method of claim 1 , wherein generating a hotword suitability score comprises: generating, for each of two or more predetermined criteria, a feature score based on an evaluation of the speech data, or of the transcription of the candidate hotword, using the predetermined criteria; aggregating the feature scores; and outputting, as the hotword suitability score, the aggregated feature scores.
| 0.5 |
1. A method, comprising: tracking frequencies of historical replacement character strings for a specific user and a community of users; and providing a list of “n” number of the historical replacement character strings in response to a character string which was previously changed or is not recognized, wherein the character string is automatically replaced when the character string exceeds a threshold of a sum of all the frequencies of the historical replacement character strings, wherein the list of “n” number of the historical replacement character strings are ranked according to a combined weighted frequency, wherein the combined weighted frequency is a sum of a user weight for the specific user and a community weight for the community of users such that the combined weighted frequency is weighted towards historical replacement character strings of the specific user, wherein the user weight is calculated based on a user frequency of a corresponding character string in comparison to a sum of all user frequencies of the historical replacement character strings, wherein the community weight is calculated based on a community frequency of a corresponding character string in comparison to a sum of all community frequencies of the historical replacement character strings, wherein the community of users comprise the specific user, and wherein the combined weight is different for each user of the community of users.
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1. A method, comprising: tracking frequencies of historical replacement character strings for a specific user and a community of users; and providing a list of “n” number of the historical replacement character strings in response to a character string which was previously changed or is not recognized, wherein the character string is automatically replaced when the character string exceeds a threshold of a sum of all the frequencies of the historical replacement character strings, wherein the list of “n” number of the historical replacement character strings are ranked according to a combined weighted frequency, wherein the combined weighted frequency is a sum of a user weight for the specific user and a community weight for the community of users such that the combined weighted frequency is weighted towards historical replacement character strings of the specific user, wherein the user weight is calculated based on a user frequency of a corresponding character string in comparison to a sum of all user frequencies of the historical replacement character strings, wherein the community weight is calculated based on a community frequency of a corresponding character string in comparison to a sum of all community frequencies of the historical replacement character strings, wherein the community of users comprise the specific user, and wherein the combined weight is different for each user of the community of users. 6. The method of claim 1 , further comprising replacing the character string with a selected one of the historical replacement character strings.
| 0.652278 |
39. A method as set forth in claim 38, further including the steps of: setting the current interaction language responsive to a termination of the invoked application program to a previous interaction language from the stored nested language. information; and removing the previous interaction language from the stored nested language information.
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39. A method as set forth in claim 38, further including the steps of: setting the current interaction language responsive to a termination of the invoked application program to a previous interaction language from the stored nested language. information; and removing the previous interaction language from the stored nested language information. 40. A method as set forth in claim 39 wherein the stored nested language information is stored in a stack.
| 0.94113 |
21. An apparatus comprising: a memory; a processor coupled to the memory, wherein the processor to: receive a request from a user to discuss content with a recipient user in a plurality of groups in a social network, wherein the recipient user is associated with a first group in the plurality of groups, wherein the first group comprising a plurality of the recipient users in the social network, create a temporary placeholder account for the user; create, a second group for the user and the recipient user in the social network in view of the temporary placeholder account, wherein the second group is different from the first group and the second group is not in the plurality of groups; initiate a live discussion between the user and the recipient user about the content in the second group, convert the temporary placeholder account to a permanent placeholder account for the user in view of a condition, wherein the convert comprises allow the user to join the first group in the social network; and send a notification of the user joining the first group to the plurality of the recipient users.
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21. An apparatus comprising: a memory; a processor coupled to the memory, wherein the processor to: receive a request from a user to discuss content with a recipient user in a plurality of groups in a social network, wherein the recipient user is associated with a first group in the plurality of groups, wherein the first group comprising a plurality of the recipient users in the social network, create a temporary placeholder account for the user; create, a second group for the user and the recipient user in the social network in view of the temporary placeholder account, wherein the second group is different from the first group and the second group is not in the plurality of groups; initiate a live discussion between the user and the recipient user about the content in the second group, convert the temporary placeholder account to a permanent placeholder account for the user in view of a condition, wherein the convert comprises allow the user to join the first group in the social network; and send a notification of the user joining the first group to the plurality of the recipient users. 22. The apparatus of claim 21 wherein the processor is configured to determine the recipient user in the plurality of groups for the request based on a relationship between the user and the recipient user.
| 0.579768 |
3. A speech recognizing apparatus according to claim 1 wherein the input speech has syllables and wherein the duration predicator predicates the duration data for each one of the recognition units of the input speech using the following equation: ##EQU17## where represents a predicated value of the duration data of an n-th syllable of the input speech; d(i) represents the duration data of an i-th syllable of the input speech; and w(i) represents a weighing value of the duration data of an i-th syllable of the input speech.
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3. A speech recognizing apparatus according to claim 1 wherein the input speech has syllables and wherein the duration predicator predicates the duration data for each one of the recognition units of the input speech using the following equation: ##EQU17## where represents a predicated value of the duration data of an n-th syllable of the input speech; d(i) represents the duration data of an i-th syllable of the input speech; and w(i) represents a weighing value of the duration data of an i-th syllable of the input speech. 6. A speech recognizing apparatus according to claim 3 wherein the reference speech is divided into a plurality of smaller reference sections, each one of said plurality of smaller reference sections forming a reference recognition unit, the speech recognizing apparatus further comprises a reference speech duration storage buffer for storing duration information of each of a plurality of factors that affect the duration of each one of the reference recognition units, and wherein the duration predicator predicates the duration of each one of the recognition units of the input speech using the following equation: ##EQU20## where represents the predicated value of the duration data of the n-th syllable of the input speech; d(i) represents the duration data of the i-th syllable of the input speech; and w(i,m) represents a weighing value relative to d(i) at an m-th one of the factors that affects the duration of each one of the recognition units.
| 0.682671 |
1. A method of generating electronic documents, comprising: maintaining a library of textual components, displaying a first textual document including a first plurality of the textual components in a word processor window, responding to user input by a first user to an interface of the work processor to edit the first textual document while the document is displayed in the word processor window, maintaining a database of marks identifying each of the components within the document displayed in the word processor window, displaying a second textual document including a second plurality of the textual components in a word processor window, responding to user input by a second user to the interface of the word processor to edit the second textural document including a second plurality of the textual components the first plurality including one or more textual components from the second plurality, detecting when one of the textual components that belongs to both the first plurality of textual components and the second plurality of textual components is updated in one of the first and second textual documents, prompting the user of the other of the first and second textual documents to accept or reject changes made to the one of the textual components, in response to the step of updating, generating in response to user input to the interface of the word processor a second version of the first textual document that includes textual components that were updated in the step of updating, and generating in response to user input to the interface of the word processor a second version of the second textual document that includes textual components that were updated in the step of updating.
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1. A method of generating electronic documents, comprising: maintaining a library of textual components, displaying a first textual document including a first plurality of the textual components in a word processor window, responding to user input by a first user to an interface of the work processor to edit the first textual document while the document is displayed in the word processor window, maintaining a database of marks identifying each of the components within the document displayed in the word processor window, displaying a second textual document including a second plurality of the textual components in a word processor window, responding to user input by a second user to the interface of the word processor to edit the second textural document including a second plurality of the textual components the first plurality including one or more textual components from the second plurality, detecting when one of the textual components that belongs to both the first plurality of textual components and the second plurality of textual components is updated in one of the first and second textual documents, prompting the user of the other of the first and second textual documents to accept or reject changes made to the one of the textual components, in response to the step of updating, generating in response to user input to the interface of the word processor a second version of the first textual document that includes textual components that were updated in the step of updating, and generating in response to user input to the interface of the word processor a second version of the second textual document that includes textual components that were updated in the step of updating. 12. The method of claim 1 wherein the step of maintaining the library maintains an indication of whether the updates to each of the components require review.
| 0.53941 |
11. A computer implemented query processing method for processing a query having one or more query terms using formally expressed knowledge against a corpus of documents based on a knowledge base containing a plurality of pieces of formally expressed knowledge, wherein each piece of formally represented knowledge further comprises an item that has been edited or analyzed, the formally represented knowledge further comprising one or more synsets wherein each synset contains a group of terms that have a same meaning, one or more taxonomies wherein each taxonomy contains one or more synsets in a subject matter area that are organized from a synset having a general meaning to a synset having a specific meaning, one or more ontologies wherein each ontology contains one or more synsets associated with an area of interest and one or more facets wherein each facet is associated with a particular ontology and wherein a document is associated with the facet when the document contains the one or more synsets associated with the facet, the method comprising: expanding, using a hardware query engine, the one or more query terms of the query using the one or more synsets and the one or more taxonomies in the knowledge base to generate an expanded query; selecting an interpretation of a concept from the expanded query and the corpus of documents; selecting one or more facets that match the interpretation of the expanded query based on the corpus of documents; and performing, using the hardware query engine, a deep concept query using the expanded query and the selected one or more facets against a corpus of documents.
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11. A computer implemented query processing method for processing a query having one or more query terms using formally expressed knowledge against a corpus of documents based on a knowledge base containing a plurality of pieces of formally expressed knowledge, wherein each piece of formally represented knowledge further comprises an item that has been edited or analyzed, the formally represented knowledge further comprising one or more synsets wherein each synset contains a group of terms that have a same meaning, one or more taxonomies wherein each taxonomy contains one or more synsets in a subject matter area that are organized from a synset having a general meaning to a synset having a specific meaning, one or more ontologies wherein each ontology contains one or more synsets associated with an area of interest and one or more facets wherein each facet is associated with a particular ontology and wherein a document is associated with the facet when the document contains the one or more synsets associated with the facet, the method comprising: expanding, using a hardware query engine, the one or more query terms of the query using the one or more synsets and the one or more taxonomies in the knowledge base to generate an expanded query; selecting an interpretation of a concept from the expanded query and the corpus of documents; selecting one or more facets that match the interpretation of the expanded query based on the corpus of documents; and performing, using the hardware query engine, a deep concept query using the expanded query and the selected one or more facets against a corpus of documents. 15. The method of the claim 11 , wherein performing the deep concept query further comprises performing a second query based on the synset expansion and the taxonomy expansion of the one or more query terms.
| 0.6217 |
1. An express spreadsheet visualization system configured for the simultaneous viewing of spreadsheet information and visualization information of a model, comprising; a. a processor; b. a display device; c. an input interface configured for use by the user; and d. a system memory comprising; i. a visualization application configured to show the visualization information for the model to a user on the display device; ii. a spreadsheet application configured to show the spreadsheet information of the model to the user on the display device, wherein the spreadsheet application is configured to allow, through the input interface, the user to make changes to components of the spreadsheet information, the spread sheet application comprising: an input manager module to monitor and interpret the changes made to the spreadsheet information by the user; and a synchronization module configured to pass along the changes made to the spreadsheet information to the visualization application, wherein the visualization application and the spreadsheet application are configured to show the visualization information and the spreadsheet information of the model on the display device simultaneously, wherein the spreadsheet application and the visualization application are configured to work with one another to synchronize the visualization information and the spreadsheet information in real-time, wherein the spreadsheet application is configured to continuously monitor the spreadsheet information and notify the spreadsheet application of changes made to the spreadsheet information; and wherein the input manager module is further configured to identify a global unique identifier of each component for which the user has changed, wherein the synchronization module is further configured to pass along the global unique identifiers to the visualization application, and wherein the visualization application is further configured to make changes to the corresponding components that match the global unique identifiers.
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1. An express spreadsheet visualization system configured for the simultaneous viewing of spreadsheet information and visualization information of a model, comprising; a. a processor; b. a display device; c. an input interface configured for use by the user; and d. a system memory comprising; i. a visualization application configured to show the visualization information for the model to a user on the display device; ii. a spreadsheet application configured to show the spreadsheet information of the model to the user on the display device, wherein the spreadsheet application is configured to allow, through the input interface, the user to make changes to components of the spreadsheet information, the spread sheet application comprising: an input manager module to monitor and interpret the changes made to the spreadsheet information by the user; and a synchronization module configured to pass along the changes made to the spreadsheet information to the visualization application, wherein the visualization application and the spreadsheet application are configured to show the visualization information and the spreadsheet information of the model on the display device simultaneously, wherein the spreadsheet application and the visualization application are configured to work with one another to synchronize the visualization information and the spreadsheet information in real-time, wherein the spreadsheet application is configured to continuously monitor the spreadsheet information and notify the spreadsheet application of changes made to the spreadsheet information; and wherein the input manager module is further configured to identify a global unique identifier of each component for which the user has changed, wherein the synchronization module is further configured to pass along the global unique identifiers to the visualization application, and wherein the visualization application is further configured to make changes to the corresponding components that match the global unique identifiers. 9. The express spreadsheet visualization system of claim 1 , wherein the change comprises modifying a component of the visualization information or the spreadsheet information.
| 0.525585 |
1. A method of correcting a spinal deformity, the method comprising: extending a first rod along a first side of a spine of a patient; securing a first anchor to a vertebra of the spine; receiving the first rod with the first anchor such that the first rod is secured against substantial lateral translation relative to the first anchor and the first rod is allowed to slide axially relative to the first anchor through a first pivot point and to change in at least two of pitch, yaw, and roll about the first pivot point during correction; securing a second anchor to a vertebra of the spine; receiving the first rod with the second anchor such that the first rod is secured against substantial lateral translation relative to the second anchor and is allowed to change in at least pitch and yaw about a second pivot point during correction; extending a second rod along a second side of the spine of the patient; securing a third anchor to a vertebra of the spine; receiving the second rod with the third anchor such that the second rod is secured against substantial lateral translation relative to the third anchor during correction and such that the second rod is secured against changes in pitch, yaw, roll, and axial sliding; securing a fourth anchor to a vertebra of the spine; receiving the second rod with the fourth anchor such that the second rod is secured against substantial lateral translation relative to the fourth anchor; and laterally coupling the first rod and the second rod such that the lateral coupling facilitates derotation and translation of the spine.
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1. A method of correcting a spinal deformity, the method comprising: extending a first rod along a first side of a spine of a patient; securing a first anchor to a vertebra of the spine; receiving the first rod with the first anchor such that the first rod is secured against substantial lateral translation relative to the first anchor and the first rod is allowed to slide axially relative to the first anchor through a first pivot point and to change in at least two of pitch, yaw, and roll about the first pivot point during correction; securing a second anchor to a vertebra of the spine; receiving the first rod with the second anchor such that the first rod is secured against substantial lateral translation relative to the second anchor and is allowed to change in at least pitch and yaw about a second pivot point during correction; extending a second rod along a second side of the spine of the patient; securing a third anchor to a vertebra of the spine; receiving the second rod with the third anchor such that the second rod is secured against substantial lateral translation relative to the third anchor during correction and such that the second rod is secured against changes in pitch, yaw, roll, and axial sliding; securing a fourth anchor to a vertebra of the spine; receiving the second rod with the fourth anchor such that the second rod is secured against substantial lateral translation relative to the fourth anchor; and laterally coupling the first rod and the second rod such that the lateral coupling facilitates derotation and translation of the spine. 7. The method of claim 1 , wherein the first and second anchors are secured to pedicles of different vertebrae.
| 0.589452 |
1. A machine translation method for translating source text from a first language to target text in a second language, comprising: receiving the source text in the first language; accessing a library of bi-phrases, each of the bi-phrases including a text fragment from the first language and a text fragment from the second language, at least some of the bi-phrases comprising words tagged with restricted part of speech tags, at least one of the restricted part of speech tags configured for identifying a compoundable word from the second language in one of the bi-phrases as being one which also forms a part of a known closed compound word in the second language in another of the bi-phrases, when combined with another compoundable word, wherein: a first of the restricted part of speech tags identifies a) a compoundable word which appears in a known closed compound word in other than a head position, and a second of the restricted part of speech tags identifies at least one of: b) a compoundable word which appears in a known closed compound word in the head position, and c) another word, where the compoundable word a), and at least one of the words b) and c) identified by the first and second of the restricted part of speech tags are all a same part of speech; retrieving text fragments in the second language from the library corresponding to text fragments in the source text; generating at least one target hypothesis, each of the target hypotheses comprising text fragments selected from the retrieved text fragments in the second language; and evaluating the target hypothesis with a translation scoring function which scores the target hypothesis according to a plurality of feature functions, at least one of the feature functions being based at least in part on a combination of the first and the second of the restricted part of speech tags; and based on the evaluation, outputting one of the at least one target hypothesis as the optimal hypothesis for forming the translation; and wherein at least one of the accessing, retrieving, evaluating and outputting is performed with a computer processor.
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1. A machine translation method for translating source text from a first language to target text in a second language, comprising: receiving the source text in the first language; accessing a library of bi-phrases, each of the bi-phrases including a text fragment from the first language and a text fragment from the second language, at least some of the bi-phrases comprising words tagged with restricted part of speech tags, at least one of the restricted part of speech tags configured for identifying a compoundable word from the second language in one of the bi-phrases as being one which also forms a part of a known closed compound word in the second language in another of the bi-phrases, when combined with another compoundable word, wherein: a first of the restricted part of speech tags identifies a) a compoundable word which appears in a known closed compound word in other than a head position, and a second of the restricted part of speech tags identifies at least one of: b) a compoundable word which appears in a known closed compound word in the head position, and c) another word, where the compoundable word a), and at least one of the words b) and c) identified by the first and second of the restricted part of speech tags are all a same part of speech; retrieving text fragments in the second language from the library corresponding to text fragments in the source text; generating at least one target hypothesis, each of the target hypotheses comprising text fragments selected from the retrieved text fragments in the second language; and evaluating the target hypothesis with a translation scoring function which scores the target hypothesis according to a plurality of feature functions, at least one of the feature functions being based at least in part on a combination of the first and the second of the restricted part of speech tags; and based on the evaluation, outputting one of the at least one target hypothesis as the optimal hypothesis for forming the translation; and wherein at least one of the accessing, retrieving, evaluating and outputting is performed with a computer processor. 10. A computer program product comprising a non-transitory recording medium encoding instructions which, when executed by a computer, perform the method of claim 1 .
| 0.675643 |
1. A system for interaction with datasets in support of scholarly commentary and other commentary, comprising a computer having a processor and a memory and a set of modules each comprising code executing in the processor, including: an editor module for a dataset container file (DCF) creator to create a DCF in which a location and a structure of one or more datasets is input, wherein at least one dataset comprises a tabular arrangement of data, the one or more datasets being stored in a database within the DCF; an import module configured to import a first dataset having a first format from the defined location; a dataset processing module configured to convert the first dataset of the first format into the defined structure; an interface module operative to obtain author-commentary and associate the author-commentary with the first dataset in response to interaction with a user, wherein the author-commentary is included in the DCF; and a synchronization module configured to coordinate on a display a presentation of a portion of at least one of the datasets defined in the DCF in accordance with a selected position on a timeline by querying the datasets in the DCF, returning a subset of the one or more datasets, and presenting one or more multimedia visualizations of that subset on the display, wherein the presentation includes the author-commentary within the timeline and wherein the selected position is input through the editor module, wherein the editor module is further configured to allow positioning of at least one of media objects and the visualizations on the timeline and defining the visual appearance and behavior of the visualizations the at least one of the media objects and the visualizations depicting one or more representations of the one or more datasets.
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1. A system for interaction with datasets in support of scholarly commentary and other commentary, comprising a computer having a processor and a memory and a set of modules each comprising code executing in the processor, including: an editor module for a dataset container file (DCF) creator to create a DCF in which a location and a structure of one or more datasets is input, wherein at least one dataset comprises a tabular arrangement of data, the one or more datasets being stored in a database within the DCF; an import module configured to import a first dataset having a first format from the defined location; a dataset processing module configured to convert the first dataset of the first format into the defined structure; an interface module operative to obtain author-commentary and associate the author-commentary with the first dataset in response to interaction with a user, wherein the author-commentary is included in the DCF; and a synchronization module configured to coordinate on a display a presentation of a portion of at least one of the datasets defined in the DCF in accordance with a selected position on a timeline by querying the datasets in the DCF, returning a subset of the one or more datasets, and presenting one or more multimedia visualizations of that subset on the display, wherein the presentation includes the author-commentary within the timeline and wherein the selected position is input through the editor module, wherein the editor module is further configured to allow positioning of at least one of media objects and the visualizations on the timeline and defining the visual appearance and behavior of the visualizations the at least one of the media objects and the visualizations depicting one or more representations of the one or more datasets. 5. The system of claim 1 , wherein the visualization module comprises a visualization library.
| 0.55878 |
8. An apparatus comprising: a user interface; a communication interface; at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, receive, through the user interface, an instruction to process an object located in the apparatus, generate a first triple including a subject, a predicate and the object, identify a subtype of the object of the first RDF triple, send, through the communication interface, the first triple to a remote apparatus, receive, through the communication interface, a representation of the object, semantically mark the object with the identified subtype, including generating a plurality of second RDF triples corresponding to the first RDF triple, the plurality of second RDF triples comprising an RDF triple including the subject and predicate of the first RDF triple as the subject and predicate thereof, generate a third RDF triple including the object of the first RDF triple or a representation of the object of the first RDF triple as the object thereof, and determine to store the plurality of second RDF triples in the RDF store.
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8. An apparatus comprising: a user interface; a communication interface; at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, receive, through the user interface, an instruction to process an object located in the apparatus, generate a first triple including a subject, a predicate and the object, identify a subtype of the object of the first RDF triple, send, through the communication interface, the first triple to a remote apparatus, receive, through the communication interface, a representation of the object, semantically mark the object with the identified subtype, including generating a plurality of second RDF triples corresponding to the first RDF triple, the plurality of second RDF triples comprising an RDF triple including the subject and predicate of the first RDF triple as the subject and predicate thereof, generate a third RDF triple including the object of the first RDF triple or a representation of the object of the first RDF triple as the object thereof, and determine to store the plurality of second RDF triples in the RDF store. 9. An apparatus according to claim 8 , wherein the apparatus is further caused to, semantically mark the object, including generating a second triple including the subject and predicate of the first triple as the subject and predicate thereof, and generating a third triple including the object of the first triple or a representation of the object of the first triple as the object thereof, and store the second and third triples in a triple store.
| 0.5 |
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 a first speech utterance beginning with a hotword followed by a particular phrase, the particular phrase not currently designated as a hotword; in response to receiving the first speech utterance beginning with the hotword, triggering semantic interpretation on the particular phrase following the hotword; designating the particular phrase as a new hotword based on the sematic interpretation determining that the particular phrase satisfies one or more predetermined criteria associated with designating voice commands as hotwords; and after designating the particular phrase as a new hotword and while the computing device is in a sleep state, receiving a second speech utterance beginning with the particular phrase, the particular phrase when designated as the new hotword causing the computing device to transition out of the sleep state and process the second speech utterance as a voice command.
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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 a first speech utterance beginning with a hotword followed by a particular phrase, the particular phrase not currently designated as a hotword; in response to receiving the first speech utterance beginning with the hotword, triggering semantic interpretation on the particular phrase following the hotword; designating the particular phrase as a new hotword based on the sematic interpretation determining that the particular phrase satisfies one or more predetermined criteria associated with designating voice commands as hotwords; and after designating the particular phrase as a new hotword and while the computing device is in a sleep state, receiving a second speech utterance beginning with the particular phrase, the particular phrase when designated as the new hotword causing the computing device to transition out of the sleep state and process the second speech utterance as a voice command. 11. The system of claim 8 , wherein designating the particular phrase as the new hotword based on the semantic interpretation further comprises determining that the particular phrase includes a voice command.
| 0.609299 |
1. A computer-implemented people matching method comprising: assessing a first location that is associated with a first user and a first non-temporal environmental condition local to the first user of a first mobile processor-based device; assessing a second location that is associated with a second user and a second non-temporal environmental condition local to the second user of a second mobile processor-based device; and generating a match, by means of a processor-based device, of the first user and the second user in accordance with an inference of mutual interest that is based, at least in part, on the first location, the first non-temporal environmental condition, the second location, and the second non-temporal environmental condition.
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1. A computer-implemented people matching method comprising: assessing a first location that is associated with a first user and a first non-temporal environmental condition local to the first user of a first mobile processor-based device; assessing a second location that is associated with a second user and a second non-temporal environmental condition local to the second user of a second mobile processor-based device; and generating a match, by means of a processor-based device, of the first user and the second user in accordance with an inference of mutual interest that is based, at least in part, on the first location, the first non-temporal environmental condition, the second location, and the second non-temporal environmental condition. 2. The method of claim 1 further comprising: generating the match in response to a search request by the first user.
| 0.579787 |
1. At a computer system including a Web browser, a method for presenting a map of user-traversed Web sites from a Web browsing session, the method comprising: for each of a plurality of Web sites the Web browser traverses during a Web browsing session: an act of tracking various activities indicative of Web browser has contact with the traversed Web sites; an act of gathering a representative portion of accessed content from each the traversed Web sites, the representative portion being actual content from the traversed Web sites; subsequent to the Web browsing session ending and for each of the plurality of traversed Web sites traversed during the Web browsing session: an act of deriving a relative weight for the traversed Web site based on the various activities tracked for the traversed Web site during the Web browsing session, the relative weight indicative of significance of contact with the traversed Web site relative to other traversed Web sites; and an act of visually displaying a Web site map of the plurality of traversed Web sites traversed during the Web browsing session, the Web site map including visually displaying a geometric shape navigable item for each of the plurality of traversed Web sites, each geometric shape navigable item being specific to a single one of the traversed Web sites, and each geometric shape navigable item visually displaying and containing the accessed representative content from the corresponding traversed Web site, and such that the size of geometric shape navigable item varying based on the relative weight for the corresponding traversed Web site so as to visually represent the significance of the contact with the traversed Web site, including increased size of geometric shape navigable items to thereby indicate traversed Web sites having more significant contact and reduced size of geometric shape navigable items to thereby indicate traversed Web sites having less significant contact, such that the geometric shape navigable items for the plurality of traversed Web sites traversed during the Web browsing session are simultaneously displayed with varying sizes to thereby indicate significance of contact with the respective traversed Web site.
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1. At a computer system including a Web browser, a method for presenting a map of user-traversed Web sites from a Web browsing session, the method comprising: for each of a plurality of Web sites the Web browser traverses during a Web browsing session: an act of tracking various activities indicative of Web browser has contact with the traversed Web sites; an act of gathering a representative portion of accessed content from each the traversed Web sites, the representative portion being actual content from the traversed Web sites; subsequent to the Web browsing session ending and for each of the plurality of traversed Web sites traversed during the Web browsing session: an act of deriving a relative weight for the traversed Web site based on the various activities tracked for the traversed Web site during the Web browsing session, the relative weight indicative of significance of contact with the traversed Web site relative to other traversed Web sites; and an act of visually displaying a Web site map of the plurality of traversed Web sites traversed during the Web browsing session, the Web site map including visually displaying a geometric shape navigable item for each of the plurality of traversed Web sites, each geometric shape navigable item being specific to a single one of the traversed Web sites, and each geometric shape navigable item visually displaying and containing the accessed representative content from the corresponding traversed Web site, and such that the size of geometric shape navigable item varying based on the relative weight for the corresponding traversed Web site so as to visually represent the significance of the contact with the traversed Web site, including increased size of geometric shape navigable items to thereby indicate traversed Web sites having more significant contact and reduced size of geometric shape navigable items to thereby indicate traversed Web sites having less significant contact, such that the geometric shape navigable items for the plurality of traversed Web sites traversed during the Web browsing session are simultaneously displayed with varying sizes to thereby indicate significance of contact with the respective traversed Web site. 9. The method as recited in claim 1 , wherein the act of deriving a relative weight to each for the traversed Web site based on the various activities tracked for the traversed Web site during the Web browsing session comprises an act of assigning a weight to a Web site based on the Web browser's time visiting other pages in the same domain as the Web site.
| 0.609277 |
1. Context sensitive text input method, comprising the steps of: determining a list of candidate words for the present input context, a candidate word being a possible textual continuation of the present context; wherein the present context comprises at least one preceding word or delimiter; arranging the candidate words in groups, each group having a group designator; displaying the group designators; prompting the user to select a group and receiving the user selection; displaying candidate words of the selected group, the displayed candidate words being arranged according to their respective contextual relevance; prompting the user to select a candidate word and receiving the user selection; and accepting the selected candidate word as text input and updating the context.
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1. Context sensitive text input method, comprising the steps of: determining a list of candidate words for the present input context, a candidate word being a possible textual continuation of the present context; wherein the present context comprises at least one preceding word or delimiter; arranging the candidate words in groups, each group having a group designator; displaying the group designators; prompting the user to select a group and receiving the user selection; displaying candidate words of the selected group, the displayed candidate words being arranged according to their respective contextual relevance; prompting the user to select a candidate word and receiving the user selection; and accepting the selected candidate word as text input and updating the context. 5. Method according to claim 1 , wherein the candidates words of the selected group are sorted according to candidate scores indicating their contextual relevance, and the candidate words are arranged according to their respective scores such that candidate words having a better score are displayed for allowing a selection with less user inputs.
| 0.653372 |
1. A method for locating unidentified breaks between words in an input character string formed of a plurality of characters, the method comprising the successive steps of storing said input character string in a computer memory element, identifying at least one morpheme in a first segment of said stored character string, reducing the number of unidentified word breaks in said stored character string by locating a first word break in said first segment of said stored character string based upon said at least one morpheme, said first word break dividing said first segment into a first sub-segment and a second sub-segment, and locating further unidentified word breaks in said first and second sub-segments by comparing said first and second sub-segments to entries in a dictionary.
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1. A method for locating unidentified breaks between words in an input character string formed of a plurality of characters, the method comprising the successive steps of storing said input character string in a computer memory element, identifying at least one morpheme in a first segment of said stored character string, reducing the number of unidentified word breaks in said stored character string by locating a first word break in said first segment of said stored character string based upon said at least one morpheme, said first word break dividing said first segment into a first sub-segment and a second sub-segment, and locating further unidentified word breaks in said first and second sub-segments by comparing said first and second sub-segments to entries in a dictionary. 3. The method of claim 1, wherein said identifying step includes the steps of locating word breaks and character-transitions by applying a set of rules to said stored character string to identify said at least one morpheme.
| 0.701195 |
13. A system for displaying user specific content, said system comprising: a processor; and a non-transitory computer-usable medium embodying computer program code, said non-transitory computer-usable medium capable of communicating with the processor, said computer program code comprising instructions executable by said processor and configured for: determining a size of a random sample of a plurality of links in a browser history; selecting a predetermined number of links from said plurality of links in said browser history for said random sample of said plurality of links; fetching content for each of said plurality of links in said random sample; extracting a plurality of topics comprising a variable number of topics from said content including text from HTML, said extracting of said plurality of topics executed in a background as a low priority process; generating a topic model from said plurality of topics extracted from said content, said topic model to be used to alter a manner in which selected web content is displayed; evaluating content of a newly selected web page against said topic model after generating said topic model to determine a probability score for each of said plurality of topics based on how accurately each of said plurality of topics describes said content of the newly selected web page and by providing every topic in said topic model with said probability score within a certain threshold of all other topics; selecting a subset of said plurality of topics based on said probability score; evaluating said content from said newly selected web page for keywords associated with said subset of topics and which represent significant trends across said subset of topics; and highlighting said keywords within said newly selected web page based on said topic model in order to display user specific content.
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13. A system for displaying user specific content, said system comprising: a processor; and a non-transitory computer-usable medium embodying computer program code, said non-transitory computer-usable medium capable of communicating with the processor, said computer program code comprising instructions executable by said processor and configured for: determining a size of a random sample of a plurality of links in a browser history; selecting a predetermined number of links from said plurality of links in said browser history for said random sample of said plurality of links; fetching content for each of said plurality of links in said random sample; extracting a plurality of topics comprising a variable number of topics from said content including text from HTML, said extracting of said plurality of topics executed in a background as a low priority process; generating a topic model from said plurality of topics extracted from said content, said topic model to be used to alter a manner in which selected web content is displayed; evaluating content of a newly selected web page against said topic model after generating said topic model to determine a probability score for each of said plurality of topics based on how accurately each of said plurality of topics describes said content of the newly selected web page and by providing every topic in said topic model with said probability score within a certain threshold of all other topics; selecting a subset of said plurality of topics based on said probability score; evaluating said content from said newly selected web page for keywords associated with said subset of topics and which represent significant trends across said subset of topics; and highlighting said keywords within said newly selected web page based on said topic model in order to display user specific content. 14. The system of claim 13 wherein each of said plurality of topics comprises a plurality of keywords that describe said content.
| 0.5 |
15. A non-transitory machine-readable storage medium comprising instructions, which when implemented by one or more machines, cause the one or more machines to perform operations comprising: obtaining one or more query terms in a first query; and for each of the one or more query terms: searching a standardized entity taxonomy to locate a standardized entity that most closely matches the query term, the standardized entity taxonomy comprising an entity identification for each of a plurality of different standardized entities; calculating a confidence score for a query term-standardized entity pair for the standardized entity that most closely matches the query term; in response to a determination that the confidence score transgresses a threshold, associating the query term with the entity identification corresponding to the standardized entity that most closely matches the query term; retrieving one or more query rewriting rules corresponding to an entity type of the standardized entity having the entity identification; and executing the one or more query rewriting rules to rewrite the first query such that the rewritten query is more restrictive than the first query.
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15. A non-transitory machine-readable storage medium comprising instructions, which when implemented by one or more machines, cause the one or more machines to perform operations comprising: obtaining one or more query terms in a first query; and for each of the one or more query terms: searching a standardized entity taxonomy to locate a standardized entity that most closely matches the query term, the standardized entity taxonomy comprising an entity identification for each of a plurality of different standardized entities; calculating a confidence score for a query term-standardized entity pair for the standardized entity that most closely matches the query term; in response to a determination that the confidence score transgresses a threshold, associating the query term with the entity identification corresponding to the standardized entity that most closely matches the query term; retrieving one or more query rewriting rules corresponding to an entity type of the standardized entity having the entity identification; and executing the one or more query rewriting rules to rewrite the first query such that the rewritten query is more restrictive than the first query. 16. The non-transitory machine-readable storage medium of claim 15 , wherein the one or more query rewriting rules include adding the standardized entity having the entity identification to the first query with an AND connector.
| 0.564756 |
9. A non-transitory computer readable medium storing instructions that, when executed by a processor, cause the processor to optimized a task graph that delineates a plurality of tasks to be evaluated in a parallel processing environment, by performing the steps of: generating a first task aggregation topology associated with the task graph that divides the plurality of tasks into a first collection of sets, wherein each set in the first collection of sets includes one or more tasks from the plurality of tasks, each task of the plurality of tasks belongs to only one set included in the first collection of sets, and the first task aggregation topology comprises a bit mask that indicates two or more tasks of the plurality of tasks that are included in a first set in the first collection of sets; compiling the plurality of tasks according to the first task aggregation topology to generate units of work to be executed in the parallel processing environment, wherein the two or more tasks included in the first set are compiled to generate a single unit of work that is executed by a first processing engine included in the parallel processing environment; collecting statistics associated with executing the units of work in the parallel processing environment; and determining whether the first task aggregation topology is more efficient in execution than any previously-defined task aggregation topology based on the statistics; and if the task aggregation topology is more efficient in execution than any previously-defined task aggregation topology, then selecting the first task aggregation topology as the most optimal task aggregation topology, or if the first task aggregation topology is not more efficient in execution than any previously-defined task aggregation topology, then selecting a second task aggregation topology as the most optimal task aggregation topology.
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9. A non-transitory computer readable medium storing instructions that, when executed by a processor, cause the processor to optimized a task graph that delineates a plurality of tasks to be evaluated in a parallel processing environment, by performing the steps of: generating a first task aggregation topology associated with the task graph that divides the plurality of tasks into a first collection of sets, wherein each set in the first collection of sets includes one or more tasks from the plurality of tasks, each task of the plurality of tasks belongs to only one set included in the first collection of sets, and the first task aggregation topology comprises a bit mask that indicates two or more tasks of the plurality of tasks that are included in a first set in the first collection of sets; compiling the plurality of tasks according to the first task aggregation topology to generate units of work to be executed in the parallel processing environment, wherein the two or more tasks included in the first set are compiled to generate a single unit of work that is executed by a first processing engine included in the parallel processing environment; collecting statistics associated with executing the units of work in the parallel processing environment; and determining whether the first task aggregation topology is more efficient in execution than any previously-defined task aggregation topology based on the statistics; and if the task aggregation topology is more efficient in execution than any previously-defined task aggregation topology, then selecting the first task aggregation topology as the most optimal task aggregation topology, or if the first task aggregation topology is not more efficient in execution than any previously-defined task aggregation topology, then selecting a second task aggregation topology as the most optimal task aggregation topology. 11. The non-transitory computer readable medium of claim 9 , wherein the statistics include a total execution time associated with executing the units of work in the parallel processing environment.
| 0.572079 |
1. A system for creating a test with one or more questions that contain one or more mathematical expressions from a collection of question data files, each question data file containing at least one content item, at least one corresponding label item, and a set of initial variables whose values are determined according to a set of variation rules, the system comprising: a data processor having a means for storing at least one computer program; and means for printing indicia on paper, said means coupled in data communication with the data processor; the data processor including: a print engine having: means for sequencing through selected question data files; means for determining the placement of the content and label items of the selected question data files on a printed sheet; means for measuring the dimension of each content and each label item; and means for processing the variation rules and replacing each of the initial variables with a result value.
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1. A system for creating a test with one or more questions that contain one or more mathematical expressions from a collection of question data files, each question data file containing at least one content item, at least one corresponding label item, and a set of initial variables whose values are determined according to a set of variation rules, the system comprising: a data processor having a means for storing at least one computer program; and means for printing indicia on paper, said means coupled in data communication with the data processor; the data processor including: a print engine having: means for sequencing through selected question data files; means for determining the placement of the content and label items of the selected question data files on a printed sheet; means for measuring the dimension of each content and each label item; and means for processing the variation rules and replacing each of the initial variables with a result value. 2. A system as claimed in claim 1, further comprising means for transferring data containing the placement and dimension of the content and label items to the means for printing indicia.
| 0.671402 |
14. A method for maximizing page yield by optimizing display depth of advertisements displayed to searching Web users, the method executed by a server having a processor and memory, the method comprising: (a) tracking click activity, by the server, on a plurality of advertisements by a plurality of users via a set of hierarchal search results pages delivered in response to a search query for a keyword by a search engine; (b) tracking bidding activity, by the server, of a plurality of advertisers related to the keyword and corresponding advertisements of the plurality of advertisements; and (c) calculating, by the processor, an optimum number of advertisements (d*) to display on a particular search results page of the set of hierarchal search results pages in response to the search query such that maximizes the expected page yield according to at least one business objective, wherein the expected page yield of the particular search results page is calculated by summing, at each of a plurality of display depths within d*, a probability of a click at the display depth times a bid price estimate at the display depth, wherein the probability of click and the bid price estimate are obtained from sampled related curves formed from the tracked click and bidding activities based on at least one query; (d) executing, by the processor, a Monte Carlo randomization procedure to include: (i) randomly sampling probability and bid/price curves related at least one different query; (ii) recalculating d* as per step (c); and (iii) repeating steps (i) and (ii) to calculate potential multiple optimum numbers (d*) of advertisements; and (e) serving, by the server, to the particular search results page at least some of the plurality of advertisements according to at least one calculated value of d* in response to the search query for the keyword.
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14. A method for maximizing page yield by optimizing display depth of advertisements displayed to searching Web users, the method executed by a server having a processor and memory, the method comprising: (a) tracking click activity, by the server, on a plurality of advertisements by a plurality of users via a set of hierarchal search results pages delivered in response to a search query for a keyword by a search engine; (b) tracking bidding activity, by the server, of a plurality of advertisers related to the keyword and corresponding advertisements of the plurality of advertisements; and (c) calculating, by the processor, an optimum number of advertisements (d*) to display on a particular search results page of the set of hierarchal search results pages in response to the search query such that maximizes the expected page yield according to at least one business objective, wherein the expected page yield of the particular search results page is calculated by summing, at each of a plurality of display depths within d*, a probability of a click at the display depth times a bid price estimate at the display depth, wherein the probability of click and the bid price estimate are obtained from sampled related curves formed from the tracked click and bidding activities based on at least one query; (d) executing, by the processor, a Monte Carlo randomization procedure to include: (i) randomly sampling probability and bid/price curves related at least one different query; (ii) recalculating d* as per step (c); and (iii) repeating steps (i) and (ii) to calculate potential multiple optimum numbers (d*) of advertisements; and (e) serving, by the server, to the particular search results page at least some of the plurality of advertisements according to at least one calculated value of d* in response to the search query for the keyword. 15. The method of claim 14 , wherein the at least one business objective comprises maximized revenue or maximized user clicks, and wherein the plurality of advertisements comprise sponsored advertisements.
| 0.574262 |
6. The method of claim 1 further comprising: wherein the statement classification method is by the group leader; the computer associating an instant messaging statement with a first topic by inserting a first topic tag into the instant messaging statement; the computer associating a plurality of subsequent instant messaging statements with the first topic; and the computer ending an association of the plurality of subsequent instant messaging statements with the first topic by inserting a second topic tag into one of the plurality of subsequent instant messaging statements.
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6. The method of claim 1 further comprising: wherein the statement classification method is by the group leader; the computer associating an instant messaging statement with a first topic by inserting a first topic tag into the instant messaging statement; the computer associating a plurality of subsequent instant messaging statements with the first topic; and the computer ending an association of the plurality of subsequent instant messaging statements with the first topic by inserting a second topic tag into one of the plurality of subsequent instant messaging statements. 9. The method of claim 6 wherein an alteration of a first configuration of a first chat participant's graphical user interface does not alter a second configuration of a second chat participants' graphical user interface.
| 0.791274 |
5. The method of claim 1 further comprising: providing a suggested correction that complies with the identified format requirement.
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5. The method of claim 1 further comprising: providing a suggested correction that complies with the identified format requirement. 6. The method of claim 5 further comprising: receiving addressee information about an addressee to whom a message is intended at the e-mail address; and wherein the providing the suggested correction includes generating the suggested correction based on the addressee information, wherein the addressee information provides information in addition to the email address.
| 0.84038 |
4. The method of claim 1 , further comprising: dynamically recalculating, by the one or more physical processor, the route in response to one or more subsequent interactions with a user refining the destination.
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4. The method of claim 1 , further comprising: dynamically recalculating, by the one or more physical processor, the route in response to one or more subsequent interactions with a user refining the destination. 5. The method of claim 4 , wherein dynamically recalculating the route comprises generating directions from the current location to the refined destination.
| 0.962404 |
1. A method for operating a data processing system to process a record, said method including defining a plurality of ALTERNATIVE statements, each ALTERNATIVE statement of said plurality of ALTERNATIVE statements comprising: a label that identifies said ALTERNATIVE statement; a signature that defines a test that is to be performed on a first field in said record; and a NEXT statement that identifies a different one of said ALTERNATIVE statements and that defines a second field in said data record to be said first field in said different one of said ALTERNATIVE statements if said test is satisfied, said data processing system generating an error if said test is not satisfied, wherein said first and second fields are different in at least one of said ALTERNATIVE statements and wherein said NEXT statement in one of said ALTERNATIVE statements specifies a plurality of fields for testing in a predetermined sequence by other ALTERNATIVE statements in a processing program, control being transferred to the first one of said other ALTERNATIVE statements in said predetermined sequence in which said test in that one of said other ALTERNATIVE statements is satisfied.
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1. A method for operating a data processing system to process a record, said method including defining a plurality of ALTERNATIVE statements, each ALTERNATIVE statement of said plurality of ALTERNATIVE statements comprising: a label that identifies said ALTERNATIVE statement; a signature that defines a test that is to be performed on a first field in said record; and a NEXT statement that identifies a different one of said ALTERNATIVE statements and that defines a second field in said data record to be said first field in said different one of said ALTERNATIVE statements if said test is satisfied, said data processing system generating an error if said test is not satisfied, wherein said first and second fields are different in at least one of said ALTERNATIVE statements and wherein said NEXT statement in one of said ALTERNATIVE statements specifies a plurality of fields for testing in a predetermined sequence by other ALTERNATIVE statements in a processing program, control being transferred to the first one of said other ALTERNATIVE statements in said predetermined sequence in which said test in that one of said other ALTERNATIVE statements is satisfied. 2. The method of claim 1 wherein one of said NEXT statements includes a first ALTERNATIVE statement, a backtrack operator, and a second ALTERNATIVE statement, control being transferred to said second ALTERNATIVE statement when a sequence of ALTERNATIVE statements beginning with said first ALTERNATIVE statement generates said error.
| 0.597258 |
5. A method comprising: receiving an image file representing an image comprising text; determining, by a processing device, a plurality of portions of the image respectively corresponding to a plurality of letters of the text; determining, for a first letter of the plurality of letters, a set of letter properties comprising at least one dependent letter property and at least one independent letter property, wherein each of the at least one dependent letter property of the first letter is dependent on another letter of the plurality of letters and each of the at least one independent letter property of the first letter is independent of all other letters of the plurality of letters; and classifying the first letter into one of a plurality of letterform classes based on the set of letter properties.
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5. A method comprising: receiving an image file representing an image comprising text; determining, by a processing device, a plurality of portions of the image respectively corresponding to a plurality of letters of the text; determining, for a first letter of the plurality of letters, a set of letter properties comprising at least one dependent letter property and at least one independent letter property, wherein each of the at least one dependent letter property of the first letter is dependent on another letter of the plurality of letters and each of the at least one independent letter property of the first letter is independent of all other letters of the plurality of letters; and classifying the first letter into one of a plurality of letterform classes based on the set of letter properties. 11. The method of claim 5 , further comprising: determining a portion of the image corresponding to a non-textual element; determining shape properties for the non-textual element; and determining that the non-textual element is not a letter based on the shape properties.
| 0.757126 |
13. The apparatus of claim 12 , further comprising: means for receiving a second packet from the second client via a second client computer across a transmission channel; means for identifying number of redundant digital representations in the second packet; and means for selecting one of the redundant digital representations in response to the first client criteria.
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13. The apparatus of claim 12 , further comprising: means for receiving a second packet from the second client via a second client computer across a transmission channel; means for identifying number of redundant digital representations in the second packet; and means for selecting one of the redundant digital representations in response to the first client criteria. 15. The apparatus of claim 13 , wherein means for identifying number of redundant digital representations includes means for determining a high resolution codec for digital signals.
| 0.810778 |
1. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristics of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristics of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein determining the emotion state of the speaker based on the comparison occurs within one day of receiving the subject utterance of speech by the speaker.
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1. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristics of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristics of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein determining the emotion state of the speaker based on the comparison occurs within one day of receiving the subject utterance of speech by the speaker. 3. The method according to claim 1 , wherein determining the emotion state of speaker based on the comparison comprises determining one or more emotions of the speaker based on the comparison.
| 0.705113 |
12. The computer system of claim 11 , wherein the certain description of the certain organization comprises usage data associated with the certain organization, and the processor is further configured to utilize the usage data to identify the first and second runs of the specific test scenario.
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12. The computer system of claim 11 , wherein the certain description of the certain organization comprises usage data associated with the certain organization, and the processor is further configured to utilize the usage data to identify the first and second runs of the specific test scenario. 13. The computer system of claim 12 , wherein both a description of an organization, considered similar to the certain description, and the certain description comprise a description of usage of a non-zero predetermined number of business processes.
| 0.878916 |
5. A computer program product for generating a graph segment providing a gist or summary of an online social network conversation, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory medium per se, the program instructions being executable by a device to cause the device to perform a method comprising: generating a graph of the online social network conversation, wherein the graph of the online social network conversation comprises a plurality of nodes and each node connecting at least one other node by an edge, each node representing a message of the online social network conversation and each edge corresponding to an action by a participant in the online social network conversation; determining an edge weight for each edge; analyzing the graph of the online social network conversation using at least the edge weight of at least some edges to generate a graph segment; and generating the graph segment, the graph segment comprising a reduced number of nodes of the graph of the online social network conversation based on analyzing the graph of the online social network conversation and the graph segment providing a gist or summary comprising an abbreviated view of the online social network conversation based on the analysis, each node of the reduced number of nodes corresponding to its own respective node of the graph of the online social network conversation.
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5. A computer program product for generating a graph segment providing a gist or summary of an online social network conversation, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory medium per se, the program instructions being executable by a device to cause the device to perform a method comprising: generating a graph of the online social network conversation, wherein the graph of the online social network conversation comprises a plurality of nodes and each node connecting at least one other node by an edge, each node representing a message of the online social network conversation and each edge corresponding to an action by a participant in the online social network conversation; determining an edge weight for each edge; analyzing the graph of the online social network conversation using at least the edge weight of at least some edges to generate a graph segment; and generating the graph segment, the graph segment comprising a reduced number of nodes of the graph of the online social network conversation based on analyzing the graph of the online social network conversation and the graph segment providing a gist or summary comprising an abbreviated view of the online social network conversation based on the analysis, each node of the reduced number of nodes corresponding to its own respective node of the graph of the online social network conversation. 6. The computer program product of claim 5 , wherein determining an edge weight for each edge comprises determining at least one of a set of factors comprising a sentiment of a post associated with the edge, a strength of a poster's online social network, a length of a message associated with the edge, a vitality of the online social network conversation and a weight of a subconversation of the online social network conversation.
| 0.752183 |
13. A method comprising: detecting a message term within an electronic message; searching for an existing stored description associated with the message term; determining the existing stored description is unavailable; determining the message term appears a threshold number of times in one or more electronic messages; in response to the message term appearing a threshold number of times in one or more electronic messages, forming a stored description associated with the message term based on analysis of a context of the message term within the electronic message and of a context of the message term when used within one or more electronic messages other than the message; and storing the stored description in a profile.
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13. A method comprising: detecting a message term within an electronic message; searching for an existing stored description associated with the message term; determining the existing stored description is unavailable; determining the message term appears a threshold number of times in one or more electronic messages; in response to the message term appearing a threshold number of times in one or more electronic messages, forming a stored description associated with the message term based on analysis of a context of the message term within the electronic message and of a context of the message term when used within one or more electronic messages other than the message; and storing the stored description in a profile. 15. The method according to claim 13 wherein the forming further comprises defining the stored description based, also, on a database containing the message term.
| 0.705948 |
1. A translation memory comprising: an aligned file having a number of source language text segments encoded in a computer readable format, each of the source language text segments positioned at a unique address and paired with a target language text segment encoded in the computer readable format; an inverted index comprising a listing of source language letter n-grams, wherein each listed letter n-gram includes an associated entry for an entropy weight for the listed letter n-gram, a count of the number of source language text segments in the aligned file that include an entry for the listed letter n-gram, and a pointer to a unique location in the translation memory; and a posting vector file having a posting vector associated with each listed letter n-gram in the inverted index, each posting vector positioned at one of the unique locations pointed to in the inverted index, each posting vector including: i) a plurality of document identification numbers each corresponding to a selected one of the source language text strings in the aligned file, and ii) a number of entropy weight values, each of the number of entropy weight values associated with one document identification number.
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1. A translation memory comprising: an aligned file having a number of source language text segments encoded in a computer readable format, each of the source language text segments positioned at a unique address and paired with a target language text segment encoded in the computer readable format; an inverted index comprising a listing of source language letter n-grams, wherein each listed letter n-gram includes an associated entry for an entropy weight for the listed letter n-gram, a count of the number of source language text segments in the aligned file that include an entry for the listed letter n-gram, and a pointer to a unique location in the translation memory; and a posting vector file having a posting vector associated with each listed letter n-gram in the inverted index, each posting vector positioned at one of the unique locations pointed to in the inverted index, each posting vector including: i) a plurality of document identification numbers each corresponding to a selected one of the source language text strings in the aligned file, and ii) a number of entropy weight values, each of the number of entropy weight values associated with one document identification number. 8. The translation memory of claim 1 wherein the listing of letter n-grams is provided in Unicode format.
| 0.685053 |
1. A system providing cross-linguistic communication and providing feedback for machine learning, comprising: a client component capturing inputs, the client component providing a user interface configured to display a translation of an input term into a different language than an input language, a retranslation from the target language back into the source language, and interface elements enabled for selecting one of whether translations should be verified before transmission, and whether a previous translation should be revised; and a server component providing the translation and the retranslation to the client component based upon the input term, the server component including, an interaction manager stored within memory of the server component, the interaction manger configured to request the translation of the inputs and access a database containing data representing a sense of the input term, the sense including a synonym for each different sense of the input term, wherein each different sense includes a different meaning for the term.
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1. A system providing cross-linguistic communication and providing feedback for machine learning, comprising: a client component capturing inputs, the client component providing a user interface configured to display a translation of an input term into a different language than an input language, a retranslation from the target language back into the source language, and interface elements enabled for selecting one of whether translations should be verified before transmission, and whether a previous translation should be revised; and a server component providing the translation and the retranslation to the client component based upon the input term, the server component including, an interaction manager stored within memory of the server component, the interaction manger configured to request the translation of the inputs and access a database containing data representing a sense of the input term, the sense including a synonym for each different sense of the input term, wherein each different sense includes a different meaning for the term. 7. The system of claim 1 , wherein the server component includes a text-to-speech module providing an audio signal to the client component for pronunciation of the input term in the different language and the input language.
| 0.507569 |
1. An end-pointer that determines a beginning and an end of a speech segment comprising: a voice triggering module that identifies a portion of an audio stream comprising an audio speech segment; a rule module in communication with the voice triggering module, the rule module comprising a plurality of rules used by a processor to analyze a part of the audio stream to detect a beginning and an end of the audio speech segment; and a consonant detector that calculates a difference between a signal-to-noise ratio in a high frequency band and a signal-to-noise ratio in a low frequency band, where the consonant detector converts the difference between the signal-to-noise ratio in the high frequency band and the signal-to-noise ratio in the low frequency band into a probability value that predicts a likelihood of a high frequency consonant in the portion of the audio stream; where the beginning of the audio speech segment and the end of the audio speech segment represent boundaries between speech and non-speech portions of the audio stream, and where the rule module identifies the beginning of the audio speech segment or the end of the audio speech segment based on an output of the consonant detector.
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1. An end-pointer that determines a beginning and an end of a speech segment comprising: a voice triggering module that identifies a portion of an audio stream comprising an audio speech segment; a rule module in communication with the voice triggering module, the rule module comprising a plurality of rules used by a processor to analyze a part of the audio stream to detect a beginning and an end of the audio speech segment; and a consonant detector that calculates a difference between a signal-to-noise ratio in a high frequency band and a signal-to-noise ratio in a low frequency band, where the consonant detector converts the difference between the signal-to-noise ratio in the high frequency band and the signal-to-noise ratio in the low frequency band into a probability value that predicts a likelihood of a high frequency consonant in the portion of the audio stream; where the beginning of the audio speech segment and the end of the audio speech segment represent boundaries between speech and non-speech portions of the audio stream, and where the rule module identifies the beginning of the audio speech segment or the end of the audio speech segment based on an output of the consonant detector. 13. The end-pointer of claim 1 , where the probability value comprises a current probability value associated with a current frame of the audio stream, where the consonant detector modifies the current probability value when the current probability value deviates from consonant probability values associated with previous frames.
| 0.500698 |
15. The method of claim 10 , further comprising: ranking each cluster.
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15. The method of claim 10 , further comprising: ranking each cluster. 17. The method of claim 15 , wherein ranking each cluster comprises: for each cluster summary, calculating a coherence score for the cluster summary; and ranking the clusters based on the coherence score.
| 0.960132 |
1. A method for providing information in response to a question in one of a plurality of natural spoken languages, comprising the steps of: recognizing a detected utterance with a speech recognition engine equipped with a plurality of small dictionaries each for respective one of the plurality of languages, each small dictionary including speech data for a selected few common words in the respective language; selecting one of the plurality of languages as the language of the detected utterance based on a number of recognized words for each language from the small dictionaries; recognizing the detected utterance using a large dictionary for the language of the detected utterance; and responding to the user in the selected language.
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1. A method for providing information in response to a question in one of a plurality of natural spoken languages, comprising the steps of: recognizing a detected utterance with a speech recognition engine equipped with a plurality of small dictionaries each for respective one of the plurality of languages, each small dictionary including speech data for a selected few common words in the respective language; selecting one of the plurality of languages as the language of the detected utterance based on a number of recognized words for each language from the small dictionaries; recognizing the detected utterance using a large dictionary for the language of the detected utterance; and responding to the user in the selected language. 8. The method as recited in claim 1 wherein a percentage coverage in the respective natural language for each of the small dictionaries of the common words is substantially equivalent to the other small dictionaries.
| 0.660657 |
2. A method according to claim 1 , further comprising determining whether the received data includes Schema elements prior to adapting portions of the received data.
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2. A method according to claim 1 , further comprising determining whether the received data includes Schema elements prior to adapting portions of the received data. 3. A method according to claim 2 , further comprising determining whether the Schema elements are capable of conversion into an XPath expression prior to adapting portions of the received data.
| 0.93631 |
9. The method of claim 1 , wherein each conversational category of the plurality of conversational categories represents a conversation formed by an amalgamation of at least two strings that each, individually, match a respective singleton template, and that the matching singleton templates, when juxtaposed, are determined to form a single query.
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9. The method of claim 1 , wherein each conversational category of the plurality of conversational categories represents a conversation formed by an amalgamation of at least two strings that each, individually, match a respective singleton template, and that the matching singleton templates, when juxtaposed, are determined to form a single query. 10. The method of claim 9 , wherein the first conversation, the second conversation, and the third conversation form the single query based on a respective juxtaposition of the first string, the second string, and the third string.
| 0.964709 |
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